A Roadmap to Real-World Data in Drug Discovery
By Allison Proffitt
August 23, 2022 | Victoria Gamerman’s love of analytics and math came from her grandmother—the first mathematician she knew. And in her nearly decade at Boehringer Ingelheim, she’s been putting that love to use as the Global
Head of Data Governance and Insights and, earlier, head of health informatics and analytics.
In the latest episode of Bio-IT World’s Trends from the Trenches podcast, host Stan Gloss, founder of BioTeam, talks with Gamerman about real world data, why it’s important for drug discovery, and the shifts happening around how
we think about data.
“There has been an evolution in how regulators like the FDA have taken to this kind of data,” Gamerman says. “Historically what I have seen and observed in terms of industry trends and trends from regulators is… a culture
of data collected for a very specific purpose. Therefore, the design of a clinical trial is very specific to address the scientific question at hand.” She describes trials designed very simply with just two cohorts, though the model leads
to challenges in the generalizability of the results.
Now Gamerman is noticing converging capabilities as we think more about precision and public health data, as our computing power expands, and as our ability to connect and share data improves. Together, these improved capabilities have, “in
my observation, been a big catalyst in being able to evolve the thinking of the real impact that real world data can have,” she says.
This great promise and opportunity, though, is not without challenges.
Gamerman notes that real-world data are collected within the context of real patients, and those patients can be dispersed internationally, experiencing healthcare very differently based on best practices and guidelines in each country. Real-world
data are also collected, stored, labeled, and organized differently by each organization. Thankfully, she notes, in recent years common data models—like OMOP—have emerged to help users understand how to compare and integrate data.
But that very challenge also reveals much useful information about the actual patient journey—how healthcare systems treat patients and diseases—and it helps us think in a more clearly patient-centric, person-focused way. A patient’s
real-world data, genomic data, and data from a clinical trial he or she might participate in represents a much fuller picture of health than any part alone.
“The trifecta of information that ultimately comes out of those data sources is what will give us the huge opportunity to better understand and create really powerful medicines for future generations,” Gamerman says.
For pharma companies just starting to add real-world data to their datasets, Gamerman suggests starting small—just one data source—and investing in bringing it in-house, finding a place to stage it, and bringing in subject matter experts
to explore and understand the dataset. Then, she says, researchers can begin asking appropriate scientific questions of the data.
“When we start with that scientific question, and combine it with a well-understood data source, that’s really when you’re able to harness the power of that single data source,” she says. “In my experience, where organizations
are really currently excelling is in the deeper understanding of a single data source.”
Starting with a single data source has additional advantages, Gamerman points out. Data governance questions can be addressed very thoughtfully: Where are the data housed? How findable is it and to whom? Which data products should interact and how
can we ensure that interoperability? And the teams working with the data can proceed in an orderly way as well, she adds, asking the right questions of the data and thoroughly exploring what is available.
“The part that I think is most impactful is the people, the culture, the change management and the opportunity that can bring to have successful adoption of our ability to explore and potentially—in appropriate situations—even integrate
insights from real-world data into some clinical drug development that is happening.”
Trends from the Trenches Podcast
Bio-IT World’s Trends from the Trenches podcast delivers your insider’s look at the science, technology, and executive trends driving the life sciences through conversations with industry leaders. As host, BioTeam co-founder Stan Gloss brings years of industry experience in science, data, and technology to conversations exploring what is driving data and discovery, and what’s
Catch up on earlier episodes on NIH’s Strategic Plan for Data Science, building AI/ML models for drug discovery, the evolution of supercomputing, digitization vs. digital transformation at Alnylam, AWS’s advice on digital transformation, NCI’s Commons of Commons approach to data management, and George Church on the value of neurodiversity. If you are enjoying the Trends from the Trenches podcast, please subscribe and rate us on iTunes, Spotify, or your preferred podcast player.