IBI Volume 6 Issue 2

Peer Reviewed

Augmenting Inspiration

With Generative Chemistry

CSOs in CDMOs

Giving mRNA Manufacturing Considerations

Are We Ready

To Formulate the Next Generation of Small Targeted Therapeutics

Recreating Life in the Lab

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Volume 6 Issue 2 – Summer 2023

04 Foreword

REGULATORY & COMPLIANCE

06 Essential Considerations for a Successful Submission under EU CTR

The European Union Clinical Trials Regulation (EU CTR), which came into force in January 2022, was the biggest change to EU medicinal product legislation since 1995 when the European Medicines Agency (EMA) and the centralised procedure for marketing authorisations were introduced. The EU CTR presents fundamental changes for clinical trials in all 30 countries of the European Union (EU) and the European Economic Area (EEA). A key feature of the EU CTR is the introduction of a single electronic portal, the Clinical Trial Information System (CTIS), which is mandatory for all EU CTR submissions. Polly Halliday, et al, explains how, CTIS enables harmonised and simplified end-to-end electronic application procedures over the lifecycle of clinical trials across the EU/EEA.

RESEARCH / INNOVATION / DEVELOPMENT

08 Augmenting

Inspiration with Generative Chemistry

The ability of computers to produce new compound structures using ‘generative chemistry’ algorithms is a hot topic in drug discovery. The field has recently been reinvigorated by new machine learning (ML) algorithms that learn what a drug-like molecule ‘looks like’ and subsequently generate large numbers of chemically meaningful structures. Matthew Segall of Optibrium, explains that medicinal chemists can apply both their experience and knowledge to guide advanced ML algorithms to explore the most fruitful directions, while the algorithms can generate and prioritise many more ideas to identify new optimisation strategies and challenge preconceptions.

14

Utilising Size Selection to Enhance Gene Synthesis in Synthetic Biology Workflows

Biotechnology harnesses cellular and biomolecular processes to develop technologies and products. These products already improve our lives and show great potential for enhancing the health of our planet. In recent years and especially during the COVID-19 pandemic, the critical role of biotechnology and biomanufacturing in developing life-saving diagnostics, therapeutics and vaccines has been demonstrated and looks poised to progress on stratospheric trajectory, if we can successfully refine the technique to suit its myriad applications. Dr. Joanne Mason, et al at Yourgenehealth, discusses how utilising a size selection technology which uses machine vision algorithms to monitor electric mobility and then respond in real time gives us the ability to enrich DNA through size selection with industry-leading precision.

MANUFACTURING & PROCESSING

18 CSOs in CDMOs

giving mRNA Manufacturing Considerations Standard and Practical Process to Fast-Track mRNA Drug Product Manufacturing

The central dogma of life has DNA on one side, protein on the other, and RNA sitting right in the centre. RNA, specifically mRNA, is the intermediary step in this dogma and is being used as the essential cargo in many therapies. Expertise in manufacturing high-quality DNA and enzymes used in the in vitro transcription (IVT), capping, and the tailing process is fundamental to mRNA production for several therapeutic modalities. Based on 25 years of experience as a contract development and manufacturing organisation (CDMO), Venkata Indurthi of Aldevron presents considerations

and practical solutions at each step of production to streamline the workflow with the appropriate quality system to deliver mRNA therapeutically.

THERAPEUTICS

22 Are We Ready to Formulate the Next Generation of Small Targeted Therapeutics?

The drug discovery pipeline is currently bursting with innovative small and medium sized modalities and targeted therapies. Progress in molecular biology and genome sequencing is fuelling the next wave of drug discovery advancements, re-inventing the space for small molecules through adding new mechanisms of action such as targeted protein degradation (TPD) previously only thought possible with larger protein and antibody therapeutics. Upon their discovery, monoclonal antibodies have revolutionised the biopharmaceutical market due to their enhanced pharmacokinetic profile and high selectivity and binding capability to extracellular targets. Dr. Ali Al-khattawi, Mahmood Al-Rifaie at MESOX & Shouq Al-Shatti at Aston University discusses how selecting the right enabling technology is a critical decision for any biotechnology or pharma company developing these novel modalities.

24 Cell Therapy: Challenges and Perspectives

The achievements of cell-based therapeutics over the last decades have bolstered efforts in recent years to bring more of these products to market and across an ever more diverse range of applications. These advanced therapeutics offer promising potential to treat conditions which, to date, have defied traditional treatment modalities. Interest and investment in this sector are at an all-time high and whilst many are hopeful of a boom in the number of approved therapies in the coming years, the industry still faces significant challenges. Anna Gregson & Dean Houston

of Mathys & Squire provides an overview of some of the key applications of cell therapies as well as look more closely at the challenges facing the evolution of this field.

TECHNOLOGY

28 Recreating Life in the Lab: How Predictive Human Organ Models are Transforming the Efficiency of Drug Discovery

An often-underreported fact within the drug discovery and development industry is that around 90% of drug candidates reaching clinical trials ultimately fail, with an even greater number discarded before reaching the clinic at all. A recent market survey of mid-sized biotech’s and large pharma companies highlighted efficacy and cost as the leading concerns during drug development. Failures are predominantly caused by a lack of efficacy, but unforeseen adverse effects in patients are also a factor for concern. Clearly, there is an urgent need for more translatable data between the preclinical and clinical phases of drug discovery and development to address the financial uncertainty caused by the high degree of drug candidate failure. Audrey Dubourg at CN Bio discusses how OOCs represent a concrete approach to reducing, refining, and complementing existing drug testing methodologies.

32 Go-to-market Challenges of CAR-T Therapies

CAR-T therapies are set to revolutionise cancer treatment. With first curative therapies gaining market access across the globe, CAR-T therapies are subject to numerous commercial and non-commercial challenges. Christian Zuberer & Maximilian Feld of Homburg & Partner explains that despite positive clinical responses, the ability to overcome these challenges will determine the future of CAR-T therapies and show whether pharmaceutical companies can make true on the promise of initiating a new era of cancer care.

This issue of IBI reflects this optimism and ingenuity which is fueling the advancement of ATMPs in general. However, as promising as these new therapies might be, it is good to see that there are research groups and companies out there, which are looking for ways to improve discovery and preclinical development of chemically synthesized, so called small molecule drugs.

Screening large compound databases for molecular entities that have a desired pharmacological effect has been and still is the way we find new drug candidates today. Unfortunately, this process is time consuming, and the identified candidates often do not have properties desirable for further drug development. Software aided screening of compounds have improved in a way that chemical structures are preselected to have desirable physicochemical properties or help to modify lead candidates to improve physiochemical properties or efficacy. The capabilities of machine learning are promising to further improve the software aided approach to lead compound discovery by having software that “knows” or “understands” how a good drug looks like. In an insightful article Matthew Segall of Optibrium explains how machine learning can help us to efficiently find new lead compounds. For some small molecule drug candidates, it is difficult to optimize the structure to improve its physicochemical properties. In these cases, drug developers are looking for smart formulations to overcome problems like bad solubility or cell permeability or even cell-/ organ specific targeting. Dr. Ali Al-khattawi and his colleagues, discusses how selecting the right enabling technology is a critical decision for any biotechnology or pharma company developing molecules that target protein specific degradation e.g., proteolysis targeting chimeras (PROTACs). In the end all drug candidates must be tested in a preclinical setting to establish its efficacy and possible toxic potential. And this is where around 90% of drug candidates fail to deliver. Driving the costs for development due to the high expense of animal-based testing which is often not even representative for humans. New methods that mimic human organs by combination of nanofluidic with living cell cultures, so-called organs-on-a-chip (OOC) enables high throughput

IBI – Editorial Advisory Board

• Ashok K. Ghone, PhD, VP, Global Services MakroCare, USA

• Bakhyt Sarymsakova – Head of Department of International Cooperation, National Research Center of MCH, Astana, Kazakhstan

• Catherine Lund, Vice Chairman, OnQ Consulting

• Cellia K. Habita, President & CEO, Arianne Corporation

• Chris Tait, Life Science Account Manager, CHUBB Insurance Company of Europe

• Deborah A. Komlos, Senior Medical & Regulatory Writer, Clarivate Analytics

• Elizabeth Moench, President and CEO of Bioclinica – Patient Recruitment & Retention

• Francis Crawley, Executive Director of the Good Clinical Practice Alliance – Europe (GCPA) and a World Health Organization (WHO) Expert in ethics

• Hermann Schulz, MD, Founder, PresseKontext

• Jim James DeSantihas, Chief Executive Officer, PharmaVigilant

testing of candidates by at the same time reducing the amount of animal tests. Audrey Dubourg at CN Bio discusses how OOCs represent a concrete approach to reducing, refining, and complementing existing drug testing methodologies.

Changing gears to the above-mentioned ATMP related articles. This issue features two articles exploring the landscape of cell therapies, giving a good insight to marketplace by looking at all aspects from funding to therapeutic areas to the future of large-scale cell production. Anna Gregson & Dean Houston of Mathys & Squire provides an overview of some of the key applications of cell therapies as well as look more closely at the challenges facing the evolution of this field. Christian Zuberer & Maximilian Feld of Homburg & Partner take a deep dive into the CAR-T space and explain the challenges which will determine the future success of these therapies despite the initial breakthrough therapies on the market.

Many of the ATMPs in development require high quality production of DNA and mRNA. As product quality is built in the production process, in particular the quality of intermediates, raw and auxiliary materials used have a high impact. Venkata Indurthi of Aldevron explains how they maintain their high quality for mRNA production. Another key aspect in DNA- and gene synthesis is length control and how to purify DNA fragments for desired length. Dr. Joanne Mason, et al. at Yourgenehealth, discusses how to use size selection technology.

I hope you all enjoy this edition. Have a wonderful summer and see you all soon.

Dr. Steven A. Watt, Head of Business Development at A&M STABTEST GmbH

• Jeffrey W. Sherman, Chief Medical Officer and Senior Vice President, IDM Pharma.

• Lorna. M. Graham, BSc Hons, MSc, Director, Project Management, Worldwide Clinical Trials

• Mark Goldberg, Chief Operating Officer, PAREXEL International Corporation

• Maha Al-Farhan, Chair of the GCC Chapter of the ACRP

• Rick Turner, Senior Scientific Director, Quintiles Cardiac Safety Services & Affiliate Clinical Associate Professor, University of Florida College of Pharmacy

• Robert Reekie, Snr. Executive Vice President Operations, Europe, Asia-Pacific at PharmaNet Development Group

• Stanley Tam, General Manager, Eurofins MEDINET (Singapore, Shanghai)

• Stefan Astrom, Founder and CEO of Astrom Research International HB

• Steve Heath, Head of EMEA – Medidata Solutions, Inc

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Regulatory & Compliance

Essential Considerations for a Successful Submission under EU CTR

The European Union Clinical Trials Regulation (EU CTR), which came into force in January 2022, was the biggest change to EU medicinal product legislation since 1995 when the European Medicines Agency (EMA) and the centralised procedure for marketing authorisations were introduced.

The EU CTR presents fundamental changes for clinical trials in all 30 countries of the European Union (EU) and the European Economic Area (EEA). The legislation has replaced the EU Clinical Trials Directive (EU CTD) and established a consistency-centred approach for clinical trial applications, assessments, and reporting. A key feature of the EU CTR is the introduction of a single electronic portal, the Clinical Trial Information System (CTIS), which is mandatory for all EU CTR submissions. CTIS enables harmonised and simplified end-to-end electronic application procedures over the lifecycle of clinical trials across the EU/EEA.

Submitting Applications Through CTIS

CTIS is the single-entry point for submitting, assessing, authorising, supervising, and reporting a clinical trial in all Member States of the EU/EEA. Through CTIS, applicants can submit a single, integrated clinical trial application dossier that covers all clinical trial applications submitted to EU/ EEA Member States, national regulatory agencies and ethics committees. Through this single application, CTIS users also register their clinical trials in a public register.

The introduction of CTIS was the most significant hurdle for the introduction of the EU CTR. The journey towards this introduction has not been without challenges. Due to its pivotal role in the EU CTR process, delays to the release of CTIS led to multiple postponements of the overall introduction of the EU CTR. However, since the launch of CTIS on 31 January 2022, there have continued to be technical issues with the system –some more problematic than others. For example, some of the technology workflows have not acted as they are described. In some cases, this meant a resubmission was needed, even though the reporting member state (RMS) and sponsor had followed all the correct processes. This was a technical glitch that could not be passed. Even though the RMS wanted to progress the application to the next step, it was not possible due to the CTIS technology workflow.

The difficulties with the CTIS portal have been experienced by all users, including sponsors, regulatory agencies, and ethics committees. As a result, some countries have set-up CTIS specific working groups across sponsors, CROs, sites, etc., so that they can exchange training, learnings, and workarounds.

