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Global Head of Data Science and AI for Global Drug Development at Novartis, leading the strategic integration of AI to accelerate how we reimagine medicine for patients. Based in Basel, I focus on fundamentally changing the speed and precision of drug development—from candidate optimization and clinical trials through CMC to regulatory submission.

The opportunity is clear: AI can compress timelines at scale without compromising rigor. My focus is on building enterprise-grade capabilities in Digital Twins, Agentic Systems, and Decision Intelligence applied to one of the industry’s most innovative drug pipelines.

Professional Foundation & Impact

Prior to Novartis, I served as the Global Senior Director of AI/ML & Decision Sciences at GSK (2019–2026), where I built and scaled a distributed team of 40+ engineers. We pivoted from a centralized CoE to an embedded, forward-deployed model, delivering AI at the point of decision-making across a global network of 37 manufacturing sites.

My work is defined by bridging AI/ML and life sciences—a journey that began with a PhD from Cambridge in Machine Learning and Epigenomics and continued at Microsoft (2015–2019), where I led AI strategy for global health and life sciences organizations.

Core Technical Pillars:

  • Accelerating Drug Development: Deploying AI to optimize the end-to-end development value chain (Candidate → Trial → Submission).
  • Physical AI & Agentic Systems: Scaling autonomous agentic workflows and Vision Language Models (VLMs) for GxP environments.
  • AI Ops at Scale: Running unified AI operations for 300+ solutions and 400k+ industrialized models with full observability and governance.
  • Strategic Transformation: Driving the evolution from traditional BI to Conversational and Agentic Decision Intelligence.

Key Achievements

  • Value Realization: Delivered significant validated business value through AI-driven yield optimization and efficiency.
  • TwinOps Innovation: Pioneered GxP-compliant digital twins that achieved +20% yield and unlocked +1M vaccine doses.
  • Governance & Compliance: Established global AI Council frameworks ensuring EU AI Act and FDA compliance across 300+ AI solutions.
  • Pioneering R&D: Founded GSK’s first AI division for vaccines, deploying protein language models and BERT-based automation.

Education

Sander obtained his PhD from the University of Cambridge and EMBL-EBI, specializing in Big Data Biology. He is a Life Member of Clare Hall, Cambridge.

Selected Past Projects

AI-Enabled Digital Health with Novartis Foundation

A long-standing collaboration with the Novartis Foundation and Microsoft to develop AI tools for early leprosy detection.

Professional Interests

Global AI Strategy · Drug Development Acceleration · Forward Deployed AI Engineering · Physical AI & Robotics · Digital Twins · Multi-Agent Systems · AI Ops & Value Realization · GxP Compliance · Decision Sciences · Genomics & Computational Biology · Cloud-Native Architecture

About me

I am a Lead Data Scientist at Microsoft in the World-Wide Data Insights CTO office focusing on cloud solutions for the Internet-of-Things, Big Data, Deep Learning, and Machine Learning. I obtained my PhD at the University of Cambridge specialising in Big Data Biology while being based at the European Bioinformatics Institute (EBI) and the European Molecular Biology Laboratory (EMBL).

In my previous "academic life", I was working in Ewan Birney's research group. My main subject was understanding non-coding variation using genome-wide molecular assays, like FAIRE and CTCF, onto Human cell line populations. Another research interest was identification of whole-body phenotypes in Human MRI scans using Machine Learning techniques.

Furthermore, I'm the co-founder of Rijschoolvergelijker. The largest driving school comparison website in the Netherlands with European ambitions.

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