Full-time – Northeast
Position Overview
The Director of QSP will provide scientific leadership for mechanistic modeling strategies supporting drug discovery, translational research, and clinical development. The role integrates biological knowledge with mathematical and computational methods to inform candidate selection, first-in-human translation, dose selection, patient population strategy, and combination approaches.
Key Responsibilities
- Build and apply mechanistic QSP models to characterize disease biology, pathway dynamics, drug effects, and treatment response.
- Establish QSP and model-informed drug development strategies for preclinical and early clinical programs.
- Perform quantitative simulations to guide candidate selection, first-in-human dosing, efficacy and safety evaluation, and clinical development decisions.
- Expand and refine modeling platforms that integrate pharmacology, biological pathways, disease mechanisms, and drug-target interactions.
- Leverage mathematical, computational, and statistical techniques to interpret complex biological and pharmacological data.
- Partner with discovery, translational, and clinical teams to incorporate QSP insights into program strategy and decision-making.
- Advance modeling methodologies, tools, and scientific applications that strengthen quantitative approaches across development programs.
Essential Qualifications
- Education: Ph.D., M.D./Ph.D., or Pharm.D. in Bioengineering, Systems Biology, Applied Mathematics, Computational Biology, Pharmacometrics, Chemical Engineering, Pharmaceutical Sciences, or a related quantitative discipline.
- QSP expertise: Deep knowledge of quantitative systems pharmacology, mechanistic modeling, systems biology, and translational science.
- Mathematical modeling: Strong foundation in ODEs, PDEs, numerical methods, parameter estimation, and optimization.
- Drug development experience: Demonstrated application of QSP approaches within drug discovery and/or clinical development programs.
- Scientific knowledge: Strong understanding of pharmacology, physiology, immunology, molecular biology, and disease mechanisms.
- Translational capability: Ability to rapidly understand new areas of biology and translate complex scientific data into mechanistically sound quantitative models.
