How can teams within biopharma ensure their real-world evidence (RWE) studies make the greatest impact internally, and reach their key stakeholders? By defining a strategy upfront, and determining the business case for the analysis, says Julie Schiffman, Senior Vice President of Scientific Engagement at Aetion.
Julie recently joined Aetion after a 17-year stint at Pfizer, bringing with her valuable experience on both the commercial and research and development (R&D) sides of the biopharma industry. Most recently, she led a 350-person data and analytics team as they ran analyses to drive Pfizer’s business—and drug portfolio—forward. Now, at Aetion, she is motivated by the powerful combination of data, analytics, technology, and scientific brainpower that culminate in RWE.
We sat down with Julie to discuss what she’s learned from her time working within and with biopharma, and how teams can leverage data and RWE to drive business impact and return on investment (ROI).
Responses have been edited for clarity and length.
Q: At Pfizer, you worked on both the R&D and commercial sides of the business. How did you come to the RWE space?
A: I have spent over a decade trying to improve overall R&D productivity within pharma, and trying to determine which levers we can pull to get medicines to patients in need faster and at a lower cost.
Pharma has made massive operational improvements in this area over time. Now we ask ourselves, how can we augment the clinical trial process to continue progress? How do we think differently about how we use data, translate it to evidence to supplement the clinical findings that we have, and support safety long-term?
With RWE, the combination of data, technology, and people who can bring those things together to draw insights is extremely unique—and a way to potentially solve the overall R&D productivity and affordability challenge. Using real-world evidence represents an opportunity to create a new paradigm for gathering evidence in complement to RCTs.
Q: How do you think about the role of analytics teams within pharma? How have you seen these teams evolve over your career, and where do you think these teams are going?
A: The most important thing for any data and analytics team is to understand the key strategic business questions and think about how data and technology can support answering or informing them. Over the past several years, the role of data and analytics teams has shifted to a position of leading the strategic discussions and partnering with commercial and scientific leaders more than we have in the past.
Because of the explosion of available data and advancements in technology, we’re now able to speed the time to insights and use data to inform clinical development and commercial strategies in ways that weren’t possible before.
Q: How can pharma leverage data to inform larger business strategy or drive business impact?
A: When designing an analysis, we can use real-world data and real-world evidence to define a strategy upfront: What is the data telling us? How do we analyze the data to answer our questions and hypotheses? And, perhaps most importantly, how do we take action and monitor impact over time? We can have all the data, technology, and insights in the world, but if it doesn’t actually inspire an action—whether it’s changing the way we communicate with physicians, our approach to patient education, or the formulary status of a product—the analysis becomes somewhat of a tree falling in the woods with no one to hear.
I'm trying to help our scientists think through not only the methodology and science, but also the resulting business action that we expect our partners to take after seeing the results. Are they going to use a different development program? Are they going to launch their product differently? Are they going to change their label? Are they going to go after another indication? The data, in and of itself, can’t inspire these next steps, we must define the action we want our stakeholder to take.
Q: How much of an analytics team’s energy do you think is spent pushing their work forward and making the business case, versus running analyses? Is it an even split?
A: My belief is always that more time should be spent framing the right strategic question. I've always encouraged colleagues to first ground themselves in the projected impact and business need we’re solving for, and then formulate the analytics, methodology, and data plans.
Before diving into any analysis, we should always ask three questions: What is the decision we’re trying to make, who is the sponsor or key stakeholder that cares about this work/decision, and do we have the unique skill set or capability to answer this question? If we can answer each of these questions, it’s much easier to formulate the right project. Appropriate business context allows an analyst to draw a straight line between the work and business impact, whether that’s improved market share, increased compliance, or faster, lower cost clinical trials.
Q: Given that enterprise RWE analytics represents a significant financial and time investment, can you speak how you can gain alignment across multiple budgets and functions to move forward with widespread adoption of RWE?
A: Sure, platforms are significant investments, but it just takes one success to get a return on investment (ROI)—one additional indication, one early product launch to get a jump on the competition, one external control arm that saves you from spending millions on the arm of a clinical trial.
After that, you have an ROI that has the potential to speak for itself 50-fold, in terms of the types of savings that you can derive or revenue that you can deliver. Many businesses are focused on how to improve top line growth or operational expenses, and real-world evidence, if used properly, offers you mechanisms to do both.
Q: What would be your top piece of advice for a growing analytics team? What strategies have you seen work around structuring teams and driving value from the team?
A: The most important thing for growing analytics teams is to maintain laser focus on the business priorities and ensure the integrity of the analytics. When you're growing in an organization, you can't compromise on the quality of what you're delivering, particularly in a nascent space.
Some level of prioritization is also important; while growing as a business and gaining experience, you need to look at your own operational data to support the resourcing decisions that you're making and the projects that you're committing to.
Not to be overlooked is the culture that you're establishing among your team. Analysts like to be a part of a community where their craft and science are respected. Creating a community where people have great pride in what they do and great support from one another is critical. Because when you're growing, you are going to experience growing pains. And you want to be in an environment where you feel supported and empowered to do your best work.
Q: What's your perspective on the future of RWE in health care? Where do you see it going? And where do you see it being most impactful?
A: I think the future of RWE is promising; making sure we find the right medicines for the right patients at the right time and at the right cost must be addressed as we combat global health care challenges.
There's an opportunity to incorporate RWE at every single step of the pharma value chain. The challenge is trying to figure out how to harness those capabilities in the safest and most productive way for patients.