Ini Vivo Clinical Trials Mini-Magazine by Informa Pharma Intelligence

In Vivo

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vol. 36 ❚ no. 05

MAY 2018

pharma intelligence ❚ informa

CLINICAL TRIALS Art Or Science? Trial Innovators Aim For Both

Pfizer’s Reference Point on Trial Innovation: Ask the Patient

Transitions In The Trial Landscape: What Will Drive RCTs Into The Clinic?

Big Data And The FDA: To Mine The Value, First Mind The Gaps

❚ CLINICAL TRIALS: Infographic

2018 PHARMA PIPELINE SNAPSHOT 8040

THE 2018 PIPELINE BY PHASE

7493

■ 2017

■ 2018

2357 2360 2064

2127 1395 1025 1006 220 214

Preclin

Phase I

Phase II

Phase III

▲

0.1%

▲

1.9%

INCREASE

DECLINE

3.0%

▲

INCREASE INCREASE fueled by a massive 3,807 new drugs debuting in development

(NEARLY FLAT)

▲

7.3%

Pre-reg

1199

116 150

79 52

Registered Launched Suspended

1,809 Antibody-based therapies in the pipeline, up 7.2% from 2017

For the first time, number of projects exceeds 15,000 but pipeline growth slows to 2.7%

Information drawn from Informa Pharma's Pharma R&D Annual Review 2018, using Informa’s R&D database Pharmaprojects, as of January. To see more from the review, go to https://pharmaintelligence.informa.com/resources/product-content/ pharma-rd-annual-review-2018-supplement 2 | In Vivo | May 2018

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CLINICAL TRIALS: Infographic ❚

TOP 10 PHARMA COMPANIES BY SIZE OF PIPELINE Novartis

223 214 216 213 205

J&J AZ Pfizer

192 206 191

Roche GSK

191 193 179

Sanofi 141

Takeda

■ 2018

TOP 10

Novartis is at the top position for a second year, but only by a narrow margin due to a shrinking pipeline.

232

250

191

Merck & Co

■ 2017

251

Johnson & Johnson climbs up three places to claim the runner-up position. It and Takeda are the only top 10 companies that increased portfolio size.

229

164

144 134

BMS 0

TOP 10

100

150

200

250

300

THE TOP 10 THERAPY GROUPS

1 ANTICANCER

5212

2 BIOTECHNOLOGY 3 NEUROLOGICAL

4751 2604

4 ANTI-INFECTIVE

2238

5 ALIMENTARY/METABOLIC 2237 6 REFORMULATIONS

2073

7 MUSCULOSKELETAL

1597

8 DERMATOLOGICAL

929

9 IMMUNOLOGICAL 10 CARDIOVASCULAR

916 893

7.6%

increase in the number of cancer candidates this year, a growth rate close to three timesthat of the overall pipeline

9.3%

decrease of anti-infective candidates

7.2%

decrease of cardiovascular candidates

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❚ CLINICAL TRIALS: Practice Innovation

Pfizer’s Reference Point for Clinical Trial Innovation: Ask the Patient Pfizer, an early leader in putting patients forward in the conduct of clinical trials, is continuing to test ways to move beyond process improvements to more ambitious initiatives at the front end of technology innovation.

CRAIG LIPSET

BY WILLIAM LOONEY

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Pfizer’s three top challenges in trial management are patient recruitment, trial site selection, and data access and interoperability. The latter issue is important in realizing a major opportunity to leverage technology advances to achieve two goals: richer, more insightful data streams and stronger engagement with patients and providers. So what? Biophama still does not test the upper limits of what is needed to improve trial management. The reason why has less to do with regulation or technology than with risk-averse company cultures – there is little recognition that a status quo mind-set is itself a source of risk.

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he landscape for clinical trials is flush with invasive growth, seeded by disruptive new technologies and the necessity to cope with a range of human impacts, from lags in patient enrollment to rising investor expectations for chart-busting gains against existing standard of care. Biopharma’s emerging response to this sprouting tangle of challenges is, surprisingly, to embrace a culture of trial innovation – and to make collaboration with patients and other external stakeholders a strategic endpoint of its own. To explore the current stateof-play in driving innovations in the trial space, In Vivo spoke last month with Pfizer Inc.’s head of clinical innovation, Craig Lipset, who outlines what the world’s largest drugmaker is doing to bring new ideas to a network of 300 trials underway involving more than 55,000 patients. In Vivo: Biopharma’s revenues and reputation depend on the progress of the clinical trial – a time-honored but still imperfect vehicle for the aspirations of millions of patients with unmet medical needs. Improving trial performance is a topic of endless debate, but can we agree that the fundamental mission of the biopharma enterprise remains the development of new drugs? Craig Lipset, Pfizer: On that point we have consensus! When you examine the time and up-front costs involved in moving a compound from discovery to approval and commercialization, there is nothing more important to this industry. I joined Pfizer 12 years ago. I had been working at a small, 30-person biotech company in the Boston area, where I was responsible for clinical and regulatory operations, when I was approached by what was then Pfizer’s Global Research & Development (PGRD) to help identify technologies derived from other verticals in the health care sector to invivo.pharmamedtechbi.com

drive improvements in Pfizer’s own clinical research. The work happened to coincide with my own passion for innovation in the design and execution of drug trials – the most critical aspect of our industry’s lengthy product development cycle, and one that offers endless opportunities to get closer to the patient. At the time, I thought I might stay at Pfizer for a couple of years, at most, but today I am still here. The reason is the impact of drug development innovation on patient outcomes is even more critical today than a decade ago. All the new ground-breaking science emerging from the lab makes the consequences of failure for the patient more profound. Pfizer itself has an internal culture driven by a consuming interest in innovation in drug development. And I continue to draw strength from it. How is Pfizer organized in drug development and where do you sit in the company’s sprawling R&D network? When I joined Pfizer in 2006, drug development and clinical trials were located in a single, very large R&D organization. Soon after, the company took the opposite approach and – in what I call the clinical trial diaspora – trials were conducted at different locations throughout the company. Drug development itself was dispersed, so if one part of the enterprise turned down a novel trial approach, another unit might take it on, allowing for multiple shots on goal and giving internal innovation the chance to flourish. The problem, which ultimately proved unsolvable, was the disincentive this decentralization imposed on our being able to scale up these innovations with the full-on commitment they required. Instead, we had a disaggregated effort that failed to mobilize our full strengths as an enterprise. Since 2016, Pfizer has pursued a different approach, with a single, integrated global drug development organization led by a C-suite level chief development officer (CDO), Rod MacKenzie. This newly centralized function brought together all the elements that fuel a clinical trial, including most of the science, R&D operations, clinicians and statisticians, among others. Rod is the ultimate owner of drug development – the single point of contact – and this has allowed my team to go a lot farther in introducing more innovations in how we design, conduct and process our trials. In that respect, the changes have led to a renaissance for my own group, which now bears the title Clinical Innovation. In the new consolidated development operation, we focus on four priorities: first, and perhaps most important, raising the profile and experience of patients in our trials; second, leveraging innovations in digital (mobile, wearables), health information technologies and social media, to improve trial efficiency, access and transparency; third, building more collaboration and partnering between Pfizer and outside stakeholders in trade and professional associations, academia and government; and fourth, serving as a laboratory to help generate ideas on topics like the integration of research conduct within the health care system and making research participation less disruptive. In a larger sense, what we do is make sure that opportunities and ideas that come from outside Pfizer are identified, evaluated and, if appropriate, brought forward for decisions on scaling these up here first. We strive to be relatable internally ©2018 Informa Business Information, Inc., an Informa company

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as well, understanding current challenges in the development business and helping to address them with thoughtful pairings of solutions we might obtain from outside. It’s important we gird this work with focus and persistence, to ensure any new options are tested to generate the evidence necessary to secure buy-in from management. We just don’t bring people in, exchange handshakes and leave it to others to move that option forward. You cannot just expect things to happen in a big organization like Pfizer, with its many teams of scientists. What’s different about your job today than when you started? How has the strategic and operational climate for clinical trials changed over the last decade? The biggest transformation is in the expectations of our stakeholders and what we in industry think is feasible from all the effort expended in our trials. When I joined the industry, the belief was the upper limit of change rested on process improvements and realizing the commitment to operational excellence. Obviously, these two areas continue as the cornerstone of much of what we do today. However, there is a real desire now to move beyond today’s processes and embrace more forward-looking innovation. There is an interest in embracing disruption, particularly if it ends up replacing a process with something new, one that might bring us to a destination we cannot even imagine today. This is the implicit charge that my team and I have from Pfizer leadership, which is to stretch and try new things to make our trials more relevant to the science and beneficial to patients. Another big change is the embrace of collaboration with others in the industry. When I joined Pfizer, the idea of working with competitors on clinical research process and trial conduct was anathema. What gradually became evident is that many actions individual research sponsors took up on their own to transform drug development were piecemeal and thus failed to add much value – in fact, in some cases, it might have slowed us down. Groups like TransCelerate Biopharma, a non-profit group of 19 major global drug companies, show that this industry’s major players are willing to aim for a higher collective standard of excellence. Today, I think we all appreciate how working solo created small differences that added up to more distraction, noise and chaos – where was the added value in remaining secretive? Not much. Finally, I’d say the skills required to prevail in this space have shifted toward the art of persuasion – the ability to sell your ideas. This is critical to the work I do here at Pfizer. It has always been easy in a science-driven organization, populated by highly credentialed academics and clinicians, to look down on the need to “sell” anything. But look closer and you will see that every grant application written by an academic is actually a sales proposal. Internal sponsors of a new molecule must sell their clinical proposition repeatedly, in a long process where the incentive for the next-stage gatekeeper is to relegate their work to the “fail fast” category. It’s actually a positive to be a good salesman – to listen well, understand what the pain point of the customer is, and thus ensure that the product being pitched is geared to solving a real problem. Too often, those proposing an innovative solution lose sight of what it means May 2018 | In Vivo | 5

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CLINICAL TRIALS: Practice Innovation

❚ CLINICAL TRIALS: Practice Innovation shrift of this issue, but you can tell my enthusiasm for the role that patients can play as their own best data aggregators in support of clinical research. I have another extended thought here as well. There are many new technologies for evaluating health data – artificial intelligence (AI) and real-world evidence (RWE) come directly to mind. It’s vital that, as these technologies advance, we share our experiments and lessons on what works and what doesn’t. It would be a tragedy if we apply what are limited resources solely to our own company interests rather than making all this potentially rich data work in the best interest of patients everywhere.

for the stakeholders who are expected to adopt the asset – and pay for it. The message can’t just be “we have a great new hammer”; instead it’s what is the impact of this tool on the specific problem and for what result?

