AI is transforming clinical research by enhancing data analytics, streamlining documentation processes, and improving patient matching for clinical trials. For instance, AI-driven analytics help researchers sift through large datasets efficiently, uncovering insights that might otherwise be overlooked. Additionally, AI tools reduce the administrative burden on healthcare professionals by automating documentation and charting tasks.

The FDA is actively engaging with AI's potential in healthcare by publishing discussion papers that outline current and future applications of AI in drug development. They emphasize a risk-based approach that focuses on accountability and transparency, ensuring that AI technologies are used responsibly while fostering innovation in the industry.

Digital twins are virtual replicas of individual patients created using their medical history and ongoing health data. They allow researchers to predict treatment efficacy and simulate safety outcomes for specific patients. This approach supports personalized medicine by tailoring therapies to individual characteristics, ultimately enhancing treatment strategies and minimizing risks.