Mind the (Evidence) Gap
Real-world evidence (RWE) has become a veritable necessity for continued commercial success. The FDA uses RWE for evaluating post-launch safety, new indications, label changes and, potentially, drug approvals. And, particularly in the case of orphan drugs with accelerated approvals and novel therapies for conditions like migraines and diabetes, payers and providers alike look to real-world data for both coverage and clinical decision-making.1
Thanks to specific regulatory activity, the pharmaceutical industry is more keenly interested in additional evidence generation methods beyond traditional randomized clinical trials. Propelled by a provision within the 21st Century Cures Act,2 the FDA released a framework for its Real-World Evidence Program in December 2018.3 In it, the FDA identifies gaps in real-world data sources as an important obstacle to address and says that, as part of its RWE program, it will “explore strategies for filling gaps in data that may be difficult to obtain from currently used electronic health records (EHRs) and medical claims data, including exploring the use of mobile technologies, electronic patient reported outcome tools, wearables, and biosensors.”4
The 21st Century Cures Act, passed in 2016, places additional focus on the use of real-world data to support regulatory decision-making, including both drug approvals and new indications for approved drugs.
Knowing the value of RWE is one thing. But how do manufacturers realistically gather—and integrate—data that supports their product value story, both pre- and post-launch?
Comparator studies have always been a part of the clinical research necessary for a drug approval. And often, for rare diseases with small patient populations, they present significant patient recruitment challenges and evidence gaps. But innovative manufacturers are now looking to RWE as the missing piece of the evidence puzzle, performing chart reviews on historical data to pull together a complete comparator study. While it may require a certain amount of rigor to meet regulatory requirements, the methodology itself demonstrates that the FDA is willing to entertain creative approaches to using RWE.
Prospective studies (PS) are another methodology that’s gaining traction as manufacturers seek to fill the evidence gap for drugs that are already FDA-approved and commercially available. Unlike traditional clinical trials, prospective studies are often unique in their design and objectives, which include collection of longitudinal patient data. In fact, manufacturers can improve the efficiency and outcome of a PS by considering unique, innovative approaches to study design and deployment. These approaches include:
- Thinking differently about study design and patient recruitment.
Traditionally, prospective RWE data has been collected by physicians’ offices across the country, which means waiting for office visits that may not happen regularly. With patient recruitment already a challenge, this approach does not support a timely or cost-effective study. Now, savvy manufacturers are tapping into rich data sources, such as health systems’ EHRs, to make patient recruitment more effective and less cumbersome.
EHRs yield large data sets that can be queried to identify potentially eligible patients. From there, a health system can perform email outreach to those patients to invite them to participate in the study. The patient then visits an online portal where they provide consent and report data for a specified duration of time. Once the patient follow-up is completed, the most modern study partners can link the patient-reported data with EHR and claims data provided by the health system to create a complete picture of a drug’s outcomes, treatment pattern, burden of disease and even the effect on healthcare resource utilization. This virtual study design eliminates the need for on-site physician visits and direct data collection. And, this innovative approach to patient recruitment and data collection can save manufacturers both time and money as they design and execute prospective studies and plan post-launch marketing activities.
- Streamlining data capture with digital tools.
The conventional practice of gathering clinical data from physician offices often involves a paper case report form that is cross-checked against the patient’s medical record during multiple data monitoring visits at the physician site(s). Now, with the help of a qualified study partner, data collection can happen via direct methods like apps (for PROs) and exports from EHRs. In most cases, site personnel enter data directly into a study’s electronic data capture (EDC) tool. These methods speed access to study data – data that is often cleaner and does not have to be source-data verified. The result is a faster turn time for a PS, which means manufacturers can more quickly bring RWE to regulatory authorities, payers, providers and marketing efforts.
Leveraging the Power of a Personal Touch
At first blush, patient retention might seem like a challenge for digital recruitment and data collection methods. Patients seeing their physicians as part of a study are generally more accountable for reporting outcomes. In cases where patients aren’t directly engaged or they’re only getting emails, the challenge of retention is a reality. But the most innovative study designs not only incorporate multiple, tailored communication methods, they also include direct engagement with patients. And what some manufacturers are finding is that patients like the relationships they forge during these studies and care about their contributions. Supplementing digital tools with human interaction can close the gap in terms of patient retention.
The Benefits of Better Design
While the efficiencies gained by these innovative approaches to study design can certainly be replicated, there are elements (data sources, communication methods) that should be right-sized and customized for a manufacturer’s product and patient population. There really is no one-size-fits-all approach to prospective studies, but the right approach can yield better RWE faster and more cost-effectively. And the right prospective study partner can combine each of these elements to create a data-driven value story.
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