The AI in Business Podcast Reducing R&D Cycle Time in Pharma Without Increasing Regulatory Risk - with Vaithi Bharath of Bayer
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Jan 7, 2026 In this discussion, Vaithi Bharath, Associate Director of Data Science & AI Solutions at Bayer, shares insights on streamlining clinical R&D processes in the pharmaceutical industry. He highlights how fragmented systems cause delays that impact timelines, reveals the complexities of regulatory validation, and introduces AI-guided workflows to improve compliance. Vaithi discusses the benefits of reusable macros and the advantages of building workflow layers over existing systems, all aimed at accelerating drug development while ensuring regulatory safeguards are met.
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Delays Stem From Fragmented Workflows
- Clinical R&D stalls mostly from fragmented systems and handoffs, not model quality.
- Multiple manual transfers and format conversions multiply delays across teams and vendors.
Six-Month Manual Zip File Workaround
- A vendor integration underperformed so teams used zip files and manual downloads for six to eight months.
- That workaround added days of human handoffs and heavy validation overhead to simple data transfers.
Validation Is Much Harder Than Testing
- Validation in GxP contexts asserts what must and must not happen, which is stricter than normal testing.
- That rigidity makes even small changes trigger lengthy documentation and retesting cycles.