This Powerpoint by the MAPS Evidence Generation Focus Area Working Group offers a comprehensive overview of Real World Evidence (RWE) and its evolving use in the biopharmaceutical industry.
Medical Affairs thought leaders discuss the Pre-21st Century Cures Act uses of Real World Evidence (RWE) in regulatory decision-making.
Cerise James, MD, moderates this podcast in which Neil Belson, JD, discusses Real World Evidence and its impact to the biopharmaceutical industry.
Download the full article here
By Robert Honigberg, MBA, MD, MS&T Consulting, LLC
Neil Belson, JD, Law Office of Neil A Belson, LLC
The 21st Century Cures Act, enacted in 2016, requires the U.S. Food and Drug Administration (FDA) to assess the use of Real-World Evidence (RWE) for applications that include new drug indications and satisfying post-approval drug study requirements. RWE can contribute to showing that a drug or medical device is safe and effective, within the context of the FDA’s “totality of evidence approach” for evaluating regulatory submissions. The FDA has approved both drugs and medical devices based on regulatory submissions which have included RWE.
KEY WORDS: Real-World Data (RWD), Real-World Evidence (RWE), totality of evidence, FDA
The 21st Century Cures Act (2016) requires the U.S. Food and Drug Administration (FDA) to assess the use of Real-World Evidence (RWE) for applications that include new drug indications and satisfying post-approval1,2. The FDA issued a final guidance document for medical devices in 2017, in which the Agency stated that the applicant could use Real-World Data (RWD) to support regulatory determinations under the right conditions3. While the FDA has not yet followed up with a guidance for pharmaceutical products, their 2018 Framework for FDA’s Real-World Evidence Program outlined the potential applications of RWE for regulatory decision-making regarding the effectiveness of marketed products4. In the instance of an original approval for a product, the FDA recommended that an evidence package could contain three types of studies: clinical pharmacology, non-clinical toxicology, and clinical studies. However, for post-marketing labeling changes (i.e., use in a new population or a new indication), the evidence package could include prior submitted evidence and new evidence, traditionally represented by randomized clinical studies but also RWE studies. What is important for Medical Affairs and Regulatory teams to understand is that regardless of study type, setting, or design, the FDA does not have to evaluate one study type (i.e., Randomized Clinical Trial (RCT)) only when making regulatory decisions. Instead, the FDA uses a totality of evidence approach, examining all available evidence in the regulatory materials submitted including the quality of the studies and context of the manufacturer’s request4.
“While Real-World Evidence analysis will not replace the randomized controlled trial, it already has been used as effective support data for drug and device labeling changes and for rare disease submissions.”
Bob Honigberg MD
Several applications for labeling expansions and other regulatory approvals have successfully incorporated RWD and RWE. The purpose of this Elevate article is to provide regulatory examples of how various companies have negotiated with the FDA and successfully utilized RWE within regulatory submissions.
Regulatory submissions that involve the submission of RWD can come from data sources that routinely collect health-related information such as claims data, electronic health records, patient reported outcomes (questionnaires and devices), registries, as well as public and private databases. The use of RWE implies the analyses of RWD through applied research methods, such as for historical controls, or other types of analyses using records that were initially collected from sources other than randomized clinical trials. It is important to first target an opportunity where the use of RWE will add to the “totality of evidence.” The role of RWD and RWE has been especially useful for rare diseases as well as for the expansion of labeling to a more broad or newly defined sub-population, and the evolution of procedural medical device techniques. Using a “totality of evidence” approach, one can determine if the new evidence from RWD sources or RWE analyses can add to the existing evidence to create a new evidence package that has value from a clinical and regulatory perspective.
A White Paper prepared in December 2019 by the Duke Margolis Center for Health Policy5 examined non-traditional study designs which have used RWE, including open-label, single-arm studies, retrospective observational and case series, retrospective cohort studies using RWD sources, non-inferiority studies, RWE-generated historical controls, the use of concurrent control groups, and the use of post-market surveillance and registry data. Table 1 is an adapted summary of examples of approvals and labeling changes for drugs using evidence generated from these non-traditional studies. This article discusses three pharmaceutical case examples in this communication: Ibrance for male breast cancer, Invega Sustenna for schizoaffective disorder and Brineura for treatment of a form of Batten disease. The article also examines the label expansion of a medical device based on RWE to include a minimally-invasive approach to aortic valve replacement using Transcatheter Aortic Valve Replacement (TAVR).
