Reflection on Recent Guidance and Applications of Incorporating AI into Drug Development

Music City Center 

Artificial intelligence (AI) has demonstrated its potential in generating unique insights and substantially increasing productivity across different industries. Its usage in drug development and supporting regulatory decision-making also experience growth in recent years. In this talk, we review the recent released draft FDA guidance on leveraging AI in generating information or data to support regulatory decision-making regarding safety, effectiveness, or quality for drugs. Specifically, the guidance lays out a risk-based credibility assessment framework consisting seven steps with a focus on assessing the AI model risk, detailed plan to establish the credibility within the specific context of use. It also highlights the importance of maintaining the AI model relevant over time when new data becomes available. We then apply this framework to use cases of AI in drug development including the intended research questions, advantage of AI over traditional methodologies, fit-for-use data source of training, tuning, testing and performance assessment, factors contributing to the success and limitations.

artificial intelligence

guidance

use cases 

Biopharmaceutical Section