DPHARM’s “How Pharma is Shifting Operating Models for More Efficient Clinical Trials” session
Sometimes, the innovation in things is to just stop and simplify.
DPHARM 2024 carried on with a leadership panel that revolved around “How Pharma is Shifting Operating Models for More Efficient Clinical Trials.” Moderated by Bari Kowal, SVP, development operations, portfolio management & biostatistics data management at Regeneron Pharmaceuticals Inc., she was joined by Deirdre BeVard, SVP, R&D strategic operation at CSL Behring; Candice Fitzgerald, MMedSc, head of CD&O regions at Boehringer Ingelheim; Angela DeLuca, MBA, PMP associate VP, head of global study operations at Amgen; and Staci Hargraves, MBA, VP, innovative health, engagement & advocacy at Johnson & Johnson Innovative Medicine, who expressed that the duty that operating models have—which is to tackle the complexities of science, technology, and regulatory requirements—couldn’t be any more essential.
It starts with a very popular term, artificial intelligence (AI). Kowal posed the question of how the panelists were incorporating AI into both their models and their day-to-day operations in order to create efficiency.
“I think it’s the beginning of the journey—it’s really an exploratory journey right now to test and pilot things that we can do. But to me, it’s about the understanding of what’re capabilities that it brings us, and one of the things I think that is a really big challenge is determining who owns the data within the organization, who is leading this very exciting way forward,” said Fitzgerald.
Bevard offered an edit to the original question—as harnessing this AI is already in the works, it’s now a matter of successfully employing it.
“We’re not waiting to apply AI. It’s being applied, especially in our research and early development areas,” she added. “But within an operational aspect is, how could we use the data in the best way possible to move the process forward?”
And there is certainly a distinction when it comes to automation versus AI, versus other types of technology. Hargraves explained that J&J is utilizing AI across various aspects of its drug development business. “If you look at it in a true operations space, I think where we often see the challenge is just, how do you take the data operationalize into tools and techniques that can get across the clinical trial process. One of the things that we’ve done recently is really looking at the diversity space, and we’re using AI to look at potential site footprints … it was tremendous. It was very helpful in terms of locating the opportunity for the clinical trial context. It’s great to have the data and the tools to identify the opportunity, but we’re actually in need of the recruitment of the application on the ground in the country. How do we operationalize that if we don’t have the infrastructure to enable it? So it’s forcing us to look at things differently.”
Pulling data scientists into the fold
Amgen is conscientious of the various sources of data, and the challenge lies in translating all of this information. DeLuca expressed that people need to not only understand the data itself, but how to use and interpret it in a way that is digestible to teams.
When it comes to revolutionizing biotech and pharma by pulling data scientists into the mix, it is certainly not a simple task, but having the right purpose could help.
“They know how to do a lot of things, probably within any industry, and they want to apply in a way where they know you’re improving lives, and that has tremendous power,” BeVard added. The work following these efforts lies in creating a career path for these individuals so that they don’t “stall out.”
Engaging the workforce from a diversity perspective
Hargraves pointed out that when it comes to DE&I, just because a company has the ideas and strategy behind a concept doesn’t necessarily mean people will have up to a clinical trial.
“I think we really need to double down and think about, how do we engage communities differently? How do we shape our operations such that we do community-based care, reaching out to trials at the local level that enable patients who don’t have access to a site to be able to come into a conceptualized trial model. All of these things have to make a difference in how we enroll diversification. It’s great to see across the industry, but I think as you think about recruiting patients, if you think about globalization of diversity, it does translate differently outside the US. Diversity and race and ethnicity go beyond that—it’s about age, it’s about disability, it’s about the LGBTQ community. There are tons of things in this diversity space we aim to do.”
Reference
Kowal B, BeVard D, Fitzgerald C, DeLuca A, Hargraves S. How Pharma is Shifting Operating Models for More Efficient Clinical Trials. September 18, 2024. DPHARM 2024. Philadelphia.