Director – Quantitative Pharmacology and Pharmacometrics – Oncology

Director – Quantitative Pharmacology and Pharmacometrics – Oncology

Requirements

• Ph.D., with at least seven years of pharmaceutical drug development experience relating to: systems biology, PKPD, pharmacometrics, mathematics, chemical/biomedical engineering or related field.
• Masters or PharmD, with at least nine years of experience, where ‘experience’ means having a record of increasing responsibility and independence in a similar role in pharmaceutical drug development.
• Experience in developing mechanistic PK-PD models and QSP models for decision making in early and/or late-stage clinical development.
• Skills in experimental design, mathematical problem solving, critical data analysis/interpretation, and statistics.
• Experience with modeling and simulation packages or programming languages (e.g., MATLAB, R, SimBiology, C/C++).
• Professional working proficiency in written and verbal communication.
• Experience in IND, NDA and other submissions to global regulatory agencies.

Responsibilities

• Serving as a QSP expert for QP2 -IO for developing and executing model-based analyses including QSP models and mechanistic PK/PD models into programs thereby strengthening our quantitative capabilities on a continuous basis in decision making and driving pipeline impact.
• Assisting asset development teams in bringing forward combination drug approaches by leveraging QSP models to design and prioritize combination clinical trials.
• Broad understanding of population pharmacokinetic models and exposure-response models for application in clinical development.
• Work in close collaboration with biologists, clinicians, clinical pharmacologists, pharmacometricians and other line functions to improve our understanding of disease mechanisms and modalities.
• Framing critical questions and strategy for optimizing model-based analyses on programs.
• Maintaining a comprehensive understanding of global regulatory expectations for small molecules and biologics (monoclonal antibodies, antibody drug conjugates, T-cell engagers, bispecifics) in Oncology, authoring regulatory documents (investigational new drugs/INDs, clinical study reports (CSRs), clinical trial applications (CTDs)), and representing QP2-IO at regulatory meetings.

Preferred Qualifications

• Experience with mechanistic modeling for antibody drug conjugates (ADCs) and/ or T-cell engagers will be preferred.
• Familiarity with R NONMEM, WINNONLIN or other similar programming language.