Pharma Focus Asia - Issue 36 by Ochre Media Pvt. Ltd.

ISSUE 36 2019

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NOVO NORDISK PHARMATECH A/S

Ensuring Quality Assurance Healthcare Evolution The growing use of wearables in clinical trials Flexible Facilities Manufacturing trends offering benefits

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Foreword CLINICAL TRIALS Leveraging wearables effectively An estimated 325 million people use connected wearable devices, according to IMARC. The global market for medical wearable devices is slated to reach $12.1 billion by 2021 indicates Markets&Markets. A quick check of clinicaltrials.gov that hosts a global database of clinical trials, will provide around 200 trials based on wearable devices or wearable technology. This shows that the technological advancements in connected devices have a key role to play in clinical trials. Some of these clinical studies focus on testing the feasibility of wearables to generate insights such as diagnosing sleep apnea through a fitness band, detecting atrial fibrillation through smart watches etc. A study conducted by Trialtrove in April 2018 offers a glimpse of wearables that have been leveraged for several drug interventional trials. The study indicates that there has been a rise in such clinical trials from 12 in 2008 to 32 in 2017. This rise could be attributed to an increase in types of diseases, wearables, and trial sponsors. The diseases for which clinical trials were conducted, with reliance on mobile devices or wearables, include Asthma, Insomnia, Smoking cessation, Alzheimer’s, Parkinson’s etc. While monitoring sleep quality and physical activity, the devices also help track drug adherence, drug delivery, postural stability etc. These devices enable patients to track and share their own health data, thereby making them collaborators during clinical trials. Rob Scott of Abbvie believes that technology will not just be a part of clinical development process but become a key component in providing researchers with better access to patients. Digital technologies facilitate real-time access to patients’ health metrics, thus providing an insight into how patients are doing in the trial. The benefits of using wearables for clinical trials include access to real-time data saving time

and costs, researchers responding pretty quickly to adverse events, baseline patient data collected over extended periods offers patterns enabling better treatment. Data from wearables, when combined with genomics, possesses the ability to develop a comprehensive overview of a patient’s health. Nevertheless, while wearable medical devices offer benefits, there are several challenges with several devices promising to enhance health and wellness but with no significant evidence to backup their promise. Reliability of devices that are not approved by regulators is one such challenges. And then there is the fact that access to data collected by wearables may vary by device. Consumer grade devices are user-friendly and process data through algorithms that helps derive insights. Medical grade devices on the other hand are not user-friendly and provide raw data, which is helpful for researchers in their studies. Over the last couple of years, companies have moved from discussions to execution of deploying digital technologies while designing clinical trials to be more data-driven. As we look into the future, clinical trials will become less labor-intensive, what with connected devices enabling researchers to gather data without manual entry. Life sciences and healthcare companies need to work in tandem with technology companies to bring out devices that enable seamless and effective data collection for trials. The cover story of this issue talks about how wearables are becoming game changers in the clinical trials segment.

Prasanthi Sadhu Editor

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COVER STORY

CONTENTS

Novo Nordisk Pharmatech A/S Ensuring quality assurance Rasmus Hother le Fevre Managing Director (Corporate Vice President) Novo Nordisk Pharmatech A/S

STRATEGY 06 Drug Pricing for Personalised Medicine Is indication-based price the solution?

Rosella Levaggi, Professor, Public Economics, University of Brescia

10 Regulatory Aspects of Genotoxic Impurities

Ambikanandan Misra, Professor and UGC-BSR Faculty Fellow, Faculty of Pharmacy, The Maharaja Sayajirao University of Baroda

16 Is Blockchain the Right Technology for the Pharma Supply Chain?

Bradley Pedrow, Director, Compliance Risk in Life Sciences Grant Thornton LLP

32 Healthcare Evolution The growing use of wearables in clinical trials

Geoffrey Gill, President, Shimmer Americas

Martina Donohue, Marketing Manager, Shimmer Ltd.

RESEARCH & DEVELOPMENT 40 Found in Translation Building an early development strategy for complex biologics

Aaron Moss, Director, Integrated Drug Development Group Certara Strategic Consulting

Suzanne Minton, Manager, Scientific Communications, Certara

Christina Mayer, Associate Director, Clinical Pharmacology Integrated Drug Development Group, Certara Strategic Consulting

46 Computer Aided Drug Design in Pharma R&D

Mallikarjuna Rao Pichika, International Medical University

Kit-Kay Mak, International Medical University

MANUFACTURING

52 Messy Marketing Deliberate disordering can improve your strategic marketing planning

Brian D Smith, Managing Director, PragMedic

56 A Quality by Design Approach Development of a robust control strategy for manufacturing

CLINICAL TRIALS 26 Compelling Pre-clinical Models For better prognosis in clinical trials

S Dravida, Founder CEO, Transcell Biologics

Samhita Bandaru, Plano Senior High School Dallas

Ria Thimmaiahgari, Sophomore, Biomedical Engineering, Duke University

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Charles Evans, Vice President, Pharmaceutical Development, MedPharm

Jeremy Drummond, Senior Vice President Business Development, MedPharm

Marc Brown, Chief Scientific Officer and Co-founder, MedPharm

62 Flexible Facilities Manufacturing trends offering benefits

Sean Riley, Senior Director, Media and Industry Communications PMMI, The Association for Packaging and Processing Technologies

68 Books

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Advisory Board

EDITOR Prasanthi Sadhu Alan S Louie Research Director, Life Sciences IDC Health Insights, USA

EDITORIAL TEAM Debi Jones Grace Jones ART DIRECTOR M Abdul Hannan

Christopher-Paul Milne Director, Research and Research Associate Professor Tufts Center for the Study of Drug Development, US

PRODUCT MANAGER Jeff Kenney

Douglas Meyer Associate Director, Clinical Drug Supply Biogen, USA

SENIOR PRODUCT ASSOCIATES David Nelson Peter Thomas Sussane Vincent

Frank Jaeger Regional Sales Manager, AbbVie, US

PRODUCT ASSOCIATES Austin Paul Jessie Vincent John Milton

Georg C Terstappen Head, Platform Technologies & Science China and PTS Neurosciences TA Portfolio Leader GSK's R&D Centre, Shanghai, China

CIRCULATION TEAM Naveen M Sam Smith

Kenneth I Kaitin Professor of Medicine and Director Tufts Center for the Study of Drug Development Tufts University School of Medicine, US

SUBSCRIPTIONS IN-CHARGE Vijay Kumar Gaddam HEAD-OPERATIONS S V Nageswara Rao

Laurence Flint Pediatrician and Independent Consultant Greater New York City

Neil J Campbell Chairman, CEO and Founder Celios Corporation, USA Phil Kaminsky Professor, Executive Associate Dean, College of Engineering, Ph.D. Northwestern University, Industrial Engineering and the Management Sciences, USA

Rustom Mody Senior Vice President and R&D Head Lupin Ltd., (Biotech Division), India

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A member of Confederation of Indian Industry

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Sanjoy Ray Director, Scientific Data & Strategy and Chief Scientific Officer, Computer Sciences Merck Sharp & Dohme, US

Stella Stergiopoulos Research Fellow Tufts University School of Medicine, USA 4

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STRATEGY

DRUG PRICING FOR PERSONALISED MEDICINE IS INDICATION-BASED PRICE THE SOLUTION? Genomic medicine has increased heterogeneity in patients’ responses, which may soon be reflected into pricing schemes. Indication-based prices may increase drug expenditure; marginal value-based prices may reduce the incentive for the industry to assess the differential in effectiveness. This calls for more research into the effects of drug price regulation on innovation. Rosella Levaggi, Professor, Public Economics, University of Brescia

ersonalised medicine is going to change the shape of the pharmaceutical market in the years to come. The advances in genomic medicine make new active principles be very effective only for an increasingly smaller number of patients, with effectiveness declining rapidly if the patient does not match the characteristics of the targeted one. This revolution is going to reshape drug pricing. The market for drugs is highly regulated, and prices are not defined according to the usual rules of perfect competition. Most economists would agree that value-based schemes

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are probably the best alternative to set the price of new drugs since costs are far more difficult to be verified. The idea behind value-based prices is to reimburse the drug according to its societal value, which in turn depends on its effectiveness (usually measured through the expected life years that the drug allows to gain) and society’s willingness to pay for such an increase. However, which value should be considered (the marginal value, the average value, or some other definition) is still debated, and the choice is going to be quite important in the light of the changes produced by personalised medicine.

Marginal value-based schemes have received quite a lot of attention in recent literature and work in this way. Let us assume that N patients, normalised to one for simplicity, could be treated with a drug that is about to be listed. For a group q of patients the drug allows to gain yH of years of good health while for the rest of the group (1-q), the number of years gained is lower (y L). Let us also assume that society is willing to pay λ$ for each unit of effectiveness. Under marginal value-based prices, the price of the drug will be λy L. If, for simplicity, we assume that the marginal cost to produce the drug is zero, the

STRATEGY

profit of the industry (revenue minus cost) is equal to the cost (the price) borne by the provider. The interesting feature of this scheme is that, by paying for a price that is equal to the marginal effectiveness, society is able to get “good value for money”. For the first q patients the price paid is lower than the value society attaches to the years gained, while the industry still has a profit. However, this model may have important consequences as concerns the incentives the industry has in investing in research & development (R&D) in order to determine the effectiveness differential. To show this, let us first assume that the industry knows the effectiveness differential. In this case, the industry has three different options for listing: Ask for listing for both indication. In this case the price will be equal to λyL Ask for listing only for the indication for which the drug is more effec-

tive. In this case the price will be equal to qλyH Ask for listing only for the indication for which the drug is less effective. In this case the price will be equal to (1-q)λyL The third option will never be taken into account: it entails a profit lower than alternative 1. The choice between 1 and 2 depends on the effectiveness differential between the two groups and its relative size. The profit for the first alternative is λyL while for the second is qλyH, which is higher if the effectiveness differential is sufficiently high . From the point-of-view of the healthcare provider, alternative 1 is preferable to alternative 2 since the price is lower and the number of people

treated is higher. However, the choice does not depend on the regulator, but with the industry, and in this case, the price for listing on both markets does not represent the best alternative for the industry. An interesting example of this conflict is the case of bevacizumab, an active principle that has proved to be effective both for colon cancer and agerelated macular degeneration (AMD). The drug has, however, been approved only for colon cancer and some physicians have started using it for AMD off label(not without quite a lot of discussions and High Court rulings). For AMD, given the quantity of active principle needed to treat the patients, the drug becomes rather cheaper compared to other alternatives, and its price no longer reflects its value. It is also interesting to note that if the industry decides to list only for the more effective group of patients, the full

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STRATEGY

value of the drug is not exploited. There are (1-q) patients that could benefit from the drug, but they will never be granted access because the drug may not be listed for their indication. Another interesting perspective on which to evaluate this payment scheme is related to the incentive that the industry may have in investing to assess the effectiveness differential; several additional costs should in fact be incurred: randomised clinical trials must be larger, and more investment is needed in research. Marginal valuebased schemes may not offer enough incentive since they tend to reduce the payment of the drug (the price will be set according to the effectiveness of the marginal patient). If the industry does not invest in finding the effectiveness differential, the price of the drug will be set according to the average expected effectiveness across patients. From the regulator point-ofview, this means an increase in cost, but also patients may be worse off. With respect to the previous system, it may in fact seem that patients are better off if the industry does not invest in finding the differential in effectiveness. Both groups are treated and some will receive a benefit higher than expected ex post (the q group), while other will be disappointed. However, let us broaden the range of drugs and also consider that a second drug may be available, but the latter is more effective for the second group. Knowing the effectiveness differential, the first group should be the first active principle while the second group would benefit from using the other active principle. However, if the return from the extra investment is not sufficiently remunerated, it may be possible that both drugs are marketed for both groups of patients with a loss of health for both groups. In the recent past, some authors have proposed new schemes that are commonly known as indication-based prices. These value-based schemes

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The market for drugs is highly regulated, and prices are not defined according to the usual rules of perfect competition.

foresee selling the drug at a price that depends on the actual effectiveness of the drug. In the example before, this would mean that the drug is sold for the price ÎťyH to the first q patients and to ÎťyL to the other (1-q). This scheme is known in industrial economics as price discrimination; in competitive markets it is expressly forbidden by antitrust agencies (it will be seen as abuse of dominant position).

The most important drawback of this scheme is that it allows the industry to reap most of the societal value of the drug. It may also seem unfair that if the industry could have a profit selling at a price equal to, it should choose to market the drug also to a higher price simply because the willingness to pay is higher for a specific group of patients. This principle is somehow accepted across countries. Drugs in low-income countries are sold at prices lower than in high-income countries, but less across patients within the same country. On the other hand, it should be considered that discovering the effectiveness differential has a cost, which may be reimbursed through this price difference. This shows that a trade-off exists between value for money and information: if the goal is to reduce expenditure, it may well be that less information on differences in effectiveness across patients will be known. In this environment, regulators will play an even more strategic role than in the past.

AUTHOR BIO

Rosella Levaggi is full Professor of Public Economics at the University of Brescia (Italy). She is Associated Editor of Health Economics, Editor of PLOS ONE and Associate Member of CIRIEC Scientific Committee. She is author of several publications on the organisation of health care markets and on the relationship between regulation and innovation in the pharmaceutical sector.

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STRATEGY

REGULATORY ASPECTS OF GENOTOXIC IMPURITIES The Genotoxic Impurities (GIs) are carcinogenic and hence their management during synthesis of pharmaceuticals is very vital so as to be detected even in trace amounts for the safe use of the drugs. This editorial gives an account of updated information about GIs and reviews the regulatory aspects for GIs in active pharmaceutical ingredients/drug formulations. Ambikanandan Misra, Professor and UGC-BSR Faculty Fellow, Faculty of Pharmacy The Maharaja Sayajirao University of Baroda

s per ICH Q3A guidelines, ‘impurity in a drug substance is any component of the drug substance that is not the chemical entity defined as the drug substance’, and as per ICH Q3B guidelines, ‘impurity in any component of the drug product that is not the chemical entity defined as the drug substance or an excipient in the drug product’. Though none of the regulatory bodies gave clear definition about specific impurities so profiling can be termed as ‘the common name of analytical activities with aim of detection, identification and/or elucidation the structure and quantifying inorganic, organic or even solvent residues present in bulk drugs and pharmaceutical final products.’ In a very broad sense, ‘a molecule which is results of degradation of drug substance over a time such degradations are results of oxidation, deamination, proteolysis and many more chemical reactions which could be affect stability of drug product over a time 10

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CLASS-2

• This class includes known animal carcinogens having trust worth data for a human carcinogens and genotoxic mechanism. The genotoxic nature of the impurity is confirmed on the basis of chemical structure present in the published literature.

• Impurities known to be genotoxic (mutagenic), but with unknown carcinogenic potential • This class includes impurities with verified mutagenicity based on testing of the impurity in conventional genotoxicity tests.

• Impurities that have an alerting structure but not related to the API's structure, and of unknown genotoxic (mutagenic) potential. • This class includes impurities with functional moieties that can be linked to genotoxicity based on structure. However, these moieties have not been tested as isolated compounds and are recognized based on chemistry and using knowledge-based expert systems for structure-activity relationships (SAR).

CLASS-4

CLASS-3

• Impurities known to be genotoxic (mutagenic) and carcinogenic

• This class includes impurities with an alerting structure related to the API and impurities that contain an alerting functional group moiety that is shared with the structure of API.

CLASS-5

and it should be quantify is called impurities’. Detailed classification of impurities is shown in figure 1. In pharmaceutical products and APIs, genotoxic impurities are generally termed as substances that do not provide any therapeutic advantage, but may have the potential carcinogenic or mutagenic effect. Therefore, levels of impurities need to be in controlled a range that is safe for human consumption. Level of impurities may project a high impact on the safety, in-process time on development, and even the sales and marketing of the drugs. For example, the time required to develop drugs can be significantly increased when it is necessary to carry out multiple attempts to characterise and remove impurities to acceptable levels. According to ICH guidelines, impurities related to drug substances can be classified into three main categories: organic impurities, inorganic (elemental) impurities, and residual solvents. From these categories, impurities that posses genotoxic effects have special attention due to a significant safety risk, even at low concentrations, because they may have mutagenic action on DNA which makes them potentially damaging to DNA and further processes. There have been many discussions about the definition of genotoxic impurity. But from the reference of ICH S2 (R1) Guideline1, genotoxicity is defined as “a broad term that refers to any deleterious change in the genetic material regardless of the mechanism by which the change is induced.” This definition is justified. It is also defined as an “impurity that has been demonstrated to be genotoxic in an appropriate genotoxicity test model, e.g., bacterial gene mutation (Ames) test”. Another term Potential Genotoxic Impurity (PGI) defined as an “Impurity that shows (a) structural alert(s) for genotoxicity but that has not been tested in an experimental test model”. Here potentially relating to genotoxicity, not to the presence or absence of this impurity. Different regulatory guidelines are discussed herewith in context to genotoxic impurities.

CLASS-1

STRATEGY

• This class includes impurities with no alerting structure or indication of genotoxic potential. On the basis of above classification system, PhRMA proposed a strategy for impurity assessment.

Figure 1: Classification of Impurities

Ich Guidance for Industry Relating to Drug Impurities and Residual Solvents

The International Conference on Harmonisation Q3A(R2) and ICH Q3B(R2) report the issue of impurities in drug substances and drug products, respectively. ICH Q3A(R2) addresses the identification and criterion of impurities in drug substances approved after issuance of the guidance, and ICH Q3B(R2) gives

brief account on only those impurities in drug products approved after the issuance of guidance that are categorised as degradation products or reaction products of the drug substance with an excipient and/ or immediate container closure system. The guidelines recommend threshold for the identification, reporting, and qualification of impurities based on the extent of drug substance or drug product to which a patient is exposed.

