Director, Quantitative Systems Pharmacology
Eisai US
Summary
The Director of Quantitative Systems Pharmacology (QSP) will lead the development and implementation of mechanistic knowledge of biology integrated into mathematical models that support drug discovery and clinical development. The Director of QSP will provide scientific leadership, define QSP strategies, and collaborate across Eisai's Deep Human Biology Learning (DHBL) project teams to translate existing knowledge and data into actionable QSP models. These models will provide functional understanding of complex nonlinear pathophysiological systems and their interactions, will allow scientists to explore system dynamics and biological hypotheses, will yield insight into responses to different pharmacological approaches to modulating biological systems, and will provide mechanistic insights to inform Eisai's R&D decisions (for example FIH translation, dose selection, candidate selection, selection of target population, and combination strategies). This Director QSP position is essential for supporting the increasing expectations of team leaders and global regulators of applying QSP methodologies to continuously improve the conceptual and mechanistic understanding of the relations among drug exposure, efficacy, and safety.
Job description
Essential Functions
- Develop, implement, and apply QSP models to understand diseases, their pathways, and their progressions. Evaluate DHBL drug candidates and treatment modalities to predict their effects and optimize therapeutic strategies (e.g., the selection of target tumor types and populations), and to support clinical introduction including first-in-human dose selection.
- Use and improve existing Neurology QSP Platforms to gain insights into the causal relationships between biological and drug-level responses, enhancing the understanding of drug-target interactions and disease mechanisms. Develop new QSP models and platforms as they are needed.
- Lead DHBL 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 Eisai's R&D programs to improve efficiency and decision-making.
- 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/timelines of assigned M&S work for the 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.
Requirements
- PhD, MD-PhD and/or PharmD in Bioengineering, Systems Biology, Applied Mathematics, Computational Biology, Pharmacometrics, Chemical Engineering, Pharmaceutical Sciences, or a related quantitative discipline.
- Deep knowledge of the principles and theoretical aspects of applied mathematical modeling, including numerical methods, ordinary differential equations (ODEs), partial differential equations (PDEs), parameter estimation/optimization, and how these tools can be applied in 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 to use a solid foundation of quantitative skills to apply newly acquired knowledge to build mechanistically sound QSP models.
Requirements
- PhD, MD-PhD and/or PharmD in Bioengineering, Systems Biology, Applied Mathematics, Computational Biology, Pharmacometrics, Chemical Engineering, Pharmaceutical Sciences, or a related quantitative discipline.
- Deep knowledge of the principles and theoretical aspects of applied mathematical modeling, including numerical methods, ordinary differential equations (ODEs), partial differential equations (PDEs), parameter estimation/optimization, and how these tools can be applied in 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 to use a solid foundation of quantitative skills to apply newly acquired knowledge to build mechanistically sound QSP models.
Benefits
- Annual Incentive Plan
- Long Term Incentive Plan
- Health Insurance
- Retirement Benefits
Company overview
Eisai US is the American pharmaceutical subsidiary of Tokyo-based Eisai Co., Ltd., a global pharmaceutical company founded in 1941. Headquartered in Nutley, New Jersey, Eisai US operates with a passionate commitment to patient care through its human health care (hhc) philosophy, which places patients and their families at the forefront of all business decisions. The company focuses on two primary therapeutic areas: oncology and neurology, with particular emphasis on dementia-related diseases and neurodegenerative disorders. Eisai US maintains a fully integrated pharmaceutical business model with end-to-end capabilities spanning discovery, development, and marketing. The organization operates commercial and clinical development organizations in New Jersey, discovery labs in Massachusetts and Pennsylvania, and global demand chain operations in Maryland and North Carolina. Notable products in its portfolio include Leqembi (lecanemab) for Alzheimer's disease, Lenvima (lenvatinib) for various cancers, and Aricept (donepezil) for Alzheimer's treatment. With approximately 1,001-5,000 employees in the United States, Eisai US represents a significant presence in the American pharmaceutical landscape, dedicated to addressing unmet medical needs through innovative therapies and comprehensive patient support programs.