To resolve the portal issues experienced by users, there are regular CTIS updates being released and more information about these is published in the CTIS Newsflash, currently

released weekly. It is important for all CTIS users to stay up to date on the new releases and workarounds since these can be critical to the success of an application.

Preparing for EU CTR Submissions

When planning for submission under the EU CTR in any EU/ EEA country, there are a number of prerequisites for managing studies in CTIS that sponsors should consider. Access to CTIS requires a high-level administrator to manage and assign roles within the system. Sponsors must ensure the correct users/ access rights are in place for CTIS activities to take place. Contract research organisations (CROs) are able to provide CTIS administration and submission support services to sponsors.

Data within CTIS relies on supporting systems to populate sections of the clinical trial information. All stakeholders that will be included in the application form, known as the structured data, must be registered in the Organisation Management System (OMS). These stakeholders may include marketing authorisation holders, sponsors, regulatory agencies, manufacturers/QP release sites, CROs, central labs, clinical trial sites, academia, hospitals, wholesale distributors, etc.

It is critical that sponsors place greater importance on site selection prior to the initial EU CTR submission. A cohort submission strategy that may have previously been possible under the EU CTR would significantly impact site activation due to the sequence of submissions and approval timelines. Therefore, it is practical to wait and ensure the site list is complete prior to initial submission to avoid any downstream delays to site activation for those sites that may not have been included in the initial submission.

Complete harmonisation of the protocol design across all EU/ EEA countries is required. Therefore, any per-country nuances in the clinical approach that may impact protocol design would need to be incorporated into the global protocol. The protocol also needs to include the EU trial number. The protocol should include an unambiguous and clear definition at the start and end of the clinical trial. Unless described in the protocol, a document describing the procedures for the inclusion of subjects and detail of what the first act of recruitment is would need to be submitted. If the end of the trial is not the last patient’s last visit (LPLV), a specification of the estimated end date and justification is required.

Requests for information (RFI) issued during assessment procedures are identified by the sponsor (or CRO) via the notices and alerts area and the RFI tab in the CTIS sponsor workspace. Responses to RFI are within a very short timeline, up to 10 calendar days (validation) and 12 calendar days (assessment), which cannot be extended. Responses to the RFI are required in CTIS, along with any applicable updates

made

Delegating to a CRO

CROs can support navigation of the CTIS system. This support can be provided independently of the organisation delivering the wider clinical trial and outside of the full-service delivery model.

It is generally acknowledged that the CTIS still presents challenges for users. The key benefits that working with a CRO can bring are knowledge and experience. For example, here at ICON, we’ve established a cross-functional initiative to ensure effective and timely implementation of the EU CTR across the organisation. Through close surveillance of the intelligence released by the European Medicines Agency (EMA) and national Regulatory Agencies and Ethics Committees, we’ve been preparing for implementation for many years.

Furthermore, at this point in its implementation, CROs have now been able to gather direct experience with preparing and making EU CTR submissions, in collaboration with sponsors and other key stakeholders. By capitalising on this knowledge and experience, they can address challenges and mitigate risks at the time of submissions. This enables sponsors the time to focus on their clinical trial overall and provides peace of mind that the submission process will be executed efficiently.

Polly Halliday Manager [CTIS], Global Regulatory Clinical Services

Jo Hulbert

Executive Director, Global Regulatory Clinical Services

Mary Hunt-Tyrell Director, Strategic Regulatory Services

Katy Hunter Director, Global Regulatory Clinical Services

Sonia Marimon Garcia

Associate Director, Global Regulatory Clinical Services

Laura Maria Simarro

Senior Regulatory Affairs Specialist

Jaishri Patel

Director, Strategic Regulatory Services

Arnet van den Brink Manager, Clinical Site Activation

Anna Zlateva

Senior Manager, Global Regulatory Clinical Services

This article was authored by the following ICON regulatory team members:

to relevant documentation in CTIS. This would include document(s) with tracked changes, translation(s), and redactions. Missed deadlines will lead to rejection and the need for resubmission.

Augmenting Inspiration with Generative Chemistry

The ability of computers to produce new compound structures using ‘generative chemistry’ algorithms is a hot topic in drug discovery. The field has recently been reinvigorated by new machine learning (ML) algorithms that learn what a drug-like molecule ‘looks like’ and subsequently generate large numbers of chemically meaningful structures.

A key advantage of ML algorithms is that they can explore the chemical space around a lead or series, and are able to generate vastly more compounds than either an individual or a team of experts. In addition, these algorithms can be combined with predictive models of target activities and other compound properties, to identify high-quality chemical suggestions. ML methods have the ability to learn from much more data than any human expert, enabling the identification of complex patterns and guiding future compound optimisation. The resulting generative chemistry systems can also be applied objectively, thereby challenging human biases to enable a more rigorous exploration of optimisation strategies.1

Unfortunately, generative chemistry methods often remain difficult to apply on a routine basis. They typically require a specialised computational expert to set up the complex array of parameters appropriately in order to generate legitimate results. Furthermore, the output is frequently a long list of compounds, many of which are irrelevant. This then creates a need for extensive post-hoc analysis and triage to find the proverbial ‘needle in a haystack’; a compound that is worthy of subsequent synthesis and experimental investigation. Exceptions to issues like this include the BRADSHAW2 and Kernel3 systems, established by GSK and Eli Lilly, respectively, which take a much more proactive approach to suggesting ideas to discovery teams.

Defining Generative Chemistry Methods

A recent paper by Goldman et al 4 describes a scale of Automated Chemical Design (ACD) Levels to classify generative chemistry

methods. This is similar to the one used for autonomous vehicles.5 The ACD Level depends on whether the compound ideas are generated by a human or by a machine, whether a human or machine selects the ideas for consideration, and whether the system performs multiple or single iterations of optimisation (see Table 1). The author of this paper notes that, in their opinion, there are not yet any examples of an ACD Level 5 system in practice.

Although the ACD Level approach provides a convenient way to classify generative chemistry methods, it makes an artificial distinction between whether machines or humans perform the idea generation and selection, when in practice, there need not be such a division of responsibilities. In a concept known as Augmented Intelligence, human experts and computer algorithms can work collaboratively to achieve superior outcomes compared to when working separately.6

Introducing, Augmented Intelligence – Dynamic Learning to Generate Better Compounds

Augmented Intelligence leverages the combined strengths of both human experts and of ML algorithms to overcome their individual weaknesses. Human experts possess an understanding of strategic objectives and context that raw data alone does not capture. With this knowledge, a human expert can guide a rigorous and objective tactical analysis of the strategic options using a ML algorithm. Supplementing human expertise, this computer algorithm can exhaustively explore far more options, learn from more data, and challenge natural human biases to facilitate innovation and thinking ‘outside the box’. The value of this approach has already been demonstrated in wide-ranging disciplines, including medicine,7 document search,8 and customer service.9

Looking at drug discovery as an example, a medicinal chemist will understand the therapeutic objectives of the project, the chemistry being explored, and the biology of the underlying disease. This knowledge goes beyond the raw data on which ML methods are trained. As discussed above, generative chemistry algorithms and predictive models can rigorously and objectively search chemical space to identify untapped optimisation strategies for expert consideration. Furthermore, compounds and new designs selected by a medicinal chemist can be used to ‘seed’ the generative chemistry algorithms, thereby sparking further rounds of idea generation.

Augmented Intelligence in Practice

How can Augmented Intelligence be achieved in practice? An Augmented Intelligence system for compound design must be able to learn from the feedback provided by medicinal chemists to recognise their objectives. The human-computer interactions within such a system must be simple and must not require the medicinal chemist to enter a complex array of definitions and parameters. For example, Optibrium’s

1. Automated Chemical Design (ACD) Levels defined by Goldman et al.4

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Inspyra™ platform employs several methods to generate compound ideas and presents them to a medicinal chemist. Requiring no initial configuration, Inspyra is able to start to work immediately when a data set of compounds is loaded. In this system, a selection of ideas based on the initial compounds are presented to the medicinal chemist for consideration, who can then react in one of four quick and easy ways:

• Select – this is the most positive response; by choosing this option, the platform will keep this idea for later and use it as the basis for further idea generation

• Like – a positive indication that the compound is promising but not good enough to keep

• Ignore – a weakly negative response; there’s nothing wrong with this compound, but it’s not interesting

• Reject – a strongly negative indication; there’s something wrong with this compound

From these responses, the ML algorithm learns the objectives and desires of a medicinal chemist in terms of the properties of a high-quality compound and the chemical diversity to explore using a statistical inference ML method.

The diversity of chemical matter is an essential concept in this exploration. Initially, it is important to explore a wide range of chemical diversity to help fully evaluate many different optimisation strategies and challenge preconceptions. However, once the expert has provided sufficient feedback, the system should learn from their experience and not return irrelevant ideas. Nonetheless, it may be appropriate to sometimes include an occasional radical idea to push the boundaries and consider alternative options.

Figure 1 shows one way to interact with such a system. A panel of ideas is shown, selected from a much larger ‘pool’ of algorithmically-generated compounds. By showing only a small number of compounds for consideration at a time, the panel avoids overwhelming the user. However, to present different ideas and optimisation strategies, the displayed compounds are occasionally updated and the user can interact with these in a highly visual and intuitive way to select, like, ignore, or reject ideas. Selected ideas are added to a data set for further investigation, as well as to inspire the generation of further compound ideas. This approach can explore a wide diversity of ideas generated from many initial compounds in a data set.

An alternative approach, directed more strongly by a chemist, is shown in Figure 2. This displays suggestions for substitutions at a selected position on an individual compound, taken from the pool of ideas. The medicinal chemist can provide feedback on the suggested substitutions, in the same way as for the compound ideas in the panel, to guide the design toward an optimal compound.

Figure 1. A panel (bottom) presents a selection of ideas from a much larger ‘pool’ created by generative chemistry methods for consideration by an expert user. These change periodically to present a variety of optimisation strategies based on the initial data set above. The coloured borders indicate the change in the optimisation property – red indicates an increase, blue a decrease. An expert user can interact with an individual idea (inset) to select (+), like (tick), ignore (repeat symbol) or reject (x) it and thus provide feedback that informs the generation and prioritisation of further compound ideas for consideration.

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So, having established these principles, does Augmented Intelligence work in practice? Figure 3 illustrates how, through interacting with compound ideas over a range of predicted solubilities, the algorithm correctly infers that the medicinal chemist prefers compounds with high solubility. This is clearly shown by the increase in the estimated likelihood that the medicinal chemist will respond positively to a suggestion with a given solubility (the black line).

Similarly, Figure 4 demonstrates how, through selecting compounds from a specific series (A) and rejecting those from other series (B and C), the algorithm infers this preference over time, reducing the likelihood that compounds from series B and C will be suggested.

Combining Human Expertise with Generative Chemistry to Accelerate Discovery

Instead of compound design driven solely by generative chemistry algorithms or by human experts, there is a

viable alternative: an Augmented Intelligence approach, in which humans and machines learn from and reinforce one another to overcome their individual weaknesses. Medicinal chemists can apply both their experience and knowledge to guide advanced ML algorithms to explore the most fruitful directions, while the algorithms can generate and prioritise many more ideas to identify new optimisation strategies and challenge preconceptions. The result? The discovery of better compounds faster.

REFERENCES

1. M. Segall, T. Mansley, P. Hunt and E. Champness, "Captuting and Applying Knowledge to Guide Compound Optimisation," Drug Discov. Today, vol. 25, no. 5, pp. 1074-1080, 2019.

2. D. V. S. Green, S. Pickett, C. Luscombe, S. Senger, D. Marcus, J. Meslamani, D. Brett, A. Powell and J. Masson, "BRADSHAW: A System for Automated Molecular Design," J. Comput. Aided Mol. Des., vol. 37, no. 7, pp. 747-765, 2020.

3. L. Vidler and M. Baumgartner, "Creating a Virtual Assistant for

Figure 3.

with

the likelihood of a user responding positively to a compound with a given solubility (black

The statistical inference uses

distributions

select (blue), like (orange) and reject (green) to transform into an updated likelihood distribution. (b) After ten interactions, the algorithm identifies that the user wishes to increase logS. (c) after thirty interactions, it fully understands the requirement for high solubility and the interplay with chemical diversity. The x-axis is the predicted log of the solubility in µM; the y-axis corresponds to the likelihood.

Figure 2. A generative designer suggests some substitutions for a region of a compound as highlighted by a user. These suggestions are shown from a much longer list and the user can scroll through the list to consider many alternatives. Through interacting with the suggestions, the expert user‘s feedback informs the generation and prioritisation of further suggested substitutions for this region or for any other region that the user subsequently selects.

(a) Starting

no a priori assumptions regarding

line).

the

of user actions –

Research / Innovation / Development

Medicinal Chemistry," ACM Med. Chem. Lett., vol. 10, no. 7, pp. 1051-1055, 2019.