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Can you identify the three most important issues driving the conduct of biopharma clinical trials right now? Patient recruitment continues to be the most critical challenge we face in running our trials. There is a serious gap in patient awareness about participating in this vital aspect of medicines research, which is reinforced by the difficulty the industry has had in engaging physicians to be more active in sharing trial options with their patients. Most patients we are looking to recruit for our studies already have the relevant diagnosis and are on existing therapy under the supervision of a practicing physician. Frankly, it’s a problem when we try to go directly to patients through ads or other forms of patient outreach instead of working with the treating physician. The best way is to encourage both parties to have an informed conversation about participating in a trial, and that requires doing a better job to give the physician the tools and the information he or she needs to support that conversation. It’s all about shared decision-making. This kind of encounter can be time-consuming, but in the end you tend to get a better engaged trial participant, with less turnover. The second salient issue is trial site selection and management. It’s harder today than in the past to identify the right sites, staffed by motivated professionals, with access to the right patients for the trial. Data alone has not helped improve the odds as much as we hoped, even though more and more of it is being applied to evaluate the feasibility of different locations and optimize the chances for a successful set down. Adoption of advanced analytics and machine learning to pull all this together coherently could help bridge the gap, which in many cases depends on ad hoc human interpretation. The third issue I’d cite is data interoperability – the ability to realize the productivity and improved health outcomes from being able to connect and share the individual patient’s electronic health record (EHR). I don’t want to make short 6 | In Vivo | May 2018

“ There is a real desire now to move beyond today’s processes and embrace more forward-looking innovation, particularly if it ends up replacing a process with something new, one that might bring us to a destination we cannot even imagine today.”

The bar for proving a new drug candidate is safe and efficacious has also been raised – it’s now necessary to show a clear clinical differentiation against current standard of care. In Pfizer’s view, does this add to the cost and complexity of drug development or does it bring a refreshing clarity and focus to your work? We see both trends at work. The pressure is on because that bar on performance keeps getting higher. Drug development is more competitive than ever; most therapeutic segments are crowded with potential game-changing entrants vying for attention from investors, payers, providers and patients. Such competition has given a lift to the diagnostics space. Newer complex biologics must rely on biomarkers to ensure their benefits are targeted to the right sub-sets of patients. Advanced, digitally enabled endpoints are emerging to help demonstrate the value of new medicines. Payers clearly want that. Complexity is also paving the way for innovations in study design, recruitment and management because trial sponsors need better and smarter ways to generate evidence. You have a special affinity for the patient’s interest, noting in several public forums recently that patients are the “most disruptive” force in today’s clinical trial space. Every biopharma company is devoting significant resources to understanding what patients want from clinical trials. The phrase you hear today inside Pfizer is “patients first.” Every biopharma company claims to be moving toward “patient ceninvivo.pharmamedtechbi.com

tricity,” though there is a startling lack of agreement on what that means. Our group has addressed the confusion by focusing on three priorities to drive Pfizer’s relationship to the patient. The first is to meet the information needs of the patient before, during and after he or she participates in a clinical trial. What are their expectations after a trial ends? With that knowledge, we pursue deliverables – including patient-friendly summaries of trial results – to share with our trial participants. Pfizer has committed to this in all countries where local law and regulation allow us to do so. Another area we have led is on experiments to give patients access to the electronic data we collect on them as research participants. Both commitments stand out as firsts for the industry; other companies are now following our lead. The second priority is on the patient’s trial experience, with an emphasis on reducing the hassle factor: is a visit to a test site necessary or can we obtain the information remotely? The third priority is to apply insights from patients to jump-start the re-design of our trial protocols. In fact, every draft protocol submitted to Pfizer’s trial protocol review committee is challenged with a simple question: what insights did you gather from the participants and how did it affect the design of the study? If the answer is “I don’t know,” or “I didn’t ask,” then chances are you are not going to get a favorable response. My group’s responsibility is to create the tools that allow Pfizer teams to tap these insights from patients in each of the therapeutic areas that comprise our core business. The outreach matters. Things change for the better when the trial sponsor is engaging with patients early in the process, and throughout the development life cycle. What about the concerns of many patient advocates that the biopharma industry is inconsistent in its claims to being patient-centric – the messaging lacks credibility. These concerns are valid and fair. Often in the past, biopharma firms would go to patient groups only when there was a crisis. If a company was slow in recruiting patients, it would ask the advocates for help; but after the advocates intervened, dialogue would stop. In truth, the failure to engage on a truly mutual basis rests on something more ambiguous. The complexity of regulatory requirements for drug approval means that a drug company, despite its best intentions, may not be able to meet an advocate’s desires for change. The problem is when patient groups perceive their voice is not being heard, or that changes are not taking place post-engagement. It’s incumbent for the company to be proactive in sharing back this information – to make it a priority to share what has changed, what did not change, and why. Given today’s punishing trial cycle, continuity in ties between the patient community and the company is the building block of trust. I see the importance attached to trust through my external work, as a scientific advisory board member of the Foundation for Sarcoidosis Research. Many advocacy groups are small and lack resources, so they benefit when big pharma does reach out. What they don’t want is an exchange of emails only to hear nothing back – about the outcome or the impact. ©2018 Informa Business Information, Inc., an Informa company

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How has the digital revolution re-shaped the contours of the typical clinical trial? Is technology ahead of practice? Digital health applications vary in their maturity and relevance to our industry. It is not a linear progression. Mobile and wearables carry the greatest impact right now because of their potential to enhance the patient experience and enable novel data capture, while artificial intelligence, machine learning and the blockchain are still evolving in terms of having a demonstrable impact. Electronic informed consent tools are helping patients to be better informed while improving the quality of clinical studies. We have to keep scaling up progress on health information technology (HIT) because it is right behind mobile in being a viable contribution to the design and conduct of trials. It will lead to improvements in trial design and execution. Specifically, data from electronic health records (EHR) will soon be entrenched at the core of how data is sourced for our trial programs – it’s coming in the near term. HIT will also enable drug companies to better find and match trial participants to specific studies. Looking at these trends overall, I believe that technology and drug development logistics are fairly well aligned. Aren’t the challenges of accessibility, utility and interoperability eroding the promise of EHR? Isn’t it still true that most patients find it too hard to access their data, resulting in a high level of opt-outs for these instruments? The premise today is that patients just don’t “do” EHR. I am a futurist at heart. I strongly disagree with this conclusion. I recently did a TED Talk laying out my view about the convergence between data and the patient. The truth is that patients today have an unprecedented level of access to their own electronic health records. Two months ago, Apple introduced its new iOS version 11.3. Embedded was a fresh enhancement of the Apple Health app, which consumers can find as a default application on the ubiquitous iPhone. With this new app, a patient can obtain health data from dozens of health systems throughout the country, streamlined through their patient portals and without any barrier to accessing it. What Apple did is adopt the so-called FHIR (Fast Healthcare Interoperability Resources) standard for data interoperability, following in line with other enabling initiatives from the federal government such as Sync for Science (https://syncfor.science. com) and Blue Button 2.0 (https://bluebutton.cms.gov). In March, the Trump administration added to the momentum on interoperability by announcing the MyHealthEData Initiative on patients’ rights to control use of their own health record. The policy makes it clear that providers and health plans must share data with patients, in a uniform and usable electronic format. It is also remarkably consistent with policies initiated by the Obama administration, demonstrating that patient data ownership is truly a bipartisan concern. Now it may take a little time, but the die is cast. Instead of a patient visiting the clinic to be interviewed by the principal investigator in person, the patient, having first given permission, will simply swipe, and, in an instant, provide the investigator with an electronic record on trusted clinical data to populate the study’s database. The savings in time and effort will be measurable and significant. May 2018 | In Vivo | 7

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CLINICAL TRIALS: Practice Innovation

❚ CLINICAL TRIALS: Practice Innovation Is Pfizer ready for this act of data consolidation – are you prepared to capture that data, process it and transform the raw material into insights capable of driving better decisions? We are making progress. Real-world evidence (RWE) for regulatory decision-making was a theoretical construct only a few years ago, but the industry is getting smarter every day in making RWE the primary tool for establishing the value of its medicines, postmarketing. It’s a real source of insight; virtually all therapeutic areas, at every stage of the product life cycle, are tapping in to it. Is AI the next wave that will completely transform the way we develop medicines? The jury is out; we will have to see. I see enthusiasm about the possibilities from AI, but I also continue to confront a lot of skepticism. In my view, however, this is a debate from the sidelines. It is now irrefutable that the field of medicine will have more data along with the capacity to interpret it for the benefit of more – many more – patients. What is the current state of collaboration within the industry on trials and drug development in general? The Hever Group of biopharma R&D leads has expressed concern about too much duplication of effort. Is this a concern for you? This was true in the past, but the situation has changed. Most of us in the industry realized some time ago that, to be effective, our collaborations had to be carefully structured and vetted to define their scope of work and to provide clarity on the expected results. There is no room for redundancy – the Innovative Medicines Initiative (IMI) the industry is funding in Europe should not tackle the same issues, with the same scope and solutions, that TransCelerate is pursuing. Pfizer works on both programs so we have an incentive to push back to ensure collaboration across consortia channels, or what our chief medical officer, Dr. Freda Lewis-Hall, refers to as “metacollaborations.” One early action we helped initiate was to create a single repository of knowledge on what was actually going on in the industry collaborative space. Faster Cures, a division of the Milken Institute, stepped up to help and now manages a dedicated website (http://www.consortiapedia. fastercures.org) to monitor the work product of more than 500 research-based collaborations to ensure that such work avoids those obvious cases of “mission creep.”

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The infrastructure for the conduct of clinical trials is under stress. Is Pfizer using its size and resources to ensure you get the best from the teaching hospitals and academic institutions you depend on to deliver the results the FDA expects? Yes. We are active in efforts to embed our research capabilities in health systems and institutions here in the US and abroad. I serve on the board of the MedStar Health Research Institute in Washington, DC. MedStarHealth operates a network of 12 hospitals in the District and Maryland, with over 4 million clinic visits and hospital admissions annually. We are working to leverage their system’s scale and reach to stimulate more trial patient referrals, take advantage of their thousands of treating physicians for investigator and other research roles, and tap MedStar’s investments in EHR technology to optimize 8 | In Vivo | May 2018

