A US Food and Drug Administration (FDA) advisory panel has rejected Pfizer’s bid to expand the use of its breast cancer drug, Talzenna (talazoparib). The panel voted against approving the medication for use in patients with a type of breast cancer known as hormone receptor-positive (HR-positive) metastatic breast cancer. The decision was based on concerns over the drug’s efficacy and safety in this patient population.
Talzenna is currently approved for use in patients with germline BRCA1/2-mutated, HER2-negative locally advanced or metastatic breast cancer. Pfizer had sought to expand the drug’s label to include HR-positive metastatic breast cancer, but the FDA panel was not convinced by the available data.
The panel’s decision was influenced by the results of the EMBRACA trial, which showed that Talzenna improved progression-free survival (PFS) compared to chemotherapy in patients with HR-positive metastatic breast cancer. However, the panel noted that the overall survival (OS) benefit was not significant, and that the drug’s safety profile was a concern.
Meanwhile, the use of artificial intelligence (AI) is being explored to enhance diversity in clinical trials. The lack of diversity in clinical trials is a significant issue, as it can limit the generalizability of trial results to diverse patient populations. AI can help identify potential trial participants from underrepresented groups and improve trial design to better reflect real-world patient populations.
The use of AI in clinical trials can also help to identify biases in trial data and improve the accuracy of trial results. Additionally, AI can facilitate the analysis of large datasets, including electronic health records (EHRs) and genomic data, to better understand disease mechanisms and identify potential therapeutic targets.
The rejection of Pfizer’s bid to expand Talzenna’s use highlights the challenges faced by pharmaceutical companies in developing effective treatments for diverse patient populations. The use of AI in clinical trials has the potential to improve the diversity and representativeness of trial participants, which could ultimately lead to more effective treatments for a wider range of patients. As the FDA and pharmaceutical companies continue to explore the use of AI in clinical trials, it is likely that we will see more diverse and representative trial populations, leading to better outcomes for patients with cancer and other diseases.
In conclusion, the FDA panel’s decision to reject Pfizer’s bid to expand Talzenna’s use serves as a reminder of the importance of diversity in clinical trials and the need for more effective treatments for diverse patient populations. The use of AI in clinical trials has the potential to address these challenges and improve patient outcomes.