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STRATEGY

This set of guidance recommends that qualification studies of an impurity are appropriate after consideration of the patient population and extent of drug use. ICH Q3A(R2) indicates that “such studies can be conducted on the new drug substance containing impurities to be controlled, although studies using isolated impurities can sometimes be appropriate.” A similar recommendation is included in ICH Q3B(R2). The ICH guidance provides some recommendation on the types of tests that should be performed; however, it does not provide definite recommendations to proceed if one or both of the genetic toxicology tests are positive. It simply states that additional testing, removal of the impurity, or lowering level of the impurity should be considered. ICH Q3C(R3) endorses acceptable concentration limits for diverse classes of solvents. The guidance does not, however, include a recommendation on limiting exposure based upon concerns for genotoxic potential. As per recommendations, only mathematical models should be used for setting exposure limits in cases where reliable carcinogenicity data are available. The ICH guidance on impurities and residual solvents do not apply to drug substances or drug products used during the clinical research stages of development. International Conference on Harmonisation Q3A15 controls impurities in new drug substances, with thresholds for reporting, identifying, and qualifying impurities. ICH Q3B16 is the equivalent guideline for impurities in new drugs. ICH Q3C17 controls residual solvents, and is the first time the ICH applied substance-specific limits. Depending on their forthcoming risk to human health, residual solvents are categorised into three classes. Class I solvents should be avoided, class II solvents have allowed daily exposure limits, and class III solvents have no health-based exposure limits if the daily exposure is 50 mg/day. ICH Q3D is presently under development and will consist of elements and limits for heavy metal impurities. 14

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The ICH M7 guidelines are currently being implemented throughout the pharmaceutical industry and international regulatory agencies because of the number of specific difficulties encountered with previous guidelines.

At this time, released ICH guidelines for impurity limits are not appropriate for most GIs. One issue related to GIs specifically is that the synthesis of drug substances often requires the use of reactive materials which have the capacity to interact with human DNA to cause mutations and cancer, even at extremely low levels. Thus, GIs should be avoided or at least reduced below a defined threshold potential. United States Food and Drug Administration (USFDA)

The USFDA released the draft guidance to address the GI issues that speaks a diversity to characterise and reduced potential life time cancer risk connected with patient exposure to genotoxic or carcinogenic impurities. The Guidelines of impurity profiling in USFDA are mentioned below. (A) Impurities in New Drug Substances Q3A, (B) Impurities in New Drug Products Q3B (R2), (C) ANDAs: Impurities in Drug Substances and (D) ANDAs: Impurities in Drug Products. The recommended approaches include prevention of genotoxic or carcinogenic impurity formation, reduction of genotoxic or carcinogenic impurity levels (maximum daily exposure target of 1.5 µg/day), additional characterisation of genotoxic or carcinogenic risk, and

considerations for suppleness in approach to better support for impurity specifications. In December 2008, the USFDA published draft guidance for industry entitled Genotoxic and Carcinogenic Impurities in Drug Substances and Products-Recommended Approaches. Since then, the guidance has not been published as final and may be substituted by the upcoming ICH M7 guideline. It provides specific recommendations regarding the safety qualification of impurities with recognised or assumed genotoxic or carcinogenic potential. The guidance has described several ways to trim down and to characterise the potential cancer risk with patient exposure to genotoxins and carcinogenic impurities. European Medicines Agency Guidelines:

In June 2006, Europe, the Middle East and Africa's (EMEA) Committee for Medicinal Products for Human Use (CHMP) published a guideline on the limits of GIs in support of a marketing application. This guideline recommends split of GIs into those for which there is ‘sufficient (experimental) evidence for a threshold-related mechanism’ and those ‘without sufficient (experimental) evidence for a threshold-related mechanism.’ The former GIs would be addressed using methods summarised in ICH Q3C(R3) for class 2 solvents. This method calculates a ‘permitted daily exposure,’ which is derived using the ‘no observed effect level or lowest observed effect level’ from the most relevant animal study and incorporating a variety of uncertainty factors. For GIs without sufficient evidence for a threshold-related mechanism, the guideline proposes a policy of controlling levels to ‘as low as reasonably practicable’. It stipulates that every effort should be made to avoid the development of such impurities during drug substance synthesis and, if that is not possible, technical effort should be made post synthesis to reduce these impurities (e.g., purification steps). Compounds that fall into this category are those that interact with

STRATEGY

will be short term, for the management of life-threatening conditions, when life expectancy is less than five years, or where the impurity is a identified substance and human exposure will be much greater from other sources. Conclusion:

From the review, it is quite obvious that identification and regulation of genotoxins in a synthetic process are challenging because of evolving nature and variable points of entry of GIs during complex aspect of drug development

AUTHOR BIO

DNA either directly or indirectly, such as alkylating agents, intercalating agents, or agents that can generate free radicals. Since any exposure to these agents can express some level of carcinogenic risk, and since entire elimination of GIs from drug substances is often unattainable, the presence of a concerning impurity requires the implementation of a perception of an acceptable risk level. Methods of acceptable risk levels are discussed in ICH Q3C(R3), Appendix 3, in reference to class 1 carcinogenic solvents. The EMEA guideline recognises these limitations and, therefore, proposes ‘TTC’ for GIs. The EMEA guideline recommends a TTC of 1.5 µg/day for all potent compounds. The guideline indicates that a TTC value higher than 1.5 µg/day may be acceptable based on a weight-of-evidence approach to the profile of genotoxicity results, in circumstances where the anticipated human exposure

process. Hence, synthetic routes should be screened for the identification of structural elements that cause genotoxicity. The ICH M7 guidelines are currently being implemented throughout the pharmaceutical industry and international regulatory agencies because of the number of specific difficulties encountered with previous guidelines. Furthermore, an appropriate balance needs to be found that takes into account patient safety against the amount of time and resources to quickly get a pharmaceutical product to the market.

Ambikanandan Misra is currently Professor and UGS-BSR Faculty Fellow at Faculty of Pharmacy, The Maharaja Sayajirao University of Baroda, Vadodara. He has been associated with the field of pharmaceutical sciences for more than 39 years. 47 PhD and 136 Master students have completed their dissertation under his guidance. He has 7 books, 45 book chapters and 174 peer reviewed publications in reputed journals. He has filed 29 national and international patents out of which 9 have been granted so far.

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STRATEGY

Is Blockchain the Right Technology for the Pharma Supply Chain?

The pharmaceutical supply chain and blockchain technology are an uncomfortable match in today's environment. Blockchain technology has not yet evolved to meet the manifold demands of the pharmaceutical industry and its many regulatory bodies. Perhaps just as crucially, the many and diverse stakeholders within the pharma supply chain have yet to converge on common standards by which an integrated blockchain solution could be achieved. That said, the future looks bright, with several US-based matchmaker pilot initiatives, backed by influential stakeholders. Grant Thornton believes that we're approaching a positive inflection point for this promising and innovative way to address the complex business problems of the pharma supply chain. Bradley Pedrow, Director, Compliance Risk in Life Sciences, Grant Thornton LLP

marriage between blockchain and the pharma supply chain is not preordained. Two years ago, the pharma industry recognised that blockchainâ&#x20AC;&#x2122;s strengths aligned well to the general 16

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supply chain challenges. Accordingly, several parallel initiatives were undertaken. Given the elapsed time, it makes sense to reassess what we have learned about practical blockchain solutions and about

the pharma supply chain to ensure that connecting these domains creates value. Starting with the pharma supply chain, some of the foundational challenges include product diversion,

STRATEGY

counterfeits, recall efficiency, inventory control, cold chain tracking, and healthcare record interoperability. Of these challenges, perhaps the most pressing was driven by the U.S. FDAâ&#x20AC;&#x2122;s regulation for a secure supply chain, passed in November of 2013, called the Drug Supply Chain Security Act (DSCSA).The DSCSA called for ten-year, phased compliance, culminating in full unit-level traceability by 2023. At the time of its passage, the industry lacked any technology solution to feasibly meet the DSCSA, which is perhaps what initially drove serious consideration of a blockchain-based solution. Why blockchain? At a fundamental level, blockchain solutions are transactional systems that allow for the tracking and/or transfer of assets, the recording of payments, and/or the memorialisation of interactions among participants who require secure, trusted, and transparent record keeping. Consensus among blockchain participants establishes the mechanism by which transactions are

verified and synchronised. Given that blockchain technology is well suited for the secure and immutable memorialisation of transactions among diverse participants, the implications for efficiency and security within pharma are manifold: Trusted: Every product hand-off between trading partners is documented in a trusted record, and the trust is derived from (and enforced by) the consensus of the participants. Distributed: Perfect copies of the transactional detail are replicated across distributed nodes, creating system resilience and mitigating against the risk of hacking, fraud, and/or sabotage. Auditable: No transactional record of trading partners can be edited or deleted; such recordings are immutable, creating an unimpeachable audit trail. Transparent: A blockchain solution could be designed so that all trading partners can see where a tracked asset is, from whence it came, and who interacted with it along the way.

Disintermediated: No one entity, or intermediary, has control over individuated transactions in particular or the system in general, thereby reducing maintenance costs and increasing trust â&#x20AC;&#x201C; for both participants and reviewers, auditors, and regulators. The life science industry certainly has noticed increasing hype around blockchain. The Pistoia Alliance 1, a global not-for-profit group, surveyed 120 life science leaders in June 2016 and found that 83 percent anticipated adopting blockchain by 2021, with nearly one quarter (22 percent) responding that they were already using or experimenting with blockchain. The biggest opportunities identified were in the areas of supply chain and medical records; regulatory issues were expected to be the biggest hurdle. Since 2016, enthusiasm for blockchain has grown rapidly. The industry envisions many opportunities for blockchain in the broader view of supply chain (as depicted below): 1 http://www.pistoiaalliance.org/

Blockchain opportunities in the life sciences LIFE SCIENCE NEED

TRADITIONAL DATABASE

DISTRIBUTED LEDGER

Secure Supply Chain to address DSCSA regulation

Verify the integrity and authenticity of an individual pharmaceutical package

Medical Records across organisations

A single complete healthcare record for an individual across multiple providers/systems

Clinical Trial Data safety and authenticity

Requires costly and time consuming source data validation

Speeds up trials while providing safe and secure platform

Inventory Management data accuracy and authenticity

Costly data discrepancy investigations or inventory write-offs

Offers data security and transparency

Recall Management as timely and complete for patient safety and compliance

Identification of Medicinal Products exchange of product data

Costly and complex regulatory data hub, with difficulty in scaling for future stricter regulations

Reliable and broadly available exchange of pharmaceutical product information

Regulatory Approvals with current and relevant regulatory data

Difficult to collect and make visible information sets across the ecosystem of stakeholders

Transparency, auditability, trust and efficiency through disintemedition

Rapid and inclusive tracking of current inventory

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STRATEGY

Participants within the pharmaceutical supply chain are developing models and use cases to meet the requirements of the DSCSA. Most recently, in June of 2019 FDA invited Merck, Walmart, IBM and KPMG to start a new pilot project using blockchain to meet the DCSCA. Similarly, in 2017, 50 healthcare supply chain stakeholders worked with the non-profit Center for Supply Chain Studies to build blockchain reference models; more detail on this initiative can be found here. These reference models simulate product and data flows that are designed to satisfy the DSCSA regulation. Building upon the reference models, six study teams then conducted their own proof-of-concept implementations. The stated goals of these six studies went well beyond DCSCA compliance; the aim was to create operational efficiencies and to develop funding models for blockchain architectures. In that same year, the blockchain technology company Chronicled brought together a representative group of pharmaceutical manufacturers and distributors to explore how blockchain could improve the supply chain and support track-andtrace efforts. The group named this blockchain project “MediLedger”, providing valuable insights such as how to protect data privacy and how to implement a saleable returns solution. This project continues to track products through the entire supply chain; more detail on this project can be found . In Europe, the Innovative Medicines Initiative (IM2I) has started a health blockchain project targeting four areas in healthcare, one of which is the supply chain. The IMI’s Blockchain Enabled Healthcare program includes nine big pharma companies with a consortium of other stakeholders. This €18 million program is just underway on what is expected to be a three-year program. Uncovering the Roadblocks

The trial implementations referenced above are building functional architec2 https://www.imi.europa.eu/

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The Pistoia Alliance, a global not-for-profit group, surveyed 120 life science leaders in June 2016 and found that 83 per cent anticipated adopting blockchain by 2021, with nearly one quarter (22 per cent) responding that they were already using or experimenting with blockchain.

tures. Each implementation experimented with balancing the challenges intrinsic to blockchain – namely, speed, cost, privacy, proof of work, centralised control, processor demands, and governance. Beyond these proof-of-concept projects, blockchain innovations continue. For example, a concept known as “Proof of Stake” has been implemented for cryptocurrency networks to validate transactions more efficiently, thereby reducing required processing power. Another innovation is “sharding”, a streamlined way of verifying transactions by processing components of a transaction via parallel nodes. As we are seeing multiple blockchain solutions independently evolve, each with their own unique strengths and weaknesses, some interoperability players are emerging that allow for interplay among various blockchain solutions. The interoperability could allow the pharma supply chain to leverage different blockchains for different functional value, potentially providing “best of all worlds” in terms of the strengths of each blockchain. But all of these cutting-edge innovations are stymied by perhaps the greatest challenge to widespread blockchain adoption–standardisation or, more accurately, the absence of standards. Even the most elegant of designs will fail if the pharma community fails to adopt it. The endgame

is to move the whole industry toward a common approach, and standards plus adoption are the keys to that endgame. Because data and products move among trading partners in a complex and interconnected web, it may be unrealistic to expect trading partners to participate in multiple blockchain solutions. As the move to Identification of Medicinal Products (IDMP) has demonstrated, alignment on standards is a slow-moving process, but it is nonetheless the right course for this industry. The evidence for the importance of this alignment abounds in precedents from other industries. In the 1970s, the grocery industry recognised the need for greater efficiency in its check-out lines. Around the same time, IBM introduced a means of storing data within a symbol comprised of black and white lines – the bar code. These symbols could be scanned via computer to capture robust sets of data instantly. By 1974, Wrigley’s gum became the first product to be marked with the UPC barcode. Today, UPC barcodes are ubiquitous in grocery stores because this single UPC barcode standard allows trading partners to exchange trustworthy and standardised data with ease and immediacy. While the barcode is a standard identifier in many industries, the adoption of the barcode for medical devices only recently gathered momentum. This slow adoption rate relates not to challenges intrinsic to the underlying technology but to the length of time it took the healthcare community to coalesce around a single, global data standard (GS1). The same is true for the adoption of blockchain for pharma. It is not the technology advancement that will be the slowest to develop, it will be the coalescence of the industry around a standard blockchain architecture. In the short-term, we will see the implementation of a variety of blockchain approaches to address the current needs of the pharma supply chain, but that variety introduces complexity as a barrier to adoption. The inefficiencies in this industry are pronounced, the

STRATEGY

Standarised blockchain across all supply chain stakeholders

Distributor Receive event

pace of blockchain evolution is rapid, and the demand for solutions is strong. Accordingly, the pharma industry would be well served to work toward standardisation. Blockchain adoption in pharma is a matter of when not if. That said, without standardisation, blockchain cannot realise broad adoption, much less its potential as a disruptive force in pharma and across all of life science. Need for Industry Convergence

Standardisation is difficult to achieve, if the blockchain stakeholders cannot align. The users, business, core developers, miners, and node operators need to collaborate to form an effective off-chain governance community. Unfortunately, governance is yet another blockchain hurdle proving difficult to overcome in pharma. In fact, alignment even within the domain of “users” is challenging, since the concept of “users” incorporates very diverse supply chain participants, including manufacturers, wholesalers, distributors, and pharmacies. Similarly, on-chain governance is taking a long time to realise. In other arenas, blockchain technical design decisions are made by core developers (and ultimately by token-holders and/or participants), but the inability to unify disparate supply chain participants “off chain” makes it profoundly challenging to identify – much less unify – on the standards and practices that comprise effective on-chain governance. However, we should not conclude that pharma as an industry is 20

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a dysfunctional family of stakeholders. All industries struggle with establishing a blockchain governance model. Arguably, the most successful model to date is Bitcoin, and that model continues to evolve – even ten years after its inception. The final major hurdle for establishing a supply chain blockchain is funding. Which stakeholder, or stakeholders, will assume responsibility for paying for the blockchain. The industry has not yet developed the model for sharing the cost even though all stakeholders are likely to benefit. Some stakeholders stand to benefit more than others, but to what degree depends on the blockchain design. For example, distributors are excited about the benefits gained to their inventory management processes, but the benefits would be tempered if they lose competitive advantages across distributors within the new visibility of upstream data flow. Another visibility concern is that of the end patient. If the patient can access a long, complicated – but safe and secure – chain of custody, will it impact customer satisfaction, or their compliance with the doctor’s orders? So the willingness to fund

AUTHOR BIO

Manufacturer Ship event

Patient Administration event

the blockchain will depend on the design of the roles and privileges of stakeholders to address transparency concerns of all stakeholders. We expect to see Drug Traceability blockchain move from pilot and narrowscope application to broader, national solutions in response to regulations such as the DSCSA. Globally, no formal harmonisation effort has yet materialised, but we expect this to change as the technology, governance, drive for change, and funding evolve. Given the increase in collaboration among pharma participants, the increase in data traceability that blockchain promises, and the compliance mandates such as the DSCSA, we envision the next year will bring significant developments that leverage blockchain technologies in the value chain. In turn, we believe the scalability and acceptance of these developments will increase the quality, safety, and the efficient delivery of care globally. Blockchain is a viable solution that is still several years away to prove out for significant investment and adoption. That said, it has all the making to be a game changer.

Bradley Pedrow is a regulatory professional serving clients within Grant Thornton’s Life Science Industry Practice. He has successfully led regulatory compliance and efficiency initiatives with global medical device and pharmaceutical manufacturers. With more than 25 years of life science experience, he has served stakeholders across the value chain.

