Translational Pharmacometrician

We are an independent, international, human-scale pharmaceutical group, governed by a Foundation. We take pride in this distinctive model; and, above all, it allows us to fully serve our purpose: a commitment to therapeutic progress for the benefit of patients.

Already a world leader in cardiology, we have chosen to become a focused and innovative player in oncology by 2030, taking on hard-to-treat cancers and dedicating more than 70% of our R&D budget to that ambition. We pursue this in parallel with our generics business, helping to keep quality care accessible and affordable for all.

We are 22,000 passionate people from more than 50 nationalities, united by an entrepreneurial spirit. Every day, we move forward with and for our patients, and with and for our teams; driven by a desire to care, to dare, to grow, and to be truly useful to those who need us.

Come and experience our commitment and help bring it to life. #MovedByYou

www.servier.com

As a senior member of the Translational Pharmacometrics team, your mission will be to apply Model-Informed Drug Development (MIDD) methods to support the selection, preclinical development, and early clinical advancement of drug candidates.

You will collaborate closely with colleagues in Quantitative Pharmacology and across Translational Medicine to ensure pharmacometric insights are converted into actionable evidence. Your expertise will be instrumental in progressing programs across our Oncology and Neurology portfolios.

Main responsibilities:

• MIDD Strategy & Execution: Lead the development and execution of MIDD strategies in alignment with internal standards and global regulatory requirements. This includes overseeing the end-to-end process from strategic pharmacometric planning to the delivery of submission-ready modeling reports.
• Modeling & Simulation: Perform expert-level Modeling & Simulation (M&S) analyses to characterize drug properties and optimize dose selection. These analyses may include population pharmacokinetics and pharmacodynamics (popPK, PKPD), Physiologically Based Pharmacokinetics (PBPK), Quantitative Systems Pharmacology (QSP), disease progression modeling, etc.
• Advanced Methodologies: Propose and implement state-of-the-art MIDD methodologies such as AI/ML-enabled techniques to enhance predictive accuracy and decision-making efficiency.
• Internal Influence & Communication: Interpret pharmacometric outcomes for project teams and partners, providing the quantitative evidence needed to optimize preclinical/early clinical study designs and guide project strategies.
• Regulatory Interaction: Prepare pharmacometric components for global registration dossiers and provide technical support when responding to requests from health authorities.
• Cross-functional Contribution: Participate in to cross-functional initiatives and therapeutic area sub-groups, acting as a Subject Matter Expert (SME) to integrate translational pharmacometrics into the broader drug development ecosystem.
• Operational Oversight: Define and oversee outsourcing initiatives, managing relationships with external partners to ensure high-quality, timely deliverables.

Profile:

Educational & Professional Background:

• A Doctorate degree in pharmacometrics or other relevant quantitative fields, such as pharmaceutical sciences, systems pharmacology, engineering or mathematics applied to life sciences, etc.
• Professional experience in preclinical or clinical drug development in the pharmaceutical industry, regulatory agencies, or academia.

Hard Skills:

• Subject Matter Expertise:
  • Advanced pharmacometric modelling and simulation skills for empirical, compartmental, and mechanistic modelling approaches.
  • Experience in ML approaches with application to pharmacometrics is preferred.
• Specialized Software Knowledge:
  • Expert user of non-linear mixed effects (NLME) modelling tools including NONMEM and/or Monolix.
  • Proficiency in PBPK and/or QSP software is preferred (e.g. Simcyp, PKSim, MoBi, Jinko, SimBiology, etc.).
  • Competence in programming and data analysis languages (e.g. R, MATLAB, Python).
• Therapeutic Area & Modality Experience:
  • Familiarity with complex biologic modalities such as ADCs, BsAbs, cell engagers, ASOs, etc.
  • Experience in Oncology and/or Neurology is preferred.
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