The FDA seeks to harness artificial intelligence (AI) to streamline drug development and the approval process. With a new program coming out of the Oncology Center of Excellence (OCE), the Information Exchange and Data Transformation (INFORMED) initiative were designed to tap into the power of big data and advanced analytics with the hopes of improving disease outcomes. Recently INFORMED expanded its focus with the U.S. White House’ American AI Initiative to drive innovation in agile development and advanced analytics.
BioWorld interviewed Sean Khozin, associate director for oncology regulatory science on the topic of AI. TrialSite News offers a summary of relevant points. Follow the link to the source below as well.
Key Summary Points:
- The FDA is experimenting with several advanced analytical and predictive machine learning methods that can potentially streamline the drug review process. Presently due to the significant requirements of validation, review of new technical capabilities and skilled human capital the FDA reports AI doesn’t play a substantial role in the review process.
- In regards to addressing industry sponsor use of AI the FDA applies risk-based approaches to the clearance of AI-based platforms. The FDA recently developed a framework for the use of AI-based applications
- FDA’s INFORMED Program is conducting foundational research on the use of AI for advancing clinical development programs supporting product development in areas of high unmet need. . .
- A big challenge is that AI requires hard-to-find specialized expertise (human capital) that should be incorporated into clinical development teams as multidisciplinary units; validation of AI algorithms requires new methods and standards that are not yet fully established meaning we have a ways to go!