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Head of Toxicology Innovation

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Sanofi
Full Time position
Listed on 2026-07-23
Job specializations:
  • Research/Development
    Data Scientist
  • IT/Tech
    AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 232500 - 335833 USD Yearly USD 232500.00 335833.00 YEAR
Job Description & How to Apply Below

Head of Toxicology Innovation —

Location:

Cambridge, MA

Overview & Mission

As 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, integrating artificial intelligence, machine learning, and advanced in vitro technologies into toxicology practice to reshape 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. You will report to the Global Head of Preclinical Safety and shape the future of toxicology at one of the world's leading biopharmaceutical companies.

Main Responsibilities
  • Strategic Innovation Leadership
    • Define and champion the long‑term vision and roadmap for toxicology innovation, aligned with Sanofi’s broader R&D digital transformation strategy.
    • Identify, evaluate, and prioritize emerging technologies, methodologies, and scientific advances 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.
    • 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.
    • Build out computational platforms, predictive modeling pipelines, and data science capabilities to support Global Preclinical Safety.
    • Establish best practices and governance frameworks for the responsible use of AI/ML tools in regulatory‑relevant safety assessment.
    • Integrate predictive models into early drug discovery workflows to enable proactive safety‑by‑design decision‑making.
  • Investigative Toxicology & Novel In Vitro Model Development
    • Direct scientific strategy and operations of laboratories in France and the United States, ensuring high‑quality mechanistic insights that inform drug development decisions.
    • Champion the development and qualification of novel in vitro models—organoids, microphysiological systems (MPS/organ‑on‑chip), and advanced cell culture platforms—to investigate mechanisms of toxicity and human relevance.
    • Translate mechanistic findings into actionable safety strategies to support candidate progression, risk mitigation, and regulatory submissions.
    • Maintain scientific rigor, quality, and compliance across all sites.
  • Ways of Working & Operational Transformation
    • Drive cultural and operational transformation within the toxicology function, embedding innovation, agility, and data‑driven decision making.
    • Develop and implement frameworks for knowledge management, data sharing, and cross‑site scientific collaboration.
    • Streamline and modernize toxicology workflows through automation, digitization, and fit‑for‑purpose technologies.
    • Benchmark Sanofi’s toxicology innovation capabilities against industry peers and academic leaders.
  • Regulatory Strategy & External Engagement
    • Engage proactively with regulatory agencies (FDA, EMA, and others) to advance acceptance of novel methodologies and computational approaches.
    • Contribute to regulatory submissions, scientific briefing documents, and responses to agency queries.
    • Build and maintain strategic partnerships with academic institutions, technology companies, and industry consortia.
  • Leadership & Management
    • Provide direct leadership, mentorship, and performance management to a global team of scientists, computational toxicologists, and digital specialists.
    • Build and sustain a high‑performing, inclusive, and diverse team culture that encourages scientific…
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