trial conduct. It is part of an initiative to build a more strategic relationship with these large health systems. Can you provide more detail on the objective here? Finding the right investigation site is a growing challenge for trial management. In many trials, we must establish as many as 100 – or more – such sites, distributed among many disconnected institutional networks. Building more strategic alignments with a few big health system partners might allow us to reach the same number of patients with greater efficiency, along with a lot more opportunity in enabling data from a big system’s integrated technology network, including EHR. Is there a Pfizer “best practice” you can cite that has helped advance the company’s contributions to innovation in clinical trials? We leaned out far on the REMOTE trial (Research on Electronic Monitoring of Overactive Bladder Treatment Experience), which was the first trial conducted virtually under an FDA Investigational New Drug Application (IND), using digital and web-based technology that eliminated the need for participants to be treated at a physical clinic location. The objective was to replicate the results of an earlier in-person study on the Pfizer drug Detrol LA (tolterodine tartrate ER) and thus open the door for a more patient-friendly “virtual” approach to clinical research. The trial itself was not a total success, but it did demonstrate the viability of virtual as a new pathway that could work for patients. Since conclusion of the REMOTE study in 2013, at least three biopharma companies have invested in a virtual trial model, in each case with tangible financial support from the VC community working across multiple start-ups with a commitment to the approach. What I see as the real marker of success is the transparent approach we took in communicating our experience to others in the industry and to the outside world, including collaboration with regulators like the FDA. We did this deliberately. I would rank as my own biggest accomplishment the more recent decision of Pfizer to report trial results to all participants and lead the industry in returning individual health data collected in our trials over to the patient. We have reinforced this through our advocacy work, in groups that range from the Multi-Regional Clinical Trials Expert Group (MCRT) to TransCelerate. I believe we have made the notion of providing deliverables to the patient acceptable and accessible to the rest of the biopharma industry. Looking at the regulatory field, is the FDA a roadblock to progress in “humanizing” the gold standard of the RCT? As an industry, we do not test the upper limits of what is required in drafting and conducting our trial programs. The constraining factor is not technology – nor is it regulation. When we launched the REMOTE study, FDA’s Center for Drug Evaluation and Research (CDER) director, Janet Woodcock, inserted a supportive quote, attributable to her, in our press release. My colleagues at Pfizer and the industry were amazed; they didn’t expect that level of support. It made it impossible to suggest the FDA was too conservative and did not want to see invivo.pharmamedtechbi.com

our experiment go forward. In addition, the Clinical Trials Transformation Initiative (CITI) (https://ctti-clinicaltrials. org), which serves as a champion of appropriate use of new digital technologies in medicines development, could not have gotten off the ground without the decision of the FDA to push it forward. Personally, I believe the FDA wants us to do more so they have real plans to react to. They want it to stimulate their own thinking. Of course, it can be frustrating when you look at FDA guidance document calendars on a single strategic issue like RWE and realize it will take the next five years to fully implement them all. But it’s a mistake to brand the FDA as a luddite. The real barrier, in my view, is company culture and the willingness of colleagues to embrace change and an appropriate level of risk. Drug developers have a choice: opt for status quo thinking or be a catalyst for real innovation in drug development. That decision requires individuals and leaders to appreciate that status quo itself brings risk.

“ In 2023, we will be talking about one big highway of data leading us forward – and away from those incremental trial-specific research detours that often turn out to be dead ends.”

If this interview were to take place five years from now, in 2023, what would we be talking about? We’ll be discussing the rise of platform trials, based on the ability for multiple molecules to be tested and evaluated under a single master protocol, with a shared trial infrastructure powered by advanced electronic technologies. This will make it easier for patients to enter the right study tailored to their personalized disease profile. The process will be less burdensome for industry as there

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will be less need to create a specific infrastructure from one study to the next. The volume of data we capture will increase significantly, due partly to the onset of validated digital biomarkers, and it will be more accessible and convenient to obtain, at lower cost. In addition, I expect we will be looking at the complementary expansion of observational studies, building on the momentum from the National Institutes of Health’s (NIH’s) long-term All of Us Research Program (https://allofus.nih. gov) on precision medicine involving 1 million patient volunteers. And there is the Google Verily Life Sciences LLC Project Baseline (https://projectbaseline. com), a four-year observational study covering 10,000 people from diverse backgrounds to investigate risk factors to prevalent conditions like CVD and cancer. Both initiatives are collecting large amounts of data available to all comers and could seed the growth of the seamless patient profile, incorporating data from trials supplemented by ongoing information obtained observationally. Hence our work as drug researchers will be bolstered by a continuous flow of insights, drawn from a diverse, progressively richer database focused on individual health status, all registered consistently over time. In other words, in 2023 we will be talking about one big highway of data leading us forward – and away from those incremental trialspecific research detours that often turn out to be dead ends. IV005333 Comments: Email the author: William.Looney@Informa.com

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CLINICAL TRIALS: Practice Innovation

❚ CLINICAL TRIALS: Trial Innovation

Transitions In The Trial Landscape: What Will Drive RCTs Into The Clinic? Clinical trial execution is both a curse and a promise in the heated stakes for first-mover advantage in new drug development. Siloed practices and legacy behaviors die hard, but the volume of diverse data and a growing push for integration are finally closing the gap between research, evidence and the patient experience with disease. Research from Tufts University concludes that real change is beginning to take root.

BY KENNETH GETZ Most of the problems that plague trial conduct are human in nature, with particular emphasis on the retention of experienced trial investigators and bureaucratic impediments to optimal selection of investigative sites.

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New asset-rich players are entering the trial space with a disruptive business model that emphasizes a flexible, integrated trial infrastructure along with adept and sophisticated use of patientcentric data. So what? Tufts research findings bolster the argument that physicians are a critical – but under-utilized – resource to boost patient enrollments and ultimately facilitate better regulatory submissions for new drug candidates.

10 | In Vivo | May 2018

The conduct of industry-funded clinical trials is at a critical juncture. Biopharmaceutical company and contract research organization (CRO) demand for patients and study conduct capacity are rising sharply as drug development pipelines continue to expand. At the same time, sponsors and CROs face tremendous pressures to deliver higher levels of efficiency and speed while reducing drug development costs. Performance and economic limitations of the traditional, stand-alone, communitybased investigative site combined with advancements in patient engagement and rich patient data and analytics have compelled sponsors and CROs to seek alternative operating models that are more flexible, integrated and efficient. For many disease indications, the current investigative-site landscape utilized by drug sponsors and CROs for more than four decades faces a marginalized future. The old landscape is giving way to clinical research that is integrated and embedded within a much larger clinical care setting. Recent industry-wide trends favoring mergers and acquisitions as a pathway to growth are accentuating this transition. This article, based on multiple studies conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD) and others, looks at the primary forces and operating conditions that are driving a radical transformation of the investigative site landscape.

Chronic Clinical Trial Inefficiencies The high and rising cost of drug development and the gradual decline in returns on development investment comprise a frustrating reality that the biopharmaceutical C-suite is working intensively to address. A growing proportion of drugs in clinical trials are targeting more focused patient subpopulations – including orphan and rare diseases – invivo.pharmamedtechbi.com

that, when commercialized, will capture a smaller global market compared with the era of small-molecule drugs for large chronic care populations. The Deloitte UK Centre for Health Solutions estimates that the average annual peak sales for a drug approved in 2017 will be roughly half that of a drug approved five years ago. Accelerating drug development speed is thus a critical factor in commercial success for the long term. But despite the implementation during the past decade of a wide variety of new practices and technologies, cycle times from first-in-human clinical trials to regulatory submission are no faster today than they were in the early 1990s. The average clinical phase duration took 6.8 years in 2017, an increase of 15% over that in 2007. Tufts CSDD research has shown that longer clinical phase durations are due in part to the growing burden of protocol design complexity. Longer clinical phase durations are also a function of poor execution and outdated operating models – among these, investigative-site management practices rank at the top. Investigative site identification, selec-

tion and clinical trial activation – collectively referred to as the study initiation process – remains not only one of the most time- and labor-intensive activities, but also one of the most ineffective and inefficient. The average duration of the full site initiation process is 31.4 weeks (nearly eight months), more than one month longer than the average duration observed 10 years ago. The overall site initiation process is 9.9 weeks shorter for repeat or familiar sites. But sponsors and CROs report that in any given multicenter study, 28% of investigative sites are new relationships with no prior history. This proportion has been steadily rising as new investigational treatments target more stratified patient subpopulations. The lengthy time commitment that sponsors and CROs put into the site initiation process does not guarantee strong patient enrollment performance. In fact, patient recruitment and retention rates are getting worse. Recent Tufts CSDD studies show that across all therapeutic areas, the planned patient enrollment duration in a given clinical trial must be

doubled to complete actual enrollment of the requisite number of patients. (See Exhibit 1.) Even after doubling planned enrollment duration, a high percentage of investigative sites will under-enroll or they will fail to enroll a single patient. On average, 11% of initiated investigative sites in Phase II and III clinical trials fall into this latter group – a proportion that has not changed during the past two decades. Nearly four of 10 initiated investigative sites will under-enroll. This is the most expensive group of investigative sites because they have been activated and now must be monitored to ensure compliance and quality, supply of clinical trial provisions and management of their clinical data. No doubt that unrealistic time lines and the heavy burden placed on clinical trial study staff to administer highly demanding protocols play a major role in these performance outcomes. Long-term failure to consistently adapt investigative-site management practices is also to blame: sponsors and CROs continue to implement practices designed to engage principal investigators and study staff,

Exhibit 1

Patient Enrollment Performance

Plan To Actual Timelines

Enrollment Activation And Achievement Rates

Increase In Planned Study Duration To Reach Target Enrollment Overall

94%

Cardiovascular

99%

CNS

116%

Endocrine/Metabolic

113%

Oncology

71%

Respiratory

95%

Well Exceed Enrollment Targets

Fail To Enroll A Single Patient

13%

39%

Meet Enrollment Targets

11%

37%

Under Enroll

May 2018 | In Vivo | 11

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CLINICAL TRIALS: Trial Innovation ❚

❚ CLINICAL TRIALS: Trial Innovation Exhibit 2

Global FDA-Regulated Investigators 32,816 29,670 24,805

2008

2009

27,604

2010

28,521

2011

■ Multi-year Filers

28,872

2012

33,920

North America

N. & W. Europe

ROW

2008

63%

17%

20%

2011

58%

19%

23%

2015

55%

22%

23%

30,069

2013

2014

2015

■ First Time Filers

SOURCE: Tufts Center For The Study Of Drug Development

but which remain largely unsuitable for the evolving demands on the drug development process.