Ibrance (Palbociclib) was approved for metastatic breast cancer in 2019. The approval was based on two large randomized controlled trials (the PALOMA studies) in women and supported by clinical pharmacology and non-clinical toxicology studies. Evidence for clinical benefit in male breast cancer was noted from post-marketing reports, insurance claims data and electronic health records. Male breast cancer is a rare condition with a high unmet need for treatment; there were approximately 2,500 new cases and 500 deaths in 2019. The FDA submission included evidence derived from RWD sources including: the IQVIA insurance database, Flatiron Health breast cancer database, and the Pfizer global safety database. The FDA noted in its approval letter that “Given the extensive established efficacy and safety of the use of Palbociclib in women observed in randomized controlled trials, the additional RWE data provided in this application for the use in men, modest as it is, does support the expansion of the Palbociclib indication to provide for the treatment of men with metastatic breast cancer.”6
In 2011, the FDA approved the Sapien 3 device for TAVR, a novel approach that provided a minimally invasive alternative to open heart surgery for clinically appropriate patients. Post-marketing surveillance requirements included the collection of data in over 100,000 procedures in the Transcatheter Valve Therapy Registry, which included a subset in 600 patients that underwent the valve-in-valve variant of the procedure. Although this procedural variant was considered off-label, the valve-in-valve procedure was shown to be an improvement as it allowed the new valve to be placed inside the diseased valve. The FDA evaluated the clinical and functional data for this procedure from the registry to expand the indication for the TAVR-enabling device. The FDA announced that even though the United States had been only the 42nd country to approve the original TAVR device, through the use of creative regulatory procedures the United States became the first country to approve the new indication.
Invega Sustenna (paliperidone palmitate) is a centrally active anti-psychotic and the only once-monthly long-acting injectable (LAI) for schizoaffective disorder. There have been several expansions to the label since its original approval in 2006 for acute schizophrenia. In 2018, a labeling change was approved related to the time to treatment failure compared to oral anti-psychotics using an unconventional clinical trial design that was more representative of the disease population. Prior RCTs had excluded adult subjects with recent incarceration or substance abuse from the trial. The PRIDE trial, which was a randomized open-label pragmatic trial, recruited many subjects from jail-release programs, homeless shelters and soup kitchens. The trial was able to build on the existing evidence provided by published RCTs and include a broader and more representative population using an unconventional RWE clinical trial design that not only showed a time to treatment failure benefit but also a medication adherence benefit compared to oral anti-psychotics.
The FDA’s approval of Brineura (cerliponase alfa) in 2017 as a treatment for a form of Batten disease, is an example of the agency comparing a “single-arm” clinical study of a prospective drug treatment against a natural history “control” obtained from RWD. This use of natural history “controls” in single-arm clinical studies of prospective treatments for rare diseases has historically been among the most common uses of RWD to support regulatory approvals7. Brineura, an enzyme replacement therapy, was the first FDA-approved treatment for slowing the progressive loss of walking ability in patients with late infantile neuronal ceroid lipofuscinosis type 2 (CLN2). CLN2 disease is a rare inherited disorder which occurs in approximately two to four of every 100,000 U.S. live births. Signs and symptoms in the late infantile form of this disease typically begin between ages two and four. Individuals with this condition often require use of a wheelchair by late childhood and typically do not survive past their teens. The clinical trial which established Brineura’s efficacy was a non-randomized, single-arm dose escalation clinical study in 22 symptomatic pediatric patients. The “control” or comparator was a group of 42 untreated CLN2 patients from a natural history cohort (an independent historical control group). Patients treated with Brineura suffered fewer declines in walking ability compared to the untreated patients in the natural history cohort.8
The 21st Century Cures Act directed FDA to evaluate the use of Real-World Data (RWD) and Real-World Evidence (RWE) in regulatory submissions. The objective of this Elevate article is to examine some of the approaches accepted by the FDA for using RWE to obtain regulatory approvals for drugs and devices. It is important to select new indication and expansion targets where there is an opportunity for RWE analysis to credibly add to the existing evidence base using a “totality of evidence” approach.
