Study finds AI can improve efficiency in clinical trials for cancer treatments

A study by the Tufts Center for the Study of Drug Development indicates that artificial intelligence (AI) can enhance efficiencies in clinical trials for cancer treatments. The analysis suggests that AI can accelerate the clinical development of cancer drugs by approximately 10 weeks and reduce direct operating costs by up to $5.6 million in late-stage trials. The efficiencies are greater when a drug targets multiple tumors, with potential net benefits reaching $565 million for treatments with 50 active uses. The study utilized a clinical monitoring agent from Medable in a phase 2 and 3 oncology drug development program. Ken Getz, executive director of the Tufts center, noted that the deployment of AI led to reduced on-site visits and quicker enrollment. Medable officials predict that AI agents could become standard in clinical trials within three to five years, assisting in record-keeping and tracking trial population diversity. However, challenges remain, such as patient recruitment and consent, and human verification of AI work may offset some time savings.