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An Outdated Landscape Since 2003, Tufts CSDD research has shown that the global investigative site landscape is highly fragmented, inexperienced and poorly positioned, lacking adequate patient volume, infrastructure and continuity. This research is based in part on periodic analysis of the US Food & Drug Administration’s Bioresearch Monitoring Information System (BMIS), a large database that routinely captures annual FDA form 1572s for each clinical investigator administering an experimental drug under an Investigational New Drug (IND) designation. Data from BMIS offer valuable insights into the maturity and productivity of the global investigative site landscape. Recent analysis of 525,000 records shows that since 2008, the number of unique investigators has grown 4.6% annually. During the past three years, the number of unique investigators has been growing at an even faster annual rate of 5.5%. At the end of 2017, there were about 38,000 unique FDA-regulated principal investigators globally. Although this landscape has had decades to scale and mature, the global community of clinical investigators has lagged behind. Roughly two-thirds of all global investigators still participate in 12 | In Vivo | May 2018

“ Since 2003, Tufts CSDD research has shown that the global investigative site landscape is highly fragmented, inexperienced and poorly positioned, lacking adequate patient volume, infrastructure and continuity.”

only one clinical trial annually. In 2015, there were 10,496 unique principal investigators (31% of the total) filing at least one form 1572 for the very first time. The proportion of novice or new filers has not changed. Each year since 2008 around one-third of all unique FDA-regulated principal investigators are first-time filers, having never before participated in an industry-funded clinical trial. (See Exhibit 2.) Turnover rates among unique FDAregulated principal investigators are also very high, particularly among the majority of investigators conducting a small number of clinical trials each year. In our recent analysis, about four of 10 unique FDA-regulated PIs worldwide who filed at least one form 1572 in 2011 have yet to file again. One in five unique principal investigators filing two or three 1572 forms in a given year chose not to conduct another industry-funded clinical trial. And around 5% and 1% of unique global principal investigators filing four to six 1572 forms and seven or more forms each year, respectively, chose not to continue their participation in subsequent years. (See Exhibit 3.) The high turnover rates are attributable to onerous regulatory requirements, heavy workload and time commitments, high study staff turnover, financial risk and lack of sufficient financial incentives. Slightly more than half of all investigainvivo.pharmamedtechbi.com

Exhibit 3

High Turnover And Inefficiency Investigator Turnover Rates Year

Site Identification To Initiation Cycle Times (Weeks)

1 Filing 2-3 Filings >4 Filings Per Year Per Year Per Year

2008

48%

19%

2009

51%

23%

2010

50%

21%

2011

49%

20%

6.5

New Sites

7.9

Repeat Sites 3.5 5.2 0

17.5

36.4 weeks

26.2 weeks

20 25 30 35

■ Site ID ■ Site Selection ■ Study Start-up SOURCE: Tufts Center For The Study Of Drug Development

tors are physicians in small, part-time community-based settings unaffiliated with academic centers and larger health provider networks. These sites primarily provide clinical care while dabbling in clinical research. Although these physicians have made progress in digitizing their patient medical records and in professionalizing their management and financial controls, they treat a relatively small volume of patients. And most are ill-prepared to accommodate the more complex trials involving advanced biologics, new trial models such as the adaptive clinical trial, and experimentation with new technologies like smartphones, mobile applications and wearable devices. Roughly 5% of the total – less than 2,000 FDA-regulated investigators – operate within larger, community-based dedicated site networks. This segment is relatively sophisticated, with IT and operating infrastructure better suited for managing a higher volume of clinical trials. Dedicated sites and site networks derive nearly all of their income from clinical trial grants, and the majority of their patients are recruited through advertising and outreach. Although this segment has been better positioned historically to manage large Phase II and III clinical trials, it is becoming less viable as sponsors and CROs seek to find patients who match elaborate eligibility criteria (e.g.,

those facing rare and orphan diseases and very targeted medical conditions). The remainder of investigators are based within academic and hospital settings. This segment has access to a relatively large community of welltrained health care professionals, very large patient populations, and relatively sophisticated patient health and medical data. Historically, industry-funded clinical trials in these settings have been more bureaucratic and inefficient. Tufts CSDD research has shown that clinical trials conducted within academic settings typically have the lowest activation and completion rates. These settings are also consistently the slowest enrollers.

Push For Data And Analytics Biopharmaceutical companies collect a large and diverse volume of data to support their new drug applications (NDAs). In addition to collecting electronic clinical data (EDC) over the course of the trial, according to a recent Tufts CSDD study, 95% of companies are gathering claims data; 71% of companies draw data from electronic health and medical records; 67% collect prescription data; and 48% gather patient-reported outcomes and survey data. Also utilized are biomarker and genomics data (38% of biopharmaceutical companies) and protocol feasibility data (29% of companies). Currently, few companies report using

social media, mobile health and wearable device data to support a new drug application. However, biopharmaceutical companies expect to increase their use of these solutions in the near term. Many factors are contributing to the exponential growth in data being collected. New scientific knowledge about the pathophysiology of many diseases, and new approaches to measuring disease progression and economic impact require collection of more data. Crowded classes of investigational therapies and the ongoing movement to develop stratified medicines are pushing research sponsors to collect more data to better target patient subgroups and to differentiate small- and large-molecule interventions. Medical scientists and statisticians often add procedures to gather more contextual data to aid in their interpretation of the findings and to guide development decisions. Research sponsors are also collecting more biomarker and genetic data, as well as outcomes, economic, cotherapy and companion diagnostics data that may be analyzed as part of a study or stored and analyzed at a future date. In addition to informing scientific decisions, the collection and interrogation of data to support more sophisticated management of the R&D process is being embraced by biopharmaceutical companies. Data from a variety of sources – including unstructured feedback from May 2018 | In Vivo | 13

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CLINICAL TRIALS: Trial Innovation ❚

❚ CLINICAL TRIALS: Trial Innovation Exhibit 4

HCP As Engagement Enablers Percent of patients feel it would be ‘Very’ and ‘Somewhat Valuable’ for clinical research options to be presented during regular office visits

68% 48%

38%

18-44

46%

42%

45-64

■ Very Valuable

43%

47%

65+

■ Somewhat Valuable

of patients rate their HCP as the top preferred source for information about clinical research

71%

of patients say that they would speak with their physician or nurse prior to deciding to participate

83%

of patients consider their physician’s recommendation a top factor influencing their decision to participate

91%

of patients agree that having clinical study procedures conducted during regular doctor visits would be more convenient

93%

of patients report feeling ‘Very’ and ‘Somewhat Comfortable’ having their medical health records routinely used to identify appropriate studies

invivo.pharmaintelligence.informa.com

SOURCE: Tufts Center For The Study Of Drug Development

patient and professional communities – are being used to support drug development planning, protocol design, site and patient identification, patient response and adverse event patterns, and study conduct convenience and performance. New applications and systems capable of storing and managing large volumes of structured and unstructured patient data are becoming more commonplace. And predictive analytics, artificial intelligence and machine learning are being piloted and implemented by biopharmaceutical companies and CROs to help accelerate data processing and provide more rapid insight for drug development scientists and operating managers. Electronic health and medical records – particularly those that integrate diverse data elements – are among the most significant. It is important to note that at this time industry intent to leverage and apply rich data and analytics is largely aspirational. Major data management challenges exist including limited data availability, quality and reliability; the high cost of data integration; and the low acceptance by regulatory agencies and payers. New technology solutions that merge disparate data sources are expected to play a key role in addressing availability and cost issues. 14 | In Vivo | May 2018

Health System Infrastructure And Patient Volume Integrated health delivery systems for large covered populations are uniquely positioned to provide rich patient data supporting industry demands for analytical rigor and sophistication. Health systems also provide the highest relative patient volume to support the identification of very targeted and rare subpopulations. According to the federal Agency for Healthcare Research and Quality (AHRQ), health systems in the US include 70% of all hospitals and 50% of all board-certified physicians. In addition, the vast majority of US-based health systems are certified electronic health and medical record users and have the capability to electronically query patient health data. Given their typically low and diminishing operating margins, health systems appear eager to compete for new revenue streams including that from clinical trials sponsored by drug development companies. Health care providers within large health systems also represent a critically important yet largely under-leveraged patient recruitment asset. They play an essential role advising, guiding and influencing patient participation in clinical research. Studies conducted since 2003 by

the Center for Information and Study on Clinical Research Participation (CISCRP) have consistently shown that health care providers are among the most trusted sources for health and medical information, including clinical trials. More than eight of 10 (84%) patients state that they would consider participating in clinical trials if their physician recommended that they do so. A high percentage (71%) of global study volunteers confirm they spoke with their physician prior to making the decision to participate in a clinical trial. And patients who receive information about clinical trials from their health care provider are significantly more likely to participate and to complete clinical trials. (See Exhibit 4.) A recent CISCRP study also finds that patients would find it more convenient to participate in clinical trials if they were better coordinated with their routine care. Nearly all (94%) respondents in a global survey of 12,500 people said it is important their physician and nurse be aware of clinical trials being conducted locally and a similar percentage (91%) of respondents said they would find it most valuable to learn about clinical trial options during regular doctor visits. But this is not happening: three of four patients invivo.pharmamedtechbi.com

Exhibit 5

HCP Readiness MDs (N=755)

Nurses (N=1,255)

Received special training on CT in school

40%

45%

Attended lecture(s) on CT at society meetings

39%

21%

Consider themselves familiar (SW/Very) with CTs

88%

69%

Comfortable (SW/Very) providing CT info to patients

88%

63%

Comfortable (SW/Very) discussing CT opportunities with patients

91%

72%

Have referred their patients to clinical trials

60%

17%

Median number of patients referred annually

3,100

5,560

Median number of patients seen annually SOURCE: Tufts Center For The Study Of Drug Development

with medical conditions claim that they have never discussed clinical trials with their health care provider. A 2017 Tufts CSDD study found that health care providers are very comfortable discussing clinical trial options with their patients. And physician and nurse interest in referring patients into clinical trials is very high, at 72% and 69%, respectively. However, the Tufts study observed wide disparity in referral rates and referral volume among health care providers. Six of 10 physicians report referring at least one patient to a clinical trial during the past year. (See Exhibit 5.) This is significantly higher than the 17% of nurses who reported doing so during the past year (P < 0.005). Physicians report referring a median of five patients into clinical trials annually, a referral rate that is less than 0.2% of their annual clinical care patient volume. Nurse referral volume is considerably lower – a median of two patients annually – representing a 0.04% referral rate. The study revealed that health care providers refer only a small number of patients each year largely due to the inability to access clinical trial information and the lack of sufficient time to evaluate and confidently discuss clinical trial options with their patients. Several factors were also found to be predictive of physician and nurse likelihood to refer patients

“ Major CROs recognize the convergence of clinical research into clinical care. They are placing strategic bets in anticipation of the change, including vertical integration into study conduct activities and expanding their data and analysis capabilities.”

to clinical trials: they were more likely to refer patients to clinical trials conducted within recognized settings and to professionals with familiar credentials. Health care providers with prior experience as clinical investigators in industry-funded clinical trials were also significantly more likely to refer.