How we contribute to the success of cancer research. Recently we transported some 2°C to 8°C temperature-sensitive biotech products in special boxes from San Francisco to a Swiss laboratory where cancer drugs are prepared to improve patients’ quality of life worldwide. This is just one of the many success stories we share with our customers.

swissworldcargo.com

We care for your cargo.

STRATEGY

Rasmus Hother le Fevre, Managing Director (Corporate Vice President), Novo Nordisk Pharmatech A/S

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COVER STORY

NOVO NORDISK

PHARMATECH A/S

ENSURING QUALITY ASSURANCE Ensuring quality in formulation: The benefits of using GMP Quats as excipients in topical, nasal and/or ophthalmic applications. Managing Director (CVP)Rasmus Hother le Fevre, Novo Nordisk Pharmatech A/S talks about the industry challenges on product quality and how to ensure a good quality control

Can you explain the role of formal documentation in quality assurance? In this highly competitive market, quality has become the market differentiator for almost all products and services. Quality control is essential to building a successful business that delivers products that meet or exceed customersâ&#x20AC;&#x2122; expectations. It also forms the basis of an efficient business that minimises waste and operates at high levels of productivity. Therefore, we are constantly working on enhancing our product quality.

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STRATEGY

A good plan is only as good as its foundation, so comprehensive and detailed product specifications are critical to success. An important component of product quality is knowing your product. And, that requires detailed product specifications that identifying exactly how the item(s) should turn out. Can you explain the benefits of using GMP Quats as excipients in topical, nasal and/or ophthalmic applications? An innovative synthesis process makes Novo Nordisk Pharmatech a leading supplier of cGMP Quaternary Ammonium Compounds (Quats) for a wide range of applications. High levels of purity for products such as Benzalkonium Chloride, Cetrimide, Cetrimonium Bromide (CTAB) and a range of others make them particularly suited for pharmaceutical applications. They act either as preservatives or active ingredients in many ophthalmic, nasal, oral and topical drugs and in a variety of solutions, ointments and creams. They can also be used as lysing or precipitating agents in vaccine production.

Since standards have become a symbol for products and service quality, customers are now keen on buying a product or service from a certified manufacturer. Therefore, Novo Nordisk Pharmatech are regularly audited by major and minor pharmaceutical companies and inspected by the Danish Medicine Agency. We are also complying with and certified according to standards such as ISO 9001 and ISO 14001. When it comes to our focus, we understand that quality control is a product-oriented process. When it comes to quality assurance, it is a process-oriented practice. When quality control makes sure the end product meets the quality requirements, quality assurance makes sure that the process of manufacturing the product does adhere to standards. Therefore, quality assurance can be identified as a proactive process, while quality control can be noted as a reactive process. Besides quality monitoring, what else can you suggest to ensure quality of materials and products? We always strive to develop and provide high quality products and services that place emphasis on the health and safety of our consumers and customers. With more than 70 years of experience, we want to ensure that the products reaching our customers meet the highest levels of quality and safety. We must incorporate the highest possible standards all along the supply chain â&#x20AC;&#x201C; from raw materials, to manufacturing, packaging and distribution. Controlling quality by utilising product inspections throughout the production cycle reduces sourcing risks and cost and ensures high quality.

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FeF™ Quats are effective at all pH levels. However, their effectiveness increases when the pH increases. The higher the pH, the lower the concentration needed to obtain an antimicrobial effect. As opposed to bacteriostatic/fungistatic compounds which only prevent micro-organisms from dividing (growing), Quats are bactericidal/fungicidal meaning they will kill microorganisms whether they are in a growth phase or not. FeF™ BKC has been tested against several relevant microbial strains and shown to be effective against a wide range of microorganisms at low concentrations. Our production and process know-how allows us to offer Quats with a completely well-defined alkyl chain length distribution, whether it is with our standard chain length or with customised chain length distributions. Our customers also receive a regulatory package, which will help the approval process of their product when using FeF™ BKC.

Hother le Fevre started as a Production Planner in Novo Nordisk A/S in 2000. In 2003 he became the head of Shipping and Customer Service and in 2004 he took up the role as Director for the purification plant responsible of purification of Insulin Levemir and Insulin Aspart. In 2006 he became Corporate Vice President heading up the purification plants and in 2010 relocated to Zürich as Global Marketing Director head of Victoza® Launch Execution Team. In 2012 he became the Managing director & Corporate Vice President at Novo Nordisk Pharmatech A/S.

AUTHOR BIO

How does Novo Nordisk Pharmatech ensure to stay on top of the pace of technology change? We have a clear vision and strategy to develop the business over the coming years. Our customers see us as the market

leader and innovator in the industry, and to meet the coming challenges requires vision and direction. We will continue to match and outperform the market as required. How does Novo Nordisk Pharmatech ensure that industry standards are met, if not exceeded? We do not compromise on quality, which is why our pharmaceutical Quats and recombinant Insulin Human are manufactured in accordance with the highest standards- the cGMP Guide ICH Q7 for Active Pharmaceutical Ingredients. We analyse according to relevant multicompendial pharmacopoeias (e.g. Ph.Eur., USP/NF, JP and BP). Both Novo Nordisk and Novo Nordisk Pharmatech are regularly audited by major and minor pharmaceutical companies, the Danish Medicine Agency as well as the FDA. Our products are used in many different pharmaceutical and biopharmaceutical drug products approved by regulatory bodies worldwide and for some products we also supply a full regulatory package. What are the biggest challenges currently facing the pharmaceutical/healthcare markets and how does Novo Nordisk Pharmatech tackle them? Big legislative and regulatory changes are coming to the industry. There is an increase in regulatory expectations from Innovators and Generics to be able to guarantee patient safety due to today’s expanding global market. We aim to be the best supplier of pharmaceutical ingredients by providing excellence at every step of the supply chain – beginning with a consistent high quality of our products, ensuring continuous availability and a secure global supply chain, to an extensive regulatory documentation living up to the highest available standards. By delivering excellence at every step, we help our customers do the same – whether they’re developing a cure for cancer or a new ophthalmic. We deliver a proven record of product purity, reliability and consistency and can even tailor products for future therapies. We help keep development on track and production flowing for hospitals and patients. How has your definition of success changed over the year? Where do you think the industry is headed? Our definition of success has not changed; we still want to maintain the position of market leader and innovator in the industry. The pharmaceutical industry quality functions are struggling to keep up with the rising demands of regulators. The increasing relevance of global markets (beyond the United States, European Union, and Japan) is adding the complexity of multiple quality standards and regulatory regimes. Compliance, robustness of processes, and efficiency will need to be squared in one equation. That is the reason why we need to be at the very forefront when it comes to meeting the industry standards and ensuring patient safety.

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CLINICAL TRIALS

Compelling Pre-clinical Models

For better prognosis in clinical trials Pre-clinical trials are the windows of clinical phases in drug discovery and developmental practice. Several invitro, invivo and insilico models have been put to use predicting safety and efficacy of drug candidates to qualify entering into clinical phase. Of these, there are some compelling pre-clinical models like that of human sourced stem cell based platform technologies with advantageous features for better prognosis., if adopted in total would revolutionise the very industry, spend, timelines and success. S Dravida, Founder CEO, Transcell Biologics Samhita Bandaru Plano Senior High School Dallas Ria Thimmaiahgari, Sophomore, Biomedical Engineering, Duke University

egardless of dedicated research and efforts from academia and industry that have driven the discovery of new treatments for many debilitating diseases, the human race continues to face significant unmet medical needs for numerous health issues. Critical analysis and introspection highlights the differences between 26

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human diseases and models of disease in practice, and have noted the failure of the latter to predict. Because of this, there has been a section advocating abandoning models and focusing on clinical trials in human patients; however, ethical hurdles to primary screening of molecules in humans are overwhelming. Medical research continues to remain dependent on model systems for establishing efficacy and safety prior to clinical applications. New approaches to validate cellular and animal models of disease that harmonise their behaviour with human disease are now being aggressively considered. These alternatives include reverse translation of human monogenetic disease to establish homologous cell-based disease models, the use of human sourced stem cells, and molecular fingerprinting of diseased tissues. The early stage of discovery, sometimes known as pre-discovery, is the founding phase across both drug discovery and development. This stage sets the path to success if assumed honestly by the discovery team. Drug discovery Research & Development(R&D) is known to be a tedious and lengthy process which is predominantly staged and grouped as pre-clinical phase before reaching the consumer market place. Traditional discovery begins with ideation, identification of a target: a mechanism affected by a diseased condition followed by chemistry to meet the targeted needs of the affected mechanism. Proof of concept (PoC) is to demonstrate that the chemistry in discussion is promising and to further verify that the theory has practical potential. Concept and feasibility tests are performed in the early stages of the design and development process. These tasks are elaborate, expensive, and time intensive; however, performing them methodically and on the right, relevant model system(s) is crucial; it can help in mitigating risk to users and preventing the discovery of unexpected failures during verification and validation. By implementing a risk-based approach in the discovery and pre-clinical phase, the value can pay

Pre-clinical studies are devised to test the effect of the drug on the organism as a whole and also on a specific biological function or system.

off in revenue and avoiding potential disasters. Unexpected failures can lead to stopping the project, a complete redesign of the product and in worst case scenarios, shelving while reasons could be bad choice of pre-clinical models. Pre-discovery, discovery stages have the need to employ pre-clinical models while the robustness and relevance if is ruthless will lead to pre-clinical experimentation. There has been an age old belief that simple model systems provide a powerful tool for developing and exploring new therapeutics. But the world of human therapeutics is different from the world of other species as the two worlds make different assumptions while co-existing. Till date, the hypothesis that if we found drugs that â&#x20AC;&#x2DC;curedâ&#x20AC;&#x2122; fly disease models and then successfully showed the same in the mouse model, the drug would magically enter clinical phase with all the approvals and regulations, and was assumed to be the winning recipe. Because it made sense theoretically, 95 per cent of failed trials did not change the deep rooted belief kicking aside the hard truth. Why Model Systems at All?

Before testing the drug within a human biological environment, conducting pre-clinical studies on model systems that yield preliminary efficacy, toxicity, pharmacokinetic, and safety information is the routine, reflecting on Why

models at all as the question. An increasing change in the drug development pipeline that has emerged in recent years has led to generation of different types of pre-clinical model systems that are surrogates for human disease. Traditionally, the process was limited to the study of drug efficacy in animal models, while the recent discovery and use of CRISPR/Cas9-mediated genome alteration has modernised our ability to generate pre-clinical models containing human pathogenic genetic variants. Any technology that holds great promise in increasing the correlation between pre-clinical and clinical disease prognosis and treatment translatability calls for compulsive adoption. There are broadly three pre-clinical model categories: in vitro (test tube or outside normal biological context), in vivo (within a biological entity like an animal), and in silico (computer simulation of the interactions). In vitro models involve testing a drug outside a living organism, normally on tissues or cells cultured in the laboratory. Initially, these models were built using 2-D systems using tissues or cell lines suspended in petri dishes. However, 3-D models have now been established, with spherical models (constructed using cell lines) and organoids (an artificially grown mass of cells that resembles a particular organ) becoming increasingly popular. The advantages of in vitro models lie in that they can be used easily for large-scale production in pharmaceutical companies. Additionally, the non-requirement of live animals decreases expenses and also dismisses the need for submission of animal protocols in accordance with the AWA (Animal Welfare Act). On a whole, in vitro models present far fewer ethical obligations than animal models do. That said, the absence of a live organism makes it difficult to predict how the drug being tested will interact with multiple organ systems. The lack of physiological exposure means that there is no complex, multicellular response that can be observed. It is also difficult to test the effect of larger, mechanical www.pharmafocusasia.com

CLINICAL TRIALS

devices (as opposed to drugs) in an in vitro setting. In vivo models, on the other hand, involve introducing a drug into a live animal. Animal models used in pre-clinical studies include rats, mice, hamsters, guinea pigs and rabbits and sometimes include calves, swine, and sheep. Pre-clinical studies are devised to test the effect of the drug on the organism as a whole and also on a specific biological function or system. Investigational areas in pre-clinical studies include cardiovascular, endocrine, anti-infective, immune, dermal, musculoskeletal and the central nervous system. These studies are designed to sense a signal that the drug is active on a patho-physiologically relevant mechanism, as well as preliminary evidence of efficacy in a clinically relevant endpoint. A recent advance in the field of animal models is the use of the xenograft, which involves transplanting a human tissue (typically a tumorous one) into an immune compromised animal such that the response of the human tumour

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to a drug can be observed without actually testing on humans. Another recent model is using Genetically Engineered Mice where the genes of mice are altered so that the expression of genes involved in tumor transformation or malignancy is modified. These models are declared to be very useful in assessing the effect of gene mutation/deletion on tumour progression. Using animal models allows for the use of more invasive procedures to assess a drug’s effects, and provides an opportunity for studying the consequences of long-term exposure to a drug. Of course, these advantages come with their own set of limitations, the first being the ethical and legal barriers that are present in animal studies. Additionally, the genetic variability, difference in size, and life expectancy of different animals render them partially unreliable when predicting test results. Finally, it is not always possible to successfully extrapolate the results of an animal study to humans, as the human body may not react to a given substance the same way that animals do. A model that acts as a compromise between the in vitro and in vivo models is the ex vivo model. It involves taking a tissue or organ from an organism and then studying it in an external environment, with conditions maintained such that it is as similar as possible to the environment within the organism. While an ex vivo model may be more useful than an in vitro model in predicting how a drug might interact in a multicellular environment, it is also disadvantageous in that it is quite difficult and expensive to maintain experimental conditions exactly similar to that of a living organism when studying a tissue outside of the organism. Similar to the in vivo system, it also ethically questionable whether it is right to remove tissues and organs from living animals for experimentation. One of the other pre-clinical models is the in silico system, which involves screening chemical compounds against biological molecules virtually. This model makes use of large datasets,

extensive bioinformatics and computerbased algorithms. Popular modelling methods used include Quantitative structure-activity relationship, and specific statistical approaches that employ experimental data and fragment-based technology. One of its advantages is its time-efficiency, with the ability to screen large datasets of chemical compounds in a matter of hours. Similar to in vitro testing, it also bypasses the ethical hurdles posed by animal testing. Another advantage of computer-based models is that algorithms enable any trends or patterns in chemical or biological behaviour to be identified and documented much faster. This model too has most of the same limitations as the in vitro model. The lack of a physiological environment fails to provide knowledge of the drug’s effects in a larger, multicellular system. Hence, tests in an in silico setting alone are inefficient to determine whether a drug is safe or effective to implement in clinical trials. While these current models each hold their own merit as discussed, there still remains a large gap between data from pre-clinical trials and actual clinical results. This is particularly true in the field of oncologics, where research has shown that 9 out of 10 attempts to bring a drug from the pre-clinical to the clinical phase fail. This establishes that there is still a dire need for more relevant pre-clinical model systems to be adopted. “We have moved away from studying human disease in humans. … We all drank the Kool-Aid on that one, me included. … The problem is that [animal testing] hasn’t worked, and it’s time we stopped dancing around the problem. … We need to refocus and adapt new methodologies for use in humans to understand disease biology in humans.” —Dr. Elias Zerhouni., Former US NIH Director. One of the alternative model systems that Pharma has been resisting is the emerging stem cell-based platform technologies.

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CLINICAL TRIALS

Toxicogenomics Signatures

The High Throughput Screening (HTS) activity is part of the drug discovery process, and consists in selecting among thousands of molecules the ones that could have a pharmaceutical use in pre-clinical setting. To do HTS, large compounds libraries or toolbox of molecules are tested on a biological model showing a specific therapeutic target. Human stem cells and their progenies with self-renewable capacity, their ability to differentiate into several tissue progenitors, and their phenotypic responsive nature combined with suitability for Transcriptomics/proteomics define them as a good platform for screening to discover new potential drugs for human diseases. The ability to procure the source, harvest, culture in large scale, batch wise primary progenitors produce make adult stem cells based platforms as the best alternative tools in developing model systems with reproducible, reliable and relevant ones for pre-clinical adoption. These platforms complemented with robots, readers, and a good data mining system, make them a compelling option to replace the irrelevant animal and transformed cell line model systems. Beyond HTS, stem cell-based approaches, search for novel predictive biomarkers of developmental toxicity, and extend the experimental approach to other tissue specific cellular systems for the prediction of developmental neuro, osteo, hepatotoxicity. Well established differentiation protocols for certain adult cell types most susceptible to chemical30

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mediated toxicity, any chromosomal abnormality during early development like cardiac, bone, and neural cells have been successfully developed. For neural cell development, stem cells can be efficiently differentiated in vitro into cell types present in the nervous system like mature neurons, astrocytes, andoligodendrocytes, while the process of differentiation acts as a test platform to evaluate neurogenesis, neurotoxicity kind of end points. On the basis of this approach, new rapid and predictive in vitro screens for developmental neurotoxicity testing have been developed. Even in stem cell based model systems, there are two fundamental criteria like potency and unlimited source availability that make them suitable for investigations spanning traditional discovery to regulatory testings. New exciting avenues of research on the role of microRNA (miRNA) in toxicogenomics and the possibility of epigenetic effects on gene expression opens the possibility to discover new molecular endpoints that might contribute to a further understanding of chemical-mediated developmental toxicity on stem cells based model systems. Furthermore, in line with new directions for toxicity testing, in the light of advances in understanding biological responses to chemical stressors involving the mapping of toxicity pathways in differentiating human stem cells and identification of critical pathway perturbations that represent molecular initiation

events for adverse effects, stem cell-based model systems are the only choice in both exploratory and regulatory testings in pre-clinical phase. www.transtoxbio.com portfolio of stem cell based products, MatTekâ&#x20AC;&#x2122;s tissue models, XCellR8, Reprocellâ&#x20AC;&#x2122;s Biopta are some of the global companies offering alternative pre-clinical model systems and based services as offerings to pharmaceutical research, professional toxicity testing labs. Each of the companyâ&#x20AC;&#x2122;s products/ services are distinct in this space serving the need of the hour to support predictive prognosis of the drug pipeline. AUTHOR BIO

S Dravida is the Founder CEO of Transcell Biologics, Hyderabad, India. She is a technocrat with track record of commercializing research driven findings to business opportunities through Transcell.

