A US Food and Drug Administration (FDA) advisory panel has rejected Pfizer’s bid to expand the use of its drug Talzenna (talazoparib) to treat metastatic prostate cancer. The panel’s decision was based on the results of a clinical trial that failed to show a significant improvement in overall survival for patients taking Talzenna compared to those receiving standard therapy.
Talzenna is a poly (ADP-ribose) polymerase (PARP) inhibitor that is currently approved for the treatment of breast cancer in patients with a specific genetic mutation. Pfizer had hoped to expand the label to include prostate cancer, but the FDA panel’s decision suggests that the company will need to provide additional data to support this use.
The rejection comes as the use of artificial intelligence (AI) in clinical trials is gaining attention, particularly in the area of diversity. Clinical trials have traditionally been criticized for lacking diversity, with many studies enrolling predominantly white patients. AI has the potential to help improve diversity in clinical trials by identifying and recruiting patients from underrepresented groups.
In the case of the Talzenna trial, the lack of diversity in the patient population may have contributed to the panel’s decision. The trial enrolled mostly white patients, which may not accurately reflect the broader population of patients with prostate cancer. The use of AI could help to identify and recruit a more diverse group of patients for future trials, which could provide more accurate and representative results.
Despite the setback, Pfizer is likely to continue exploring the use of Talzenna in prostate cancer, potentially using AI to improve the diversity of future clinical trials. The company may also consider conducting additional studies to address the concerns raised by the FDA panel. The use of AI in clinical trials has the potential to revolutionize the way that new treatments are developed and tested, and it will be interesting to see how this technology is used in the development of future cancer therapies.
The FDA panel’s decision highlights the need for more diverse and representative clinical trials, and the potential role that AI can play in achieving this goal. As the use of AI in clinical trials continues to evolve, it is likely that we will see more diverse and representative patient populations, which could lead to more effective and targeted treatments for a range of diseases, including cancer.