AI Readiness Audit — Biotech

Where AI pays off in Biotech

• AI for drug discovery and lead optimization — protein structure prediction (AlphaFold-class models), generative chemistry, target identification, and lead optimization that compresses early-discovery timelines.
• AI for clinical trial design and operations — patient recruitment optimization, site selection ML, protocol design support, and trial-monitoring AI that compress the largest single cost line in R&D.
• Generative AI for regulatory and medical writing — IND, NDA, CSR, and protocol drafting copilots that compress the medical-writing burden without compromising the regulator-ready quality the documents require.
• AI for real-world evidence and post-market — RWE generation, post-market surveillance ML, and label-expansion analytics that lift the value of approved products beyond the original NDA.