Samhita Bandaru Plano Senior High School Dallas

Ria Thimmaiahgari Sophomore, Biomedical Engineering, Duke University

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CLINICAL TRIALS

HEALTHCARE EVOLUTION

THE GROWING USE OF WEARABLES IN CLINICAL TRIALS

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Wearable sensors have the potential to dramatically reduce the duration and cost of clinical trials by enabling objective, real-time, real-world data to be used as health outcomes measures. While most efforts to improve clinical trials have focused on making the existing processes more efficient, wearables represent a real game changer. Geoffrey Gill, President, Shimmer Americas Martina Donohue, Marketing Manager, Shimmer Ltd.

harmaceutical development is in crisis. According to the Tufts Center for the Study of Drug Development, it now costs US$2.6 billion to bring a drug to market, which is a 145 per cent increase in 10 years. While some question Tufts’ methodology, there is no question that costs are exploding. There are many reasons for this dramatic increase, but part of it stems from the changing nature of healthcare. With ageing populations around the world, and the success in treating infectious and other acute diseases, chronic disease management has come to dominate healthcare. In fact, one study indicated that 84 per cent of healthcare spending in the US was on adults with chronic conditions in 2006 and that number will continue to go up. In this context, many of the reliable old measures (such as five-year survival rates) are now irrelevant. Today, many studies end up relying on subjective measures, such as doctors asking patients how they are feeling or how much pain

they are in, to gauge quality of life. Not only is this highly subjective, but patients will just answer based on their experiences during the past one to two days. As a result, these measures are unreliable and uncertain. To get more reliable data, clinical trials need larger sample sizes, which drive higher costs and longer trials. And, often that is not enough. Most pharmaceutical companies have stories of a drug that looked great in Phase 2 trials, only to fail in Phase 3. Adding to pharma’s woes is a crowded market where cost containment has emerged the driving factor. Just about every condition has an existing treatment, and many of them are quite good. As a result, the incremental increased value from new treatments is getting smaller. Profits are getting squeezed. Deloitte conducted a study last year that estimated the return on pharma R&D at 1.9 per cent. That’s less than a U.S. Treasury bond. No company will continue to invest for long at those rates of return.

Clinical Trials are the Major Cost Driver

Clinical trials need to be transformed. There are many efforts being conducted along these lines, but this article will focus on the impact of digital/mobile technologies. Some of the tools focusing on eConsent and eRecruitment are incremental improvements. They make the existing process more efficient, but they do not change the nature of the trials. Transitional tools, like electronic patient-reported outcomes (ePRO), and medication adherence solutions, start to adjust the content of the trial and can have significant impact. But outcome measures need to change to truly transform clinical trials. Novel endpoints change the definition of success for a clinical trial, fundamentally altering the process. Instead of looking at patient-reported outcomes, or the results of tests done every few months in a doctor’s office, putting sensors on the patient allows his or her progress to be documented continuously. For example, an activity monitor on www.pharmafocusasia.com

CLINICAL TRIALS

Transformational Transitional

• Novel Endpoints

• ePRO • eAdherence

Incremental • eConsent • eRecruitment

a patient with Parkinson’s disease or Chronic Obstructive Pulmonary Disease (COPD) can determine quantitatively if their activity level is increasing or decreasing over time. It can even provide detailed gait metrics and analysis of freezing episodes. This activity can be monitored 24 hours a day, seven days a week. In doing so, infrequent and often subjective outcomes are replaced by continuous objective metrics that dramatically improve the reliability of the trial. Transitioning to Continuous, Quantitative Outcomes

Continuous objective measurements dramatically reduce measurement uncertainty. Increased reliability reduces the chances of getting an incorrect assessment from the trial. Therefore, they can be used to reduce sample sizes or potentially shorten the trial. In addition, by monitoring patients continuously, it is possible to detect unexpected deterioration in their overall health, identifying potential adverse events earlier and increasing patient safety. Finally, it may be possible to use the output of the monitoring device to adjust drug doses in some cases. For example, 34

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many patients with Parkinson’s disease experience involuntary movements as a side effect of Levodopa medication. One of our customers has a product that distinguishes between Levodopa-induced tremors and Parkinson’s disease tremors. This information is used to adjust the drug dosage, improving the performance of Levodopa. This type of assessment may be possible in many other cases. But what do global regulatory bodies, such as the U.S. Food and Drug Administration (FDA), think about the use of digital and mobile technologies? They are very supportive. In fact, leveraging real-world data is a key strategic priority for the FDA. With all these benefits and the support of regulatory agencies, wearables should be adopted rapidly. At some level they are. Based on an analysis of Clinicaltrials.gov data, Shimmer estimates that the number of trials using wearables has more than doubled in less than two years. Unfortunately, it was starting from a really low base — under one per cent of trials using wearables — and doubling got the penetration to just over one per cent. What’s Delaying Adoption?

• Lack of accepted endpoints • Proprietary/non-transparent algorithms • Lack of raw data

• Excessive burden on sites and participants • Compliance Even measuring something as simple as weight can require some thought. How many results should you average? What are the thresholds to determine success? Measuring something as complex as continuous activity or sleep really requires industry standards. A second barrier is the use of proprietary, non-transparent algorithms. For example, is Fitbit’s definition of sleep the same as Apple’s? What exactly are ‘steps’? What are the error levels? If there was a questionable result, how could the source of the error be identified? If a participant has 3,000 steps in an hour, were they really active or did they just put their device on the dog? Addressing these issues requires access to the raw data. Raw data, such as those from acceleration, are consistent across manufacturers. Raw data also allow analysts to recalculate results as algorithms improve. A database of raw data can grow and be useful over time. If a bug creeps into the calculation, it can be identified and fixed. Virtually all of the research conducted in academia is based on raw data, allowing sponsors to leverage literally tens of thousands of researcher years of effort. Furthermore, Artificial Intelligence (AI) and big data techniques will almost always work better with raw data. In short, choosing wearables that provide raw data is critical to long-term success. Then, there are the devices themselves. Many of the wearable devices represent a significant burden for participants. Even the best consumer wearables require frequent recharging. Many of the more scientific wearables are clunky. In addition, sites can be required to provide a huge amount of support, which they may not be well equipped to do. If the wearable isn’t really simple to use, compliance will fall and sponsors can be left with huge gaps in the data. That creates additional risk and cost for the trial — something no sponsor wants.

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CLINICAL TRIALS

CTTI Novel Endpoint Tools

But there is hope. For example, in the U.S., the Clinical Trials Transformation Initiative (CTTI), which is a publicprivate partnership established to develop and drive adoption of practices that will increase the quality and efficiency of clinical trials, has some recommendations. As novel endpoints are among the more challenging techniques to adopt, CTTI chose them as one of its first areas to address. The organisation has compiled a selection of tools to help pharma and clinical research organisations (CROs) to move more quickly down that path. • Interactive Selection Tool1 • Flowchart of Steps for Novel Endpoint Development2 • Detailed Description of Steps for Novel Endpoint Development3 • Quick Reference Guide4 These tools provide a roadmap for qualifying novel endpoints. Shimmer has also identified several success factors for moving forward. Leverage Academic Research

There is no question that the science required to make wearable data useful can be challenging. Fortunately, many smart people have been working on answers for years. Shimmer sensors alone have been used at more than 1,000 leading institutions for more than 10 years. Much of this research is publicly available — thousands of these results have been reported at dozens of conferences each year for more than a decade. Of course, academic work generally does not result in a product. But the basic science has often been done. All that is left is the engineering. And the original researchers are often able and 1 https://www.ctti-clinicaltrials.org/files/interactiveselection-tool.xlsx 2 https://www.ctti-clinicaltrials.org/files/novelendpointsflowchart.pdf 3 https://www.ctti-clinicaltrials.org/files/detailedsteps.pdf 4 https://www.ctti-clinicaltrials.org/files/quickreferencefda-contact.pdf

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eager to help to adapt their work for clinical trials. Learn from Other Industries

Many industries use remotely deployed sensors, and there is a lot to be learned from them. For example, Innerscope Research, Inc. developed a consumer neuroscience kiosk that enabled medical-grade electrocardiography (ECG), galvanic skin response (GSR), eye tracking, and facial action coding results to be obtained very efficiently from study participants viewing advertising materials in malls and movie theatres around the country. Researchers could download content and recruiting specifications on a Thursday night and by Friday morning be recruiting and running tests. They could get participants set up, expose them to 8-10 minutes of content, ask them some survey questions, and complete the whole study in about 20 minutes.

The data would be automatically uploaded and available immediately. They routinely collected data on 250 participants and could have easily scaled up to 2,000 participants in a weekend. That team collected data from more than 100,000 people. The total average cost per participant was less than US$50. What can we learn from this? Every part of the process was integrated, from recruitment to content selection, to data upload. The custom content was selected in real-time based on the demographics of the individual recruited. The entire project was managed in real-time. The researchers could see at a glance what data were being collected. If certain sites were having trouble recruiting their quotas, their quota could be moved to another site. Perhaps the most important lesson is collaboration. Innerscope did not build this system alone; it partnered with

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CLINICAL TRIALS

Pharmaceutical Companies Need to Lead

Collaboration is critical, but the reality is that pharma needs to take a leadership role. It is a matter of simple economics. Let’s consider the potential value generated by the introduction of wearables. Tufts estimated the cost of bringing a single drug to market at US$2.6 billion. We estimate the entire market for wearables in clinical trials at less than half that —US$1 billion per year. A 20 per cent saving in the cost of bringing a single drug to market is likely larger than the entire profit generated by all wearables companies in this market in a year. First of all, pharma needs to collaborate with a variety of partners to define new endpoints. No company is going to gain a competitive advantage from proprietary endpoints. Everyone — pharma, regulators, healthcare systems, and patients — will benefit if the industry agrees on standards. An important step in this collaborative development has been initiated in Europe with the €50 million Mobilise-D project to define appropriate endpoints for motion-based sensors. Second, pharma needs to fund exploratory research as part of its ongoing clinical trials to help support the development of endpoints. The incremental cost would be relatively modest, but there is no way that wearables companies can economically do this on their own. Finally, pharma needs to allow access to data to enable the development of algorithms and endpoints. Although intellectual property is the lifeblood of pharma, this area is pre-competitive. We believe that data generated in a trial should belong to the sponsor. But, fortunately, when asked most sponsors grant access to that information so

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Based on an analysis of Clinical trials. gov data, Shimmer estimates that the number of trials using wearables has more than doubled in less than two years. Unfortunately, it was starting from a really low base—under one per cent of trials using wearables— and doubling got the penetration to just over one per cent.

that we can develop our algorithms. We encourage sponsors to continue to expand that approach. Wearables Vendors Need to Collaborate

Of course, the responsibility for progress doesn’t all fall on pharma. Wearables companies need to do their share. In fact, we recommend that sponsors consider several key attributes when looking for a wearables partner. First, the wearable needs to provide raw data. Using wearables without

getting the raw data leads to a dead end. Raw data are required to leverage academic work, understand anomalies, and develop a database that can be used going forward. Second, wearables companies must be willing to collaborate and be transparent with their algorithms. Not only do researchers need access to raw data, but they also need to know how it is processed, so they can share that knowledge across the industry. It may be difficult for some wearables companies to accept, but the industry needs to find other ways in which to compete. And last, a wearable sensors platform should be optimised for clinical trials. Participants need to be able to put on the sensor and not touch it for an extended period (months, not days) — no recharging, no data uploads, or anything else required. Ideally, participants would never need to take it off, even when showering or bathing. Raw data need to be uploaded automatically to a completely integrated system with a dashboard that allows the CRO to track what is happening by site and drill down to an individual device if a problem arises. There have been several themes throughout this article, but the most important one is the need for collaboration. The opportunity to improve clinical trials is huge and we will be able to achieve it much faster if we work together.

Geoffrey Gill is the president of Shimmer Americas. In addition to leading all U.S. operations, he is heavily involved in global product strategy and is the product champion of the Verisense™ platform – a wearable sensor solution designed from the ground up to meet the challenges of clinical research.

AUTHOR BIO

Shimmer and eWorks and leveraged their technologies and capabilities. As a result, the whole system was built and operational in less than a year.

Martina Donohue is marketing manager for Shimmer Ltd. She is responsible for developing Shimmer’s global marketing strategy for its wearable research and enterprise products and for managing Shimmer’s brand in the clinical health and consumer neuromarketing fields.

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RESEARCH & DEVELOPMENT

FOUND IN TRANSLATION Building an early development strategy for complex biologics

This article will describe a translational pharmacology roadmap for complex biologics in early development, spanning new molecular entity declaration to Phase 1 clinical study design, and including milestone activities such as developing a target product profile, evaluating first-inhuman risk, and selecting the first-in-human starting dose. Aaron Moss, Director, Integrated Drug Development Group, Certara Strategic Consulting Suzanne Minton, Manager, Scientific Communications, Certara Christina Mayer, Associate Director, Clinical Pharmacology, Integrated Drug Development Group, Certara Strategic Consulting

hat is a Complex Biologic? Biologics are drugs isolated from natural sources, and include proteins, nucleic acids, viruses and cells. Biologics are usually complex mixtures produced by biotechnology which are not as easily characterised or manufactured as small molecule drugs. They are typically administered parenterally or subcutaneously to bypass degradation in the gastrointestinal tract. Complex biologics have development complexity arising from novelty of the platform, target(s), mechanism(s), nonclinical to clinical translation, manufacturing, or development strategy. Examples include bi-specific platforms, Chimeric Antigen Receptor (CAR) T-cell therapies, vaccines, Antibody-Drug Conjugates (ADCs), and gene therapies. 40

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Requisite Development Milestones

A few important milestones that need to be met during drug development are New Molecular Entity (NME) declaration, pre-Investigational New Drug (IND) or Preclinical Trial Application (CTA) meeting, and IND/CTA submission. In preparation for these milestones, it is critically important to prospectively establish a preclinical / translational strategy to answer critical questions related to biology, pharmacology, and toxicology, which will drive formation of a strong clinical development plan. What data are required to move your therapeutics through these milestones? How are you going to collect these data? When do you need them? For complex biologics, answering common preclinical development questions often involves

RESEARCH & DEVELOPMENT

determining what to do in the absence of certain data or models. Much like painting a picture, the integrated body of data will point to the answer(s). Establishing a Target Product Profile

The Target Product Profile (TPP) is a dynamic resource that serves to guide development decisions across functional areas by creating alignment around attributes and outcomes for a product candidate. The TPP should be considered a living document that evolves throughout development as additional information is generated and integrated. Assessing First-in-Human (FIH) Risk

The goal of an FIH risk assessment is to understand potential safety concerns relating to administration of the therapeutic and help guide the starting dose selection strategy. To determine the level of risk associated with a compound, drug and system characteristics should be considered, including novelty, mechanism, potency, specificity, species or model relevance, safety findings, pharmacodynamics (PD), time course and reversibility of effects, off-target effects, exposure-response and exposure-safety relationships, and translatability. Critical questions including, but not limited to, the following list should be answered to guide the risk assessment for your candidate product: • Is any component of the therapeutic novel? Is it a novel drug substance or product, target, or platform? • What is the biological mechanism of the human target? What is the structure, regulation, tissue distribution, expression, and disease specificity for the target? Does the biological mechanism have potential for uncontrolled downstream effects the magnitude of which should be considered, for example, cytokine release syndrome (a potentially fatal systemic inflammatory response)? • Does the drug cross-bind to similar targets? Are there potential off-targets closely related structurally and functionally to the intended one? • Is the translational animal model relevant and, if so, in what aspect is it relevant? What is known about interspecies differences in target expression, distribution, structure, Pharmacokinetics (PK) and metabolism, www.pharmafocusasia.com

RESEARCH & DEVELOPMENT

PD, on- and off-target binding affinities, target engagement and Receptor Occupancy (RO)? For example, perhaps target expression in a non-human primate is much lower compared with humans, and that would need to be considered in a translation • What are the characteristics of the safety findings in preclinical toxicology studies? What are the potential safety findings in humans? • What are the PD characteristics, and what is their relationship to PK? Are there irreversible drug effects or long lasting findings? What is the shape of the doseresponse curve? • What are the uncertainties related to projection of human exposures? How relevant and specific are the inputs being used to calculate the FIH starting dose? How accurate is the human PK projection based off the target-mediated drug disposition observed in a non-human primate? How reliable are the “minimum anticipated biological effect level” (MABEL) assays? What percent RO is appropriate for the target mechanism? By considering these characteristics, you can develop a sense of the overall relative risk (low, moderate or high) for a drug being administered to humans for the first time and can then implement strategies to mitigate specific risks in both clinical dose selection and study design. A deep understanding of the molecular engineering, biology, toxicology, pharmacology and translational science is required to properly evaluate risk in an FIH study, and this requires cross-functional team integration across areas of expertise.