4. B. Goldman, S. Kearnes, T. Kramer, P. Riley and W. Walters, "Defining Levels of Automated Chemical Design," J. Med. Chem., vol. 65, no. 10, pp. 7073-7087, 2022.

5. Society of Automative Engineers, "Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor

Vehicles," 30 04 2021. [Online]. Available: https://www.sae.org/ standards/content/j3016_202104/. [Accessed 03 08 2022].

6. J. Hurwitz, H. Morris, C. Sidner and D. Kirsch, Augmented Intelligence: The Business Power of Human-Machine Collaboration, Auerbach: Taylor & Francis, 2019.

7. G. Bazoukis, J. Hall, J. Loscalzo, E. Marshall Antman, V. Fuster and A. Armoundas, "The Inclusion of Augmented Intelligence in Medicine: A Framework for Successful Implementation," Cell Reports Med., vol. 3, no. 1, p. 100485, 2022.

8. A. Hafner, N. Damij and D. Modic, "Augmented intelligence for state-of-the-art patent search," in IEEE Technology and Engineering Management Conference (TEMSCON EUROPE), Izmir, Turkey, 2022.

9. A. Lui and G. Lamb, "Artificial intelligence and augmented intelligence collaboration: regaining trust and confidence in the financial sector," Info. and Commun. Tech. Law, vol. 27, no. 3, pp. 267-283, 2018.

Matthew Segall

Since 2001, Matthew Segall, PhD, CEO, Optibrium, has led teams developing predictive models and intuitive decisionsupport and visualisation tools for drug discovery. He has published over 60 scientific articles and book chapters on computational chemistry, cheminformatics and drug discovery. In 2009, Matthew led a management buyout of the StarDrop™ business to found Optibrium, which develops novel technologies and ground-breaking AI software and services that improve the efficiency and productivity of drug discovery.

Figure 4. A graph of the relative likelihood of suggesting compound ideas from three chemical series, A, B and C, as a user interacts with compound suggestions, selecting the compounds from series A and rejecting those from series B and C. The algorithm has no access to the series labels, it instead infers the user’s preference only based on the structural similarity of the generated compounds.

Utilising Size Selection to Enhance Gene Synthesis in Synthetic Biology Workflows

Biotechnology harnesses cellular and biomolecular processes to develop technologies and products. These products already improve our lives and show great potential for enhancing the health of our planet. In recent years and especially during the COVID-19 pandemic, the critical role of biotechnology and biomanufacturing in developing life-saving diagnostics, therapeutics and vaccines has been demonstrated and looks poised to progress on stratospheric trajectory, if we can successfully refine the technique to suit its myriad applications. Utilising a size selection technology which uses machine vision algorithms to monitor electric mobility and then respond in real time gives us the ability to enrich DNA through size selection with industry-leading precision.

Next-generation size selection instruments enable the dynamic target enrichment of DNA. The core automated size selection functionality is complemented by the ability to perform fragment length analysis and fluorescence assays for next-generation sequencing (NGS) quality control applications. For example, Yourgene Health’s Ranger® Technology offers a fast, effective and efficient automated solution for separating DNA molecules based on their size and electrical charge; it uses patent-protected, machine vision algorithms to interpret the gel electrophoresis process in real time.

Overcoming Challenges in Gene Synthesis

Gene synthesis forms the foundation of the new field of synthetic biology. It is also accelerating research in well-established fields by providing critical advantages over more laborious traditional molecular cloning techniques. De novo gene synthesis is required when template DNA molecules are not available, such as for codon-optimised sequences. It has been shown that synthetic modified viral sequences produce safer, more effective DNA vaccines. Codon optimisation can increase both the immunogenicity and the therapeutic anti-viral effects induced by DNA vaccines on various targets.

Some of the exciting areas are the clinical, pharmaceutical and other technology sectors struggling with sample purity. When considering the work done in these arenas, everything is highly dependent on the ability to manufacture new drug candidates in novel ways. This relies to an increasing extent on synthetic biology, which is an application that we have really good utility overlap with. Size selection is about enriching and purifying, in other words getting rid of the stuff that you don’t want and keeping the high value targets that you do want by differentiating based on size.

Gene synthesis can be challenging. Traditionally, we talk about a process that uses a lot of old bench techniques that have been around for decades. The process is predicated on synthesising a construct which is as pure as possible and

then you’ve got to clone it. Of the many risks and difficulties associated with the process, this is the largest hurdle in a market which demands complex, quality DNA on increasingly tight turnaround times.

There are many stages in which impurities and error can be introduced early during the building of the construct, and several steps further down the line which jeopardise the chances of isolating your construct, not least when transforming it into a bacterial host. Then you have to let it grow for a while once it’s plated out, and finally begin the laborious task of sampling dozens of colonies before you find the exact construct of interest.

In those sectors requiring long DNA constructs on tight turnaround, but which inherently struggle with sample purity, size selection can be used to help clear that hurdle. It’s able to clean up a lot of those reactions that end up being heavily polluted with truncation or concatenated products which are concomitant with the target product. Technologies that can cope with a huge range of fragment sizes are especially important in gene synthesis because it is here that short fragment lengths become less relevant, and long fragment recovery really comes into play.

Cloning Workflows Made Effective with Next-Generation Size Selection

There are two key themes for size selection in synthetic biology:

1. Continue to pursue the traditional approach to gene synthesis using a plasmid vector and get a superior hit rate at the end because the clones are purer.

2. Incrementally improve the iterative stages of new enzymedriven gene synthesis techniques so that longer (high value) building blocks can be stitched together in fewer stages.

Using machine vision algorithms to monitor electric mobility and then respond in real time to intelligently tune the voltage gives us the ability to enrich DNA through size selection with industry-leading 97% precision (Figures 1–3).

The user selects their range of desired DNA lengths, anywhere from approximately 50–20,000 bp. The “tightness” of the recovery window can be optimised by customisable reagents and consumables. Dynamic voltage adjustment is then applied across all channels, allowing for the synchronised arrival of the desired fragment sizes at extraction wells. Electrophoresis platforms that monitor the migration of the sample all the way along the lanes, rather than at just a single point across all channels, allow for improved accuracy during the size selection process.

Delivering Desired DNA Lengths with Greater Precision

Off-targets get produced much more often than desired products: when taking a sample from your construct to clone, it’s often not of adequate purity because the processes used to synthesise it are imperfect. Additionally, the presence of numerous concomitant truncation products frequently results in a success rate below 10% in complex synthetic reactions, meaning that fewer than 10% of the bacterial colonies from which the construct is harvested actually contain the desired construct. Size selection can increase that up to as high as 90% (Figure 4). If you can do that, you don’t need to check as many colonies before you find your true positive construct. Therefore, the efficiency of one of the most laborious stages of a very time-consuming process is greatly enhanced.

Turbocharging Therapeutic Pipelines

Complicated DNA needs to be turned around on a tight timeline. It normally takes months from the time that it’s ordered until the construct is delivered and so this kind of turnover time is incompatible with an R&D environment, particularly in the pharmaceutical industry. If you have an idea about how to make a new therapeutic, you need to have X number of genes made to be able to have them transcribed in order to make the product and, you have to iterate on that cycle many times. But, if it takes months every time you iterate, then it’s not conducive to coming up with new therapeutics.

Being able to generate these larger constructs has more economic value for groups like pharmaceutical companies; think about vaccine manufacturers as a topical example. The gene synthesis industry as a whole is really trending towards taking this and trying to turbocharge it to be able to make it work well at scale. However, the huge challenge here is the inefficiency with which large constructs are made. Researchers experienced with molecular cloning know that, despite improvements over the past several decades in recombinant DNA tools, such as enzymes and cloning vectors, getting the clone you want is hardly a fool-proof endeavour. Even the seemingly simple task of isolating a gene using PCR cloning or restriction digestion can be tedious and error-prone depending on the sequence.

Figures 1–3: DNA migration through a gel cassette illustrating synchronised arrival at the extraction wells using Ranger Technology (Yourgene Health).

Figure 4: Comparison of gene synthesis with and without next-generation size selection technology. The number of colonies sequenced to identify the target construct is significantly reduced using Ranger Technology (Yourgene Health).

For longer DNA constructs, size selection can help greatly reduce the signal-to-noise issue. In the context of gene synthesis, we can use size selection to get rid of the noise associated with truncation products and recover the full-length construct of interest. Achieving this reduces your sequencing costs, and a range of other costs necessary to identify a synthetic construct that has the desired sequence – a valuable input for manufacturing new therapeutics for pharmaceutical entities. This is perhaps less applicable for simple processes like synthesising short constructs or a simple PCR amplicon, but it is certainly applicable for situations where you require larger and more complicated constructs.

Scaling Synthetic Biology Processes

One of the early adopters of Yourgene’s Ranger® Technology is utilising the high-throughput NIMBUS Select platform to reduce the turnaround time for the delivery of their complicated DNA products for the pharmaceutical industry. They deliver gene constructs to their pharma partners who require inputs for their own novel drug pipeline, enabling them to make and test more candidate products than before. Another adopter, a complex DNA firm, utilises our size selection service to affirm the purity of their samples, assuring them of the quality of their constructs between steps and enabling them to make much larger DNA synthetically.

In talking about supplanting industrial products, we also turn our attention beyond biotherapeutics and vaccines to the territory of petrochemical and coming incumbents, such as plastics. While the market economics of that have previously been a little bit questionable, that’s less and less the case today. The White House itself released a memo1 in September 2022 describing how synthetic biology could be used in manufacturing that accounts for about a third of global output, an estimated $30 trillion in terms of value. The White House also laid out plans to initiate programs to

increase biomanufacturing and expand opportunities within this sector.

Where speed, complexity and cost matters, next-generation size selection technologies that deliver the highest degree of automation alongside scalable, precise and robust electrophoretic analysis offer clinical and research groups a viable option for the analysis of DNA constructs at high volumes, adding value in various synthetic biology applications to great efficacy.

REFERENCES

1. https://www.whitehouse.gov/briefing-room/presidential-actions/ 2022/09/12/executive-order-on-advancing-biotechnology-andbiomanufacturing-innovation-for-a-sustainable-safe-and-secureamerican-bioeconomy/, visited 28 Jun 2023

Joanne has been a champion of modernising diagnostics having previously held positions as VP Biodiscovery with Cambridge Epigenetix (now biomodal) and Director of Sequencing and Sample Acquisition for Genomics England. She has acted as an advisor on the DOH Rare Disease Policy board, MHRA Genomics for Diagnosis forum and UK NEQAS – Genomics England Steering Committee and Genomics England sequencing advisory board. Joanne holds a PhD from Cambridge in Molecular and Cellular Biology.

Email: jo.mason@yourgenehealth.com

Joanne Cross

Joanne has over 20 years’ experience in the molecular diagnostics sector as a marketing professional across oncology and reproductive health fields. Prior to Yourgene, Joanne held roles at QIAGEN as the Global Communications Manager – Companion Diagnostics and Personalised Healthcare and Marketing Manager at DxS, a personalised medicine company. She has a BSc in Medical Microbiology from the University of Newcastle-Upon-Tyne and a Postgrad Diploma from the Chartered Institute of Marketing.

Email: joanne.cross@yourgenehealth.com

Jennifer Golding

Jen has eight years’ NHS experience in Cellular Pathology, having attained the Certificate of Competence in Cervical Cytology in 2011 and pursued her special interests in HPV testing and male fertility analysis. Now with three years’ commercial experience as a Product Manager in the molecular diagnostics industry, Jen has worked with medical devices including NGS, FISH probes, PCR assays and NIPT technology. Jen has a BSc in Medical Biochemistry from the University of Birmingham and is an HCPC registered Biomedical Scientist.

Email: jennifer.golding@yourgenehealth.com

Dr. Joanne Mason

CSOs in CDMOs giving mRNA Manufacturing Considerations Standard and Practical Process to Fast-Track mRNA Drug Product Manufacturing

The central dogma of life has DNA on one side, protein on the other, and RNA sitting right in the centre. RNA, specifically mRNA, is the intermediary step in this dogma and is being used as the essential cargo in many therapies. Expertise in manufacturing high-quality DNA and enzymes used in the in vitro transcription (IVT), capping, and the tailing process is fundamental to mRNA production for several therapeutic modalities. Based on our 25 years of experience as a contract development and manufacturing organisation (CDMO), we present considerations and practical solutions at each step of production to streamline the workflow with the appropriate quality system to deliver mRNA therapeutically.

