04 Sep A Perspective on Possible Applications of Artificial Intelligence to the Clinical Trial Workforce

The Association of Clinical Research Professionals

Clinical trials provide the scientific foundation for justifying the safety and efficacy of drugs, biologics, and devices—but are laborious, expensive, and risky. Only 10% of drugs entering clinical trials receive U.S. Food and Drug Administration (FDA) approval, while common reasons for trial failure include poor patient selection, recruitment challenges, and complex study designs.{1} The pharmaceutical industry has begun leveraging artificial intelligence (AI) to streamline numerous aspects of drug development from identification of novel drug targets to clinical trial design.{2} Moreover, AI is being leveraged to predict clinical parameters ranging from disease onset to mortality, drug-target connections, and drug repositioning suggestions.

In response, the FDA is devising an ongoing regulatory framework that will consider feedback from various stakeholders within drug development to spur innovation, while promoting patient safety.{3} The clinical research professionals working behind the scenes play a vital role in the drug development process, yet face administrative burden, burnout, and high turnover rates that all adversely impact clinical trial quality and the safety of new therapies.{4}  For instance, a little more than half of the U.S. clinical trial workforce reported burnout since the 2020 COVID-19 pandemic.{4} Read more…