Silo Solution: Integrating Separate Worlds Although the public and patient communities likely don’t realize it, health care and clinical research function as completely separate worlds with limited overlap and integration of personnel and infrastructure. This must and will change as the public, providers and payors demand access to more effective and affordable medical treatment options, and as industry strives for better performance and more cost-efficient R&D and commercialization capabilities. Legacy-site management practices implemented today and structural characteristics of the global site landscape constrain biopharmaceutical companies and CROs from achieving higher levels of performance and efficiency. The global community of investigative sites characterized by high levels of inexperience and turnover, along with low clinical trial activity and patient volume, prevents sponsors and CROs from continuously improving May 2018 | In Vivo | 15

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CLINICAL TRIALS: Trial Innovation ❚

❚ CLINICAL TRIALS: Trial Innovation Exhibit 4

CRO Integration Into Study Conduct Buyer

Target

Deal Type

Transaction Date

QuintilesIMS

HighPoint Solutions

Acquisition

Sep.2017

ICON

Mapi Group

Acquisition

July 2017

QuintilesIMS

DrugDev

Acquisition

July 2017

QuintilesIMS

Coté Orphan

Acquisition

May 2017

QuintilesIMS

TKL Research

Acquisition

Nov. 2016

QuintilesIMS

DaVita Dialysis Centers

Strategic Alliance

Aug. 2016

Bioclinica

Compass Research

Acquisition

July 2016

PPD

Synexus

Acquisition

May 2016

Bioclinica

Clinverse

Acquisition

Jan. 2016

ICON

PMG Research

Acquisition

Dec. 2015

Bioclinica

MediciGroup

Acquisition

July 2015

PPD

CRA/Radiant Research

Acquisition

Apr. 2015

LabCorp

Covance

Acquisition

Feb. 2015

invivo.pharmaintelligence.informa.com

SOURCE: Tufts Center For The Study Of Drug Development

through innovation. Large health systems and clinical care institutions are well positioned to advance this dynamic, given their relatively high patient volume; rich patient data secured through electronic health and medical record platforms; and access to large untapped communities of health care providers who can act as facilitators of patient engagement. At first blush it is ironic that industry-funded clinical trials may end up returning to a dependence on these larger institutions – a community that experienced dramatic loss of industry study grant revenue as clinical trials migrated over to the private sector some 30 years ago. Major CROs, their parent-companies and private equity funders recognize the convergence of clinical research into clinical care. They are placing strategic bets in anticipation of the change, including vertically integrating into study conduct activities and expanding their 16 | In Vivo | May 2018

data and analytics capabilities. In 2017, nearly 190 transactions seeking to secure this strategic advantage were completed. Leading CROs have also formed alliances and operating agreements with large health systems. (See Exhibit 6.) Several established site networks and study-conduct services companies are positioned, or are positioning themselves, to offer flexible placement of clinical research personnel and systems to support the administration of clinical trials within clinical care settings. New companies (e.g., Elligo Health Research Inc. and MonARC Bionetworks Inc.) – some with venture capital funding – have been launched within the past 18 months to facilitate and support this convergence. Many of these players rely on cloud-based systems, the use of mobile applications and wearable devices, and roving teams of research professionals who can be conscripted to assist health care profes-

sionals in engaging patients within health systems and running the actual clinical trials. Other companies – like Science 37 Inc. – are using remote data collection devices and telemedicine visits with companyaffiliated investigators to support flexible clinical trials that combine high tech and high touch elements. The convergence of clinical research and clinical care is driving the adoption of disruptive new models of study conduct. This integration holds promise in offering better medical care to patients, stronger and faster advancements in public health, and data that is leveraged to drive a performance-optimized process of drug development. IV005331

Kenneth Getz is director of sponsored research and associate professor at the Tufts University Center for the Study of Drug Development, Boston MA. invivo.pharmamedtechbi.com

Coverage

specific patient segments

Select Smarter

US, Japan, France, Italy, Spain, Germany and United Kingdom

London, UK 3 Site Locations

Rome, Italy

Los Angeles, USA

8 Site Locations

Tokyo, JAPAN

1 Site Location

12 Site Locations

New York, USA 4 Site Locations

NEW to Sitetrove

Select clinical trial sites with pinpoint accuracy. 1. Match patient populations of interest with qualified investigators for faster, more successful clinical trials. 2. Get insight into diseased population size to drive country, site and experienced investigator selections for maximum feasibility and rapid decision-making.

Visit https://goo.gl/LmnHrR to find out more.

Sitetrove

ÂŠ2018 Informa Business Information, Inc., an Informa company

Pharma intelligence | informa

May 2018 | In Vivo | 17

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CLINICAL TRIALS: Trial Innovation â?&#x161;

❚ CLINICAL TRIALS: Regulatory Perspective

Big Data And The FDA: To Mine The Value, First Mind The Gaps

Shutterstock: Ryzhi

INFORMED is a new initiative at the FDA to incubate new ideas in applying big data to boost the scientific, economic and social returns from the regulation of drugs and medical devices, with a particular focus on cancer.

BY WILLIAM LOONEY INFORMED is a collaborative exercise with no fixed budget. It pursues linked-up projects with other FDA departments, the wider federal government, academia and industry.

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INFORMED’s work is focused on improving the scale and relevance of clinical trial content and broader regulatory science in RWE, AI/machine learning, EHR, and patient-friendly biosensors and mobile apps. So what? Big data’s prospects as a gamechanger in the development, delivery and financing of medicines depends on a supportive institutional structure buttressed by coherent methodologies, consistently applied. This is why the emerging active engagement of FDA on digital and data science is so critical to the future growth of biopharma, which in many ways is now an information business. 18 | In Vivo | May 2018

NFORMED is a new initiative at the FDA to incubate new ideas in applying big data to boost the scientific, economic and social returns from the regulation of drugs and medical devices, with a particular focus on cancer. Innovation is the spark of creation that waits for no one. Least of all for the regulator, whose reaction to something new is often to regulate it – usually after the need to regulate has passed. That’s why it’s a surprise to see the FDA take the lead in tackling what’s arguably the key challenge to progress in drug development: how to transform the explosive growth in “big” data into “smart” data, delivering actionable insights to advance efficacy, safety and quality – in other words, more innovation – at every stage of the drug life-cycle. The objective is to make data analytics an integral part of regulatory decision-making, supported by novel public-private collaborations to engage industry, academia, patients and other FDA stakeholders in a common assault against the silos that limit big data’s potential in fighting disease, particularly for biologically complex conditions like cancer. Although the FDA has a formal strategy to broaden access to data-based digital health products – 51 such devices and drugs were authorized by the agency last year – its most important actions in the big data space have been taking place behind the scene. Specifically, it’s investing time and treasure – in the form of inter-agency and outsider expertise, not money – to create the first FDA data science “incubator” – the Information Exchange and Data Transformation Initiative (INFORMED). Announcing the formal launch of INFORMED at the AcademyHealth Datapaloozaconference on April 26, Commissioner Scott Gottlieb noted how advances in information technologies are forcing “a rethink of our mandate on how we enable safe, effective innovation in this novel area, and to support its benefits to patients.” invivo.pharmamedtechbi.com

Based in the FDA’s Oncology Center of Excellence, INFORMED has actually been at work since May 2016, when the FDA applied to the Department of Health and Human Services (HHS) Innovation, Design, Entrepreneurship and Action (IDEA) Lab as part of a competitive program to help the agency recruit a few “entrepreneur-inresidence” positions under a special HHS hiring authority covering projects of transformative potential in government. The IDEA Lab selected INFORMED for hiring support, allowing the FDA to move forward on a collaborative incubator applying data science to oncology drug development and regulatory decision-making. Thus, from a purely organizational standpoint, INFORMED is an innovation in itself, seeking to emulate the entrepreneurial mind-set of a Silicon Valley startup. It has no allocated budget. Staffing relies on these secondments or fellowships from other FDA departments, the federal government, industry and various academic and non-profit research partners.

Busting Those Data Silos Sean Khozin, a physician oncologist and acting associate director of the FDA Oncology Center, serves as founding director of INFORMED, where he manages pilot collaborations with other oncologists, data scientists, programmers, statisticians and several entrepreneurs-inresidence, whose pay is funded by the FDA. “There is a gap in expertise and understanding between the tech world, the data science profession and the life sciences community, and it happens to be very wide, even today,” Khozin said in an interview with In Vivo. “INFORMED is committed to closing that gap using agile, diverse and consolidated data technologies to address real-world challenges that slow progress for cancer patients.” Khozin is strong on creating a durable infrastructure to process and make accessible large volumes of integrated data as a decision support in drug development. That requires eliminating data silos; supporting novel, evidence-based methodologies to extend the horizon of the traditional RCT and related postmarketing research; and promoting a more data-rich systems approach to the field of regulatory science, a priority of FDA commissioners for the past decade.

“ There is a gap in expertise and understanding between the tech world, the data science profession and the life sciences community, and it happens to be very wide, even today.”

– Sean Khozin

In other words, big data sets now rule the day at FDA – and will set the agenda for tomorrow. It’s a commitment reaffirmed by Commissioner Gottlieb’s Datapalooza pledge to “modernize our framework for advancing the most promising digital health tools. This will help us better understand variations in individual patient experience using diverse data from clinical trials, electronic health records (EHR) and biometric monitoring devices.” This modernization is focused on two areas: (1) organizing FDA’s existing clinical trial data sets into a common standard to better facilitate their use in research and regulatory decision-making; and (2) building out the FDA’s data storage and assessment capabilities to incorporate these new and diverse data streams, which, in addition to the above, includes artificial intelligence/machine learning, the emerging fields of DNA- and RNA-based multiomics as well as less structured data in the form of patientreported outcomes and social media. Some results are already in place, primed and ready to go. One example is a new Premarketing Digital Safety Program for drugs, announced by Gottlieb on April 26. Its key feature is the establishment of a unified data standard for the notification of adverse events occurring during a clinical trial conducted as an investigational new drug (IND) application, a category much larger than trials for new drug (NDA) or biologic license (BLA) applications. The FDA has long been aware that such reporting, conducted on an analogue, paper-based platform, was inadequate to meeting the seven- to 15-day time frame required by law, and often led to lags in signal detection and medical review. INFORMED took the responsibility to test the new digital data standard in a pilot project with four of the biggest biopharma companies (see sidebar next page), with positive results that will allow the initiative to enter into force this year. Another collaboration is moving the FDA a step forward to incorporating realworld evidence (RWE) in its regulatory decision-making, particularly in finding new insights on how drug regimens shape the patient experience where it counts most – directly at the point of care. The focus is a data-sharing partnership agreed in June 2017 between INFORMED May 2018 | In Vivo | 19

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CLINICAL TRIALS: Regulatory Perspective ❚

❚ CLINICAL TRIALS: Regulatory Perspective and the American Society of Clinical Oncology (ASCO), covering ASCO’s CancerLinQ inventory of thousands of deidentified patient treatment records from nearly 100 oncology practices in the US. Ongoing review of these records will focus on the latest immunotherapy advances in melanoma cancers to plumb insights such as the impact of combination therapies and to use this to identify areas of improvement in design of clinical trials as well as the approval evaluation process at the FDA itself, including the

approach to drug labeling. “There is strong pressure on the FDA to render the right decisions on access to patients as the science of cancer pharmacology improves. We see such partnering as a way to ensure the FDA is responsibly in synch with the pace of change, and how it affects patients in the actual clinical setting,” Khozin says. Khozin notes that INFORMED is supporting similar work involving a unique crowdsourcing model to test the impact of RWE on outcomes for patients with

prostate cancer, in conjunction with Project Data Sphere, an independent non-profit sponsored by the CEO Roundtable on Cancer. Likewise, INFORMED has forged an ongoing work relationship with [Flatiron Health Inc.], a leader in the development of digital data technologies for cancer acquired by Roche in February. Again, the focus is on application of RWE, using EHR files involving patients in community-based cancer clinics. A joint study presented last June at the 2017 ASCO Annual Meeting found that