THE STANDARD WORKFLOW OF AN IVT REACTION

Plasmid

Vector Design Serving as a Linear Template

Using a consciously designed plasmid backbone that has optimized untranslated regions (UTRs) and poly(A) tail with a well-placed restriction site for linearisation is critical in the first step of mRNA manufacturing as they may affect the downstream processes. The 5’ and 3’ UTRs regulate the transcription of the gene of interest, affect translation efficiency, and provide molecule stability. This is where experience in the design process provides the opportunity for optimisation. For example, customers who decide to encode a poly(A) tail within their linear DNA template design also must contend with the limitations of E. coli in propagating structural DNA elements like the poly(A) tail. Once the template is manufactured, linearisation with a blunt end restriction site is recommended as a best practice (Step 1 in Figure 1). Before proceeding into the IVT reaction (Step 2 in Figure 1), the digestion should be fully optimised to a 100% rate. Failure to achieve complete digestion prior to IVT can produce impurities with subsequent steps of the reactions. These considerations in plasmid vector design should be accounted for when choosing a manufacturing partner to get the optimal mRNA synthesis.

Cap it – By Either Enzymatic or Co-transcriptional Methods

Both enzymatic and co-transcriptional capping is accepted by industry standards for the manufacturing of mRNA. With co-transcriptional capping, the big advantage is that it is a one-pot reaction. However, enzymatic capping has been observed to be more efficient than co-transcriptional since it is the natural capping method using wild-type enzymes (Step 3 in Figure 1).

When establishing manufacturing standards, capping efficiency can be determined by state-of-the-art analytical methods. The challenge is that conditions must be optimised for every RNA construct. Best practices include using liquid chromatography followed by mass spectrometry to evaluate the final product. Therefore, when selecting your manufacturing partners, ask what methods will be utilised in determining capping efficiency. It should be clear how the capping efficiency

is being measured, and the process should be tailored to the specific individual construct(s).

Finish with Tailing

The poly(A) tailing of RNA can be done in two ways. One is encoding the sequence into the plasmid. The other way of doing it is enzymatically after the RNA transcription (Step 4 in Figure 1). When the poly(A) tail is encoded within the DNA template, the risk is that bacteria do not see long poly(A) tails as natural, often leading to the tail’s truncation. Typically, anything that has more than 95 to 100 bases is very difficult to retain in an E. coli strain when propagating a plasmid. Therefore, the ideal length is somewhere around 90. Also, selecting a dedicated bacterial stain engineered to handle constructs with these elements provide high yield, and fidelity should be considered. Therefore, working with a CDMO that understands the importance of the cell strains and certain conditions that can retain long poly(A)s is necessary.

Workflow of an IVT Reaction

Figure 1. The mRNA synthesis process starts with the linearisation of the plasmid DNA template in the first step. Then this linearised template can be used in step 2 for the in vitro transcription reaction that generates the mRNA molecule. In the final steps, the mRNA is capped in Step 3 and tailed in Step 4 by enzymatic reactions to finalize the drug substance.

CONSIDERATIONS FOR MRNA SAFETY AND QUALITY Getting Rid of the Impurities

Initially, part of the impurities originates from E. coli , including specific genomic DNA, RNases, and endotoxins as a by-product of plasmid manufacturing. Therefore, it is highly recommended to perform quality control (QC) and assurance to ensure the aforementioned impurities are not present before going into the IVT process used to make RNA. After template linearisation, IVT, and capping, the final mRNA product still contains impurities that include the linearised DNA, so it is necessary to detect and purify them at this step. On the other hand, no impurities are generated in the IVT reaction, including no endotoxin, given that it is a cell-free process. So, it is very important to make sure that these are being measured at the appropriate stage and that there is no carryover to the next step.

Once IVT enzymes generate the mRNA, it must be isolated and purified from the reaction mixture using multiple purification steps to achieve clinical purity standards. Typically, doublestranded RNA (dsRNA) is a major impurity generated because the polymerase can run over, forming additional sequences and folding back on itself. The best way to remove double-stranded RNA is by reverse-phase chromatography. However, a challenge with reverse-phase chromatography is that it uses flammable solvents like acetonitrile. Not all RNA manufacturers have fully equipped facilities with the safety and capacity to handle the solvents in this process. Therefore, it is highly recommended to have a clear understanding of a manufacturer’s full suite of capabilities to prevent surprises later that risk delaying or eliminating your program for production.

Highly experienced manufacturers are positioned well to deal with impurities and remove them through various forms of purification. These steps are critical, especially for mRNA therapeutics and vaccine programs, because these impurities can trigger an undesired innate immune response within patients. Therefore, when considering mRNA manufacturing, it is always worthwhile to find a CDMO that offers a complete production workflow, analytical testing, and a quality release system all under one roof.

Optimise the Analytics Methods

The basic analytics must measure both the process impurities of the drug substance and the impurities within the final drug product for appropriate quality release. As mentioned earlier, for the process impurities, testing is necessary for the stages of RNA synthesis, from any residual DNA to any of the small molecules, such as nucleotides and the other reaction components. It is extremely critical to have a strong analytical panel for testing the drug substance through downstream purification, as this will be the material moving forward to produce the final drug product.

For drug substance, it is critical to evaluate the performance of the mRNA. Therefore, part of industry-standard analytical assays in the release panel includes identifying the sequence of the RNA, RNA integrity, potency, capping efficiencies, and poly(A) tail length. This can be challenging for most because it needs to be developed for every construct. The complexity also lies in the development of the proper analytical assay based on the mRNA molecule to evaluate the potency and

integrity of the RNA. Therefore, relying on a manufacturing partner that can accommodate the construct specificity for analytics is extremely beneficial.

Another very important consideration is selecting a capping method with the highest efficiency. Insufficient capping can not only introduce uncapped RNA, as mentioned above, but it can also generate dsRNA impurities within the product. Both the dsRNA and uncapped RNA can trigger unintended immunogenicity. Therefore, it is extremely necessary to identify the purity of the mRNA molecule developed for your therapeutic application.

In the case of the drug product, the analytical panel and release depend mostly on the formulations and the technology of the delivery system. The essential analytics to confirm the RNA sequence, purity, and potency of the RNA are similar between drug substance and drug product. Still, in the case of final product release, it is also important to look at the concentration and encapsulation efficiency. Furthermore, the industry is moving away from random mixing and using state-of-the-art technology in microfluidics to help control drug formulation and mitigate these impurities.

Analytics can be put in two buckets. The first is analytical innovation/method development, and the second is method validation. Analytical innovation requires a highly skilled technical expert to provide the appropriate data. It is very rare to have this expertise in the industry. For method validation, working with an experienced partner that understands the assay readout is critical to manage the risk and move your mRNA program toward success. In the table below, the specific considerations and the potential negative outcome should be evaluated for each of the production steps to prevent any delays or failures in mRNA drug product manufacturing. Therefore, discussing the specification in detail with a manufacturing partner and determining their in-house capabilities based on your specific needs and final application is critical.

Analytics

Steps

Template Optimisation

Considerations

• Design of the UTR

• poly(A) tail stabilisation

Risks

• Inefficient IVT reaction

• Diminished mRNA expression

• Immunogenicity

• Loss of poly(A) tail in a bacterial production cell line

Polymerases

Capping or poly(A) tailing

Delivery Methods

• Endotoxin

• Residual plasmid DNA interference

• Optimal synthesis methods

• Method development of liquid chromatography and mass spectrometry

• LNP Formulation

• Method assay of encapsulation efficiency

• Lower mRNA synthesis

• Impurities of the final product

• Immunogenicity by uncapped mRNA

• Timeline delays

• Timeline delays

• Ineffective mixing

• Impurities of product

• mRNA efficacy loss

• Inefficient Drug Product delivery

THE NEW FRONTIER FOR DELIVERY AND THERAPEUTICS mRNA Delivery

In the last few years, new therapeutic developers have utilised a range of synthetic materials, including lipid nanoparticles

(LNPs) and polymers, for clinical application to facilitate the delivery of mRNA to target cells. Traditionally, viral vectors such as an adeno-associated virus (AAV) had been used but were often overkill, as it delivers the cargo to the nucleus. In the case of mRNA, the target is delivered to the cytoplasm to utilise the cellular translational framework to produce the target antigen. In the case of LNP and polymers, the delivery mechanism meets the demand to deliver the mRNA to the cytoplasm efficiently.

There is increased interest in using LNP for mRNA delivery, mainly due to the multiple formulations currently available for targeting specificity. The recent years of vaccine development has leveraged the field to the next set of discoveries utilising mRNA-LNP as a drug product for therapeutics. Leading the charge in this new era of drug development has been a collaboration between academics and the biotech industry to test different formulations of LNPs for optimal RNA delivery to specific target sites.

mRNA Therapeutics

mRNA-LNP has opened a new perspective for different vaccine and therapeutic applications. The impact of mRNA COVID vaccines is not behind us, as it paves the way for other mRNA-based vaccines targeting pathogens like influenza and respiratory syncytial virus (RSV). Furthermore, the field has been pushing the possibility of a multivalent vaccine immunising against COVID, influenza, and/or RSV. That is an exciting prospect and serves to highlight the potential of mRNA technologies to impact global healthcare.

An alternative approach to LNP targeting is to modulate and control tissue-specific expression, thereby enabling expression only in appropriate cells or tissues. Therefore, the industry has begun exploring frontiers for mRNA cancer vaccines and therapies that would likely be part of a patient’s overall treatment plan and be combined with traditional

chemotherapeutics. Furthermore, rare diseases are a consideration and can be a possibility in the near future.

The possibilities are endless based on the way RNA is designed, despite the basic elements remaining the same. How it is optimised for therapeutic programs will always be different, given the need for analytical tests required for each of the individual constructs. This is only the beginning, mRNA is well known and has had a jump start in different therapies. However, research has expanded the sequence design to include self-amplifying RNA (saRNA) and circular RNA (circRNA). As told in their names, saRNA can replicate using molecular machinery and is not as dependent on the cell, whereas circRNA is a closed-loop structure that is more stable, but each of these three RNA sequences has its advantages and disadvantages. The only limitation is the time for the field to determine how to maximise each RNA sequence and for which of the many diseases and disorders the industry has just begun to address.

Venkata Indurthi

Venkata Indurthi, Ph.D., has been a member of the Aldevron team since he received his doctorate in pharmaceutical sciences from North Dakota State University, Fargo, ND, in 2016. He has held a variety of positions in increasing responsibility and focus, including Senior Scientist in product and process design, Director of RNA Operations, Director and then Vice President of Research and Development before being named Chief Scientific Officer in 2022. Indurthi received his Bachelor of Science in Biotechnology from SRM University, Chennai, India, in 2010. He has been recognized with several awards and honors from a variety of organizations, served on or lead many panels, and has authored or participated in numerous published articles.

Are We Ready to Formulate the Next Generation of Small Targeted Therapeutics?

The drug discovery pipeline is currently bursting with innovative small and medium sized modalities and targeted therapies. Progress in molecular biology and genome sequencing is fuelling the next wave of drug discovery advancements, re-inventing the space for small molecules through adding new mechanisms of action such as targeted protein degradation (TPD) previously only thought possible with larger protein and antibody therapeutics. Upon their discovery, monoclonal antibodies have revolutionised the biopharmaceutical market due to their enhanced pharmacokinetic profile and high selectivity and binding capability to extracellular targets (Pei et al., 2019). With antibodies, though, it is difficult to target intracellular proteins/targets due to their large molecular size.

Shift towards druggability optimisation

Despite their phenomenal success, years of research have not yet unravelled the dilemma associated with druggability of many pathogenic targets and complete selectivity and safety of biologic treatment modalities. In fact, many compelling drug targets are yet to be drugged as 85% of the disease-causing proteins are believed to remain unexploited with the current large molecule approaches (Neklesa et al., 2017). Therefore, a paradigm shift towards druggability optimisation has been noticed, in quest for molecules that serve as an extension of the oral druggable space. Ideally, these molecules possess the best of all preceding therapeutics, with drug-like characteristics of small molecules and selectivity of monoclonal antibodies and gene therapy (Neklesa et al., 2017).

It is noteworthy that Lipinski’s rule of five served as a rule-of-thumb for the selection of drug candidates with the potential of oral administration. However, the time has come to exploit molecules with drug-like properties far beyond these boundaries. PROTACs, or proteolysis targeting chimeras, come into play with their unique mode of action that distinguishes them from other therapeutic modalities. They induce the degradation of pathogenic proteins by utilising the body’s natural protein disposal machinery known as ubiquitinproteasome system (Pei et al., 2019). PROTACs can unlock the undruggable space as they behave in a catalytic manner that is based on a transient interaction rather than constant, sustained binding. PROTACs tend to knockdown the target at lower doses compared to small molecule inhibitors, thus potentially minimising dose-related toxicity (Chen et al., 2023).

Any Delivery or Formulation Challenges?

