Christopher Boone, PhD, is Vice President, Global Head of Health Economics and Outcomes Research at AbbVie. He is also an adjunct assistant professor of health administration at the New York University's Robert F. Wagner Graduate School of Public Service, an active board member of several health care organizations. Prior to AbbVie, he served as the Vice President and Head of Global Medical Epidemiology and Big Data Analysis at Pfizer.
Chris spoke at Panalgo's 2021 IHD User conference about the evolution of Real-World Evidence (RWE) and how pharma needs to reimagine its function - to better enable clinical discovery, development and the commercialization of drug therapies in a post-COVID-19 world. Here are the key highlights from his talk.
I believe the biopharma industry is certainly ripe for disruption. Prior to the pandemic, there were attempts by many pharma companies to be more progressive by establishing Chief Digital Officer and Chief Data Officer roles, but those had relatively limited impact. Since COVID-19 hit, however, many of these digital and data transformation efforts have really taken shape and have begun to be incorporated into the strategies of many biopharma companies.
A: There are three main reasons. First, there's a major push by regulatory agencies who are expressing strong interest in the use of RWE as a complementary evidentiary base. This interest is growing particularly as we get more success stories where RWE has been appropriately used – for example, as it pertains to the COVID-19 vaccines from both Pfizer and Moderna and their effectiveness in rural areas.
Secondly, there's been a dramatic increase in the availability of data, both structured and unstructured. The power comes from our ability to really look at this unstructured data which we’re just beginning to explore in depth.
This exploration has been empowered by the third reason, which is the significant advances in AI and many of our predictive modeling capabilities coupled with the ideas around knowledge management and other technologies that we're seeing when it comes to the RWE function.
A: The explosion of genome sequencing and digital technology allows us to obtain data about people in real-world situations. Further interoperability among these various systems enables us to exchange bi-directional information allowing us to create comprehensive longitudinal records giving us a wealth of information that we can explore. But despite the growth of new data, there's been a number of studies that say we’re analyzing less than 5% of this available data. So in reality, we don't know what we don't know. One of the key things that we'll have to think about moving forward is how do we start to reframe our questions when conducting analyses. We have this wealth of information, but yet we're still fundamentally asking the same questions we were asking 10, 15, or 20 years ago. Hopefully with the better incorporation of many of the advanced analytical capabilities, we'll start to ask more appropriate questions that will give us greater insight.
A: Companies can take different approaches and it all depends on their culture, leadership and preferences. A federated approach keeps you much closer to the business so you can better understand the priorities. The problem with a highly federated system is that it can be very limiting when it comes to scaling learnings and insights since you can only grow as far as your RWE resources can take you.
The lack of resources to build RWE functions across different business units have caused many businesses to move to a centralized approach which generally takes the form of a Center of Excellence (CoE). This approach allows for greater consistency, quality of the analysis and knowledge sharing under one roof. But even that can be a step removed from the business and depending on the culture of the organization and the leadership’s support of the CoE it can be somewhat limiting in its effectiveness.
I think ultimately the world will shift to a hybrid of the two which is sometimes referred to as hub-and-spoke. This approach provides best of both worlds where you have a CoE as a centralized knowledge sharing center, but you also have units that are somewhat dispersed throughout the various business entities that are interconnected in some way. This network-type approach really starts to institutionalize the use of RWE.
A: According to a 2020 Deloitte RWE survey, 94% of respondents said that using RWE in R&D will become important or very important to their organizations by 2022. Survey respondents said they expect a shift in the appreciation of RWE in the next two to three years, with the highest impact being in R&D including supporting regulatory filings and augmenting clinical trials. Most respondents expect a wide range of benefits from using RWE in R&D with the biggest gains coming in the form of cost reduction in post-marketing commitments and executing clinical trials. Seven out of 10 respondents say that a lack of research-grade data is hindering RWE efforts in R&D. This emphasizes the importance of establishing strategic partnerships and is the reason that more than 80% of surveyed companies said they are entering into strategic partnerships to access new sources of data.
This all suggests that we need to be much more strategic and opportunistic in how we think about data. Nearly all the companies surveyed expect to increase investments in talent, technology and external partnerships to strengthen their RWE capabilities. That means building partnership ecosystems that complement your capabilities and enable you to do your work much more efficiently and effectively than you have in the past.
A: We need to look back in order to look forward so we can learn from the things that we’ve done well and how the entire healthcare ecosystem has taken shape on a global level.
The early days of the RWE function involved mostly data sourcing and procurement focused on identifying RWE-like studies and showing senior leaders the type of impact that was being made using RWE. It was about identifying and sharing best practices throughout the organization. In this phase, the RWE group was leading many pilot programs to the point of being in pilot purgatory.
Today, there is increased discussion around talent and community development and the hiring of more data scientists who can push and elevate our thinking. There is more of a push to establish centralized or hybrid/hub-and-spoke RWE sharing models. There is also a focus on technology enhancements and ways to create centralized repositories and analytics platforms that enable the establishment of shared coding libraries. More importantly, organizations are looking to identify high value RWE use cases that will have meaningful impact that can drive the business.
In the future you will see a world that has novel partnerships and is focused on advanced RWE capabilities. That means applying advanced analytics to RWE generation to deliver impact at scale. Just like any other function, the RWE function needs to continue to evolve to be highly effective.
A: First, actively deploy strategies to elevate your understanding, accessibility and communication of RWE value drivers to the enterprise with high-value use cases. Second, establish agile operating models that drive adoption and integration of RWE across the pipeline while developing risk mitigation plans. Third, deploy rapid cost-effective data analytical platforms that can democratize the use of data and analytics at scale. Fourth, focus on developing and/or expanding robust partnership ecosystems. Finally, think about ways to shift the expanded use of advanced RWE capabilities and recruit high-performing diverse talent to achieve that success.
A: If you’re not thinking about the RWE function as a cross-sector partnership and ecosystem that involves everyone, you're doing yourself a disservice. Leveraging RWE no longer involves the biopharma life sciences sector operating in isolation. We have to be interconnected to the other sectors within the industry to really achieve the goals we need to in this space.
One of the great quotes I love is from Thomas Davenport – a great leader and thinker around big data and analytics – who once said that “Every company has big data in its future, and every company will be in the data business.” That's across industries, sectors, and functions. So you should be thinking about how you use data more strategically than we have in the past. While the biopharma industry has more progress to make, I'm hopeful that we can elevate our game and certainly be leaders in this space.
To learn how the life sciences industry is adopting more advanced analytics and RWD, download our 2021 Benchmark Report: Data Analytics and Machine Learning in Life Sciences.
If you would like to learn how Panalgo's IHD Analytics can support your RWE teams, reach out to email@example.com