health

Capgemini: Exploring the Impact of AI on Biopharma

Thorsten Rall, Global Industry Lead for Life Sciences at Capgemini, discusses AI’s role in improving candidate quality and reshaping scientific research

Capgemini: Exploring the Impact of AI on Biopharma

TL;DR

  • AI-driven platforms are expected to account for 60% of new molecular entities in the next decade, a significant increase from the current 12%.
  • AI's role has expanded from data analysis to defining experiments across the entire R&D lifecycle, including target identification and proposing experiments based on live results.
  • AI improves drug quality by enabling deeper optimization before clinical trials and allows for better assessment of drug candidates based on previous trial data.
  • Precision medicine is advanced by AI's ability to model disease biology and patient characteristics at a finer level, identifying specific patient subgroups for potential drug efficacy.
  • The tight coupling of AI with automated, data-rich wet labs creates closed-loop environments for real-time hypothesis generation, testing, and refinement.
  • AI is improving clinical trials through better patient recruitment, site operations, and trial design, with potential for AI-generated synthetic control arms.
  • Ensuring safety, trust, and explainability is paramount for AI adoption, particularly with AI agents that must justify their conclusions in a way human researchers can interrogate.