It seems that PROTACs intrinsically address the delivery challenges associated with the previously discussed therapeutic modalities as they seem to be more selective. However, our experience from a formulation perspective shows a number of challenges with these type of molecules despite their intricate molecular design. In fact, PROTACs possess challenging physiochemical properties as they fall within the chemical space of what is

called the beyond-the-rule of five space (Bro-5 for short, Figure 1 shows an example of one of these molecules, MZ1) (Madan et al., 2022). Because of the properties imposed by this chemical space such as their high molecular weight, polar surface area, and high lipophilicity, PROTACs come with their own set of challenges, namely poor cellular permeability, poor aqueous solubility, and subsequently low oral bioavailability (Chen et al., 2023). They are also characterised with molecular flexibility, better described as chameleonicity, which adds to their complexity and may account for changes in their physicochemical properties depending on their conformation (Yokoo et al., 2023). Yet, two Oral PROTACs, ARV 110 and ARV 471, managed to reach phase two clinical trials in 2022, reflecting the promising balance of efficacy and pharmacokinetic/ CMC profile of these molecules (Yokoo et al., 2023).

An ideal drug delivery system for these oral bioavailable molecules should be able to address the above challenging physiochemical properties to attain PROTACs with desirable pharmacokinetic profiles and enhance their performance.

What are the Available Formulation Options?

A number of technologies have been suggested to tackle the solubility, permeability, or site-specific accumulation of PROTACs. These efforts include formulating them into nano-sized carriers, prodrugs, and nucleic-acid based delivery systems (Chen et al., 2022). For example, to address the solubility and stability of ARCC-4, a PROTAC targeting androgen receptor, Pöstges and colleagues (2023) embedded ARCC-4 into amorphous solid dispersions (ASD). They aimed to stabilise the amorphous PROTAC within the polymeric matrix by generating an aqueous supersaturated solution of the drug resulting in enhanced solubility.

Figure 1. Chemical structure of MZ1 with arrows highlighting the Bro-5 violating zones. The table shows how MZ1, as a model PROTAC, violates Lipinski’s rule of five.

In two other attempts, researchers have worked on addressing the delivery challenges of ARV-825, a PROTAC that degrades BRD4 which plays a role in tumour progression. Yang et al. (2022) incorporated the PROTAC in nanopolymeric micelles with the aim of overcoming its low water solubility and increasing its accumulation in the brain. Similarly, Saraswat et al. (2022) reported embedding ARV-825 in nanoliposomes anchored with galactose for enhanced targeting of hepatocellular carcinoma.

On the other hand, to improve the pharmacokinetic profile of a BRD4 targeting PROTAC, MZ1, another group of researchers reported encapsulating MZ1 in polymeric nanoparticles that were further conjugated with trastuzumab to treat HER2+ breast cancer (Cimas et al., 2020). Compared to raw MZ1, the conjugated nanoparticles containing the PROTAC revealed stronger cytotoxic effect against MZ1 resistant cell lines. This could be attributed to improved internalisation and uptake by the cells that results in releasing most of drug molecules at the affected site upon conjugating the drug-loaded nanoparticles with trastuzumab.

At MESOX, we have formulated several complex molecules including the model PROTAC mentioned above, MZ1. Our preferred approach for this is a mesoporous carrier, called MesoPAC, engineered from an FDA-approved cellulose derivative (Figure 2). MZ1 dissolution was enhanced within this carrier by more than 2.5X in 30 min (from 19% to 49% release for raw and loaded drug, respectively), whilst stability of the molecule is ensured by a combination of surface anchoring (hydrophobic interactions) and spatial confinement (pore size 20 nm).

decision for any biotechnology or pharma company developing these novel modalities.

REFERENCES

1. Chen, Q., Liu, C., Wang, W., Meng, X., Cheng, X., Li, X., Cai, L., Luo, L., He, X., Qu, H., Luo, J., Wei, H., Gao, S., Liu, G., Wan, J., Israel, D. I., Li, J. & Dou, D. (2022) Optimization of PROTAC ternary complex using DNA encoded library approach. ACS Chemical Biology, 18(1): 25–33

2. Chen, Y., Tandon, I., Heelan, W., Wang, Y., Tang, W. & Hu, Q. (2022) Proteolysis-targeting chimera (PROTAC) delivery system: advancing protein degraders towards clinical translation. Chemical Society Reviews, 51(13): 5330–5350

3. Cimas, F., Niza, E., Juan, A., Noblejas-López, M., Bravo, I., Lara-Sanchez, A., Alonso-Moreno, C. & Ocaña, A. (2020) Controlled delivery of BET-PROTACS: in vitro evaluation of MZ1-loaded polymeric antibody conjugated nanoparticles in breast cancer. Pharmaceutics, 12(10): 986

4. He, Y. et al. (2017) Mesoporous silica nanoparticles as potential carriers for enhanced drug solubility of paclitaxel. Materials Science and Engineering C, 78: 12–17

5. Madan, J., Ahuja, V., Dua, K., Samajdar, S., Ramchandra, M. & Giri, S. (2022) PROTACS: current trends in protein degradation by proteolysistargeting chimeras. BioDrugs, 36: 609–623

6. Neklesa, T., Winkler, J., & Crews, C. (2017) Targeted protein degradation by PROTACs. Pharmacology & Therapeutics, 174: 138–144

7. Pei, H., Peng, Y., Zhao, Q. & Chen, Y. (2019) Small molecule PROTACs: an emerging technology for targeted therapy in drug discovery. RSC Advances, 9(30): 16967– 16976

8. Pöstges, F., Kayser, K., Appelhaus, J., Monschke, M., Gütschow, M., Steinebach, C. & Wagner, K. G. (2023) Solubility enhanced formulation approaches to overcome oral delivery obstacles of PROTACS. Pharmaceutics, 15(1), 156

9. Roots analysis (2023) Targeted Protein Degradation Market: Focus on Technology Platforms and Therapeutics (2nd Edition) [online]. Available from: https://www.rootsanalysis.com/reports/view_document/proteindegradation-market/289.html.

10. Saraswat, A., Vemana, H., Dukhande, V. & Patel, K. (2022). Galactosedecorated liver tumor-specific nanoliposomes incorporating selective BRD4-targeted PROTAC for hepatocellular carcinoma therapy. Heliyon, 8(1): e08702

11. Yang, T., Hu, Y., Miao, J., Chen, J., Liu, J., Cheng, Y. & Gao, X. (2022) A BRD4 PROTAC nanodrug for glioma therapy via the intervention of tumor cells proliferation, apoptosis and M2 macrophages polarization. Acta Pharmaceutica Sinica. B, 12(6): 2658–2671

12. Yokoo, H., Naito, M. & Demizu, Y. (2023) Investigating the cell permeability of proteolysis-targeting chimeras (PROTACs). Expert Opinion on Drug Discovery

Unlike traditional ASDs and other nanocarriers for oral delivery, mesoporous carriers such as MesoPAC offer complete release and tuneable release profiles which can be used to design the desired pharmacokinetic profile and adjust the dose given to patients. Furthermore, it is compactable at high drug loads into tablets (being a plastically deforming material) and ensures a smooth translation to high speed tableting machines. Therefore, mesoporous carriers emerge as contender drug delivery system that could accelerate the development of these new therapeutic modalities.

The formulation challenges of the new generation of small/ medium sized molecules are not to be underestimated in the future. This is an area where little formulation experience exists in the field due to non-conformance to existing small molecules ‘rules’. Selecting the right enabling technology is a critical

CEO/Founder of MESOX and the inventor of MesoPAC technology, with expertise in nano-engineered carriers and spray drying projects for pharmaceuticals. He has delivered multiple particle engineering projects for international pharmaceutical clients including for blue-chip companies and SMEs in the last decade.

Mahmood Al-Rifaie

Mohammed is a Formulation scientist at MESOX with a focus on spray drying technology and mesoporous carriers.

Shouq Al-Shatti

Shouq Al-Shatti is a researcher at Aston University with a focus on oral targeted delivery using mesoporous carriers.

Dr. Ali Al-khattawi

Figure 2: SEM image of the MesoPAC technology carrier.

Cell Therapy: Challenges and Perspectives

The achievements of cell-based therapeutics over the last decades have bolstered efforts in recent years to bring more of these products to market and across an ever more diverse range of applications. These advanced therapeutics offer promising potential to treat conditions which, to date, have defied traditional treatment modalities. Interest and investment in this sector are at an all-time high and whilst many are hopeful of a boom in the number of approved therapies in the coming years, the industry still faces significant challenges, particularly with regard to the manufacture and regulation of these cell-based products. In this article, we will provide an overview of some of the key applications of cell therapies as well as look more closely at the challenges facing the evolution of this field.

To date, the applications of cell therapies have largely fallen into two broad categories; tissue regeneration and immunomodulation. With regard to the former, cell therapy has been viewed as one of the most promising techniques for the repair of damaged tissue, with applications in cardiovascular disease, neurodegenerative disease (for example, Parkinson’s and Alzheimer’s), musculoskeletal injury or degeneration and endocrine dysfunction (for example, type I diabetes).

Cell therapies have proven particularly effective in the repair of articular cartilage, for which the intrinsic capacity for repair is low. The most established of these therapies have employed the patient’s own cells, i.e. autologous cells. In brief, harvested chondrocytes are expanded ex vivo, seeded into a collagen matrix and then re-implanted into cartilage defects in joints. Such products have been available for around a decade now (ChondroCelect, developed by TiGenix was first approved in the EU in 2009) and have shown considerable efficacy, although use of these advanced options is still low when compared to traditional treatment modalities (for example, joint replacement and analgesics). Whilst cartilage repair applications have tended to employ the terminally differentiated chondrocyte, bone repair applications have made use of the regenerative capacity of stem and progenitor cells. Bone marrow-derived mesenchymal stem cells (MSCs) have been proven in a range of orthopaedic applications over recent decades, including in the treatment of infants with osteogenesis imperfecta and in the repair of non-union fractures. Unfortunately, obtaining sufficient yields of pure MSC populations from bone marrow has proven difficult and there has been a switch in recent years to utilise MSCs derived from other sources, such as adipose tissue.

Autologous cell therapies like those discussed above all depend on obtaining sufficient cell numbers from the donor patient and the ability to expand functional cells ex vivo. Off-the-shelf cell therapies, which clinicians can employ for a range of patients, as and when needed, without concerns over yield or expansion protocols, are likely to represent the

future of cell therapy. UK-based biotech, ReNeuron, is one such company forging ahead with allogeneic cell therapies. Interestingly, ReNeuron’s neural stem cell line for the treatment of the disabling effects of stroke were cryopreserved prior to utilisation in the PISCES I (Phase I) clinical trial. Cryopreservation is just one of a number of advancements which will be necessary to bring off-the-shelf cell products to reality.

Whilst the regenerative applications of cell therapies have, at the very least, been researched for some time now, the immunomodulatory applications of cell therapy, in particular, chimeric antigen receptor (CAR) T cells, is a more recent development. Indeed, it was only in the early 90s when first-generation CAR T cells (which contained an antibody/T cell receptor fusion molecule) were developed and around the same time researchers were investigating adoptive transfer of patientderived virus-specific T cells. Since these early days, significant leaps forward have been made. In 2017, Novartis’ Kymriah (tisagenlecleucel) became the first CAR T cell therapy to be approved by the FDA, with Kite Pharma’s Yescarta (axicabtagene ciloleucel) following shortly thereafter. Data from the UK’s Cell and Gene Therapy Catapult clinical trials database indicates that there were around 22 clinical trials investigating the safety and efficacy of CAR T cells in the UK alone in 2018. The success of CAR T cells to date has largely been shown for haematological malignancies (indeed, Kymriah and Yescarta are approved for the treatment of acute lymphoblastic leukaemia and large B-cell lymphoma respectively). In contrast, despite extensive research, CAR T cell therapy for solid tumours hasn’t had the same impact, not least because of the challenges of targeting solid tumours including identifying a suitable target antigen and homing the cells to the hostile, tumour microenvironment. Nonetheless, strides are being made by combining CAR T cell therapy with other biologic agents, specifically checkpoint inhibitors such as pembrolizumab and nivolumab which target programmed cell death protein 1 (PD-1) a key regulatory protein found on T cells. The University of Pennsylvania, for example, is recruiting for a Phase I clinical trial assessing the safety of a CAR T cell/ pembrolizumab combination therapy for the treatment of glioblastoma. This follows preliminary evidence from the Memorial Sloan Kettering Cancer Center that showed both safety and efficacy of a mesothelin targeting CAR T cell and pembrolizumab combination therapy in patients with malignant pleural disease. Thus, the use of CAR T cells for the treatment of solid tumours appears to be progressing.

Immuno-modulatory cell therapies other than CAR T cells are also being investigated in the clinics. By way of example, Fate Therapeutics is currently assessing the safety of its off-the-shelf Natural Killer (NK) cell therapy. Unlike traditional CAR T cells, Fate’s NK cell therapies are derived from an induced pluripotent stem cell (iPSC) line allowing the production of large numbers of well-defined cells without relying on a patient’s own immune cells (which are often depleted in many cancers). Preclinical studies showed the efficacy of these cells in the treatment of

checkpoint inhibitor resistance tumours. At present, Fate has a pipeline of at least five different NK cell therapies.