• MABEL for the highest risk molecules, where the most sensitive and specific in-vitro assays would likely be used • Modified MABEL for moderate-tohigh risk molecules, where target RO, Minimal Pharmacologically Active Dose (MPAD), or Minimally Effective Dose(MED) based on pharmacology parameters are utilised • A toxicology parameter, such as No Observed Adverse Event Level (NOAEL) or Highest Non-Severely Toxic Dose (HNSTD), scaled to a Human Equivalent Dose (HED). Typically, more than one method is used to calculate potential starting doses and knowledge of similar drugs is also considered; integration across approaches results in triangulation on the selected (optimal) starting dose. A starting dose calculated from MABEL approaches will usually be lower than a predicted optimal biologic dose. The lowest starting dose, while safe, is not always the best choice. In the case of a low-risk complex biologic, such as for a well-understood target, platform, or mechanism with substantial clinical precedent, a higher starting dose using a toxicology-based approach may be acceptable. Use of NOAEL or HNSTD requires appropriate toxicology species and justification. Following conversion of the NOAEL dose into an HED, a safety factor of 10 or other multiplier may be added to account for differences in affinity, expression, or other unknowns. 100%

MABEL

Therapeutic window

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Unacceptable toxicity

NOAEL

FIH Dose Selection

Selecting the FIH starting dose is a truly difficult aspect of preclinical development. Complex biologics, especially those that modulate the immune system, have the potential for exaggerated and unexpected pharmacology. Preclinical models often fail to predict the potential for human toxicity. They may also underestimate or fail to predict beneficial immune modulation. The major dose selection methods include:

In the case of high-risk complex biologics, an in-vitro calculated MABEL is likely most relevant for dose selection. Certain drug candidates may be considered high risk for multiple reasons, including a possibility of unexpected cytokine release, a novel mechanism of action, or difficulty in calculating an FIH dose due to limited data. A master ‘MABEL Table’ is recommended to summarise the key pharmacological assay results under consideration for MABEL or modified MABEL starting dose selection (see Figure 2). Notably, this table can enable meaningful comparisons across assays as well as with comparator molecules. For MABEL calculation, relevant assays should be considered, which include those that are closest to the mechanism of action. The selected assay is typically the most sensitive of the parameters relevant to the mechanism of action. Once the FIH MABEL dose is calculated, the team must then also consider the feasibility of formulating and administering the MABEL starting dose to patients as well as whether the MABEL dose will provide any clinical benefit. In the case of moderate- to high-risk biologics, a modified MABEL approach may be employed, which often uses in-vivo RO to understand the proportion of a pharmacological target receptor that is bound by drug. In theory, the response to a drug increases with increasing RO. By establishing a human PK projection

Dose escalation

Effect

Animal tox Minimal PD Effect 10

100

1000 Dose or exposure

10000

Figure 1: Relationship between MABEL, NOAEL, therapeutic window and toxicity in FIH trial. Liu, Pharmacokinetics of monoclonal antibodies and Fc-fusion proteins, Protein Cell. 2018 Jan; 9(1): 15–32. (http://creativecommons.org/ licenses/by/4.0/)

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OUTPUT Assay

PROCESS

Read-out

Human

CynomolgusMonkey

Human

CynomolgusMonkey

Biacore/SPR

KD=?

low cytometry (B Cells)

KD=?

Whole blood

EC 50

Lymph node-like

EC 50

Proliferation

EC 50

CD 86

EC 50

CD 23

EC 50

HLA-DR

EC 50

Binding affinity

Cytokine release

B-cell

Figure 2: Example â&#x20AC;&#x2DC;MABEL Tableâ&#x20AC;&#x2122; compiled to summarise key pharmacological assay results under consideration for MABEL starting dose selection

from your most relevant species, such as non-human primates, you can then link PK to the RO established in preclinical models to project human RO. The goal is to determine what human PK and what dose of drug can result in your target percent RO. Early Clinical Development Strategy for Complex Biologics

The primary objective for a Phase 1 FIH study is to demonstrate safety, and selection of a safe starting dose is critical to achieving this objective. However, clinical pharmacology strategy for biologics in early development extends beyond starting dose, particularly in oncology and other indications where Phase 1 studies are conducted in patient populations and the potential benefit must also be considered with the risk. In addition to starting dose, other Phase 1 dosing considerations for complex biologics may include evaluating the need for repeated dosing, exploring feasible dosing intervals based on the ability to achieve PK and/or PD targets, the decision to use weight-based or flat dosing, dose escalation increments and targeted dose range based on the anticipated therapeutic window, and setting a maximum dose in the absence of dose limiting toxicity (DLT) or safety signals. As with FIH starting dose selection, the strength 44

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of these dosing recommendations will depend upon the quality of preclinical data generated to inform them, such as dose-ranging PK/PD and efficacy studies in relevant animal models. A robust clinical pharmacology strategy also includes study design and analysis considerations such as DLT period duration, 3+3 vs adaptive design, sentinel dosing, expansion and PK/PD cohorts, strategic sampling for PK, RO, anti-drug antibody (ADA)/immunogenicity, and PD to drive robust mechanistic modelling and exploratory analyses, timing of bioanalytical assay readiness, interim cohort-by-cohort analyses, iterative population PK analyses, and early dose-safety or dose-response evaluations. For Phase 1 combination studies, dosing considerations include combination dose and interval for all agents driven by an understanding of potential synergy and drug-drug interactions, patient-level escalation and de-escalation plans to ensure interpretability of resulting data, sequencing, duration of dosing, and intelligent sampling plans for identification of changes in PK, RO, ADA, and PD as compared with mono-therapies. Choosing the Right Biomarkers to Model PD

Progressing clinical development requires making important decisions often in the

absence of guidance. PD biomarkers can inform those decisions if critical questions have been clearly established earlier in preclinical development. In the early development of complex biologics, where PD biomarkers are commonly included as an exploratory endpoint of Phase 1 studies, strategies which are not recommended include creating a list of biomarkers without clear rationale, implementing a nonspecific shotgun approach to investigate panels of biomarkers for a possible lead, or exclusion of biomarkers with sole reliance on outcome measures. Instead, it is crucial to leverage the expertise of translational research and pharmacology experts to design and implement intentional biology-driven biomarker strategies which can be used to enable key development decisions. Recommended Phase 2 Dose Selection

In Phase 2, the primary objective is proof of concept for efficacy, and selection of the optimal biologic dose as the Recommended Phase 2 Dose (RP2D) is critical to achieving this objective. Recommended Phase 2 dose selection considers the totality of available data, including safety, PK, PD, efficacy, modelling and simulation, and target product profile. For complex biologics, PD biomarkers are especially critical for

RESEARCH & DEVELOPMENT

elucidating biology to drive RP2D selection in the absence of maximum tolerated dose. Ultimately, we evaluate all the available information to try to understand drug behaviour and patient responses. The quantitative relationship between all parameters and the time course of all endpoints are used to drive rational decisions for RP2D regimen (dose and interval). As with Phase 1 dose selection, RP2D selection is like painting a picture, where the integrated body of data will point to the answer(s).

AUTHOR BIO Aaron Moss is a Director in the Integrated Drug Development Group at Certara Strategic Consulting. Moss has 10+ yearsâ&#x20AC;&#x2122; experience in translational modeling and simulation and supports the progression of lead candidates for discovery and early clinical development through to regulatory submission. He has a PhD in Pharmaceutics from the University of Washington.

Suzanne Minton is the Manager of Scientific Communications at Certara. She has a PhD in Pharmacology from the University of North Carolina - Chapel Hill.

Summary

Biologics are growing in complexity. Key milestones that must be carefully considered in early development include the TPP, FIH safety risk evaluation, FIH starting dose selection, and Phase 1 study design. By using a well-designed clinical pharmacology roadmap, we can drive complex biologics toward successful marketing authorisation and bring new safer, more effective drugs to market.

Christina Mayer is an Associate Director of Clinical Pharmacology in the Integrated Drug Development group at Certara Strategic Consulting. Mayer has expertise in non-clinical, translational, and early- to mid-stage clinical development of biologics. She has a PharmD from the University of North Carolina - Chapel Hill and completed a postdoctoral fellowship in Clinical PK/PD.

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COMPUTER AIDED DRUG DESIGN IN PHARMA R&D The number of new US FDA approved drugs is declining in spite of lots advances made in science. This fact signifies the complexity of drug development process. Pharma companies are closing down their R&D efforts and hoping that recent advances in computational techniques provide a solution to improve the efficiency. Mallikarjuna Rao Pichika, International Medical University | Kit-Kay Mak, International Medical University

Molecular Entities (NMEs) approved by the United States Food and Drug Administration (US-FDA) is shown in Figure 1. NME is defined as medication containing an active ingredient that has not been previously approved for marketing in any form in the United States. Although the number of US-FDA approved NMEs per annum has remained constant over the years, pharma R&D efficiency (NMEs approved per billion US$ spent on R&D) is declining. The reasons for this decline could be attributed to stringent requirements imposed by US-FDA especially after disastrous thalidomide incident. During the 1960s thalidomide was marketed as a mild sleeping pill. However it caused thousands of children to be born with malformed limbs.

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60 50 40 30 20 10 0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 (1st half)

Pharma R&D landscape : The number of New

Figure 1: The new molecular entities (NMEs) approved by US-FDA since 1993.

RESEARCH & DEVELOPMENT

Drug Discovery Strategies

The main chronological strategies that have been used in drug discovery are phenotypic screening followed by target-based screening and drug repurposing. Phenotypic screening involves testing of a large number of randomly selected compounds in a systems-based assay. Target-based screening involves manipulation of a selected enzyme or receptor to produce a desired therapeutic response. In general, the minimum duration of drug discovery cycle from concept to market in either phenotypic or target-based screening is 10 years while it takes only three years in drug repurposing. Recently, Big Pharma have tended to incline towards computational techniques for the discovery of innovative drugs with the hope of improving the R&D efficiency. The two main approaches in computer aided drug

discovery (CADD) are structure-based drug discovery (SBDD) and ligand-based drug discovery (LBDD), which could be applied in all the aforementioned drug discovery strategies. In SBDD, three-dimensional (3-D) structure of protein is analysed to identify potential binding sites and key interactions producing respective pharmacological activities. Using this information, attempts are made to discover novel drugs with high potency and selectivity. In LBDD, the structure of target protein is unknown and it focusses on chemistry of bioactive ligands to develop a structure-activity relationship between physiochemical properties and bioactivities. Using this information, novel ligands will be designed with improved bioactivity. Figure 2 shows the various computational tools used in all the three types of drug discovery strategies.

Structure Based Drug Design (SBDD)

Bioinformatics

Docking Molecular dynamics

Docking Molecular dynamics Pharmacophore modelling De novo design

In silico ADMET profiling PB-PK simulation

For treatment of another disease

Validation

Assay

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Target Fishing Reverse docking

SAR/QSAR Pharmacophore modelling Similarity search Shape search Ligand Based Drug Design (LBDD)

Bioinformatics Target fishing Docking Reverse docking Molecular dynamics Pharmacophore modelling De novo design SAR/QSAR Similarity search Shape search

For treatment of one disease

Figure 2: Drug discovery strategies and associated computational tools

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Structure-based Drug Discovery (SBDD)

This approach is used if both the target protein structure and ligand are known in which the ligand inhibits the activity of the protein through competitive binding mechanism. It is neither a single tool nor technique but it a mixture of both experimental and computational techniques. It has the highest success rate, therefore it is a preferred method of CADD approach. A typical flow chart of activities in SBDD approach is shown in Figure 3. Ligand-based Drug Discovery (LBDD)

This approach is used if the target protein structure is not known but the ligand structure is known in which the ligand modulates the function of the protein. It has a lower success rate compared to that of SBDD. It is a mixture of both experimental and computational techniques. A typical flow chart of activities in LBDD approach is shown in Figure 4. Representative Success Stories of CADD

Figure 3: Typical workflow in Structure based drug discovery

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A binding pocket for a new class of drugs to treat AIDS was discovered using docking while considering the flexibility of the receptor through molecular dynamics. This information leads to discovery of orally available HIV integrase inhibitor, raltegravir (IsentressÂŽ), approved by FDA in 2007 and received approval for paediatric use in 2011. The same molecule (HTS466284), a 27nM inhibitor, was discovered independently using virtual screening by Biogen IDEC and traditional enzyme and cell-based high-through put screening by Eli Lilly. The computational work involved pharmacophore-screening of 200,000 compounds and used as a starting point. The compound discovered experimentally at Lilly required in vitro screening of a large library of

RESEARCH & DEVELOPMENT

Drug Design

compounds to find potential inhibitors in a TGF–β–dependent cell-based assay and chemical synthesis. A CADD program (homology modelling, virtual screening, hit to lead optimisation and in silico profiling) led to clinical trials of a novel, potent, and selective anti-anxiety, anti-depression 5-HT1A agonist in less than 2 years from the start and requiring less than 6 months of lead optimisation and synthesis of only 31 compounds. Applying QSAR algorithms to toxicity data and corresponding chemical structures led to the development of in silico tools that predict toxicity response (mutagenicity, carcinogenicity) and toxicity dosing (no observed effect level, NOEL; maximum recommended starting dose, MRSD). Aggrastat (Tirofiban), from Merck, a GP IIb/IIIa antagonist (myocardial infarction, it is an anticoagulant and platelet aggregation inhibitor, proteinprotein interaction inhibitor) results from a lead compound that was further optimised using ligand-based pharmacophore screening.

Figure 4: Typical workflow in Ligand based drug design approach

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THE DATABASES AND ANALYSIS TOOLS FOR CADD 1. Commercially available compound databases. 2. Pharma compound libraries through ‘Open Innovation’ programme 3. NIH Clinical Collection consists of compounds that have were used in human clinical trials 4. RepoDB, a comprehensive database of approved and failed drugs and their indications 5. Zinc Database: Commercially available chemical compounds. 6. TDR Targets contains genomic and chemical datasets mainly for identification of drugs and drug targets in neglected diseases 7. PROMISCUOUS is a database of protein–protein and drug–protein interactions 8. cMap is a catalogue of gene expression data collected from human cells treated with chemical compounds and genetic reagents. 9. ChEMBL:Series of drug discovery databases. 10. Chemspider: RSC Chemical compounds. 11. CoCoCo: Multiconformational molecular databases for High-Throughput Virtual Screening. 12. SIDER is an information portal on marketed medicines and their recorded adverse drug reactions 13. NCGC Pharmaceutical Collection (NPC) is a resource of clinically approved drugs 14. DrugBank: Detailed drug (i.e. chemical, pharmacological and pharmaceutical) data. 15. PubChem: NCBI database of chemical compounds. 16. TCM: Database on traditional Chinese medicine, for virtual screening. 17. SCUBIDOO: Virtual products originating from building blocks and organic reactions. 18. Mcule database: Commercially available small molecules. 19. WOMBAT: Database of compounds with bioactivity annotations. 20. Approved Drugs: FDA approved drugs. 21. e-Drug3D: Database of U.S. pharmacopeia of small drugs. 22. GLASS.: Database of experimentally-validated GPCRligand interactions. 23. Structural Database (CSD: Repository for small molecule crystal structures in CIF format. 24. SPRESIweb: Integrated database containing over 8.7 million molecules, 4.1 million reactions, 658,000 references and 164,000 patents covering the years 1974 - 2009. 25. MMsINC: Database of non-redundant, annotated and biomedically relevant chemical structures. 26. ZINClick.: A database of triazoles generated using existing alkynes and azides, synthesizable in no more than three synthetic steps from commercially available products.

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27. KKB (Kinase Knowledgebase): Database of kinase structure-activity and chemical synthesis data. 28. DUD.E. (Database of Useful Decoys: Enhanced): DUD-E is designed to help test docking algorithms by providing challenging decoys. 29. GPCR-Bench: Provides a high quality GPCR docking benchmarking set. 30. GLL. (GPCR Ligand Library): Database of 25145 ligands for 147 GPCRs. 31. GDD. (GPCR Decoy Database): For each ligand in GLL, 39 decoys were drawn from ZINC ensuring physical similarity of six properties (molecular weight, formal charge, hydrogen bond donors and acceptors, rotatable bonds and logP), but structural dissimilarity. 32. LEADS-PEP: A benchmark dataset for assessing peptide docking performance. 33. DNP (Dictionary of Natural Products): Comprehensive and fully-edited database on natural products. 34. ChemIDPlus: Database of compounds and structures by US National Library of Medicine 35. ChemBank: Data derived from small molecules and smallmolecule screens, and resources for studying the data. 36. eMolecules: Database of unique molecules from commercial suppliers 37. GLIDA (GPCR-Ligand Database): Information on both GPCRs and their known ligands. 38. Comparative Toxicogenomics Database (CTD): Database of manually curated data describing cross-species chemical-gene/protein interactions and chemical and gene disease relationships to illuminate molecular mechanisms underlying variable susceptibility and environmentally influenced diseases. 39. SuperDRUG2: Database of more than 4,600 active pharmaceutical ingredients. 40. Ligand Expo: Provides chemical and structural information about small molecules within the structure entries of the Protein Data Bank. 41. Glide Ligand Decoys Set: Collection created by selecting 1000 ligands from a one million compound library that were chosen to exhibit "drug-like" properties. Used in Glide enrichment studies. Provided by Schrödinger. 42. Glide Fragment Library: Set of 441 unique small fragments (1-7 ionization/tautomer variants; 6-37 atoms; MW range 32-226) derived from molecules in the medicinal chemistry literature. Provided by Schrödinger. 43. Virtual library Repository: Libraries of 30,184 (redundant) and 4,544 small-molecule fragments, all less than 150 dal tons in weight, derived from FDA-approved compounds. 44. NRDBSM (Non Redundant Database of Small Molecules): Database aimed specifically at virtual high throughput screening of small molecules.

RESEARCH & DEVELOPMENT

Conclusion

CADD, combined with biophysical approaches and HTS, does help the drug discovery process. CADD approaches assist in decision making, contribute to improve the R&D efficiency, generate new ideas and concepts, suggest solutions to problems and rapidly test the hypothesis. They allow the investigation of the activity of new compounds before they are even synthesised. CADD approaches also help to analyse millions of heterogeneous data points originating from multiple sources. They assists in identifying the either molecular mechanism or polypharmacology or ADMET properties of a compound. Now-a-days, there is a massive improvement of data mining and artificial intelligence technologies for systematic analysis of massive data that is being generated by both experimental and computational experiments. Analysis of 142 drug discovery and development projects from Astra Zeneca revealed five critical factors (5R frame work; Right Target, Right Tissue, Right Safety, Right Patients and Right Commercial Potential) that could improve the R&D efficiency.