“While our understanding of the potential applications of RWE and the appropriate standards for its use is still evolving, RWE will almost certainly have an increasingly important role in future regulatory submissions for drugs and medical devices.”
Neil Belson JD
|
1 |
PRODUCT |
SPONSOR |
DISEASE |
STUDY DESIGN |
|
Bavencio (avelumab) |
Pfizer and Merck KGaA |
Metastatic merkel cell CA |
Open-label single-arm multicenter trial |
|
|
2 |
Blincyto (blinatumomab) |
Amgen |
B-cell precursor ALL |
Open-label single-arm multicenter trial |
|
3 |
Brineura (cerliponase alfa) |
Biomarin |
Infantile Batten Disease |
Non-randomized single-arm dose-escalation study Non-randomized comparison with natural history cohort |
|
4 |
Carbaglu (carglumic acid) |
Recordati Rare Diseases |
Hyper-ammonemia |
Retrospective unblinded uncontrolled case series |
|
5 |
Cordarone (amio darone HCl tabs) |
Sanofi |
Arrhythmia |
Retrospective open-label self-controlled study |
|
6 |
Ibrance |
Pfizer |
Male breast cancer |
Retrospective cohort study using HER data, insurance billing data, and post-marketing studies |
|
7 |
Inactivated polio vaccine |
NFIP (March of Dimes) |
Polio |
Randomized blinded placebo-controlled trial with additional observed controls |
|
8 |
Intravenous ganciclovir |
Exela Pharma Sciences |
AIDS and CMV retinitis |
Retrospective non-randomized study |
|
9 |
Invega Sustenna (paliperidone palmitate) |
Janssen |
Schizophrenia, schizoaffective disorder |
Prospective randomized open-label active-controlled parallel-group trial |
|
10 |
Luthathera (lutetium Lu 177 dotatate) |
Advanced Accelerator Applications (Novartis) |
Somatostatin receptor positive GEP-NETs |
Randomized open-label, active-controlled multicenter trial Retrospective study |
The digital health revolution implies a clear understanding of strategy, using technology as an enabler to create better outcomes for patients and to power value creation across the healthcare ecosystem. As data specialists, Medical Affairs professionals will be at the forefront of this transformation.
The medical world is changing and changing fast. As multiple new technologies start to transform every aspect of the healthcare ecosystem and the lines between biosciences and data science fade, companies need medical leaders who not only understand the latest medical advances but also the potential and scope of data and digital, along with their implications – not least that this new paradigm requires strategists who are comfortable with organizational transformation and who can lead change. Dr Rajni Aneja is one such strategist: she specializes in the crossover between business and technology across a variety of health sectors.
“My training falls at the intersection of business and technology and I have worked across all different healthcare sectors from payer to a consumer digital company to pharma, as well as being involved in an advisory capacity for innovation and strategy in health for MIT and Harvard Innovation Lab, along with Oliver Wyman, and many other start-up companies.
“From an industry standpoint, I am interested in the role of digital facilitating consumer as well as HCP engagement strategies, or patient journeys through a variety of touch points leading to better clinical outcomes, better clinical interactions, better patient experiences, better healthcare provider experiences, as well as better delivery of healthcare.”
This approach is all about strategically using digital as an enabler driven by data. “When we create a strategy around a digital experience, it’s not about the technology. I see the technology as an enabler: when you apply the right technology at the right point and have the right interventions designed – either for the provider or patients – that is when it actually is impactful or meaningful.”
Longer term, advances in bioscience and digital technology have the potential to add value to the system in multiple ways: for example, by transforming the R&D process to potentially make it shorter, more specific, and take out cost; by ensuring better health outcomes for patients, bringing forward new treatments more quickly, and generally improving the patient experience; and by providing opportunities for physicians through new options to advance patient care and offering new ways to engage and learn.