As well as the immuno-oncology applications, cell therapies are also being trialled for immuno-regulatory applications such as in the treatment of autoimmune disease and graft versus host disease. These trials have largely involved the use of autologous, expanded, regulatory T cells (Treg cells) which, through a range of mechanisms, are able to suppress a variety of immune cells. Treg cells used in studies to date have been isolated from both umbilical-cord blood and peripheral blood. A variety of Phase I studies have been completed or are in the process of assessing the safety of Treg cells for the treatment of type I diabetes. Although in the early stages of development, data to date is showing that Treg cells are well tolerated in patients and the ex vivo expansion methods are capable of generating sufficient numbers of stable and functional Treg cells. Future Phase II/III trials will of course be needed to reveal the true potential of these cells.

Global investment in cell-based therapies increased to US$7.6 billion in 2018, a 64% increase from the previous year. In spite of this, the sector still faces a number of significant challenges before these advanced therapeutics become widely used.

Research and development in this sector is undeniably booming, though difficulties in expanding, manufacturing and transporting cell products may be hampering the commercial viability and ultimate availability of these products. Achieving the quantity of cells needed with current production methods, especially if uptake of these therapies becomes more widespread, is one of the major hurdles facing the industry. By way of example, the recommended dose of ChondroCelect is 1 million cells/cm2 of cartilage defect. CAR T cell therapy

Yescarta is dosed at a staggering 2 million cells per kg (around 140 million cells for an average adult male). The issue is magnified somewhat by the focus of today’s research on the cell product per se; emerging biotech companies with innovative cell therapies should, at an early stage, consider the processes that will be necessary to achieve the desired cell numbers for later Phase II/III trials and beyond. These challenges also bring opportunities however, and there are now a number of innovative companies seeking to develop solutions for the industry, to simplify, accelerate and improve cell therapy manufacturing and supply.

Automation of the manufacturing processes is currently of significant interest to the community. At present, the manufacturing processes employed in the generation of cell therapies largely resemble those utilised in other biopharmaceutical areas (for example therapeutic antibodies). Unlike therapeutic antibodies production, however, cell therapies (especially those relying on patient or donor cells) vary significantly from batch to batch, requiring complex and adaptive processes to generate consistent products within the regulatory confines. Through the implementation and training of a variety of mechanisms, e.g. sensors, robotics and image acquisition as well as processing software, researchers believe variability and reliability of current manufacturing processes can be improved.

Whilst improvements in the manufacturing processes will hopefully lead to a reduction in the costs associated with the production of cell therapies, it should be noted that, unlike traditional therapeutic modalities, cell therapies are often a one-off treatment option for patients. Biotech companies must bear this in mind when attempting to recoup their research and development costs and, as such, costs are always likely to be higher than traditional biologics. As it stands, the high

costs associated with these therapies is proving challenging for healthcare providers to justify.

The cost of these therapies is at least in part due to the convoluted path from bench to bedside. Cell therapies are considered differently to the conventional biopharmaceutical agents and have to undergo even more rigorous regulatory and quality assessments. This of course ensures public safety, but has also put the brakes on the number of cell therapies actually being approved (despite the ample number of trials). As is so often the case, the regulatory frameworks in place have not been able to keep up with the unprecedented scientific advances in this field. What’s more, the absence of harmonisation across jurisdictions has placed undue burden on the smaller players in this field. The lengthy timescales involved in obtaining regulatory approval (even after showing clinical efficacy) are exemplified by Holclar, an autologous cell therapy (comprising human corneal epithelial cells and limbal stem cells) for the repair of damaged cornea, which despite having shown clinical efficacy as early as 1997, only obtained regulatory approval in 2015.

Regulation is of course paramount to ensure the safety of patients receiving advanced therapeutics (including cell and gene therapies) which have long been shrouded in safety concerns. These concerns are not without basis. Indeed, safety has been a major sticking point for stem cell therapies. The primary concern regarding stem cell therapies is unwanted differentiation, as has been shown in the cardiovascular setting, where calcifications have been identified in the myocardium of patients treated with MSCs following infarction (MSCs, of course, give rise to cells of bone and cartilage as well as muscle). Tumorigenesis has also been a concern for stem cell therapies, although this appears to have been unwarranted based on current data. In the immuno-oncology field, CAR T cells have also been associated with safety concerns including the development of cytokine release syndrome in patients receiving CAR T cell therapies, the engagement of target antigens on non-pathogenic tissues and host immune response to the specific recombinant proteins found in these cells. Pleasingly, the industry is seeking solutions to these problems and research is ongoing to improve the safety profile of these therapies. In the CAR T cell space, the incorporation of suicide or elimination genes into delivered cells is being investigated

as a means to selectively deplete these cells in the body when necessary. The approved cell therapies are largely still in their infancy and data from future Phase IV clinical trials will be indispensable in assessing the long-term safety of these therapies.

The number of cell therapies actually approved for clinical use remains small. This highlights that, despite the significant scientific advances and investment, the sector is largely still at the research and development stage. Having said that, the industry appears to have reached a critical mass and with the number of clinical trials in this field growing steadily, we can only assume that we will be seeing more and more of these therapies in the clinics. The industry seems to have clicked and more emphasis is now being placed on the challenges of efficiently, yet safely, manufacturing these products. Improvements in this key area could pave the way for wider implementation and access to these therapies. A multidisciplinary approach will be essential in the coming years to increase the number of approved therapies whilst still ensuring affordability and, importantly, patient safety.

Anna Gregson

Anna entered the patent profession in 2008, working in private practice before qualifying as a European Patent Attorney and a Chartered Patent Attorney in 2012. Anna has worked with a diverse range of clients; from university technology transfer organisations to international corporations. In the 2020 edition of The Legal 500, she is praised for being 'simply outstanding. Professional, pragmatic, approachable and always on hand for advice'.

Dean Houston

Dean has a strong background in the life sciences, possessing both an honours degree in Medical Sciences, as well as a PhD in Molecular Biology. Dean works on a wide variety of inventions related to biotechnology and biochemistry.

Recreating Life in the Lab: How Predictive Human Organ Models are Transforming the Efficiency of Drug Discovery

An often-underreported fact within the drug discovery and development industry is that around 90% of drug candidates reaching clinical trials ultimately fail, with an even greater number discarded before reaching the clinic at all. A recent market survey of mid-sized biotechs and large pharma companies highlighted efficacy and cost as the leading concerns during drug development, further demonstrating the impact that failed drugs can create. These failures are predominantly caused by a lack of efficacy, but unforeseen adverse effects in patients are also a factor for concern. Clearly, there is an urgent need for more translatable data between the preclinical and clinical phases of drug discovery and development to address the financial uncertainty caused by the high degree of drug candidate failure.

The NAM Revolution

Scientists now have access to a large range of preclinical tools for evaluating drug safety and efficacy, including simple in vitro 2D/3D cell culture assays and in vivo animal models. The former is convenient and scalable, enabling large numbers of candidates to be screened rapidly but these assays lack physiological relevance. The latter compensates by providing the complexity of a living system; however, animal models lack human relevance. A new wave of technologies, collectively called New Alternative Methods, or New Approach Methodologies (NAMs), aim to bridge this gap by modeling the physiological processes that occur in our organs and systems. NAMs are defined as any technology, methodology, approach, or combination that can provide information on drug hazard and risk assessment and avoid the use of animals. They include in silico, in chemico, in vitro, and ex vivo approaches. The complementary role of NAMs in drug discovery and development has become increasingly apparent following the FDA's Modernization Act 2.0. The “Alternatives to Animal Testing” bill now allows the FDA to consider data generated from non-animal drug testing methods in IND submissions, where enhanced performance is proven.

An Introduction to Organ-on-a-chip

Organ-on-a-chip (OOC) technology has gained rapid traction within the NAM market over the past decade. OOCs, also referred to as microphysiological systems (MPS), were first described in 2010 with Harvard University’s lung-on-a-chip model, derived from microfluidic devices that assisted academics with cell culture.1 This has since paved the way for the commercial development of many additional organ models and technology providers.

OOC technologies generate 3D microtissues that recapitulate the microarchitecture, functions and physiological responses of human organs and tissues more accurately than conventional preclinical models. 3D microtissues are grown by co-culturing organ-specific primary human cells in the presence of microfluidic perfusion (to mimic the bloodstream), providing

biomechanical stimuli, oxygen, nutrients and waste removal. Furthermore, OOC technology enables complex stimuli such as growth factors to activate cellular processes, interferons to trigger an immune response, fat loading to mimic western diets, and drugs to predict their human effects.

The capacity to recreate an environment that more accurately represents the human body makes OOC useful in almost every step of drug discovery and development. When combined with existing methodologies (and other NAMs), OOC provides human relevant insights that can supplement, cross-validate, or query existing datasets, providing a “bigger picture” for more informed decision making. For this reason, independent research suggests that 26 % of all R&D costs will be saved where OOCs are integrated into Pharma workflows.2 Market research supports this hypothesis, highlighting the top three reasons for OOC purchase; to reduce costs, improve the human translatability of results, and detect/recover flawed drugs.

OOC Applications Across the Preclinical Landscape

In early discovery, OOC technology facilitates a deeper understanding of human physiology and disease mechanisms to support target identification/validation. Here, OOCs complement patient-derived clinical samples, animal models and other in vitro preclinical tools by corroborating target-specific data, or unlocking new avenues to explore. The insights this provides are highly sought after by drug developers.

The same OOC models can also be used within lead optimisation to complement and inform in vivo efficacy studies by enabling a larger range of conditions to be explored ahead of costly animal studies. By allowing the effective therapeutic dose range to be refined ahead of time, the approach supports a reduction in the number of animals required.

During this drug discovery phase, OOCs are also utilised to generate toxicology profiles. Drug-induced liver injury (DILI) remains a major contributor to late-stage drug failures and market withdrawal, however, it is possible to de-risk the process by incorporating liver-on-a-chip models into the preclinical toolbox. Offering enhanced performance versus standard techniques,3 liver-on-a-chip provides a more sensitive way to uncover potential adverse effects early enough to recover promising, but flawed, drugs.

Further along the development pipeline, these predictive human models can be used alongside animal studies to confirm, or query, unexpected drug efficacy, toxicity, or Absorption, Distribution, Metabolism and Excretion (ADME) results. Here, OOC models reduce risk of false reporting due to interspecies issues. In certain cases, OOCs provide a direct alternative to animals – especially where translatability to humans is poor. Human-specific drug modalities (e.g., cell, antibody and gene therapies), for example, pose a significant development challenge. Interspecies differences in genetics, metabolism, or

immunological response render animal models less suitable for safety and efficacy testing when studying advanced therapies. Similarly, when predicting immune-mediated, or idiosyncratic toxicity, OOC offers significant benefits when compared to conventional methods. By incorporating tissue-specific immune cells and peripheral blood mononuclear cells (PBMCs), OOC models recapitulate elements of the human adaptive and innate immune response to provide improved assay sensitivity. Should adverse effects pass undetected within discovery and be reported during clinical trials, the final use of OOCs can be to recreate the clinical scenario and help unlock the cause.

OOC in the Lab

Adopting OOC models into drug discovery and development workflows is a straightforward process, with a variety of hardware, consumables, kits, and pre-validated cells commercially available. Furthermore, OOC models are a highly versatile option, enabling users to precisely adjust the type and ratio of primary human cells to recreate a broad spectrum of environments. For example, simple primary human hepatocyte (PHH) monocultures are used in isolation to overcome the limitations of standard drug metabolism assays to predict the human in vivo clearance rates of slowly metabolised drugs, or to identify rare or human-specific metabolites.4

To model more complex systems that can recapitulate human immune responses, duo-cultures of PHH and Kupffer cells allow researchers to investigate immune-mediated toxicity in DILI assays5. The model can be further enhanced with the addition of circulating PBMCs into the flow that perfuses organs to flag idiosyncratic toxicity.6

To recreate common, but therapeutically un-met, metabolic liver diseases such as Non-alcoholic steatohepatitis (NASH), a co-culture of PHH, Kupffer and human stellate cells are grown to form a liver microtissue that is subsequently exposed to fat loading, thus inducing disease state. In 2021, Kostrzewski et al., 7 demonstrated that the model accurately recapitulates

key aspects of the human condition, whilst Vacca et al.8 used transcriptomic profiling to demonstrate that the model more closely replicates changes found in NASH patients than the conventional murine WD model. This same predictive human model can be used to identify increased DILI susceptibilities for patients with the underlying disease to reduce the risk that therapeutics exacerbate the pre-existing condition.

Liver-on-a-chip tissues are metabolically active, functional and ready for experiments after four days of culture. Each liver chip can be studied for up to four weeks, depending on the needs of the application, and the dosing schedule. For toxicity studies, optimal results can be obtained over eight to ten days, however, disease modeling and efficacy studies may benefit from extended periods to observe longer-term drug effects. As such, these models provide a faster, more human-relevant, and cost-effective approach versus animal models.

