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# Director- Quotative Systems Pharmacology(QSP)

- **Company:** TEEMA
- **Location:** Blythewood, SC, United States
- **Salary:** $208,000.0 - $270,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Computational Biology
- **Published:** September 21, 2026
- **Apply:** https://www.careerjet.com/job/us83acd743596209ae4d98c2feee268616/eaa

## About the Role

Deep knowledge of the principles and theoretical aspects of applied mathematical modeling, including numerical methods, ordinary differential equations (ODEs), partial differential equations (PDEs), and parameter estimation/optimization, and how these tools apply to the development of complex biochemical models
Deep expertise in quantitative systems pharmacology (QSP), mechanistic modeling, systems biology, and translational science
Demonstrated experience applying QSP approaches to support drug discovery and/or clinical development programs with measurable program impact
Strong understanding of pharmacology, physiology, immunology, molecular biology, and disease mechanisms
Ability to learn quickly in new areas of biology and apply a solid foundation of quantitative skills to build mechanistically sound QSP models

## Description

We are recruiting on behalf of a pharmaceutical client to fill a Director, Quantitative Systems Pharmacology (QSP) role - a scientific leadership role responsible for developing mechanistic knowledge of biology, integrated into mathematical models, to support drug discovery and clinical development. This role defines QSP strategy and collaborates across project teams to translate existing knowledge and data into actionable models that inform R&D decisions, including first-in-human translation, dose selection, candidate selection, target population selection, and combination strategies.
If you bring deep quantitative modeling expertise and know how to translate mechanistic insight into R&D decisions that move programs forward - this role was built for you.
What you will be doing:
QSP Model Development & Application
Develop, implement, and apply QSP models to understand diseases, their pathways, and their progressions
Evaluate drug candidates and treatment modalities to predict their effects and optimize therapeutic strategies (e.g., selection of target tumor types and populations), and support clinical introduction including first-in-human dose selection
Use and improve existing Neurology QSP platforms to gain insights into causal relationships between biological and drug-level responses, enhancing understanding of drug-target interactions and disease mechanisms; develop new QSP models and platforms as needed
Preclinical & Clinical Strategy
Lead preclinical and early clinical QSP development strategy to support optimal dose selection with simulations based on mechanistic understanding to assess efficacy and safety
Advocate for model-informed drug discovery and development (MIDD) approaches; provide scientific leadership, present research at scientific conferences, and integrate MIDD strategies into R&D programs to improve efficiency and decision-making
Cross-Functional Leadership & Data Analysis
Foster collaboration across functional groups and promote the development of new modeling tools and methods; advance the adoption of QSP capabilities to improve the predictive power of these tools to support the design and optimization of drug combinations
Manage the expectations and timelines of assigned modeling & simulation work for relevant project teams
Use mathematical, computational, and statistical tools to analyze and interpret large, complex data sets to gain insights into the causal relationships between drug-target interactions and disease mechanisms
Provide scientific/strategic expertise across multiple therapeutic areas to support decision-making in the conversion of discovery to clinical through the design, development, and execution of quantitative mechanistic models to support the translational process
What you must have:
PhD, MD-PhD, and/or PharmD in Bioengineering, Systems Biology, Applied Mathematics, Computational Biology, Pharmacometrics, Chemical Engineering, Pharmaceutical Sciences, or a related quantitative discipline


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