Leveraging AI to turbocharging the lead-to-optimization cycle
06 May 2026
Lead Generation & Optimization
- How can we effectively integrate generative AI / customize AI workflow to shorten the "Design" phase of the DMTA cycle?
- What are the primary bottlenecks in moving from AI-predicted leads to experimental validated drug candidate, and how can we bridge this gap?
- What are currently available multi-objective optimization algorithms / approaches can simultaneously balance potency, selectivity, and ADMET properties to reduce late-stage failures?
- How do we address data scarcity and quality issues when apply AI for niche therapeutic targets?
- To what extent can AI-driven prediction replace traditional high-throughput screening as the primary driver of lead generation?
Industry Expert