❚ US FDA’S KHOZIN ON DEFINING BIG DATA, SAFETY SIGNALING, AND THE PATIENT

invivo.pharmaintelligence.informa.com

EXPERIENCE IN CANCER

In Vivo: What does the FDA mean when it references the term “big data”? Like so many issues today involving advanced technologies, the concept is fuzzy but the implications – particularly on patients – are profound. That’s especially true given the focus of your work on INFORMED is cancer research. Sean Khozin, acting associate director of the FDA Oncology Center, and founding director of INFORMED: The reason why big data is so important today is the potential it has in better capturing the actual experience of the patient in medicine. It is not just about the “big” factor – we don’t evaluate its promise solely as a volume-based exercise, although this tends to appear first in the conversation. A common definition of big data is built around four dimensions: (1) volume (data size); (2) variety (data type); (3) veracity (data noise and uncertainty); and (4) velocity (data flow and processing). At the FDA, most approval decisions are still based on data of limited variety, mainly from traditional randomized clinical trials, and are highly structured within data sets that are relatively small in size and are processed intermittently as part of a regulatory submission. The challenge for the FDA – and indeed all users of big data – is to develop the human organizational and technical capacity to turn the “big” into the “smart,” through applied analytics to personalize therapies around the distinctive disease characteristics of each patient. What this means in practice is to put much more emphasis on that second dimension, data variety. This includes tracking the patient journey through the health system to accurately and consistently record the outcomes of treatment. But it also must incorporate data generated by the patients themselves, on an ongoing basis, in the form of diverse, web-based apps and wearable devices. The FDA is aware that this approach works: in one trial published in the Journal of the American Medical Association (JAMA) last year, metastatic solid tumor cancer patients who were given a web-based platform to record their side-effects from chemotherapy for real-time evaluation by cancer care teams experienced a fivemonth improvement in overall survival versus those who did

20 | In Vivo | May 2018

not record. It was a simple experiment but it showed nonetheless that involving the patient with data relevant to their own condition can produce a positive health effect. INFORMED is embedded in the FDA’s Oncology Center of Excellence. Why the focus on cancer and what impact will your work have on the pace of treatment for a disease that will strike nearly 2 million Americans this year alone? Cancer is an extremely complex and varied condition, to the point where oncology drug development has largely become an exercise in evaluating huge volumes of data drawn from disparate sources. Our increased understanding about the genetic origins of individual cancers has led to the DNA sequencing of solid tumors, creating a data pool so vast it outpaces our technological capacity to analyze it. Big data in oncology also incorporates not just individuals’ genetic information but data drawn from the microbiome, as well as in that larger environment outside the body – the exposome of external and life-style exposures occurring from the prenatal period onward through life. These drive in turn the similarly endless variations in treatment response, where data is critical to providing insights on the potential of an increasingly diverse set of therapies, many of which work differently in focusing on an immune system response or are administered in combination with both new and older drugs. The important point is that this trend runs counter to the traditional reductionist approach to drug treatment, relying on a single drug to attack an undifferentiated set of tumor sites and characteristics. This approach is not scalable to what we know about the biology of cancer today. For example, the most common mutation in non-small cell lung cancer, the epidermal growth factor receptor (EGFR), is present in only about 15% of the patient population, which means that fishing for the therapy that’s right for the individual patient requires a much bigger net – and a more nuanced approach. It demands a holistic therapeutic strategy focused on the complex signatures

invivo.pharmamedtechbi.com

patients with non-small cell lung cancer (NSCLC) receiving PD-L1 checkpoint inhibitors experienced different outcomes than revealed through the RCT format, a result that the FDA hopes will be analyzed to shape the design of future trials involving checkpoint inhibitors, particularly for patients subject to previous co-morbidities, in addition to NSCLC. Now that INFORMED has been publicly launched, Khozin expects his group’s work output to increase. “This year we aim to demonstrate how big data is going

to extend the boundaries of translational research into new areas focused on oncology. It’s foundational work that needs to be done if the FDA, industry and academia are to fulfill the public’s expectations for the changes in drug development, laid out in the 21st Century Cures Act passed by Congress in December 2016.” The tools of choice will be publication as well as additional new collaborations. “We publish for reasons very different than the norm of seeking a credential embellishment – instead, it’s to get ideas that we think are

identifiable through systems biology and the entire multiomic milieu of gene and protein-based analytics. Only the biggest data sets can help researchers do that, which makes cancer the place where an incubator like INFORMED has the potential to contribute to the science and benefit patients. Collaboration is a key rationale for INFORMED. How would you assess the biopharma industry’s response to your work to date – is it ahead of you or slower than it should be in helping advance your objectives on digital transformation? Although we strive to cast our net widely, INFORMED welcomes the support we have earned from many big pharma players. One of INFORMED’s first projects was a pilot we conducted with four companies – Astra Zeneca [AstraZeneca PLC], Genentech [Genentech Inc.], Merck & Co. [Merck & Co. Inc.] and Novartis [Novartis AG] – where we tested the feasibility of a new digital framework for reporting of important safety events occurring in clinical trials subject to investigatory new drug (IND) regulations. Instead of submissions that were disaggregated on receipt and sorted in paper and PDF files, INFORMED put together a team that included technical experts from the FDA Office of Surveillance and Epidemiology to develop a new digital framework in which the reports were processed electronically as machine-readable data sets, amenable to standardized visualization and analytical tools, including AI-based methods to conduct safety signals detection and systematically identify gaps in meeting regulatory requirements. The overall aim was to uncover missing or inconclusive safety signals. Reports from the four companies were successfully registered in the new system, validating the new digital format. The format is now being institutionalized here in the US as the FDA Premarket Digital Safety Program announced by Commissioner Gottlieb last month, beginning with oncology NDA submissions. The FDA Office of Oncology has concluded that digitization of the adverse event reporting process will also be a major productivity booster, saving the equivalent of 500 man-hours of work time every month once the program is fully implemented. Overall, we see the four companies’ contributions to making our idea work in practice as a highlight of what can be achieved through collaboration, using the big

important out to the community of users, who relate to the actual experience of patients.” It’s a long-term game, says Khozin, but one where risks can be controlled with metrics to guide product development, making the process more predictable to research sponsors.

What’s Ahead: Practical Apps Four areas of investigation will attract the most attention from INFORMED this year. The intent is very grounded: to build a framework of foundational learnings

data tools allowed by the technology revolution. What’s important about this is that FDA reviewers used to have to read cumbersome paper and PDF files to identify safety signals; there was no signal detection based on an accessible, organized data-set approach, in the premarket setting. And it’s really a global issue. We may decide in the near future to take our framework as a new foundation for the global harmonization of premarket safety event reporting. Biopharma companies sometimes cite mixed signals from the FDA as a reason for not moving more aggressively to innovate in the use of data and evidence to advance pipeline performance. Is this perception still valid or has the situation truly changed? It’s no surprise that industry will worry about what the world’s largest regulatory agency thinks. And siloed, insular thinking is a recurrent challenge to any large organization, including the FDA. I spend a good deal of time explaining to industry colleagues that the FDA today has a strong technology- and datadriven outlook toward innovation. We are in no means a barrier to the creative application of digital technology to generate more and better evidence to drive drug development. In fact, the agency is on the leading edge of change in this area, which in large part is due to efforts from the commissioner’s office to promote technology innovations and greater evidence diversity throughout the agency. Ironically, that top-level commitment is not always present in the private sector. It is particularly hard in large biopharma companies to sustain that seamless flow of ideas where the clinical development teams join forces with the commercial leads in exploiting novel evidence generation tools like RWE; each group has a history of approaching the product development cycle from a different perspective. I see technology, data science and digital as a bridge across the divide, but it takes initiative and a willingness for taking calculated risks outside organizational norms. Some organizations have been slower than others in confronting the disruptions this may entail, but I am confident both government and industry are moving in the right direction. IV005338

May 2018 | In Vivo | 21

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CLINICAL TRIALS: Regulatory Perspective ❚

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❚ CLINICAL TRIALS: Regulatory Perspective around big data and then help translate these to the actual practice of drug development and FDA regulatory science. The first is to continue looking at the use of EHR to test the utility of RWE both inside and outside the trial space, involving drugs under the FDA regulatory authority, and which will hopefully shape the development of future agency guidance to industry in this area. Second, INFORMED is actively examining the potential of the Blockchain in addressing concerns about privacy, security and operability of sharing data, especially for the large-scale transactions required in the oncology space. “We have underway a very exciting project with IBM Watson Health looking at whether we can use Blockchain to create a worldwide web for health data exchange – one that, like the Internet today, will belong to no one and everyone, at the same time,” Khozin says. “It’s a data ecosystem that will be both secure and decentralized.” He tells In Vivo that INFORMED and Watson now have a technological solution reliant on Blockchain that is in the late alpha, early beta stage of testing. “Later this year, we are going to demo this solution and launch a public discussion on ways to take the model forward, to feed into this big data ecosystem we and our collaborators are seeking as the end game.” The third focus is on artificial intelligence (AI) and machine learning. In a collaboration with the Harvard Medical School Program in Therapeutic Science (HiTS – http://hits.harvard.edu), INFORMED is pursuing work that leverages the significant knowledge about AI (new technology around neural networks is a prime example) accumulated since the 1970s. INFORMED is supporting a postdoctoral two-year fellowship to build contacts with academic institutions (Massachusetts Institute of Technology, Harvard University and Tufts University) and research hospitals (Dana-Farber Cancer Institute, Massachusetts General Hospital and Brigham and Women’s Hospital) to design, test and implement AI and machine learning models to support improvements in regulatory review, drug development and patient outcomes. In addition, the Harvard group was expanded this month to include a partnership with Aetion Inc., a New York22 | In Vivo | May 2018

based, privately held software company specializing in RWE. In the project, which is being funded and led by the FDA Center for Drug Evaluation and Research (CDER), Office of Medical Policy, Aetion will seek to replicate, with its own proprietary analytically based RWE platform, the results of 30 FDA published RCTs, covering CVD, and endocrine, musculoskeletal and pulmonary conditions, this time in actual clinic settings. The goal for this three-year effort – results of which will roll out sequentially, with some early milestones due later this year – is to determine whether RWE would have produced the same regulatory decisions as the FDA took originally, in relying on the RCT standard. If so, it will help to validate greater use of RWE to accelerate drug approval and access decisions, and thereby help fulfill a key legislative mandate of the 21st Century Cures Act. “The FDA is the standard bearer on evidence in medicine for the entire nation, so I believe the methodology we hope to develop through this project will give more certainty and structure to use of RWE in access decisions taken by the major commercial payers and health plans,” Sebastian Schneeweiss, MD, ScD, Aetion’s co-founder and science lead, who also serves as a professor at Harvard Medical School and vice chief of the Division of Pharmacoepidemiology and Economics at Brigham and Women’s Hospital, tells In Vivo. Adds Aetion CEO Carolyn Magill, “If we find that RWE can indeed play a role to augment the traditional RCT, or, in some cases, allow the FDA to support a trial entirely using real-world data, the result will be lower costs in bringing drugs to market – and faster access for patients.” Specific to machine learning, INFORMED will disclose results from another collaboration with Project Data Sphere, where a study has been conducted on using sophisticated algorithms to detect tumor dynamics based on computer vision and AI as well as to map changes in tumor composition over time. These algorithms will expand on the current human visual inspection of radiological screens and, through a combination of mathematics and predictive analytics, may accurately automate the review of the changes in tumor growth, in a three-dimensional format. “Obviously, the

