On June 2, the FDA introduced Elsa, an AI-driven large language model aimed at expediting drug approvals by enhancing operational efficiency. FDA Commissioner Marty Makary announced that Elsa would assist in reading, writing, and summarizing, significantly shortening clinical protocol reviews and scientific evaluations. Despite its promise, concerns over the lack of transparency and accuracy in Elsa’s outputs have been raised by industry professionals. Critics highlight the risks associated with AI, including its potential to generate misleading information. Human reviewers are expected to verify AI-generated content, but studies suggest that human oversight alone may not ensure accuracy. As Elsa is integrated into FDA processes, questions persist about its role in regulatory decisions and safeguarding proprietary information. Experts advocate for clearer guidelines and benchmarks to evaluate Elsa’s performance effectively. This initiative reflects a broader trend of AI adoption across industries but emphasizes the need for cautious implementation.
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