In addition to these benefits, many OOC models enable imaging and/or sample recovery to be performed periodically throughout experiments, delivering high content longitudinal data to measure responses such as metabolite formation, biomarker production, or phenotypic responses. Data from OOC assays are generated using standard laboratory techniques such as microscopy, histology cytometry, sequencing, mass spectrometry and multiplexed immunoassays to produce rich insights from each sample. Studies from high profile groups such as the FDA have highlighted the robustness of OOC data; confirming the reproducibility of drug response data collected from two distinct batches of primary human Kupffer cells at multiple test sites using the PhysioMimix® liver MPS and the superior performance of this approach for drug metabolism, toxicity and accumulation applications relative to in vivo animal models.3

Beyond culturing single-organ models in isolation, it is now possible to interconnect OOC models together into fluidically linked multi-organ systems. Integrating liver models with other models such as the lung or gut, for example, recapitulates common routes of drug administration. Multi-organ systems simulate processes such as drug absorption and metabolism to predict bioavailability and provide preclinical, human-relevant insights. In conjunction with physiologically based pharmacokinetic modeling OOC data can be extrapolated from an in vitro result into an in vivo prediction to inform dose setting. Multi-organ models also provide a means to facilitate interorgan crosstalk for evaluating on- and off-target drug effects or to interrogate the effects of inflammation or other risk factors when investigating drug effects.

A Look to the Future

As such, OOCs represent a concrete approach to reducing, refining, and complementing existing drug testing methodologies. With market research showing that 66% of respondents are currently using, or plan to adopt OOC in the next two years, these technologies are set to transform the way that drugs are discovered and tested by enabling in vitro recapitulation of human physiology. They provide lower cost, higher throughput animal alternatives that can replace or complement, as needed. By improving the translatability of data between the laboratory and the clinic, more accurate predictions of human responses can now be made in the

discovery and development phases to decrease the risk of unexpected failures during human clinical trials. Ultimately, the field still strives towards the end goal of the ‘body-ona-chip’, where multi-organ systems can accurately replicate precise genetic or gender differences to support development of advanced, personalised therapies. Only time will tell if the approach saves incalculable time and billions of dollars in research and development costs alongside additional NAMs, such as in silico modeling and AI, but right now the future for OOC looks bright.

REFERENCES

1. Huh D, et al. (2010) Reconstituting organ-level lung functions on a chip. Science. Jun 25;328(5986):1662-8. doi: 10.1126/ science.1188302. https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC8335790/

2. Franzen et al (2019). Impact of organ-on-a-chip technology on pharmaceutical R&D costs. Drug Discov Today. 2019 Sep;24(9):1720-1724. doi: 10.1016/j.drudis.2019.06.003. Epub 2019 Jun 8. PMID: 31185290. https://pubmed.ncbi.nlm.nih. gov/31185290/

3. Rubiano, A et al (2021). Characterizing the reproducibility in using a liver microphysiological system for assaying drug toxicity, metabolism, and accumulation.Clinical and Translational Science, 14(3), 1049-1061. https://doi.org/10.1111/cts.12969

4. Docci L, et al (2022) . Exploration and application of a liver-ona-chip device in combination with modelling and simulation for

quantitative drug metabolism studies. Lab Chip. 15;22(6):11871205. doi: 10.1039/d1lc01161h. PMID: 35107462.)

5. Novac, O et al. (2022). Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro. J. Vis. Exp. (179), e63389, doi:10.3791/63389 https://www.jove.com/t/63389/ human-liver-microphysiological-system-for-assessing-drug-induced

6. https://cn-bio.com/applications/safety-toxicology/immunemediated-toxicity/, visited on 24 May 2023

7. Kostrzewski T, et al. (2019). A Microphysiological System for Studying Nonalcoholic Steatohepatitis. Hepatol Commun. Nov 13;4(1):77-91. doi: 10.1002/hep4.1450. PMID: 31909357; PMCID: PMC6939502. https://pubmed.ncbi.nlm.nih.gov/31909357/

8. Vacca, M, et al (2020). Bone morphogenetic protein 8B promotes the progression of non-alcoholic steatohepatitis. Nat Metab 2, 514–531 https://doi.org/10.1038/s42255-020-0214-9

Audrey Dubourg

Audrey Dubourg is CN Bio’s Product Manager for their PhysioMimix™ Organ-On-Chip lab benchtop platform, which enables researchers to model human biology in the lab through rapid and predictive 3D tissue-based studies harnessing microfluidic technology. Audrey has significant experience in 3D cell culture using MPS technologies and a post-doctoral background in microbiology.

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Go-to-market Challenges of CAR-T Therapies

CAR-T therapies are set to revolutionise cancer treatment. With first curative therapies gaining market access across the globe, CAR-T therapies are subject to numerous commercial and non-commercial challenges. Despite positive clinical responses, the ability to overcome these challenges will determine the future of CAR-T therapies and show whether pharmaceutical companies can make true on the promise of initiating a new era of cancer care.

Setting the Scene

In 2019, the commercial pharmaceutical industry recorded global sales of ~1300bn USD, and is expected to grow at a CAGR of 6.8% until 2024. Even though the majority of sales is still generated with traditional single-compound medicines, biologics are the major growth driver of the pharmaceutical industry. Development of simple compound medicines has reached its limits and research in this area is almost at peak. Today, biologics are the most promising technology which, combined with increased knowledge of medicinal chemistry and new methods of production, enable companies to develop completely new drugs and treatments.1 In 2019, biologics accounted for ~21% of global drug sales2 and represented 21 of 69 Drug License Application Approvals granted by the FDA.3,4

improve damaged tissue or organs by combining scaffolds, cells and biologically active molecules.6

As illustrated in Figure 1, there are currently ~1000 registered clinical trials for advanced therapies, accounting for ~15% of all clinical trials conducted globally. The trial landscape is coined by gene therapies focussing on rare diseases across numerous indications and curative cell therapies focussing on oncology. The majority of the ~625 cell therapy trials is investigating the potential of CAR-T treatments, which are regarded to be a revolution in cancer therapy.7

CAR-T Therapies at a Glance

CAR-T therapy refers to chimeric antigen receptor (CAR)-T-cell therapy, an innovative and individualised cancer treatment method that combines the capabilities of cell, immune and gene therapy into one therapy concept. T-cells are ex-vivo genetically modified to express a chimeric antigen receptor on their surface that recognises and binds to a specific antigen on the surface of malignant cells. Once the receptor binds to an antigen, the T-cell is stimulated to attack and destroy the malignant cell. Due to the fact that CARs have the ability to combine both antigen-binding and T-cell-activating functions into a single receptor, they are defined as chimeric.8,9

T-cells leveraged for the manufacturing of CAR-T therapies may originate from the patient (autologous) or an external donor (allogeneic). As all currently approved CAR-T therapies are autologous, the drug manufacturing process is integrated into the patient treatment journey. Figure 2 illustrates the manufacturing process of a CAR-T therapy.9

“GO-TO-MARKET CHALLENGES OF CAR-T THERAPIES”

Within the field of biologics, advanced therapies have emerged as the innovative spearhead focusing on novel curative treatments. They comprise cell and gene therapies, as well as tissue engineering, as shown in Figure 1.5 Curative cell therapies today are mostly oncology-focused treatments where genetically modified T-cells are transferred into a patient to target a specific protein and destroy the malignant cells. Gene therapies are treatments that focus on delivering therapeutic DNA into a patient´s cells to cure the underlying disease. Current methods comprise the editing of genetic material, the addition of genetic material and the targeted silencing of genes. Tissue engineering is the umbrella term for therapies which restore, maintain and/or

Overview of curative advanced therapies

Prerequisite to initiating the CAR-T manufacturing process is the referral of an identified patient to a specialised CAR-T centre. Only after passing a CAR-T treatment eligibility assessment is the patient approved to undergo leukapheresis.

(PhaseI – 120,PhaseII –210,PhaseIII – 32)

~

Leukapheresis is the separation and collection of the patient’s white blood cells and resembles the first step of CAR-T manufacturing.8

The obtained sample of white blood cells is frozen and transported to a specialised manufacturing laboratory, where T-cells are isolated from the sample. Following the isolation is the activation of the cells using monoclonal antibodies. Once the T-cells are activated, they are genetically modified to express a specific CAR on their surface. This is achieved by utilising modified viral vectors to deliver a strand of therapeutic DNA into the cell. Modified CAR-T-cells are then duplicated to achieve a clinically significant number of cells and prepared as an infusion for the patient. The CAR-T therapy is transported back to the CAR-T center and administered to the patient.10

Today, there are two CAR-T therapies that have received market approval. Both, KYMRIAH® (Novartis) and YESCARTA® (Gilead Sciences) are curative CAR-T therapies which target liquid tumours with the surface antigen CD19.11 As targeting these specific surface proteins has proven to be successful in the treatment of haematologic cancer, the majority of clinical trials (~95%) within the field of CAR-T therapies is focussed on liquid tumours for late-stage relapse and refractory patients.7 So far, translating the mode of action of CAR-T therapies has not proven to be successful.

Even though big pharma has been the first mover with regard to CAR-T market approval, innovation in this field is driven by small biotech firms.12

Despite the curative potential and promising clinical responses, CAR-T therapies face numerous go-to-market challenges. These challenges can be divided into noncommercial and commercial challenges, and need to be overcome for CAR-T therapies to gain market traction and make true on the promise to revolutionise cancer treatment. In the following section, the main challenges of CAR-T therapies will be highlighted, and potential solutions on how to tackle these challenges carved out.

Non-commercial Go-to-market Challenges of CAR-T Therapies Manufacturing

An essential part of manufacturing CAR-T therapies is the ex vivo genetic modification of autologous T-cells. The process incorporates the manufacturing process of gene therapies into the manufacturing of cell therapies. Following the isolation, enrichment and activation of the T-cells, viral vectors are

leveraged to insert therapeutic DNA into the T-cells to trigger the expression of the CAR on the cell surface. This complex multi-level process is not only cost-extensive and time-consuming, but also subject to a high failure rate and thus a low production efficiency (8).

The low efficiency of CAR-T manufacturing is amplified by the fact that autologous T-cells gained through leukapheresis are often not usable as they express lasting damage from previous chemotherapies. This again leads to a decreased efficiency in the expansion of the modified CAR-T-cells and thus the production of the therapy.14

Furthermore, the complex process entails manufacturing of CAR-T therapies in highly specified laboratories. Availability of these laboratories is limited, leading to capacity shortage in production. 10 This contrasts with the conventional industrial manufacturing of pharmaceutical products, which allows for high-output production and follows clear Good Manufacturing Practice (GMP) guidelines. As CAR-T therapies are manufactured on a patient-individual basis in a laboratory, it is challenging to implement dedicated quality assessments that ensure a continuous quality control along the manufacturing process.10,13

In order to overcome the manufacturing challenges, pharmaceutical companies should consider whether to:

• Leverage innovation in gene therapy to improve viral vector efficiency and consider potential alternatives for genetic modification (i.e. CRISPR-Cas9)

• Foster early storage of “healthier” T-cells in hospitals for patients likely to receive CAR-T therapy to increase manufacturing efficiency and time

• Cooperate with academic institutions to leverage their laboratories and increase manufacturing facilities

• Define standard operation procedures (SOPs) for CAR-T manufacturing to allow for dedicated quality assessment along the manufacturing process steps.

Supply Chain

The limitation to produce CAR-T therapies in highly specified laboratories entails a high degree of centralisation of the available manufacturing facilities.13 Due to the centralisation and the fact that all currently approved CAR-T therapies are autologous, a patient’s blood sample is required for every batch of CAR-T therapy produced.16 Transporting the blood sample from the CAR-T centre to the specified laboratory, and the genetically modified CAR-T therapy back to the hospital,

1

Source: Homburg & Partner | 8, 9

2. Leukapheresis:Tcells removal from patient’sblood

1. Patient’sblood drawnforeligibility testing

6. Modified T-cells are re-transferred to patient

3. Isolationand activationofT-cells

4. Genetic modification of T-cells to enableCAR formation

5. Reproductionof modified T-cells

Figure 2 – CAR-T manufacturing process8,9

requires a complex and sophisticated delivery system with a flawless cooling chain. The stakeholder within this delivery system – specified CAR-T centres, dedicated courier services and the manufacturing laboratories – need to be able to meet the requirements with regard to storage, packaging, shipping and sample tracking. All steps in the delivery system must be coordinated in a way that the time-to-treatment for the patient is optimised. This process is often referred to as patient scheduling.5

Sample tracking is the essential part of the delivery system. The tracking system is bi-directional and requires an error-free tracking of the patients’ blood sample and the respective individualised CAR-T therapy. As current therapies are autologous, errors in the adequate tracking of a sample lead to the disposal of the therapy and a prolongation of the manufacturing process.13

Another challenge related to the supply chain of CAR-T therapies is the availability and production of viral vectors. In addition to CAR-T therapies, gene therapies are also applying the same viral vectors. As there are only a few companies specialising in manufacturing viral vectors, they are not able to meet the continuously increasing global demand. This limited availability entails waiting times during CAR-T development and manufacturing.16 Furthermore, viral vector production is very cost-extensive and time-consuming, as it is coined by low yields per viral batch (approximately one clinically useful viral particle out of 100,000 produced) due to a low transfection efficiency.18

In order to overcome the supply chain challenges, pharmaceutical companies should consider whether to:

• Invest in laboratories/cooperate with academic laboratories to decentralise manufacturing facilities and decrease transportation time and effort

• Cooperate with digital companies / courier services specialising in tracking software and leverage cloud-computing for real-time tracking of patient samples

• Provide end-to-end software to improve overall patient scheduling and supply chain processes by leveraging digital health solutions

• Set-up in-house production facilities for viral vectors or enter exclusivity contracts with manufacturers to avoid supply bottlenecks and decrease costs

• Foster innovation towards allogenic CAR-T therapies to develop patient-independent “off-the-shelf” treatments with simplified supply chain.