results using these technologies have to be validated,” Khozin observes, “but one can imagine how measuring tumor progression using precision mathematics and pattern recognition will minimize human error and thus be very useful in making FDA guidance more relevant and effective in the clinic. To FDA, that’s the bottom line.” The fourth priority is research on the use of biometric sensors, in close collaboration with providers and patients. With the National Institutes of Health’s National Cancer Institute (NCI), INFORMED is conducting a small observational study to apply sensors to track the progress of cancer patients on basic indicators of performance (physical and cognitive functionality) that will then be analyzed against a cohort of patients without sensors, to determine criteria for clinical trial participation and administration of drug therapy. The idea is to also create incentives for industry device-makers to develop new biomarkers guided by the specific technology needs identified in the study. The active sponsorship of Commissioner Gottlieb and high-profile staff such as Director of the Office of Hematology and Oncology Drug Products Richard Pazdur, MD, will be crucial to the momentum of this highly leveraged initiative going forward. Broad support from a crosssection of interests is necessary to avoid INFORMED projects from becoming “data dumps” that fail to drive changes in regulatory practice carrying a measurable impact on drug developers, providers and patients. So far, however, reaction from one key constituency – biopharma – has been positive. Bill Louv, a former corporate venture capitalist for GSK and new president of the CEO-backed cancer trial open-access advocacy group, Project Data Sphere, tells In Vivo, “In the competitive world of pharma today, it takes a set of truly visionary leaders from industry, government and academia to work together. The FDA is a big part of this collaborative vision, so we look forward to continue working with INFORMED and the agency to advance transparency in regulatory science and improve the lives of cancer patients.” Sounds like an endorsement – and an invitation to FDA to deliver. IV005339 Comments: Email the author: William.Looney@Informa.com invivo.pharmamedtechbi.com

May 2018 | In Vivo | 23

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CLINICAL TRIALS: Regulatory Perspective ❚

❚ CLINICAL TRIALS: Pipeline Progress

2017 Completed Trials: Status Quo Or No?

Shutterstock: kentoh

Trialtrove data provides a window onto the landscape of industry-sponsored clinical trials completed during 2017. Novartis and Takeda were top sponsors of completed trials attaining primary endpoints.

BY CHRISTINE BLAZYNSKI AND LAURA RUNKEL Sponsors saw slightly lower success rates of completed trials in 2017 compared with 2016. Only eight sponsors showed a success rate of 25% or higher last year – half the number of the year before.

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But in terms of overall success rates, top sponsors and trial volumes reflect the status quo, despite some shifts among those leading the pack.

completed clinical trial landscape provides a more granular view of how companies are progressing their pipelines and the disease strategies they are pursuing, compared with static pipeline snapshots. During 2017, a total of 3,534 Phase I through Phase III/IV industrysponsored trials were completed, according to a review of data from Informa Pharma Intelligence’s Trialtrove. This year’s metric is comparable to what was reported for 2016’s completions (3,420 trials) and for 2015’s (3,028 trials). At the therapeutic area level, 2017’s completed trials in oncology again dominated, with 910 trials, and type 2 diabetes was the disease with the largest number of completed trials, at 171. Roche was the top sponsor in 2017 – surpassing the previous year’s leader, Novartis AG, and as was reported for the previous year, 2017 also saw a significant volume of industry partnering for trials. The latest review is based on clinical trials exported from Informa Pharma Intelligence’s Trialtrove on February 13, 2018. The search was limited to industry-sponsored trials with primary completion dates, or primary endpoint reported dates between January 1, 2017 and December 31, 2017. The nearly 700 trials terminated in 2017 were not included in the analysis.

Top-line Trial Landscape Metrics Across the nine therapeutic areas (TAs) included in Trialtrove, the rank order with respect to numbers of completed trials remained unchanged between 2016 and 2017. (See Exhibit 1.) The top three TAs remain oncology, autoimmune/inflammation (A/I) and central nervous system. In terms of absolute numbers, just over 80 more oncology trials completed in 2017 compared with 2016. The other TAs with more trials in 2017 24 | In Vivo | May 2018

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Exhibit 1

Completed Industry-Sponsored Trials Ranked By Therapeutic Area THERAPEUTIC AREA

RANKING

TRIAL COUNT

2017

2016

2015

2017

2016

2015

Oncology

910

826

764

Autoimmune/Inflammation

656

677

542

CNS

582

547

562

Metabolic/Endocrinology

484

516

495

Infectious Diseases

401

435

453

Cardiovascular

309

249

247

Vaccines

157

149

178

Ophthalmology

Genitourinary

Exhibit 2

Completed Trials Distribution By Therapeutic Area And Phase Oncology A/I CNS M/E Infectious Diseases Cardiovascular Vaccines Ophthalmology Genitourinary 0

100 I

200 I/II

300

400

II/III

500 III

600

700

800

900

III/IV

Note: Trials may span multiple therapeutic areas. Infectious disease does not include vaccines trials.

include CNS, cardiovascular, vaccines, ophthalmology and genitourinary. Although oncology, A/I and CNS again led in terms of total number of trials, a view of the distribution of trials by phase reveals a few surprises. (See Exhibit 2.) For absolute counts of Phase III trials, metabolic/endocrinology slightly edged out oncology for third place, whereas A/I and CNS ranked first and second, respectively. Relative to each TA’s total completed trials, Phase III oncology tri-

als accounted for 13%, while Phase III comprised 32% for ophthalmology and vaccines each. But oncology’s 351 Phase II trials (37% of all its trials) suggest that, should most of these programs progress to the next phase, 2018’s completed trials ranking by phase may be different. Within each TA, we compared the top 10 diseases with completed trials in 2017 with the prior three years. The sum of trials for these diseases was highest in 2017, and apart from trials assessing

efficacy in hepatitis C virus (HCV), the absolute numbers of trials for 2017 were close to, or exceeded the 2016 counts. (Go online for detailed table.) Yet, for most of 2017’s top disease completions, the watermarks reported for 2014 remain the highest – type 2 diabetes, breast cancer, respiratory infections, non-small cell lung cancer (NSCLC), nociceptive pain, HIV, rheumatoid arthritis (RA) and hypertension. (Data for 2014 are higher due to a three-week later snapshot date, as well as contractually expanded disease coverage in Trialtrove.) Trialtrove analysts assign a trial outcome to completed trials when that information becomes available in the public domain. Across all phases and diseases, the success rate (defined as numbers of trials attaining primary endpoint divided by total trials) was 31%. The success rate varied by phase, with Phase I trials having the lowest, at 12.4%. However, reporting of results for Phase I trials is often unavailable. (Within Trialtrove, Phase I trials are only tagged with outcomes provided they have efficacy or efficacy biomarker outcomes. Low percentage of reporting reflects low availability in part due to the absence of these endpoints in trials.) For Phase II and III, the overall success rates were 39.6% and 43.0%, respectively. The diseases with 25 or more trials that attained primary outcome(s) were led by breast cancer, with a total of 58 trials, which accounted for 34.7% of all completed trials. (See Exhibit 3.) The topranked disease, multiple myeloma, had 26 of its 45 trials hit endpoint.

Completed Trials Landscape: Sponsor Assessment Thirteen sponsors completed over 70 trials in 2017. The top five sponsors (see Exhibit 4) showed some movement compared with the prior three years, with Roche moving to the top of the leaderboard, Merck & Co. Inc., slipping to seventh place, and AstraZeneca PLCemerging into the top five rankings. The more telling metric is that of the top sponsors whose trials hit their primary endpoint(s). For those sponsors with more than 70 completed trials (see Exhibit 5), the overall success rates varied between a low of 15% (Boehringer IngelMay 2018 | In Vivo | 25

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CLINICAL TRIALS: Pipeline Progress ❚

❚ CLINICAL TRIALS: Pipeline Progress Exhibit 3

Diseases With 25 Or More Trials Attaining Endpoints DISEASE

# TRIALS ATTAINING PRIMARY ENDPOINT(S)

% OF ALL TRIALS

RANK#

Phase I

Phase I/II

Phase II

Phase II/III

Phase III

Total*

Breast

34.7%

Vaccines

33.8%

Colorectal cancer

45.5%

Non-small cell lung cancer

34.4%

Type 2 diabetes

24.6%

Pain (nociceptive)

32.8%

Non-Hodgkin's lymphoma

45.2%

Respiratory Infections

21.5%

Melanoma

52.5%

HIV

27.4%

Multipla Myeloma

57.8%

Liver

38.5%

Prostate Cancer

32.5%

Note: Trials may span multiple diseases. No Phase III/IV trials among these top diseases completed, or if completed, attained primary endpoint. Rank based on percentage of trials attaining primary outcome per disease.

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heim GMBH) to a high of 40% (Novartis). When Phase I trials are ignored, the success rates increase with a range from 28.6% (Gilead Sciences Inc.) to 52.9% (Takeda Pharmaceutical Co. Ltd.). The sponsors with the five highest success rates for Phase II through Phase III were: Takeda (52.9%), Pfizer Inc. (47.2%), Bristol-Myers Squibb Co.(45.8%), Novartis (44.5%) and AstraZeneca (40.7%). Co-sponsor Trial Activity Nearly 90% of the completed industrysponsored trials involved only a single top 20 pharma (by pharma sales based on the Scrip 100 league tables) or a single other pharma company (all other pharma, or AOP). Fewer than 4% of the trials involved two top 20 sponsors, and only 3% of trials were powered by two AOP sponsors. A total of 420 trials had some combination of co-sponsors. (See Exhibit 6.)

Top Three Therapeutic Areas: Success Assessment By Disease And Sponsor Across all TAs, the overall success rate is 30.9%; when Phase I trials are not included, the success rate rises to 41.4%. 26 | In Vivo | May 2018

Exhibit 4

Top Five Sponsors Completing Trials In 2017 2017 (RANK)

2016 (RANK)

2015 (RANK)

2014 (RANK)

Roche

160(1)

160 (2)

123 (3)

244 (2)

GlaxoSmithKline

155 (2)

158 (3)

119 (4)

239 (3)

Novartis

152 (3)

165 (1)

147 (1)

265 (1)

AstraZeneca

138 (4)

Pfizer

135 (5)

140 (4)

120 (5)

225 (4)

Merck & Co.#

110 (7)

134 (5)

127 (2)

203 (5)

SPONSOR

Note: Trial count includes co-sponsored trials. AstraZeneca’s metrics before 2017 are unavailable because prior year analyses were limited to the top five sponsors. Merck & Co. ranked seventh, behind Lilly, in 2017

Across Oncology, the overall success rate is higher than the overall average, at 39.5%; when Phase I trials are excluded, the rate rises to 47.4%. For A/I, the overall success rate is 29.9%; it rises to 40.5% when Phase I trials are excluded. In CNS trials the success rate is 27.0% across all phases, while for Phases II and III it jumps to 38.4% (data not shown).

