Drug Digest: How Advanced Analytics Partnerships Enhance the Biopharma Value Chain

In a special combined episode of BioPharm and PharmTech Drug Digest, Matt Truppo, global head of Computational and AI Strategy for R&D at Sanofi, Brian Drapeau, founder and principal consultant of GxP Frame, and Richard Jaenisch, senior director of Education, Outreach, and Digital Experience at Open Biopharma Research and Training Institute, discuss artificial intelligence (AI) integration across drug discovery, biomanufacturing, supply chain operations, and workforce development and how strategic partnerships play a role.

Truppo describes AI's primary value as connecting signals across previously siloed data types, including molecular structure, biological assay results, patient demographics, and clinical site performance, to improve scientific decision quality rather than generate autonomous answers. At Sanofi, for example, disease-specific target identification engines integrate genetics, proteomics, transcriptomics, and single-cell data to help researchers determine target druggability, tissue expression, and optimal therapeutic modality, he explains.

How should biopharma companies govern AI tools to maintain data integrity and regulatory compliance?

On manufacturing and supply chain, Drapeau emphasizes that the most valuable AI applications are not headline-grabbing but operational, such as deviation management, batch record review, predictive maintenance, and supply and demand forecasting. In cell and gene therapy (CGT), specifically, he notes that supply chain is patient-specific, making chain of identity and chain of custody the true measures of AI's value. He also notes that no single manufacturer owns the full CGT supply chain, making cross-company partnerships essential.

Drapeau adds that effective partnerships between biopharma and AI tech and/or advanced analytics companies require a partner capable of integrating across multiple domains while maintaining strict data governance. "Completion is not competency," he stresses, cautioning against operators who can execute AI-assisted tasks but lack the independent judgment to troubleshoot or critically evaluate model outputs.

All three experts emphasize that human oversight must be structurally embedded in AI workflows, not applied as an afterthought. Jaenisch states that explainability is non-negotiable, cautioning that AI outputs used in regulated environments must be traceable and defensible to inspectors.

“There are [many] pieces that an explainable AI system is able to retrieve and provide with every output, and if you do not have that, then you are probably not going to have a good time when an audit comes,” he explains.

Truppo adds that data governance, source traceability, and clearly stated model uncertainty are prerequisites for trustworthy AI integration across biopharma R&D and manufacturing operations when dealing with a strategic partner.

Interview featuring

Matt Truppo, Global Head of Computational & AI Strategy, R&D, Sanofi

As the global head of Computational and AI Strategy at Sanofi, Dr Truppo oversees platform capabilities across all therapeutic areas and modalities to advance the company’s drug discovery ambitions. He focuses on embedding AI and predictive technologies throughout R&D to accelerate timelines and enable the development of first-in-class therapies. Prior to Sanofi, he led Protein Therapeutics API Development and Biologics Discovery at Johnson & Johnson and spent more than a decade at Merck working across both small- and large-molecule discovery and development. He holds a PhD in Chemistry from the University of Manchester and undergraduate degrees in Chemical Engineering and Engineering Biology from Princeton University. Over a 20+ year career, Truppo has contributed to bringing 13 medicines to market and advanced many more into the clinic, a quest driven by his commitment to improve global health through innovative science.

Richard Jaenisch, Senior Director of Education, Outreach, and Digital Experience, Open Biopharma Research and Training Institute

Jaenisch has spent the past 15 years in patient advocacy since he began and fought off end stage liver disease and more than 15 years in STEM education, marketing, and consulting. Among his duties at Open Biopharma, he is leading several data projects regarding generative AI integration and exploring generative AI in biomanufacturing training. At Prompting Integration and Consulting LLC, he develops training courses and works alongside his brother, a seasoned AI/ML engineer to develop bespoke generative AI integrations for business in life sciences and healthcare and deliver educational programming on generative AI.

Brian Drapeau, Founder and Principal Consultant, GxP Frame

A private consultant to some of the largest biotech companies in the industry, Drapeau brings more than 5 years of experience in workforce development and training across the biotechnology and pharmaceutical sectors. His expertise includes new hire training, instructional program development, contract development and manufacturing organization (CDMO) training requirements, and high-volume ramp-ups. Drapeau also authors The GxP Frame, a newsletter covering FDA enforcement trends, CDMO training failures, and pharmaceutical manufacturing operations.

Sponsors

This episode of Drug Digest is sponsored by:

• Cygnus Technologies
• FUJIFILM Biotechnologies
• Veltek Associates

About BioPharm Drug Digest

Drug Digest is a video series with the BioPharm International® editors, who conduct in-depth interviews with industry experts around the latest research and pipeline developments as well as emerging opportunities, obstacles, and advances in the biopharmaceutical industry related to the manufacturing, distribution, supply, and regulatory compliance of bio/pharmaceutical products.

Upcoming episodes

August 2026: Regulatory and Quality Updates in Biologic Drug Development

September 2026: Targeting the Undruggable

October/November 2026: The Future of Biopharma Operations and Supply Chains

*No December 2026 episode