Trained Workforce Drives Technology Advancement in Clinical Trials

“Digital technologies are one of the most promising tools we have for making healthcare more efficient and more patient-focused,” U.S. Food and Drug Administration (FDA) Commissioner Scott Gottlieb, MD, told attendees of a Bipartisan Policy Center conference in a speech he delivered late last month (January 28).

Specifically, Gottlieb cited new streams of real-world data gathered from electronic health records, lab tests, wearable devices, insurance claims, and social media. Each “can provide important evidence on product safety and effectiveness in settings or populations that may be very different than the information gleaned from registration trials used for approval,” he added.

“This isn’t an indictment of the randomized controlled trial,” Gottlieb said. Instead, “it’s a recognition that new approaches and new technologies can help expand the sources of evidence that we can use to make more reliable treatment decisions. And it’s a recognition that this evidence base can continue to build and improve throughout the therapeutic life of an FDA-approved drug or medical device.”

In many cases, these tools also help make prospective trials more efficient and more reflective of how care is delivered in the “real world,” Gottlieb added.

Transformational Technologies in Pharma: What’s Here and What’s Coming

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Lauding Gottlieb’s commitment to providing clinical trial practitioners with the best possible tools, ACRP Executive Director Jim Kremidas noted it is the people behind the scenes who ultimately determine clinical trial success. “Clearly, new tools and ideas are increasingly valuable as we work together to make trials safer and more efficient,” he said. “However, if we don’t provide adequate training and set meaningful standards to help define performance, even the best tools will remain underutilized.”

Meantime, the FDA just released its “2018 Drug Trials Snapshots Summary Report” highlighting 59 novel drugs, and the extent to which the safety and efficacy data is based on demographic factors. The data are designed in part to “promote dialogue” on the appropriate representation of different subgroups in clinical trials.

Author: Michael Causey