Oncology The five cancer indications with the largest numbers of trials that met primary endpoint(s) were breast cancer (58), colorectal cancer (44), NSCLC (43), non-Hodgkin’s lymphoma (NHL; 36), and melanoma (31). Roche and Novartis outpaced all other sponsors, with 38 and 34 trials hitting endpoints, respectively. invivo.pharmamedtechbi.com

Exhibit 5

Top Sponsors With Trials Attaining Primary Endpoints

SPONSOR

TOTAL OVERALL COMPLETED SUCCESS RATE TRIALS (RANK) (RANK)

# TRIALS ATTAINING PRIMARY ENDPOINT(S) Phase I

Phase I/II

Phase II

Phase II/III

Phase III

Total*

Roche

160 (1)

32.5% (5)

GlaxoSmithKline

155 (2)

23.9% (10)

Novartis

152 (3)

40.1% (1)

AstraZeneca

139 (4)

31.2% (6)

Pfizer

39*

135 (5)

28.9% (8)

Eli Lilly

117 (6)

20.2% (12)

Merck

113 (7)

24.5% (9)

Bristol-Myers Squibb

88 (8)

31.0% (7)

Sanofi

85 (9)

34.5% (3)

Gilead

84 (10)

21.4% (11)

AbbVie

84 (10)

33.3% (4)

Takeda

76 (11)

37.3% (2)

Boehringer Ingelheim

72 (12)

15.2% (13)

Note: Pfizer had one Phase III/IV trial that hit endpoint.

Besides these top two sponsors, those with 10 or more trials that attained primary endpoints included AstraZeneca, GlaxoSmithKline PLC, Pfizer, BMS and Celgene Corp. (See Exhibit 7.) Relative success rates, however, reveal that Takeda and Celgene were the top performers last year. When considering only Phase III trials, Pfizer’s success rate led at 81.1% (nine of 11 trials), followed by Eli Lilly & Co.at 71.4% (five of seven trials) and AstraZeneca (five of eight trials). The top sponsor by relative success for completed Phase II trials was Takeda, with nine of 12 trials attaining primary endpoints (75.0%). For trials that were co-sponsored solely by top 20 pharma, 23 of 53 (43%) attained primary endpoints. Five of the completed Oncology trials involved three top 20 pharma sponsors. Amgen Inc., Bayer AG and Sanofi completed two of these trials: a Phase I/II pancreatic cancer trial and a Phase I acute myelogenous leukemia trial. Forty-eight trials involved two top 20 sponsors, with 21 trials meeting primary endpoints (43.8%). Of these trials, 19 were co-sponsored by GSK and Novartis, with

eight hitting primary endpoints. The next most frequent sponsor pairings were Astellas Pharma Inc./Pfizer with five trials; AbbVie Inc./Roche and Johnson & Johnson/Roche completed four trials each (and both co-sponsor pairs had two trials meet primary endpoints). Trials sponsored by a sole top 20 sponsor totaled 405, with 150 attaining primary endpoint for a lower overall success rate of 37%. Trials sponsored by a sole AOP company numbered 358, with 146 attaining primary endpoint (40.7%) for a slightly higher overall success rate compared with top 20 sponsors. Notably, Celgene completed 27 trials (44.4% success); Otsuka had eight of its 14 trials meet endpoint (57.1%); and Merck KGAA held third place with 11 trials, of which only three hit endpoint (27.2%). There was far less collaboration among AOP sponsors, with only 29 trials having two sponsors in this group (41.4% meeting endpoints) and seven trials having three AOP sponsors (57.1% success). A small number of trials were sponsored by both top 20 and AOP; of these 57 trials, 23 met primary endpoint – a 40.3% success rate.

Autoimmune/Inflammation Across the diseases in this therapeutic area included in Trialtrove’s coverage, five diseases had 50 or more completed trials: rheumatoid arthritis (105 trials), psoriasis (108), asthma (81), chronic obstructive pulmonary disease (66), and osteoarthritis (54) (data not shown). But, when looking at percentage of trials by disease that attained primary endpoint, the top five diseases are: transplantation/graft versus host disease (66.7%), other inflammatory arthritis (62.5%), Crohn’s disease and pulmonary fibrosis (57.1%) and allergic rhinitis (52.2%). For the top five diseases, RA had a success rate of 16.2%, psoriasis 21.3%, asthma 14.8%, COPD 47% and OA 30.2%. If Phase I trials are excluded from the group, the success rates change to 33.3%, 34.4%, 8.7%, 45.2% and 30.2%, respectively. AstraZeneca completed the largest number of trials last year, but ranked third by the metric of success. As observed for the Oncology area, rank by volume differs from rank by success rate. (See Exhibit 8.) When Phase I trials are May 2018 | In Vivo | 27

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CLINICAL TRIALS: Pipeline Progress ❚

❚ CLINICAL TRIALS: Pipeline Progress Exhibit 6

Distribution Of Co-sponsored Trial # SPONSORS

PHASE I

PHASE I/II

PHASE II

PHASE II/III

PHASE III

PHASE III/IV

TOTAL

1 Top 20

557

403

377

1414

2 Top 20

137

3 Top 20

1 AOP

641

138

539

321

1671

2 AOP

105

3 AOP

7 AOP

1 Top 20 / 1 AOP

146

1 Top 20 / 2+ AOP

2 Top 20 / 1 AOP

3 Top 20 / 1 AOP

Exhibit 7

Top Sponsors With Completed Oncology Trials NEGATIVE OUTCOME

OUTCOME INDETERMINATE

OUTCOME UNKNOWN

POSITIVE OUTCOME

N/A

TOTAL TRIALS (RANK)

SUCCESS RATE

Takeda

22 (9)

54.5%

Celgene

37 (5)

48.6%

BMS

39 (4)

43.6%

Novartis

80 (2)

42.5%

AstraZeneca

41 (3)

41.5%

Bayer

29 (8)

41.4%

GSK

39 (4)

41.0%

Pfizer

39 (4)

41.0%

Roche

95 (1)

40.0%

Sanofi

31 (7)

38.7%

Eli Lilly

35 (6)

31.4%

# SPONSORS

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Note: “Indeterminate designation” is assigned to trials when the outcome is neither clearly positive or negative. “Unknown” is assigned to trials that have yet to report full results for primary endpoint(s). “N/A” indicates trials with no results available in the public domain.

excluded, the top three companies by volume also finish in the top three rank by success, although the rank order differs: AstraZeneca (26 trials; 46.2% success), Novartis (24; 75.0%), AbbVie (26; 42.9%) (data not shown). A total of 280 trials were run solely by a single top 20 sponsor; of these, 59 reported success (21.1% success). A small number of trials (23) had two top 20 sponsors, and 11 of these hit endpoint (52.3% 28 | In Vivo | May 2018

success). The partnered AbbVie/BI trials accounted for 10 of these trials (five of which attained endpoints). Three hundred nine trials were sponsored solely by one AOP company; 107 reported attaining primary endpoints (34.6%). Only 20 trials were sponsored by two AOP companies (40% success). Nineteen trials were sponsored by a single top 20 and single AOP company; seven of these trials involved Regeneron and Sanofi (data not shown).

CNS The 10 diseases with the most trial completions ranged from a high of 118 for nociceptive pain, to migraine and multiple sclerosis, which tied with 34 each. When trials from each phase are included in the success rate calculation, not one of these top 10 diseases came close to even 50% success. Parkinson’s disease had the highest overall rate of 36.4%. When Phase I trials are excluded, invivo.pharmamedtechbi.com

Exhibit 8

Top Sponsors With Completed A/I Trials # SPONSORS

NEGATIVE OUTCOME

OUTCOME INDETERMINATE

OUTCOME UNKNOWN

POSITIVE OUTCOME

N/A

TOTAL TRIALS (RANK)

SUCCESS RATE

28 (4)

46.4%

Novartis

AbbVie

30 (3)

36.7%

AstraZeneca

45 (1)

28.9%

GlaxoSmithKline

39 (2)

20.5%

Boehringer Ingelheim

25 (6)

20.0%

Roche

25 (6)

18.5%

6 (9)

16.7%

27 (5)

14.8%

Astellas

7 (8)

14.3%

Bristol-Myers Squibb

15 (7)

13.3%

25 (6)

8.0%

Merck Pfizer

Eli Lilly

SOURCE FOR ALL EXHIBITS: Trialtrove, February 2018

schizophrenia’s success rate rose from 18.2% to 87.5%, migraine from 29.4% to 60% and Parkinson’s disease moved from 36.4% to 50% success (data not shown). Eli Lilly topped the sponsors with 25 completed trials, followed by Johnson & Johnson (J&J) with 21, and Lundbeck with 19. (Go online for detailed table.) Otsuka’s 18 completed trials had the highest overall success rate – 50.0%. When Phase I trials are excluded, Otsuka’s success fell slightly to 46.7%, whereas Eli Lilly, Pfizer and BI hit 50% each. UCB Group’s five successful trials yielded a success rate (sans Phase I trials) of 55.6%, making this sponsor the overall leader. Sponsors saw slightly lower success rates in 2017 compared with 2016. Novo Nordisk AS’s 46% success rate for 2016 was higher than Novartis’ success rate of 40.1% for 2017. Sixteen pharma sponsors had 25% or higher success rates in 2016, compared with eight in 2017. Trying to assign any reason for this decline, other than slow trial outcome reporting, would be highly speculative. The analysis performed last year indicated a significant degree of cosponsorship of trials, and of these, a higher percentage of trials attained

primary endpoints compared with singlesponsored trials. However, no strong co-sponsor pairings emerged in the 2017 dataset (compared with 2016: Sanofi/ Regeneron’s 13 trials in Autoimmune/ Inflammation with 38.5% success, or the Lundbeck/Otsuka pair with five of nine trials in CNS hitting endpoints). Whether or not the small number of partnered trials represents a true return to “going it alone” remains to be seen with our analysis of 2018 completed trials. Overall, the top sponsors and trial volumes reflect the prior years’ status quo, year-over-year for completed trials activity; but the individual successes from 2017 demonstrate that there was ample shifting and evolution during 2017. IV005334 Comments: Email the authors: Christine.Blazynski@informa.com and Laura.Runkel@informa.com

Editor’s note: The full report contains additional information such as differing strategies and trial success rates for novel products, novel formulations, label expansions, life-cycle management changes, and me-too versions. It is available at https://bit.ly/2L5gdR6

INTERACTIVE DATA ONLINE 2017 Completed Trials Interactive versions of this article’s exhibits, plus additional tables, are posted online to allow deeper analysis and customizable views. Explore more at: https://bit.ly/2L5gdR6

May 2018 | In Vivo | 29

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CLINICAL TRIALS: Pipeline Progress ❚