AI in Pharma: From Molecule to Market with Siemens' Patrick Ansems

In this Tech & Drugs episode, I sit down with Patrick Ansems, globally responsible for life sciences strategy at Siemens across pharma and medical devices, to explore how AI, data, automation, and platforms are reshaping drug development.Recorded live in London at the Pistoia Alliance meeting 2026, this conversation looks at a central question for the industry: can pharma make drug development learn faster than it forgets?Patrick has worked across science, software, R&D, lab informatics, and manufacturing, with experience at PerkinElmer Informatics, Tetrascience, Dotmatics, and now Siemens. In this episode, we discuss why AI is forcing leaders to think differently, why FAIR data has new urgency, and why pharma still depends so much on Excel, PowerPoint, documents, and institutional memory.We also explore the “messy middle” of tech transfer, the role of context in scientific data, and the idea of “pharma in the loop” — connecting discovery, development, and manufacturing into a more integrated learning system from molecule to market.Key themes discussed:- Why AI is changing leadership in pharma and life sciences- FAIR data, AI-ready data, and why data context matters- The gap between scientific progress and slow decision-making- Why pharma workflows still rely on Excel, PowerPoint, Word, and institutional memory- Tech transfer as the messy middle between R&D and manufacturing- How to reduce corporate amnesia in scientific organizations- The role of Dotmatics within Siemens- Scientific intelligence platforms and the future of connected lab data- Lab automation, manufacturing, simulation, and AI-enabled experimentation- Why AI is not a silver bullet for messy infrastructure- “Pharma in the loop” from molecule to marketWhy this matters:AI will only create real impact in pharma and biotech if it is connected to high-quality data, scientific context, robust workflows, and the realities of development and manufacturing. For R&D, digital, data, technology, and manufacturing leaders, the challenge is no longer just adopting AI tools. It is building systems that can learn across the full drug development lifecycle.Guest information:Guest: Patrick AnsemsRole: Global Head of Life Sciences at Siemens Digital Industries SoftwareCompany: SiemensLinkedIn: https://www.linkedin.com/in/patrickansems/Company website: https://www.siemens.com/en-us/company/about/businesses/digital-industries/About the podcast:Tech & Drugs explores how data, AI, and technology are changing pharma, biotech, and drug R&D. Hosted by Thibault Geoui, the podcast brings together leaders, scientists, technologists, and builders working at the interface of science and technology.If you enjoyed this conversation, subscribe to Tech & Drugs for more discussions on AI, data, and the future of pharma and biotech.#AIinPharma #DrugDevelopment #LifeSciences #PharmaR&D #TechAndDrugs