We are only at the start of this journey today but Dr Aneja points to significant potential that already exists. “As a physician, when you see patients in clinics, you’re only seeing 15 to 20 patients in a day. But if you have technologies like telemedicine, where you are delivering consultations on videos, or you’re delivering care to remote areas, your impact and outreach becomes much wider and much more significant.
“I see telemedicine as one of the technologies to have gained a lot of momentum, not only for its potential in clinical trials but also for prevention and wellness visits, or even acute care visits. But what’s coming next? I think the future is where data is driving or enabling these technologies, and this is where artificial intelligence or machine learning comes into play. However, if the data is not good enough, anything that is going to come out of it is not going to be good enough: garbage in, garbage out. The importance of data as an asset is that you drive intelligent decision-making and that is only done through insights generated by the power of data that is collected from a variety of technology enablers.” As an example, she cites finding the right patient for the right clinical trial at the right time for the right medical condition, while delivering the right care, all of which can be powered and informed by the data.
Today, real-world evidence (RWE) and data – especially continuous real-time data – sits at the heart of where the healthcare ecosystem is headed, not least in the context of value-based health design and care delivery, where (especially in the US) the system is moving from volume to value, and there is more emphasis on better outcomes. This implies that data can be both shared and combined effectively, and also that RWE – including data directly from the consumer, say from wearables – can be integrated with historical data and combined with real-time analytics.
“There’s an evolving trend that we’re seeing: in the last two to three years pharmaceutical companies have started to work very closely with the payers. But the industry is becoming disrupted and I think all these stakeholders can learn from each other to say: ‘How am I going to be a leader in the game instead of a follower?’”
The trend within the healthcare sector is asking for more integration of data and collaboration between organizations – joining the dots – to generate insight from the payers as well as from pharma and from consumers. “This is a collaborative effort around value-based care and an outcome-based approach, which will lead to better patient care and better clinical trials. But there are many challenges remaining before this data utopia becomes reality, including a lack of agreement on definitions of what constitutes value. What is considered good-quality data, data privacy, data governance and data security and many others factors would play a vital role in shaping the thought process as we move along this transformation journey.”
So, what are the hurdles? The regulatory environment is one, but regulators and government are increasingly aware of the need to advance. We have seen the introduction of the 21st Century Cures Act; as well as statement from FDA commissioner, Scott Gottlieb about the importance of digital health and real-world evidence, and there are efforts now around guidance from the governing bodies. Commercial sensitivity is another issue, but industry is increasingly acknowledging the need for collaboration – perhaps through neutral consortium – to harness the power of data and analytics. As an example, Dr Aneja cites the NEWDIGS project, through MIT’s Center of Biomedical Innovation, which brought together various pharmaceutical partners in a neutral, non-biased, cohesive setting. However, she acknowledges that “we’re taking baby steps and are in exploration mode with a desire for more collaborative models, and not yet ready for prime time yet.”
And what about the benefits? There is clearly substantial value in a system that encourages us to learn about the patient – not least, greater customization, personalization, and simplicity for the patient. This encompasses patient-reported outcomes, behavioral profiles, social, and other demographic data leading to consumer segmentation, which in turn can deliver on targeted interventions and interactions.
Dr Aneja elaborates: “I’ll give you an example. Rajni is a 40-year-old female who runs every day and is pretty healthy and motivated and doesn’t take any medicine, but is very interested in her well-being. Because of the combination of data from different sources, we can create a profile of what Rajni wants, what Rajni needs, how we engage her, how we motivate her and do that on a continuous long-term basis; and data can enable targeted, personalized interventions – interactions that are actually applicable to Rajni, not one-size-fits-all. Data can help you get to that level of granularity, but I always say that with a word of caution: we’re not there yet. But that doesn’t mean that we can’t get there; it’s just that we’re on our way to this kind of transformation.”