AUTHOR BIO

45. ChEBI (Chemical Entities of Biological Interest): Freely available dictionary of molecular entities focused on ‘small’ chemical compounds. Provided by the European Bioinformatics Institute. 46. KEGG DRUG: Comprehensive drug information resource for approved drugs in Japan, USA, and Europe. 47. Bingo” Relational database management system (RDBMS) data cartridge that provides fast, scalable, and efficient storage and searching solution for chemical information. 48. JChem for Excel: Integrates structure handling and visualizing capabilities within a Microsoft Excel environment. 49. ChemDiff: Indigo-based utility for finding duplications and visual comparison of two files containing multiple structures. 50. IXTAB: It is a transversal compounds library management tool to create, import, explore and analyse databases. 51. e-LEA3D: Searches the FDA approved drugs either by keyword or by substructure. 52. Combinatorial library design: Web server providing a click chemistry engine to connect one or more reactants on a central core (scaffold). 53. eDesign: Web server providing a de novo drug design engine to create new molecules either from scratch (lead-hopping) or based on a userdefined scaffold on which R-groups have to be optimised. Alternatively, the same tool can be used to screen a library of molecules. 54. GFscore: Web server to discriminate true negatives from false negatives in a dataset of diverse chemical compounds using a consensus scoring in a Non-Linear Neural Network manner. 55. wwLig-CSRre: Online Tool to enrich a bank a small compound with compounds similar to a query.

Zanamivir is a neuraminidase inhibitor (transition-state analogue inhibitor) used in the treatment and prophylaxis of influenza caused by influenza A virus and influenza B virus. Zanamivir was the first neuraminidase inhibitor commercially developed and It is currently marketed by GlaxoSmithKline under the trade name Relenza as a powder for oral inhalation.

Mallikarjuna Rao Pichika, Professor, Associate Dean (Research & Consultancy) and Head of Centre of Excellence for Bioactive Molecules and Drug Delivery at Internatoinal Medical University, Kuala Lumpur, Malaysia. He is specialised in medicinal chemistry with special interest in computational drug discovery approaches. He authored numerous number of research publications and hold few patents.

Mak Kit-Kay, Lecturer in Pharmaceutical Chemistry department with lots of enthusisam in Artificial intelligence. She is the recipient of Wellcome Trust Fellowship from Wellcome Centre for Anti-infectives Research and Artificial intelligence molecular screen (AIMS) award from Atomwise. She is one of the top 3 contestants in the BioSolveIT Scientific Challenge.

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MANUFACTURING

MESSY

MARKETING

Deliberate disordering can improve your strategic marketing planning In pharmaceuticals, the strategic marketing process is typically a formal, structured process. Whilst this may be efficient, it is often ineffective at generating novel thinking and differentiated strategies. But it doesn’t have to be this way. By making the process a little messier – adding problems that aren’t normally considered, adding personnel who aren’t normally involved, setting objectives that aren’t normally considered – strategic leaders can stimulate innovative, counter-intuitive thinking. This article describes practical approaches to making your strategic planning process less tidy but more effective. Brian D Smith, Managing Director, PragMedic

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n any large life science company, strategic marketing planning is a carefully organised, timetabled and structured process. There are several good reasons for this: a systematised procedure is necessary to coordinate multiple, cross-functional activities; a clear methodology, in which every step is visible, is essential when justifying large investments; and the exceptional technical and commercial risks inherent in the life sciences industry can only be mitigated by a deliberate and rigorous process. But this regimented approach also has disadvantages. It often leads to

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tick-box behaviour, in which the goal is to fill-out templates rather than to add real value. Mechanised processes encourage mechanised thinking, resulting in plans that look much the same from year to year. And tightly controlled processes also tend to drive out innovative ideas because adherence to the process is valued above the quality of the output. In practice, many executives find the annual strategic planning a laborious task with limited value. But strategic marketing planning needn’t be a robotic act that leads to unoriginal thinking and cookie-cutter strategies. In this article, I look at how the annual planning cycle can be shaken up so as to keep its strengths whilst avoiding its weaknesses. Deliberately Disordered Marketing Planning

The strategic marketing planning process is a cycle of four fundamental stages (see box 1, derived from the work of Professor Malcolm McDonald). All effective marketing processes include these four stages, even if they are sometimes implicit. And each of these four stages offers the opportunity to deliberately disorder the process to create better outcomes without losing the benefits of a systematic approach. And there are also four basic approaches to disordering the marketing process (see box 2, which is inspired by Tim Harford’s excellent book, Messy). Each of these four disordering methods can be thoughtfully applied at any of the four stages of marketing, so offering plenty of opportunity to shake-up and re-invigorate your marketing plan. The following four examples illustrate how this disordering process works in practice, although this is far from an exhaustive list.

making. Too often, however, it creates nothing more than huge slide decks that do little more than repackage what is already known. Not only does this not help strategic thinking, it hinders it by burying people under data and causing ‘paralysis by analysis’. This undesirable situation occurs because, when we ask for a situation analysis, the implied question is ‘what do we know about the market?’. If instead we rephrase that to ‘what do we know about the market that no one else does?’, it forces a search for true insight upon which competitive strategy can be built. For example, we might know a lot about the patient journey, the prescribers’ experience and the rates of non-adherence to medicines. But so, usually, do our competitors who buy the same market data from the same research agencies. But the challenge to find something only we know forces market analysts to look at the same data again and again until real insight, which is unique to us, emerges. For example, we might see that non-compliance occurs mostly at a certain stage in the patient journey as a result of a negative prescriber experience. This would be a genuine and strategi-

cally useful insight (See note at the end of article). Example 2: Improving Strategic Focus by Defining the Output Differently

The second stage of the marketing cycle, making strategic decisions, is supposed to make and justify clear choices about where to focus resources, decisions which should create competitive advantage. and guide the third, implementation stage. Typically, though, the result is a blurred, indecisive compromise that fails to do either of those things. This results in scattergun tactics and, worse, a misplaced sense that there is a strategy when none exists. This strategic muddle is the result of a semantic assumption. When we ask for a strategic decision, we assume that everyone knows and agrees what a strong marketing strategy looks like. This is very far from the truth. We can obviate that assumption by making clear exactly what we are expecting from the strategic decision process and this clarity forces the strategists to work harder. For example, we can make clear that the marketing strategy should take the format known as “Drucker’s Definition” and that it should score highly against the objective

Understanding the market

Measuring and learning

The Marketing Process

Making strategic decisions

Example 1: Improving Insight by Asking a Different Question

The first stage of the marketing process, understanding the market, is supposed to deliver the insight that goes into the second stage of strategic decision

Implementation Box 1

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tests known of strategy diagnostics (See note at the end of article). This dare, to come up with a marketing strategy that is both clearly defined and objectively strong, encourages strategists to develop, test and reiterate their strategies until they have something better. For example, it demands a strategy that identifies the target market in terms of prescribing context, rather than simply the target patient or prescriber and strategy that offers a much stronger value proposition to that target, one based on both product and beyond-the-product value. Example 3: Improving Implementation by Closing down the Obvious Options

The third stage of marketing activity, implementation, is intended to identify and enact the operational and tactical activities that deliver value to the target segment or segments. But it is much more common that the implementation actions are little more than a reheated version of last year’s plan that have little impact on customer preference. This results in incomplete, incoherent and ineffective activities that not only consume resources but also have a high opportunity cost.

Implementation ineptitude is, in many cases, the result of inertia. Marketing teams spend what money they have become accustomed to, to do mostly what they have done before with methods and agencies with whom they are comfortable. This inertia is as powerful as it is invisible, but it can be broken by removing options that have traditionally been open to marketers. For example, we can request an activity plan that assumes there is no sales team or that congresses are not allowed or that the budget is halved. Even if these options are not, in reality, closed down and the budget not halved, the more constrained scenario forces people to think what they would do if they could not cut and paste last year’s plan. For example, it might force an honest reassessment of the role of sales people, the value of congresses and the return on marketing spend.

Example 4: Improving Measuring and Learning by Introducing a New Perspective

The final step in the loop of strategic marketing activities, measuring and learning, should do three things. It

ASK A QUESTION DIFFERENTLY

How a question is phrased determines its answer. Asking a question in a different way forces the answerer to think differently.

DEFINE AN OUTPUT DIFFERENTLY

Any human process will try to deliver what those humans think is being asked for. Defining the required output in a different way encourages a more innovative output.

CLOSING DOWN THE OBVIOUS OPTION

Business processes are like water in that they tend to flow down the easiest channel. Closing that alternative off, even hypothetically, stimulates fresh thinking.

INTRODUCE A DIFFERENT PERSON OR PERSPECTIVE

Individuals and teams bring their ingrained habits to the planning process. Introducing a new person or perspective to the team forces them to look beyond their embedded behaviours.

Box 2: Four Disordering Methods

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should test assumptions made during planning, provide information that guides strategy adjustments during execution and, after execution, tell us if the strategy has actually worked. In practice, marketing metrics usually give only limited, low-resolution information about what was sold, from which we can only indirectly infer some of these three things. This means that implementers have little chance to alter strategic course and each planning cycle is little better informed than the one before. The inadequacy of marketing metrics has its origins in the perspective of the people who asked for those metrics. In most cases, metrics are demanded by leaders and finance colleagues who need to report upwards. And, since what they need to report is spending, sales and profit, then that is the focus of most marketing metrics. This situation can be improved by adding the perspective of other people in the organisation. For example, if we asked what the sales person, with her short-term focus, wants of metrics, we would develop metrics that predicted success in the immediate future and guided adaptation of the strategy during, not after, execution (so-called lead metrics). If we took the perspective of the strategists who have to write next year’s plan, we would develop metrics that tested and improved planning assumptions year on year (so-called learning metrics). Combined with traditional sales and profit data (examples of so-called lag metrics), these new perspectives would push marketers to develop so called 3L (lead, learning and lag) metrics (see footnote). Disorder, but be Deliberate

As these examples show, the deliberate disordering of the strategic marketing planning process can energise the lumbering behemoth of your annual planning cycle. But one can’t be reckless, because that would put at risk the benefits of a rigorous, clear and systematic process. It may well be necessary and desirable to inject some disorder into one or more

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Turbo Charging the Juggernaut

The English word juggernaut is derived from Sanskrit and refers to an unstoppable force or heavy, lumbering vehicle. In many pharmaceutical and medical technology companies, juggernaut is a good description of the strategic planning process, with its inability to be flexible

and original. There are good reasons for this rigidity, such as coordinating complex activity and managing risk, and like a heavy vehicle it would be naïve to expect the process to be nimble. But it is possible to improve your strategic planning process by the judicious, deliberate use of the four techniques described in the article (see box 2) at one or more stages of the marketing process (see box 1). Done deliberately, disordering your strategic

AUTHOR BIO

of the four stages of the marketing cycle, but one should do so with care. Use the four approaches from box 2, but consider carefully how you do it. For example, defining the output differently risks being seen as ‘moving the goalposts’ and may be resisted by some marketers. Closing down options may be seen as Draconian, especially if it kills pet projects or threatens individuals’ status. As with any kind of change management, tread carefully and seek to gain commitment to, rather than impose, change.

marketing process can turbocharge your juggernaut. Note: Readers who would like to know more about insight creation, Drucker’s Definition, strategy diagnostics, 3L metrics and other methodologies referred to in this article should read ‘Brand Therapy’ by Professor Brian D Smith, which is available on Amazon and all other book stores.

Professor Brian D Smith is a globally recognised a authority on the evolution of the pharma and medtech sectors. Working at both the University of Hertfordshire and SDA Bocconi, he welcomes questions and comments at brian.smith@pragmedic.com

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How to jet mill a sticky API using QbD

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A QUALITY BY DESIGN APPROACH

Development of a robust control strategy for manufacturing

Scaling up the manufacture of a topical drug formulation to supply toxicology, clinical, and commercial batches requires a well-defined strategy. Process development requires modest time and financial investment and it is not only development programmes for New Chemical Entities (NCEs) that can benefit from process development. Charles Evans, Vice President, Pharmaceutical Development, MedPharm Jeremy Drummond, Senior Vice President, Business Development, MedPharm Marc Brown, Chief Scientific Officer and Co-founder, MedPharm

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y 2022, the Global Topical Drug Delivery market is expected to exceed more than US$125.5 Billion. The Asia-Pacific market is expected to witness the highest growth driven by the increasing economic power of the expanding population. Robust supply chains and manufacturing processes for these complex formulations will be fundamental in order to capture this growth. Robust manufacturing, in particular, requires the supplier to have scaled up the manufacture of a topical drug formulation based on well-planned strategy. Process development requires modest time and financial

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investments when compared to the risk of batch failure and its consequential impact on project timings, costs, and success. Development programmes for generic drug products as well as for new products based on New Chemical Entities (NCEs) can benefit from structured process development, a step that is often mistakenly omitted. In the case of generics it is often not understood that originator products may not have been fully optimised and the correct process parameters needed for their consistent manufacture may not be well defined and some critical parameters may be on a knife edge. The impact of a structured Quality by Design (QbD) approach remains with a product throughout its entire life and de-risks initial scale-up for toxicology or clinical batches through to commercial scale and future plant-to-plant transfers. In combination with six-sigma tools, QbD provides a methodology from which a robust process control strategy can be derived. This approach to builtin quality has multiple benefits: Very importantly it demonstrates to regulatory authorities that the product owner has established control over consistent manufacturing. It also reinforces the commercial viability of the product. It addition to using experimental design to challenge Critical Process Parameters (CPP), there are a number of different six-sigma tools that add to the power of the QbD approach. These include, Failure Mode Effect Analysis (FMEA), inputoutput diagram, voice of the customer, benchmarking, and evaluation criteria. QbD Application to Topical Formulations

Defining a control strategy around Critical Material Attributes (CMAs) and CPPs is of particular importance with semi-solid products. The composition of these semi-solid products is carefully derived by considering all aspects of the target product profile while acknowledging the scientific and technical constraints imposed by the API, the excipients and their combination. The characteristics of

each material used can not only have a profound effect on the resultant formulation for both safety and efficacy, but they can also heavily influence, even dictate, the manufacturing process. This is especially the case in areas such as dissolution, mixing parameters, and heating or cooling processes. The safety and efficacy of topical pharmaceutical formulations are clearly intimately associated to the composition of the product. There often exists a lack of appreciation for the relationship between clinical performance of topical formulations such as creams, gels, foams, and ointments, and their microstructure, which are typically highly dependent on upon manufacturing process parameters. A process development programme targeting product optimisation must be taken into account a broad range of processing parameters in order to ensure its consistent manufacture to the chosen specification. Creams are notorious for being one of the more complex topical pharmaceutical formulations. For these products require defined processes for the combination of two immiscible phases including order of addition, speed of mixing and stirrer timings etc. More often than not, a controlled heating and cooling rate during the process will also need to be pre-determined. The more complex

these various processing requirements, the more the CPP is expected to have an influence upon the control strategy and greater is the complexity of the scale-up programme. Generation of CQAs

The Quality Target Product Profile (QTPP) ensures that the broad objectives of the project are captured and is a key tool to use from the start of any pharmaceutical development programme to ensure the overall objective is understood. It covers the patient and prescriber requirements and the attributes needed to ensure a safe, effective, and commercially viable treatment. When determining the impact of material attributes and process parameters on product quality the QTPP should always be referred back to. Using the QTPP, the critical quality attributes (CQAs) of the product may be determined in combination with assessing the likely impact of individual raw material attributes and processing parameters on product quality. Benchmarking against competitor products, especially in the generic-drug market, is a useful guide to the QTPP as it can highlight key commercially relevant differentiators for the new product1. 1 http://www.pharmtech.com/qbd-strategies-secure-scalesemi-solid-topical-formulations?pageID=2

INPUT

PROCESS

OUTPUT

Excipient A, Excipient B, Excipient C

Mixing

Excipient C dissolved, Homogenous Solution (1)

Solution (1), Excipient 4 and Water

Mixing

Homogenous Solution (2)

Excipient 5, Excipient 6 and Excipient 7

Heating, Mixing

Clear Melt at 65Â°C Homogenous Solution (A)

API added to Solution (2)

Mixing

API dissolved Homogenous Solution (3)

Homogenous Solution (3)

Heating

Mixture at 65Â°C Homogenous Solution (B)

Homogenous Solution (A) Homogenous Solution (B) Excipient 8

Homogenisation

Combined Solutions

Combined solutions

Stirring, Cooling

Final Product

Table 1: IPO Diagram showing the unit operations ofasample manufacturing process. www.pharmafocusasia.com

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A six-sigma tool to aid the compilation of the QTPP is Voice of the Customer (VOC) as it allows both the company sponsoring development and the end-user to provide clarity on their requirements. In the case of a topical pharmaceutical product, the VOC or patient voice is paramount alongside other significant ‘voices’ such as prescribers and investors. Simple surveys of patients or Key Opinion Leaders (KOLs) are a highly effective means of acquiring valuable VOC data, and for orphan products, this is often efficiently captured through internet-connected patient groups. VOC and the QTPP play a crucial role in the determination of CQAs2. Incorporating Risk Management

A key component of any efficient process development programme is risk identification and mitigation. It is widely recognised that the deployment of FMEA as a risk management tool, together with an appropriate design of experiments, leads to control strategies that reliably produce drug products of the appropriate quality. This is the case whether they are based on NCEs or generic drugs. FMEA is a sequential approach for estimating the potential risk arising from all possible failures in the design or processing of the topical product. If any potential risks 2 http://www.pharmtech.com/qbd-strategies-secure-scalesemi-solid-topical-formulations?pageID=2

Process /Step Input

Dispersion of Carbopol in Water

Glycerol and Propylene Glycol mixing

Focusing in on the CPPs

The marriage of experience, QbD, six-sigma tools, and experimental design ensure that the manufacturing scale-up of complex topical products can be conducted with minimum risk.

arise, the FMEA defines the most suitable process controls in order to highlight where efforts should be deployed in risk mitigation. Whether by design or necessity, many liquid and semi-solid topical pharmaceutical products are highly complex systems. These products often involve multiple phases (e.g. oil and water emulsions) with a defined range of droplet sizes. As such, failures can occur in a number of varying processing areas, including, but not limited to, heterogeneity of drug content, or consistency, and physical, chemical, or microbial instability. The homogeneity, stability and ease of use heavily impact the efficacy, uniformity of dose, and safety of topical pharmaceuticals.

