Head of Toxicology Innovation
Listed on 2026-05-25
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IT/Tech
AI Engineer, Data Scientist
Job title:
Head of Toxicology Innovation
Location:
Cambridge, MA
Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions.
Position Overview & MissionAs Head of Toxicology Innovation (Digital and Investigative Application), you will lead a transformative global function that sits at the intersection of cutting‑edge science, digital technology, and patient safety. This senior leadership role is responsible for defining and executing the strategic vision for toxicology innovation across Sanofi's Global Preclinical Safety organization. You will drive the integration of artificial intelligence, machine learning, and advanced in vitro technologies into toxicology practice — fundamentally reshaping how we predict, investigate, and understand safety liabilities in drug development.
With direct oversight of laboratory operations in France and the United States, and digital capabilities in Germany, you will lead a truly global, multidisciplinary team united by a shared commitment to scientific excellence and patient safety.
Reporting to the Global Head of Preclinical Safety, this role offers a rare opportunity to shape the future of toxicology at one of the world's leading biopharmaceutical companies.
About SanofiWe’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.
Main Responsibilities- Define and champion the long-term vision and roadmap for toxicology innovation, aligning with Sanofi's broader R&D digital transformation strategy and preclinical safety objectives
- Identify, evaluate, and prioritize emerging technologies, methodologies, and scientific advances with the objective to enhance safety assessment and reduce drug attrition
- Serve as the organizational authority and thought leader on the application of new approach methodologies (NAMs), digital tools, and investigative science in toxicology
- Represent Sanofi in external scientific forums, regulatory discussions, industry consortia, and academic partnerships to advance the field and position Sanofi as an innovation leader in toxicology
- Lead the development, validation, and deployment of AI and machine learning models for the prediction of safety liabilities, including target organ toxicity, genotoxicity, cardiotoxicity, and other key endpoints
- Drive the build‑out of computational platforms, predictive modeling pipelines, and data science capabilities in support of Global Preclinical Safety
- Establish best practices and governance frameworks for the responsible use of AI/ML tools in regulatory-relevant safety assessment
- Drive integration of predictive models into early drug discovery workflows to enable proactive safety-by-design decision-making
- Direct the scientific strategy and operations of laboratories in France and the United States, ensuring delivery of high-quality mechanistic insights that inform drug development decisions
- Champion the development and qualification of novel in vitro models — including organoids, microphysiological systems (MPS/organ‑on‑chip), and advanced cell culture platforms — to investigate mechanisms of toxicity and understand human relevance
- Oversee the translation of mechanistic findings into actionable safety strategies, supporting candidate progression, risk mitigation, and regulatory submissions
- Ensure laboratory operations meet the highest standards of scientific rigor, quality, and compliance across all sites
- Drive cultural and operational transformation within the toxicology function, embedding innovation, agility, and data‑driven decision making as core ways of working
- Develop and implement frameworks for knowledge management, data sharing, and…
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