4 Areas of Interest for Artificial Intelligence in Clinical Research

In recent years, the artificial intelligence (AI)-hype train has picked up steam. Its promise has caught the attention of countless industries, and it was only a matter of time until clinical research jumped on board.

The most challenging part of seamlessly integrating AI into clinical research is that it must meet stringent regulatory guidelines. There are still unknowns surrounding the promise of AI, creating a great amount of risk when integrated into an industry with the goal of improving the lives of patients—real human-beings.

While there are certainly obstacles that need to be overcome, AI has the potential to address age-old challenges in clinical research including long timelines, insufficient data, inaccurate study models, and more. In this slideshow, Steve Young, chief science officer, CluePoints; Diane Lacroix, vice president, clinical data management, eClinical Solutions; Niven Narain, PhD, president, CEO, BPGBio; and Sonia Lwoff, director, clinical operations, Rho, each share an area of clinical research in which they think AI can be beneficial.

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