Potential Failure Mode

Potential Failure Effects on Critical Quality Attributes

Potential Causes

Detection Mode

Incomplete dispersion

Viscosity, content uniformity, visual appearance, homogeneity

Addition too fast inadequate mixing

Visual, rheology, assay

Viscosity, API release, content uniformity

Too much shear applied to formulation

Rheology, assay, IVRT

Inadequate mixing

Visual in process check

Too much Shear applied

Incomplete mixing

None

The CPPs are derived by establishing the relationship between the processing parameters, the CMAs of both the API and excipients, and the CQAs of the product. A succinct way of expressing the process parameters is the six-sigma input–process–output (IPO) diagram (see example in Table I). The IPO diagram highlights the unit operations and which operational parameters should be investigated during the manufacturing process. A pre-screening study is the first form of experimental design (DoE) derived from the outputs of the FMEA (see example in Table II) and the IPO diagram. The objective of this stage is to confirm the output from the FMEA, uncover any interactions between key parameters, and to distinguish any truly critical processing parameters. The FMEA allows the operator to capture the knowledge and decide which areas of the process are most critical and require further experimental investigation and the DoE then validates this thinking statistically and quantitatively. Pramod et al. noted that “though design of experiments is not a substitute for experience, expertise, or intelligence, it is a valuable tool for choosing experiments efficiently and systematically to give reliable and coherent information”. Both the experience and expertise of the technical project team and efficient experimental design software are essential for this approach.

Severity Probability Delectability Total

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Potential Controls

Slow addition into a vortex to allow dispersion. Visual check to ensure dispersed.

Use of educator during Carbopol addition Keep sped and/or time of homogenisation to a minimum. Avoid homogenisation if possible.

Table 2: The FMEA is used to highlight unit process operations that pose the most risk to product quality. IVRT is in-vitro release testing. 58

Current Controls

Visual check during manufacture to ensure homogenous.

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KNOWLEDGE SPACE DESIGN SPACE

CONTROL SPACE

Figure 1: A graphical representation of the relationship between knowledge space, design space and control space.

Key Factors in the Design of Experiments

It is essential for topical formulations that during the pre-screen and full DoE experiments are conducted using equipment that is representative of larger-scale equipment in order to derive meaningful qualitative CPP data. At MedPharm, IKA LR1000 lab reactors are used, which allow for the control of all typical processing parameters. This approach crucially avoids â&#x20AC;&#x2DC;noiseâ&#x20AC;&#x2122; generation and ensures the quality of the output and therefore the robustness of the resultant control strategy. Understanding the influence of scale on the CPP from high-quality experimental work conducted on a small scale forms the basis of any future scale-up work and technical-transfer activities. For a complex cream, typically 12 experiments covering two to four CPPs are conducted in a pre-screening study in preparation for the manufacture of toxicity or clinical batches. The need to expand the actual number of experiments will depend on the outputs from this early screen and the associated risks. Experimental design in both the pre-screen and full study should ideally attempt to push the product to failure to allow clear understanding of the design and control space boundaries. Problems can arise if the developer is conservative in experimentation due to a misunderstanding of the boundaries between success and failure (see Figure 1). A third important factor is the identification of what six-sigma calls the Key 60

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Process Output Variable(s) (KPOV), those that determine success. It is critical to have evaluation criteria to establish whether the method employed to measure the KPOV will detect critical failure. If not, a mitigation plan needs to be in place as the output of any experimental work will only be as good as the analytical method allows. An array of analytical techniques is required to evaluate the quality of topical pharmaceutical products. These range from commonplace methods, such as High-Performance Liquid Chromatography (HPLC) and viscosity testing, to more sophisticated methodology, such as rheological evaluation, accelerated stressing to show the potential for separation, and in-vitro release testing to check that there is no change in the release/thermodynamic activity of the drug from the formulation. The design space is defined as the multidimensional combination and interaction of input variables and process parameters that have been demonstrated to provide assurance of quality 3. It satisfies the QTPP and CQAs for the product and provides the boundary of any process parameters to which a product can be made. It is important to stress that the knowledge space is not a hard boundary and that defined process inputs are just as important as the measured output. Interpretation of the DoE using statistical techniques such as Analysis of Variants (ANOVA) plots, which show the mean and distribution around the mean, should clearly show the significance of any parameter and any key interactions between parameters and any associated variability. With an increase in sophistication of many experimental design software packages (e.g., SPSS, Minitab, JMP, and Design Expert) it is easier than ever to highlight statistically significant affects across a range of parameters and present them in a concise graphic that decision makers find easy to understand. It is important to note that any process change made within the design space is not considered a regulatory 3 https://www.camo.com/products/pat-qbd-overview.html

change, and hence, directly allows for the flexibility of any future manufacturing process. Having a strong understanding about the boundaries of success and failure from the outset, creates a foundation for a good control strategy. Furthermore, it reduces the impact any changes in excipient suppliers and specifications or site of production may have upon a product over its lifetime. Ensuring a Robust Process

The control space represents a range of critical parameters within which the process will yield an assured output to meet the CQAs and target specification at all times. The further use of experimental design is essential when navigating from the design space to the control space. This will typically involve, two to five factors in full, or fractional factorial, or some other surface response design informed by the data from previous experiment design work. A useful guide to DoE in this scenario can be found online in the form of the engineering statistics handbook . Undoubtedly, the control space for the CPP must sit well within the boundaries of the design space and sufficiently away from the edge of failure to ensure robustness. The outcomes of an optimisation design will provide interpretation and conclusions to show the most desirable settings to achieve a topical product that meets the QTPP and CQAs. A confirmation batch using these settings aims to demonstrate that the response values from the DoE are close to their predicted values. Conclusion

Using a step-by-step and disciplined QbD approach during the development and late-stage formulation of topical products provides a sound and robust platform in establishing the design space for process development. This methodology will ultimately enable the developer to provide a reliable control strategy for manufacturing. The often-complex liquid and semi-solid processing for topical products cannot be underestimated

and missing this critical step, as is often the case in the past, can lead to poor processing and physical instability in topical products, which directly impacts development timelines, product performance and ultimately patients. The marriage of experience, QbD, six-sigma tools, and experimental design ensure that the manufacturing scale-up of complex topical products can be conducted with minimum risk. Above all, the experience of industry leaders has shown that a well thought out QbD-based process development strategy with in-depth knowledge of the products and processes de-risks topical formulation development, saving both time and money. References are available at www.pharmafocusasia.com

AUTHOR BIO

MANUFACTURING

Charles Evans has been with MedPharm for over 10 years as part of the formulation and analytical development teams and leads MedPharm’s rigorous approach to developing formulations from proof of concept to robust commercial products. He has many years expertise in all types of topical, inhalation and transdermal formulations and played a key role in the development of MedPharm’s proprietary MedSpray® technology currently under license to customers to enhance their products' performance. Jeremy Drummond joined MedPharm in February 2017. He has spent over 20 years leading the commercial supply of product and services to the pharmaceutical companies across the globe. He is responsible for leading revenue growth, key client relationships and marketing MedPharm to its global customer base. Most recently he was Sales Director – Formulated Products with Aesica, the pharmaceutical contract manufacturer. He started his career as a technical formulator and has a PhD in organic chemistry from the University of Cambridge. Marc Brown co-founded MedPharm in August 1999. He has been the guiding force behind all of MedPharm’s scientific developments and intellectual property. He has been Professor of Pharmaceutics in the School of Pharmacy, University of Hertfordshire since 2006 and has visiting/ honorary professorships at the Universities of Reading and King's College London. He has over 200 publications and 26 patents describing his work. His research interests lie mainly in drug delivery to the skin, nail and airways. To date, he has been involved in the pharmaceutical development of over 38 products that are now on the market in Europe, America and Japan. Prior to MedPharm he was an academic in the Pharmacy Department at KCL.

www.pharmafocusasia.com

MANUFACTURING

FLEXIBLE FACILITIES

Manufacturing trends offering benefits

Modular facility design is a potential game-changer for bio-pharmaceutical manufacturers. It allows those companies seeking a more efficient, sustainable building method, the ability to grow or change locations. This design option, which implements standardised pieces that can be used as simple building blocks for factory setup, allows for flexibility and easy expansion. Sean Riley, Senior Director, Media and Industry Communications PMMI, The Association for Packaging and Processing Technologies

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n the early 21st century, one of, if not the primary goal of a pharmaceutical facility was to maintain large production lines and attain exceptional productivity and product throughput. Today’s pharmaceutical industry embraces smaller, more modular and flexible lines, with shorter lead times. The primary industry driver away from the big factory model is the growth of personalised medicines, the need for smaller batches and regionalised manufacturing. An excellent example of regional manufacturing is vaccine manufacturing, particularly in underdeveloped markets. (As the pharmaceutical marketplace continues to globalise, the expanding middle class in “pharmerging” countries. China, Brazil, Russia, India, Algeria, Argentina, Colombia, Bangladesh, Indonesia, Mexico, Nigeria, Pakistan, Poland, Saudi Arabia, South

MANUFACTURING

Africa, Philippines, Turkey, Romania, Chile, Kazakhstan and Vietnamâ&#x20AC;&#x201D;now have access to supply chains and more importantly, money, for healthcare and vaccines1.) Some years ago, there was a disruption in the global flu vaccine supply due to equipment cleaning issues. This led to more localised vaccine manufacturing and greater use of singleuse components. The industry has come to view regional vaccine manufacturing as more cost-effective and ultimately safer. It eliminates some of the logistical 1 https://www.packexpointernational.com/big-changesbig-pharma

headaches associated with getting vaccines to other countries with limited infrastructures and, in turn, has led to the growth of more modular production facilities. In short, the industry is moving away from the big factory model. We see today more off-the-shelf performance modules that enable drug manufacturers to select components with shorter lead times. This also aligns with the growth of personalised medicines in which batches are smaller. Along with modularity is the trend of equipment with toolless changeover. Being able to pull out components and replace them quickly

is partly the result of the rise of singleuse modules and helps reduce downtime significantly2. Single Use

Every pharmaceutical company looking to turn a profit understands the value in reducing manufacturing costs while maintaining a supply of drugs to treat patients. Yet the biopharmaceutical industry per its reluctance to change has been slow in transitioning to modern technologies for achieving these goals. 2 https://www.pharmaceuticalonline.com/doc/majortrends-in-pharmaceutical-packaging-0001

www.pharmafocusasia.com

MANUFACTURING

Currently, a paradigm shift in biopharmaceutical production is underway with the convergence of two complementary modern technologies, single-use systems and continuous production methods. Single-use pre-sterilised and disposable polymerbased components eliminate cleaning, sterilisation and associated validation steps. They also diminish contamination risks in product change-over, reduce manufacturing and energy costs, minimise plant footprints, and save time and labor. The environmental impact is favourable when compared to reusable steel equipment. Years ago when the U.S. Food and Drug Administration (FDA) first allowed biotech manufacturers to go from producing biological products in dedicated facilities to providing multiple products in the same facility under the condition that the equipment met certain cleanliness thresholds, manufacturers began investigating single-use technology as high classification clean-room facilities are costly. With no standard definition of “clean,” defining cleanliness and proving clean equipment to an adequate level proved very difficult. Switching to single-use machinery removes the question of cleaning validation and speeds product time to market. Single-use equipment—per its name—is used only once in a pharmaceutical manufacturing facility. Each new batch of pharmaceuticals (or in some cases, each campaign) requires new pieces. This eliminates the need for equipment cleaning and re-sterilisation throughout the manufacturing process, saving time and costs. Manufacturers do not need to halt production or allocate extra time to prepare the various components for the subsequent batch. They also no longer must purchase cleaning supplies for that purpose, dispose of used cleaning fluids, or use excessive amounts of water for cleaning, rinsing, and steam generation. Reducing cleaning materials, eliminating downtime, and keeping production in motion lead to overall improvements to the bottom line. 64

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More significant benefits of the single-use design lie in alleviating concerns of facility equipment being unclean or compromised. Replacing pieces with systems that are virgin, preassembled, and pre-sterilised eliminates the worry about sterilisation, cleanliness, or exposure. Using fresh materials means the drug has a lower risk of contamination during production. Ultimately this benefits consumers and helps protect brand reputation. Despite reducing bottom line costs for manufacturers, at first glance, single-use facility design seems to run counter to the pharmaceutical industry’s commitment to sustainability. Typically, the terms “recyclable” and “reusable” go hand-in-hand with sustainability. Manufacturing components are usually required to have these characteristics to qualify as environmentally friendly; however, in the case of single-use components, the matter is not so simple. Made from a combination of plastics that are not themselves recyclable, incinerating or melting down singleuse systems and converting them into reusable energy makes the systems infinitely recyclable. Eliminating the cleaning and sterilisation processes for the materials save significant water and energy. For manufacturers considering

By using a modular facility design in developing countries, pharmaceutical companies can build facilities more cost effectively, allowing them to set local drug or vaccine prices to meet emerging market needs.

switching to this type of facility design, a big picture perspective is critical. Although single-use pieces do not appear to be eco-conscious at the outset, they do offer pharmaceutical companies a long-term investment in sustainability3. Even with all the benefits, there are still challenges in implementing singleuse systems. Currently, the biggest issue is to qualify the safety of extractables and process-derived leachables from fluid-contact plastics. While analytical methods exist, Good Manufacturing Practices (GMP) regulations require a demonstration of safety. The FDA does not prescribe the extent of studies and allowable limits, challenging suppliers and users with anticipating what and how much data is expected by regulatory authorities. Recently, several industry organisations published a standardised consensus recommendation, and USP is developing a standard. However, since regulatory authorities consider safety and quality aspects of extractables and leachables on a product-specific basis, there will always be some user and regulator judgment required and extractables and leachables data will never be standardised for all drug products. When looking for a single-use solution, there are some critical issues to consider. It is important to ensure that the suppliers’ manufacturing processes are validated. Be sure suppliers have sufficient data to demonstrate the reliability and safety of their products, and that they have adequate quality systems in place. Another consideration is useful data on the consistent supply of raw materials. A robust change management and change notification system need to be in place to ensure minimal change along with clear change notifications. There is a concern when a supplier makes changes to the raw materials that affect the extractables and leachables profile. Look into security, continuity, adequacy of supply. 3 https://www.pharmaceuticalonline.com/doc/modularfacility-design-single-use-equipment-considerations-forpharma-manufacturing-0001

MANUFACTURING

facilities with single-use equipment can be assembled anywhere in the world and are not dependent on sophisticated local engineering, capital, and resources. By using a modular facility design in developing countries, pharmaceutical companies can build facilities more costeffectively, allowing them to set local drug or vaccine prices to meet emerging market needs5. Single + Modular=Lower Cost

More Modular, More Flexibility

Modular facility design may also be a game-changer for pharmaceutical manufacturers seeking a more efficient building method and the ability to grow or change locations. This design option, which implements standardised structures as simple building blocks for the factory setup, allows for flexibility and natural expansion. With these modular components, manufacturers can assemble a facility in a fraction of the time needed for traditional installation, saving costs and building time. These pieces also do not require the expense of stainless-steel tanks and piping for the transport of rinsing materials, cleaning solutions, and steam seen with traditional stainless-steel design facilities, so they are not as difficult to assemble and cost less4. No pharmaceutical company predicts their drug failing in the marketplace, but the modular design allows for quick dismantling or conversion if a drug isn’t successful and production must cease. The parts can be rearranged with relative ease to fit the model for a new drug. The standardised nature of the modular pieces also means a manufacturer has flexibility in factory size. A facility can shape-shift 4 https://www.pharmaceuticalonline.com/doc/modularfacility-design-single-use-equipment-considerations-forpharma-manufacturing-0001

relatively quickly to accommodate the size and setup required for a different drug. A manufacturer can even build vertically if they need less square-footage. Standardising manufacturing materials and equipment may also help speed up global pharmaceutical expansion. If each piece of equipment in a facility is similar or standard, companies can mix and match the pieces as necessary depending on product and location. Also, if they all fit together in the same way, adding or subtracting from a facility can be attached or detached with ease. Often pre-fabricated and shipped in containers, modular pieces are suitable for manufacturers looking to open new facilities around the world. If they use components that reflect this standardisation and familiarity, sophisticated facilities can be replicated in markets where construction might otherwise be difficult or, in some cases, impossible. Additional global facilities are key for pharmaceutical manufacturers looking to meet international demand for vaccines and other drugs already maximised in North American or European markets. Standardised modular AUTHOR BIO

Qualifying must go further than just documentation. It’s essential to audit all suppliers consistently.

