Clinical trial sites, sponsors and contract research organizations (CROs) are keenly interested in ways to improve the design, operation and results of studies. A number of organizations are exploring artificial intelligence (AI), machine learning (ML), and other advanced technology, and how they can positively impact trials.

Outsourcing-Pharma (OSP) recently talked with Jennifer Bradford (JB) head of data science with Phastar a global CRO offering trial reporting, data management, data science and other services around the globe. She told us now AI and machine learning are making a difference in trials, and how such technologies change the future of clinical research.

OSP: What are some of the key ways in which AI and ML have been impacting the way clinical trials are run? 

JB: The most successful and documented uses of AI in clinical trials have been for target identification and drug repurposing, given the large volumes of structured data available in this area. ML-based predictive analytics can also be used in recruitment and retention activities, for example, identifying the right candidates at a faster rate, which can accelerate R&D timelines.

During a trial, applications of AI are also emerging from a clinical operations perspective; supporting data management teams to automatically detect erroneous data. For example, in risk-based management, going beyond a rule-based approach applied to the clinical and meta data to identify problematic sites or even patients based on patterns of behavior, identification of outliers etc.