Success in the Real World: Insights to Optimize Real-world Evidence Generation
By: Louise Parmenter, PhD | March 12, 2015
Gathering clinical trial data is an integral component of the value delivery process. But these data don’t address the simultaneous need for data about real-world outcomes. This disparity is creating an information gap that if not addressed will make it increasingly difficult to secure market access for new therapies.
In the last several years, the lens has widened from an almost singular attention on clinical outcomes to a much broader focus on combined clinical, economic and humanistic outcomes. This is putting increased pressure on biopharma companies to deliver more holistic evidence, including real-world outcomes, to support healthcare-decision making in support of their products.
At the same time, unprecedented access to new data channels, innovative designs and improved analytical techniques are driving a paradigm shift in real-world research methodologies. Never before has the world of healthcare evidence generation been so rich or so complex. Understanding the right research questions to ask and making sure that the right research approaches are followed is key to success in this age of complex data collection.
It is increasingly challenging for companies to know what real-world evidence to collect. The evidentiary needs of regulators, payers, providers and patients differ, and perspectives change from regional to national and sub-national level. Regulators want evidence to know whether a drug is safe and effective. Payers want evidence to help determine whether a drug should be included on the formulary and what it should cost. Providers want evidence to know whether the treatment should be incorporated into clinical practice guidelines. Local decision makers want to know whether a treatment should be available for their specific patient population. And patients want to know whether a treatment will make them feel better — and is affordable.
Biopharmaceutical companies can optimize their portfolio of real-world and late phase studies by seeking first to understand the needs of the broad spectrum of decision-makers and marrying these needs with insights into real-world data access and availability. The result is a more streamlined, insight-driven program of real-world and late-phase research.
The starting point for a real-world evidence strategy is to plan early, ideally late Phase II, early Phase III. In parallel, it is important to implement a centralized, yet locally-informed decision making and funding process for real-world research. A purely centralized process may miss critical local needs. A highly localized process can be inefficient and less impactful.
Insight generation should be comprehensive and timely to inform your real-world and late phase research program. Knowledge should be gathered from reviewing current available evidence in the existing product database, reviewing published literature, studying the primary research on existing care pathways, synthesizing evidence requirements of HTAs and interviewing affiliates, among many others. With insights developed it is possible to evaluate evidence gaps and elucidate the most important research questions. To answer the research questions requires an evaluation of real-world data sources to enable the elaboration of research approach.
Once the research approach has been identified, studies can be run to generate the evidence. The process commences with development of a protocol. The challenge at this stage is to ensure a study design responsive to multi-stakeholder, multi-country needs, but not overly complex. A recommended strategy can be to develop a core global protocol for with additional data elements to meet local needs. In such a way, fragmented local studies can be combined for increased statistical power and efficiency. Increasingly, such “elephant studies” are emerging to provide a rich stream of evidence to support market access.
There are opportunities for evidence generation and dissemination throughout the life of an observational study. Examples include descriptive analysis of baseline characteristics and interim analyses that can rapidly be communicated through conference abstracts and publications. A robust publication plan ensures that, even studies of many years in duration, add value from start to finish, and beyond.
Successful leverage of real-world evidence is critical in today’s competitive multi-stakeholder environment. Turning data into evidence requires an understanding of healthcare decision maker needs, early planning throughout the product life cycle and centralized yet locally- informed research plans.
The benefits of this approach are confidence in the relevance of the study results for decision making at all levels, fewer, more impactful studies, and studies that leverage available real-world evidence, where exists, for faster more cost effective research.