And this opens up a whole world of further possibilities: Rajni might be part of a cohort that you could segment in the context of preventative health and screening, and so on. So there’s an opportunity to gain a depth of insight into individual patients within a population. “Imagine if you could understand, in your population, who are my well people? Who are my sick people? Who are the people who are very, very motivated? Who are people that actually need a lot of nudging because they’re not motivated? With the years of data, you have the ability to be not only predictive but at some point can be prescriptive, especially for precision medicine.”
Beyond this, digital needs to make life simpler and more convenient for patients. Healthcare is already becoming more consumer-centric. “I think it’s already happening. You already have Uber Health; we have telemedicine solutions; we have remote monitoring; we have wearables and sensors. I think the trend that we see is consumers becoming more involved in taking responsibility for health; they’re becoming more informed. Consumers want to manage their health, want to see their healthcare data, and want to be equally responsible for decision-making.
What needs to happen going forward? “I think it’s an industry shift.” There is recognition that we need to accelerate this process, according to Dr Aneja. In conclusion, she sees a significant role for Medical Affairs within this new environment – as the conduit of the digital transformation. MA can help define the problems we are trying to solve, along with the data sets and technology that will enable a solution. “They are absolutely vital. You would not create an initiative in a silo; technology is an enabler. Ultimately the insights coming from MA about what problems we need to create an effective solution for will lead to better patient outcomes as well as better patient experience.”
Biography
Rajni Aneja is an MIT Connection Science Fellow, healthcare strategist, public speaker, and transformative change agent with expertise in population health management and digital health. She serves as an adviser to a variety of health and wellness organizations. Dr Aneja encompasses various vantage points as a clinician, executive, adviser, entrepreneur, speaker and technology advocate serving in senior leadership roles. These include Chief Medical Officer for WebMD health, EVP of Joslin and a strategic executive and transformation leader at Humana. Most recently she contributed to the building of a digital consumer strategy at Novartis. Dr Aneja received her MD from Research Medical Center in Kansas City and her MBA from the University of Massachusetts.
Real world data (RWD), when captured and analyzed, produces the Real-World Evidence (RWE) that underpins the economic case for innovative medicines. Furthermore, RWD can inform the understanding of disease, help identify new therapeutic intervention points, and improve the efficiency of research and development (R&D), especially clinical trials. Unlocking the potential of any promising tool like RWD is not free from challenge and its full potential has yet to be realized. This Webinar aims to provide practical insight into the challenges surrounding RWD and RWE generation with interactive conversation on how individual companies are approaching these challenges.
By participating in this Webinar and/or the subsequent workshop at the MAPS EMEA 2018 Annual Meeting, attendees will be better able to:
Join Dr Omar Dabbous, Vice President, Health Economics and Outcomes Research (HEOR) and Real World Evidence (RWE) at AveXis, and Russell Becker, MA, HEOR Consultant, demonstrate HEOR’s front-and-center role in forging the modern healthcare agenda.
As healthcare systems worldwide become increasingly budget-constrained and cost conscious, stakeholders are placing greater emphasis on health economics demonstration and product potential in real-world practice. Once viewed solely as a support function, HEOR now often takes center stage in the internal decision-making process. As life sciences companies bring HEOR professionals and brand strategists together to formulate streamlined value chains, the function now provides essential data for licensing and R&D, as well as pricing and market access strategies, helps dictate research, planning and sales strategies.
This MAPS eCademy Webinar will:
Making the best possible choices about health care requires the best possible evidence upon which to base these important decisions. High quality evidence comes from many sources including real world data (RWD). The sources of RWD are numerous including electronic health records, claims and billing data, product and disease registries and patient-reported data.
Analysis of RWD leads to clinical evidence known as real world evidence (RWE) regarding the usage and risks and benefits of a therapy. Under the right conditions, RWD and the RWE that follows may be used to support regulatory decisions and contribute to the knowledge of a drug or therapy. RWE may help to support improved decision-making about health and health care.
After completing this Webinar, participants will be able to:
•List the sources of real world data (RWD),
•Understand how real world evidence (RWE) can help to support a regulatory decision,
•Recognize when in the product life cycle RWD/RWE may be useful,
•Utilize a patient-centric framework to develop a RWD/RWE generation plan.