A Decade of AI in Drug Discovery - Where Are We Now?

The AI revolution in drug discovery has progressed from early theoretical promise to tangible real-world applications over the past decade. This evolution has seen significant advancements in computational methods, algorithm refinements, and integration with traditional drug development processes, leading to an increasingly complex landscape of opportunities and challenges.

This discussion will explore the current state of AI in drug discovery, examining breakthrough cases, persistent limitations, and the evolving integration of AI technologies across the pharmaceutical development pipeline. We will assess what has been achieved against initial expectations and outline realistic trajectories for the coming years.

Join us to discuss:

• How has the implementation of AI in drug discovery evolved from early applications to current integrated approaches?
• What evidence exists for AI's impact on reducing time-to-market, development costs, and success rates in pharmaceutical R&D?
• How might the intersection of AI with emerging technologies like quantum computing reshape drug discovery paradigms in the next five years?