Commercial Go-to-market Challenges of CAR-T Therapies Administration

The administration of a CAR-T therapy entails complex infrastructural, personnel and regulatory requirements. Since the patient is incorporated into the supply and manufacturing process, hospitals and physicians are also integrated. They need to be able to conduct leukapheresis, handle cryopreserved patient blood samples, collaborate with couriers and integrate the sample tracking into their pharmacy supply systems. Furthermore, physicians need to have CAR-T medical expertise and the hospital needs to have specific SOPs in place that allow for a CAR-T dedicated reporting and

documentation of side-effects and patient responses. The hospital must be able to cooperate with the manufacturing team at the laboratory with regard to patient information about treatment history, therapy responses and current health status during conditioning therapy. This complexity results in the need for multi-stakeholder cooperation at a scale that the majority of hospitals is not able to deliver. Therefore, administration of CAR-T therapies is allocated to a limited number of dedicated CAR-T centres that can meet these requirements.17

Like the manufacturing facilities, specialised CAR-T centres are also coined by a high degree of centralisation. This results in the fact that fragile late-stage cancer patients have to travel to these centres for their diagnosis, treatment preparation, treatment and follow-up monitoring, resulting in a high health risk for the patient. In addition, CAR-T centres face the challenge of patient referral by treating physicians in other hospitals.17 Thus, the greatest challenge for pharmaceutical companies with regard to administration is transferring the eligible patients to the CAR-T centres and understanding the roles and responsibilities of the stakeholders involved in the patient referral process.

In order to overcome the administration challenges, pharmaceutical companies should consider whether to:

• Support clinics with dedicated services and support knowledge and capability building to increase amount and capacity of approved CAR-T centres

• Develop a sophisticated patient-monitoring programme that can be conducted in non-CAR-T centres and the outpatient sector to decrease pressure on CAR-T centres

• Establish an international CAR-T patient register to improve identification of potential CAR-T therapy candidates

• Invest in laboratories/cooperate with academic laboratories to decrease transportation time and simplify communication with CAR-T centres.

Costs & Reimbursement

Currently, CAR-T therapies entail high costs for the healthcare system. Due to the complex manufacturing, elaborate supply chain and the cost- and time-extensive R&D process, CAR-T therapies come along with a high price tag of >350,000 USD per therapy.22 This high price, based on the curative nature of the therapy and in contrast to conventional treatments, is concentrated into a single upfront payment. High one-time payments challenge the current budget planning of payers and hospitals, which is set up to spread therapy costs over a defined treatment period.23 Furthermore, there is a lack of adequate data with regard to long-term efficiency, safety profile and the need for additional patient care of curative CAR-T therapies10. This results in the payer having the burden of carrying the financial risk of a therapy upfront, without assurance that the therapy will work efficiently in the long run.

Currently, the pressure on the healthcare system exerted from the high-priced CAR-T therapies is manageable, as only small patient populations receive the treatment. With additional CAR-T therapies coming to market, the price

Gain a competitive edge in CAR-T race

Be the innovative leader in R&D

1. Drive CAR-T development towards off-the-shelf allogenic therapies

2. Invest in early R&D on solid tumors

Create best practices in CAR-T manufacturing

1. Replace viral vector technique with innovative gene editing methods

2. Drive operational excellence in manufacturing with clear operating procedures (SOPs)

Manage commercial CAR-T ecosystem

1. Support to connect laboratories, physicians, clinics to establish CAR-T ecosystem

2. Identify and build-up labs for de-bottlenecking manufacturing capacity

Manage access and referral

1. Offer broad “bouquet” of contracting options to payers (annuity vs. one-time)

2. Understand drivers and barriers in patient referral process to CAR-T centers

pressure is set to increase, suggesting significant marketaccess challenges across countries in the future.22

In order to overcome the cost and reimbursement challenges, pharmaceutical companies should consider whether to:

• Lead price negotiations with long-term cost-benefit assessments and innovative contracting solutions (i.e. annuity-based contracts, outcomes-based contracts)

• Understand the patient referral process to foster transfer of patients to CAR-T centres to increase market uptake and patient access of CAR-T therapies

• Choose a targeted patient population to be assigned to the right comparative therapy and avoid price cuts (in case of non-superior benefit assessment).

Strategic Recommendations

Set to disrupt and revolutionise conventional cancer therapy, CAR-T therapies – and in turn the developing pharmaceutical companies – are facing numerous challenges, as broadly illustrated. At the same time, defining the right strategy and choosing the most relevant measurements for a successful go-to-market is a challenge itself. Figure 3 outlines four key recommendations for pharmaceutical companies to gain a competitive edge over their industry peers and to overcome go-to-market challenges of CAR-T therapies.

Success with CAR-T therapies will be defined by companies willing to take risks, strive for innovative leadership and set industry standards. This, combined with a strategy focussing on building networks and establishing clearly defined innovative contracting options to secure therapy access and reimbursement, will be the foundation to become an industry leader in CAR-T cancer treatment, despite the present challenges.

REFERENCES

1. Visiongain ‘Global Biologics Market, Industry and R&D: Forecasts 2015-2025 – Challenges and Opportunities from Rising Drug Demand and Biosimilar Competition’. https://www.visiongain.com/report_ license.aspx? rid=1485 visited on 22 Mar. 2020.

2. HKExnews. Size of the global chemical drugs and biologics pharmaceutical market from 2014 to 2023 (in billion U.S. dollars) [Graph] (2019). Statista. https://www.statista.com/ statistics/1085563/revenue-chemical-drugs-and-biologics-globalpharmaceuticals/ visited on 23 Mar. 2020.

3. Food and Drug Admistration (FDA). New Drug Therapy Approvals 2019 (2019). https://www.fda.gov/media/134493/download, visited on 19 Mar. 2020.

4. Food and Drug Admistration (FDA). 2019 Biological License Application Approvals (2019). https://www.fda.gov/vaccines-blood-biologics/ development-approval-process-cber/2019-biological-licenseapplication-approvals, visited on 19 Mar. 2020.

5. Abou-El-Enein, M., Elsanhoury, A. & Reinke, P. Overcoming challenges facing advanced therapies in the EU market. Cell Stem Cell, 19(3), 293-297 (2016).

6. European Medicines Agency. Advanced therapy medicinal products: Overview (n.d.) https://www.ema.europa.eu/en/human-regulatory/ overview/advanced-therapy-medicinal-products-overviewTbd, visited on 23 Mar. 2020.

7. U.S. National Library of Medicine, ClinicalTrials.gov https:// clinicaltrials.gov visited on 23 Mar. 2020.

8. June, C. H., O’Connor, R. S., Kawalekar, O. U., Ghassemi, S. & Milone, M. C. CAR T cell immunotherapy for human cancer. Science, 359, 1361-1365 (2018).

9. Levine, B. L., Miskin, J., Wonnacott, K. & Keir, C. Global manufacturing of CAR T cell therapy. Molecular Therapy-Methods & Clinical Development, 4, 92-101 (2017).

10. Jørgensen, J., Hanna, E. & Kefalas, P. Outcomes-based reimbursement for gene therapies in practice: the experience of recently launched CAR-T cell therapies in major European countries. Journal of Market Access & Health Policy, 8(1), 1715536 (2020).

11. Philippidis, A. Top 10 Companies Leveraging Gene Editing in 2019. Genetic Engineering & Biotechnology News, 39(10), 16–17 (2019).

12. Papathanasiou, M. M., Stamatis, C., Lakelin, M., Farid, S., Titchener-

Figure 3 – Key recommendations for pharmaceutical companies

Hooker, N. & Shah, N. Autologous CAR T-cell therapies supply chain: challenges and opportunities? Cancer Gene Therapy, 1-11 (2020).

13. Rafiq, S., Hackett, C. S. & Brentjens, R. J. Engineering strategies to overcome the current roadblocks in CAR T cell therapy. Nature Reviews Clinical Oncology, 17, 147-167 (2020).

14. Li, C., Mei, H. & Hu, Y. Applications and explorations of CRISPR/Cas9 in CAR T-cell therapy. Briefings in Functional Genomics, 1-8 (2020).

15. Eyles, J. E., Vessillier, S., Jones, A., Stacey, G., Schneider, C. K. & Price, J. Cell therapy products: focus on issues with manufacturing and quality control of chimeric antigen receptor T‐cell therapies. Journal of Chemical Technology & Biotechnology, 94(4), 1008-1016 (2019).

16. Greinix, H. T., Attarbaschi, A., Girschikofsky, M., Greil, R., Holter, W., Neumeister, P., Peters, C., Petzer, A., Rudzki, J., Schlenke, P., Schmitt, C. A., Schwinger, W., Wolf, D., Worel, N. & Jaeger, U. Ensuring center quality, proper patient selection and fair access to chimeric antigen receptor T-cell therapy: position statement of the Austrian CAR-T Cell Network. memo-Magazine of European Medical Oncology, 1-5 (2020).

17. Capacity Analysis for Viral Vector Manufacturing: Is There Enough? https://bioprocessintl.com/manufacturing/emergingtherapeutics-manufacturing/capacity-analysis-for-viral-vectormanufacturing-is-there-enough/ visited on 24 Mar. 2020.

18. Tarnowski, J., Krishna, D., Jespers, L., Ketkar, A., Haddock, R., Imrie, J. & Kili, S. Delivering advanced therapies: the big pharma approach. Gene therapy, 24(9), 593-598 (2017).

19. Callréus, T., El-Galaly, T. C., Jerkeman, M., de Nully Brown, P. & Andersen, M. Monitoring CAR-T-Cell Therapies Using the Nordic Healthcare Databases. Pharmaceutical Medicine, 33(2), 83-88 (2019).

20. Ghosh, A. & Gheorghe, D. CAR T-Cell Therapies: Current Limitations & Future Opportunities (2019). https://www.cellandgene.com/doc/ car-t-cell-therapies-current-limitations-future-opportunities-0001, visited on 25 Mar. 2020.

21. Patel, N., Farid, S. S. & Morris, S. How should we evaluate the cost-effectiveness of CAR T-cell therapies? Health Policy and Technology (2020).

22. Kefalas, P., Ali, O., Jørgensen, J., Merryfield, N., Richardson, T., Meads, A., Mungapen, L. & Durdy, M. Establishing the cost of implementing a performance-based, managed entry agreement for a hypothetical CAR T-cell therapy. Journal of market access & health policy, 6(1),

Christian Zuberer

Christian is a Partner in the Mannheim office of Homburg & Partner. He is responsible for the (bio-) pharmaceutical competence centre. His focus is on healthcare, (bio-) pharmaceuticals and biosimilars / generics, with particular expertise in market access & pricing, strategy, marketing & sales (digital, multichannel) and transformation & organisation. His therapeutic focus is on (immune) oncology, haematology and rare diseases. Christian studied Business Administration (Master of Science) with a focus on Strategy and Finance at HHL Leipzig Graduate School of Management.

Maximilian Feld

Maximilian Feld is a Consultant in the Düsseldorf office of Homburg & Partner. He is part of the (bio-) pharmaceutical competence centre and his focus is on healthcare, (bio-) pharmaceuticals and biosimilars / generics with expertise in market access & pricing, strategy, marketing & sales (digital, multichannel). His therapeutic focus is on (immune) oncology, haematology and rare diseases. Maximilian studied International Business (Master of Letters) with focus on Strategy & Innovation at the University of St Andrews.

1511679 (2018).

23. Santomasso, B., Bachier, C., Westin, J., Rezvani, K. & Shpall, E. J. The other side of CAR T-cell therapy: cytokine release syndrome, neurologic toxicity, and financial burden. American Society of Clinical Oncology Educational Book, 39, 433-444 (2019).

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