The result of this increased control is the ability to quickly change the flow or size of production as necessary, suggesting less labor, lead time, downtime and new equipment costs. Manufacturers can match their facility set up to reflect changes in their sales or to adapt to market trends and needs. It is this open-ended flexibility and decreased risk of capital loss that makes a modular facility design highly appealing. Although each type of facility design offers its own benefits if a manufacturer implements both single-use and modular facility design in one system, options for flexibility and cutting costs may be unmatched. Modular pieces of equipment can be designed as single-use materials, which can result in smaller or low-level cleanrooms and standardised steps of purification. Marrying these methods can also cut down on resources and assembly time, reducing costs on a pharmaceutical manufacturer’s entire operation. Combining these facility designs may also allow for a speedier entry into the market6. 5 https://www.pharmaceuticalonline.com/doc/modularfacility-design-single-use-equipment-considerations-forpharma-manufacturing-0001 6 https://www.pharmaceuticalonline.com/doc/modularfacility-design-single-use-equipment-considerations-forpharma-manufacturing-0001

Sean Riley is currently PMMI’s Senior Director, Media and Industry Communications. He was Editor-in-Chief for PMMI’s Packaging Machinery Technology Magazine for nearly a decade and has over 20 years of experience working with and as a member of the packaging and processing media.

www.pharmafocusasia.com

DATWYLER’S STARTER PACK

Successfully mastering the global healthcare challenges

Massimo Mainetti, Head Strategic Marketing, Datwyler Sealing Solutions

As the healthcare industry faces increased complexity and stricter requirements for drug development, market leaders are looking for new and innovative ways to address these concerns. As a result, pharmaceutical and biotech companies are looking for a strong partner that can meet these standards set by the industry and provide products that ensure the safest and most effective solution for their drug product. As two long-term industry players, Datwyler and SCHOTT have developed a new packaging solution, ideal for complexities faced during drug development: the Starter Pack. On average, the development of a new medicine takes 10 to 15 years and costs around US$2.6 billion. Drug development involves comprehensive clinical trial phases, of which less than 12 per cent of the candidate medicines make it into phase I, where clinical trials are eventually approved by the authorities. Driven by the latest developments in the field of medicine, such as cell & gene therapy, tissue engineering and regenerative medicine, the complexity is expected to increase even further in the future. Considering all critical aspects within drug development, Datwyler and SCHOTT developed the Starter Pack, which provides a range of compatible primary and secondary packaging components to be used in every drug development application – from drug discovery to drug delivery. The Starter Pack is designed to provide customers with a complete, robust, ready-to-use packaging system, easy to order and ready to be globally delivered in small quantities. The combination of the Datwyler Omni Flex stopper, Prime Cap, and SCHOTT adaptiQ® vial

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provides an ideal sealing solution which prevents leaks and other seal integrity concerns throughout manufacturing and handling.

Starter Pack: from drug discovery to drug delivery

Datwyler’s Starter Pack provides a range of compatible primary and secondary packaging components to be used in every drug development application. This allows manufacturers to incorporate highquality components and commercial packaging solutions into their testing and clinical trial strategy, including diagnostic research, clinical trials, and product launch. After that, the quantities can be ramped up. The Starter Pack consists of Omni Flex stoppers, Prime Caps, and SCHOTT adaptiQ® vials. The products provided are ready-to-use (RTU) and have been sterilised in accordance with pharmaceutical and regulatory guidelines. All of Datwyler’s vial closure solutions are produced, controlled, and tested under the most stringent conditions in order to guarantee patient safety. • Datwyler Omni Flex stoppers meet the demands for quality and performance for highly sensitive, large molecule drugs. The coating not only provides barrier properties, but also eliminates the stopper as a source of silicone oil and, therefore contributes to the reduction of silicone oil-based subvisible particles. This enables a safe and consistent administration of the drug even after a longer period of storage

• Datwyler Prime Caps are designed for flawless machine ability on high-speed filling lines, provide low bioburden and particulate levels. All of the company’s facilities worldwide deliver Prime Caps in the same quality and with all existing specifications, including the highest quality alloy, two different sizes, center-gated disc for enhanced machine ability and container closure integrity • SCHOTT adaptiQ® vials can be processed on a wide range of new and existing fill & finish equipment, allowing the vials to remain nested throughout the fill & finish process, including during lyophilisation. The vials are made out of FIOLAX® clear borosilicate glass in TopLine quality for high dimensional and cosmetic quality. The adaptiQ® nest design operates completely glass-to-glass contact free and reduces the risk of glass breakage. adaptiQ® vials are produced in a cGMP and ISO certified environment, with statistical in-process control and a 100 per cent camera inspection.

functionality testing, and container closure integrity testing. Datwyler is a partner in drug development throughout the entire value chain, from the pre-clinical trial phase, over the phases 0 to III, up to the product launch.

Guaranteeing the highest quality standards

The Starter Pack is designed to provide its customers with products that ensure complete Container Closure Integrity (CCI). The combination of the Datwyler Omni Flex stopper, Prime Cap, and SCHOTT adaptiQ® vial, provides an ideal sealing compatibility, preventing leaks and other seal integrity concerns throughout manufacturing and handling. Using standard CCI testing methods required by pharmaceutical and regulatory authorities, Datwyler can provide a total packaging solution for storing and administering sensitive drug products. With the launch of the Starter Pack in collaboration with SCHOTT, Datwyler provides support for players in the healthcare industry as a strong partner throughout the drug development process. As the requirements and the complexity of medical solutions are rising and, therefore, posing multiple challenges for manufacturers in the field of drug development and drug testing, the Starter Pack is not only designed to provide the right packaging, but also to support the testing and launch process. With its commitment and trust in the innovation of healthcare companies, Datwyler is a reliable partner to improve patients' lives.

Figure 1: A single source solution for drug development and clinical trials

A service offering to meet your testing needs In addition to the Starter Pack, Datwyler offers its customers analytical and rubber compounding expertise during product selection and testing, which is based on the company’s extensive industry knowledge. With more than 100 years of multi-industry experience, Datwyler is aware of the challenges that customers are facing in their respective fields and can help them to find the right packaging solution for their needs. The implementation of these in-house programs presents customers with a comprehensive solution for parenteral packaging. The service offering includes pharmacopoeia and normative testing,

Massimo Mainetti is Head Strategic Marketing at Datwyler Sealing Solutions. He holds a master degree in business administration from the University of Milan. In January 2015, he joined the global sales team of Datwyler Pharma Packaging as Key Account Manager Injection-Systems. And since June 2017, he has been acting in his current position as Head Strategic Marketing. He brings broad experience from diverse backgrounds in Key Account Managing, Distribution and strategic and international marketing into the company.

Advertorial www.pharmafocusasia.com

Books

The Impact of Regulation on Drug Development (Pharma, Biotech and Bioscience: Science, Technology and Business)

Packaging Solutions for Pharmaceutical Products: Pharma Packaging

Author(s): New York Times Company

Author(s): Anupam Chanda

Author(s): Heinz Guenter Hennings

Year of Publishing: 2019

Year of Publishing: 2020

No. of Pages: 224

No. of Pages: 250

Description: To many Americans, the term big pharma evokes thoughts of greedy organizations that put profits ahead of people's health. It's difficult to put a price tag on drugs that improve or save lives. It's even harder to stomach the thought of being unable to afford medicines when we may need them most. With the price of pills reaching an all-time high, we are looking for justifications and turning to our government for solutions. The articles in this collection provide valuable coverage and insights into the practices of drug manufacturers, the driving forces behind the costs we face today, and what, if anything, can be done to satiate the hunger of big pharma. Media literacy questions and terms will engage readers beyond the text and aid them in considering the many facets of this complicated issue.

Description: The impact of regulation on drug development provides the reader with a basic understanding of the evolution of global regulatory standards relevant to the research and development process of medicinal products and the role regulatory science plays, i.e. the science of developing new tools, standards and approaches to assess the safety, efficacy, quality and performance of regulated products. This book provides practical guidance on how to obtain such advice efficiently and how it is incorporated in global regulatory planning and strategies.

Big Pharma: The Money Behind the Pills (In the Headlines)

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Year of Publishing: 2019 No. of Pages: 444 Description: The book is designed both to meet the needs of those studying for the Diploma in Packaging Technology, a university student and to act as a comprehensive reference for packaging professionals also provides very systematic and comprehensive coverage of the theory as well as the illustration of application.

Make Better Decisions: Finding and Evaluating Generic and Branded Drug Market Entry Opportunities (DrugPatentWatch Business Intelligence Series)

Pharmacotherapeutics for Advanced Nursing Practice, Revised Edition

Planning and Analyzing Clinical Trials with Composite Endpoints

Author(s): Tammie Lee Demler Year of Publishing: 2019

Author(s): Geraldine Rauch, Svenja Schüler, Meinhard Kieser

Author: Yali Friedman

No. of Pages: 772

Year of Publishing: 2018

Year of Publishing: 2019 No. of Pages: 160 Description: Make Better Decisions helps generic and branded companies alike find and evaluate drug market entry opportunities. Billions of dollars can change hands when key drug patents expire and generics launch. Brands can experience precipitous revenue erosion as generic drugs rapidly gain market share. All the while patients, physicians, payers, pharmacists, and other healthcare stakeholders must race to keep up. Make Better Decisions answers the following questions to help you adapt: • When will key drug patents expire? • How can I write stronger patents? • How can I defeat drug patents?

Description: Pharmacotherapeutics for Advanced Nursing Practice, Revised Edition focuses on the critical information necessary for prescribing drugs for common diseases and disorders. As the role of the advance practice nurse expands, this text is an outstanding resource for nurse practitioners and physician assistants which will prepare them for an increased role in everyday healthcare while introducing the latest updates on drug information.

No. of Pages: 255 Description: This book addresses the most important aspects of how to plan and evaluate clinical trials with a composite primary endpoint to guarantee a clinically meaningful and valid interpretation of the results. Composite endpoints are often used as primary efficacy variables for clinical trials, particularly in the fields of oncology and cardiology. These endpoints combine several variables of interest within a single composite measure, and as a result, all variables that are of major clinical relevance can be considered in the primary analysis without the need to adjust for multiplicity. Moreover, composite endpoints are intended to increase the size of the expected effects thus making clinical trials more powerful.

• How can I find, evaluate, and plan for generic market entry opportunities? • How can I find proprietary out-of-court settlements and deal terms?

www.pharmafocusasia.com

Books

Biocontamination Control for Pharmaceuticals and Healthcare

Redefining Innovation: Embracing the 80-80 Rule to Ignite Growth in the Biopharmaceutical Industry

Outsourcing Clinical Development: Strategies for Working with CROs and Other Partners

Year of Publishing: 2018

Author(s): Ruchin Kansal, Jeff Huth

Author(s): Jane Baguley, Jane E Winter

No. of Pages: 374

Year of Publishing: 2018

Year of Publishing: 2016

Description: Biocontamination Control for Pharmaceuticals and Healthcare outlines a biocontamination strategy that tracks bio-burden control and reduction at each transition in classified areas of a facility. This key part of controlling risk escalation can lead to the contamination of medicinal products, hence necessary tracking precautions are essential. Regulatory authorities have challenged pharmaceutical companies, healthcare providers, and those in manufacturing practice to adopt a holistic approach to contamination control. New technologies are needed to introduce barriers between personnel and the environment, and to provide a rapid and more accurate assessment of risk. This book offers guidance on building a complete biocontamination strategy.

No. of Pages: 228

No. of Pages: 193

Description: In the book, we examine the evolution of the biopharmaceutical industry to understand how it became what we term a "unicorn industry" with a unique, US-centered business model that has led to multiple blockbuster products (aka, unicorns) year after year. We explore how past success has created perceived barriers to innovation diversification beyond the chemical or biological-based biopharmaceutical product, and highlight the warning signs of the industryâ&#x20AC;&#x2122;s decline. We define a potential pathway for transforming the industryâ&#x20AC;&#x2122;s business model by broadening the definition, sources, and enablers of innovation beyond the traditional biopharmaceutical product. We introduce and advocate for the 80-80 Rule - "Being 80% confident that you will only be 80% right the first time should feel normal." The 80-80 Rule is a theme that emphasizes speed and willingness to embrace uncertainty and overcome internal barriers to change. It sets the standard for redefining innovation as a platform to reignite growth of the biopharmaceutical industry.

Description: The challenges facing large pharmaceutical companies are stark: sales are slowing, and research and development costs are rising. There is an overwhelming need to reduce development costs by as much as 30-40%, while at the same time significantly shortening development cycle times. Pharmaceutical spend on outsourcing faces double-digit growth for the next three to five years and yet, if outsourcing is to meet these challenges, new models of collaborative and cooperative working are needed now. Outsourcing Clinical Development offers a guide to these new models and to future clinical outsourcing strategy. There is advice on the basis for an outsourcing strategy and guidance on how to work most productively with CROs (contract research organisations); geographical issues, including working in low-cost environments, are also covered.

Author(s): Tim Sandle

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Nanoparticulate Drug Delivery Systems

Manufacturing Operations Management

Author: Raj K Keservani, Anil K Sharma

Author(s): Sanjay Sharma

Drug Delivery Nanosystems for Biomedical Applications (Micro and Nano Technologies)

Year of Publishing: 2018

Author(s): Chandra P Sharma

No. of Pages: 212

Year of Publishing: 2018

Description: This book includes broad coverage of production and associated services. Since the success of manufacturing operations depends on the demand information and costs and revenue, qualitative and quantitative techniques of demand forecasting and also financial analysis are covered in this book. Topics such as facilities layout, inventory, project management, production, planning and management are explained in detail. Additional topics include quality control and work study.

No. of Pages: 451

Year of Publishing: 2019 No. of Pages: 446 Description: Focusing on nanoparticulate nanocarriers and recent advances in the field of drug delivery, the volume begins with chapters that provide an informative introduction to polymeric nanoparticlesâ&#x20AC;&#x2022;their general physicochemical features and characteristics, their applications in drug delivery systems, and the challenges involved. Specific applications are discussed, with attention paid to treatment of particular diseases and disorders and the targeting of specific organs. Part 2 looks at more specific applications and techniques of nanoparticulate nanocarriers for drug delivery, such as the use of magnetic nanoparticles, gold nanoparticles in therapeutics, and superparamagnetic iron oxide nanoparticles (SPIONs) for the treatment of cancer. Part 3 discusses lipid-based nanoparticulates for various applications, including skin care. The last section of the book explores some of the newer nanoarchitectures, including dendrimers in gene delivery and carbon nanotubes for drug delivery.

Description: Drug Delivery Nanosystems for Biomedical Application reviews some of the most challenging nanosystems with different routes of delivery that are useful for specific drugs, from both efficacy and bioavailability points-of-view. The chapters explore how this area is developing, the present state of the field, and future developments, in particular, inorganic, metallic, polymeric, composite and lipid nanosystems and their possible evolution to clinical applications. The book is a valuable research reference for both researchers and industrial partners who are not only interested in learning about this area, but also want to gain insights on how to move towards translational research.

www.pharmafocusasia.com

PRODUCTS & SERVICES Company........................................................................Page No.

Company........................................................................Page No.

STRATEGY BioGenes GmbH...........................................................................15

CLINICAL TRIALS Datwyler............................................................................ 31, 66-67

Cantel Medical..............................................................................11

Hoong-A Corporation...................................................................39

Emirates SkyCargo.....................................................................IBC

Quantys Clinical Pvt. Ltd...............................................................61

Qatar Airways................................................................................29 Swiss World Cargo.......................................................................21 SWOP 2019...................................................................................19

Thermo Fisher Scientific...............................................................05

Syneos Health...............................................................................09

MANUFACTURING Akzo Nobel Chemicals (India) Ltd.............................................. IFC

Turkish Cargo............................................................................OBC

BioGenes GmbH...........................................................................15

Valsteam ADCA Engineering........................................................37

Cantel Medical..............................................................................11 Datwyler............................................................................ 31, 66-67

RESEARCH & DEVELOPMENT Akzo Nobel Chemicals (India) Ltd.............................................. IFC

Dishman Carbogen Amcis Limited...............................................35

F. P. S. Food and Pharma Systems Srl.........................................55

F. P. S. Food and Pharma Systems Srl.........................................55 Kompress (India) Pvt. Ltd.............................................................13 Novo Nordisk Pharmatech A/S......................................... 03, 22-25 Quantys Clinical Pvt. Ltd...............................................................61

Hoong-A Corporation...................................................................39 Kompress (India) Pvt. Ltd.............................................................13 Novo Nordisk Pharmatech A/S......................................... 03, 22-25

Rousselot......................................................................................45

Syneos Health...............................................................................09

Thermo Fisher Scientific...............................................................05

Valsteam ADCA Engineering........................................................37

SUPPLIERS GUIDE Company........................................................................Page No.

Company........................................................................Page No.

Akzo Nobel Chemicals (India) Ltd.............................................. IFC www.kromasil.com

Qatar Airways................................................................................29 www.qrcargo.com/qrpharma

BioGenes GmbH...........................................................................15 www.biogenes.de

Quantys Clinical Pvt. Ltd...............................................................61 www.quantysclinical.com

Cantel Medical..............................................................................11 www.cantelmedical.com

Rousselot......................................................................................45 www.rousselot.com

Datwyler............................................................................ 31, 66-67 www.sealing.datwyler.com

Swiss World Cargo.......................................................................21 www.swissworldcargo.com

Dishman Carbogen Amcis Limited...............................................35 www.dishmangroup.com

SWOP 2019...................................................................................19 www.swop-online.com

Emirates SkyCargo.....................................................................IBC www.skycargo.com/emiratespharma

Syneos Health...............................................................................09 www.syneoshealth.com

F. P. S. Food and Pharma Systems Srl.........................................55 www.foodpharmasystems.com

Thermo Fisher Scientific...............................................................05 thermofisher.com/TriPlus500

Hoong-A Corporation...................................................................39 www.ha1511.com

Turkish Cargo............................................................................OBC www.turkishcargo.com

Kompress (India) Pvt. Ltd.............................................................13 www.kompressindia.com

Valsteam ADCA Engineering........................................................37 www.valsteam.com

Novo Nordisk Pharmatech A/S......................................... 03, 22-25 www.novonordiskpharmatech.com To receive more information on products & services advertised in this issue, please fill up the "Info Request Form" provided with the magazine and fax it. 1.IFC: Inside Front Cover, 2.IBC: Inside Back Cover, 3.OBC: Outside Back Cover

THE WORLD'S HEALTH IS IN THE SAFE HANDS OF TURKISH CARGO As the cargo airline that flies to more countries than any other, we carry all your health and wellness needs, from pharmaceuticals to medical supplies without ever interrupting the temperature-controlled cold chain.

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