Clinical Pharmacometrician

Position Summary

The Clinical Pharmacometrician will set and implement the quantitative strategy across a diverse portfolio of cell therapy products, translating advanced cellular kinetics and exposure–response modeling into dose optimization, patient selection, program decision and strategy.

You will ensure innovative model-informed drug development (MIDD) is implemented to support AstraZeneca's cell therapy pipeline, integrating innovative modeling with novel cell therapy biomarkers, translational endpoints, and clinical data. Working cross functionally and with external partners, you will build mechanistic and empirical models, advise trial design and dose selection.

Responsibilities

• Build MIDD across cell therapy portfolio.
• Partner with project teams (physicians, clinical pharmacology scientists and statisticians, etc.) to build population PK, PKPD, and exposure-response models to support design and interpretation of clinical studies, influence key decisions in research and development, and support regulatory submissions of cell therapy products.
• Develop mechanistic and empirical models, enabling clear decision making, optimized dosing regimen, and streamlined development paths.
• Ensure modeling strategies align with regulatory expectations (e.g., FDA MIDD), supporting submissions, dose justifications, and scientific advice.
• Monitor and adopt emerging methodologies (QSP for cell therapies, AI/ML for biomarker integration, MIDD regulatory pilots, etc.).
• Advance AstraZeneca's leadership through speaking, publications, and consortium participation in cell therapy modeling.

Education and Experience

• Minimum of a PhD in pharmacometrics, pharmacokinetics, biostatistics, or related field.
• Minimum of 0 – 3 Years of industry drug development experience in pharmacometrics supporting decision-making, dose selection, study design and regulatory interactions.
• Hands on experience and advanced proficiency in using pharmacometrics software including NONMEM, Phoenix/NLME, R, SAS, Python, MATLAB, etc.
• Be able to work in a matrix team environment and influence the team with a data-driven approach.
• Knowledge of global regulatory, compliance, processes, standards and issues specific to pharmacometrics.
• Ability to plan and implement pharmacometrics approaches (PopPK, PKPD, exposure–response, QSP, Bayesian/adaptive methods) that drive dose selection and enable go/no‑go decisions.
• Integration of quantitative pharmacology with innovative biomarkers, AI‑enabled analyses, novel endpoints, and adaptive trial design.

Preferred Experience

• Experience in application of AI and ML in pharmacometrics highly desirable.
• Pharmacometrics experience across cell therapy platforms (CAR T, TCR, autologous, allogeneic, in vivo, etc.) and disease areas (hematology, oncology, immunology, etc.) highly desirable.