Associate Director, Quantitative Systems Pharmacology

GSK

1d•Onsite

About The Position

As an Associate Director of Quantitative Systems Pharmacology (QSP) Expert, you will develop and apply QSP models to guide clinical study designs and mechanistic interpretation of study results in support of development of treatments and combination of treatments for a variety of diseases and therapeutic areas. Quantitative Systems Pharmacology (QSP) is a discipline that uses mechanistic mathematical models and disease platforms to enhance the robustness and quality of decision-making from exploratory research through clinical development. This role requires a highly motivated individual to develop and apply QSP models to guide clinical study designs and mechanistic interpretation of study results in support of development of treatments and combination of treatments for a variety of diseases and therapeutic areas. The successful candidate will be responsible for integrating and sharing data and knowledge in a highly stimulating, collaborative, and multi-disciplinary environment to influence clinical study decisions and develop a deeper understanding of physiological systems and disease mechanisms within oncology. This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following: Build and utilize QSP models of biological, physiological, and pathophysiological processes to evaluate a disease, its pathways and progression, as well as drug candidates or treatment modalities. Work in close collaboration with biologists, clinicians, clinical pharmacologists, pharmacometricians, QSP and nonclinical modelers, and other partner line colleagues to inform research and development programs and improve our understanding of disease mechanisms. Serve as QSP modeling & simulation point-of-contact in on project teams to solve challenging problems in drug research and development; contribute to preclinical and clinical study design and mechanistic interpretation of data. Develop and/or utilize state-of-the-art mathematical tools to gain insight into causal relationships between individual components of system-level and drug-level responses of drug-target-biomarker-disease-patient interaction. Analyze and interpret complex data sets in the context of disease mechanisms and pathways. Explore new QSP opportunities in combining QSP with other analytical approaches and build synergies through collaboration with computational groups including human genetics and functional genomics. Provide both scientific and strategic expertise in oncology therapeutic area to facilitate, develop and deliver quantitative support for decision making in clinical development programs. Perform scientific rigor and biological suitability assessment of QSP models and methodologies through establishing a context-driven verification & validation process (reviewing QSP model goals, assumptions, methodology, model code, model outputs, uncertainty quantification). Oncology Translational Medicine within the Oncology Research Unit is a science driven group delivering clinical pharmacology modelling & simulation excellence to research and development programs. We use quantitative pharmacology approaches, as part of the model-informed drug discovery & development paradigm (MID3), to evolve understanding of compound behavior and optimize dose across the research and development continuum, delivering a competitive label for a filing. Our activities include: Advise on dose, regimen and study design to optimize understanding of compound characteristics and variability in exposure and response across all drug development phases. Provide insights to programs through mechanistic modeling of drug-target-biomarker-disease-patient interaction (QSP modeling). Identify opportunities to re-use clinical data to extrapolate to untested scenarios, avoiding unnecessary additional clinical trials.

Requirements

PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with experience in the application of mathematical and statistical methods
Experience working with the theory, principles, statistical aspects of mathematical modeling and simulation, including numerical methods, parameter estimation/optimization, ordinary differential equations (ODEs), and how these can be applied in the development of complex models of biological pathways and system
Computational experience with one or more modeling and simulation packages or programming languages (e.g., MATLAB, R, Julia, SimBiology, C/C++)
Experience working with common tools for quantitative clinical pharmacology (such as NONMEM, R, WINNONLIN, Simcyp, SAS)
Experience developing mechanistically-sound PK-PD models
Experience translating, condensing, summarizing outcomes of modeling and simulation analyses into information that can be understood by project teams

Nice To Haves

Familiar with mathematical modelling methods, guidelines, and best practices, as well as associated technology.
Familiar with drug development practices, especially within the area of oncology.

Responsibilities

Build and utilize QSP models of biological, physiological, and pathophysiological processes to evaluate a disease, its pathways and progression, as well as drug candidates or treatment modalities
Work in close collaboration with biologists, clinicians, clinical pharmacologists, pharmacometricians, QSP and nonclinical modelers, and other partner line colleagues to inform research and development programs and improve our understanding of disease mechanisms
Serve as QSP modeling & simulation point-of-contact in on project teams to solve challenging problems in drug research and development; contribute to preclinical and clinical study design and mechanistic interpretation of data
Develop and/or utilize state-of-the-art mathematical tools to gain insight into causal relationships between individual components of system-level and drug-level responses of drug-target-biomarker-disease-patient interaction
Analyze and interpret complex data sets in the context of disease mechanisms and pathways
Explore new QSP opportunities in combining QSP with other analytical approaches and build synergies through collaboration with computational groups including human genetics and functional genomics
Provide both scientific and strategic expertise in oncology therapeutic area to facilitate, develop and deliver quantitative support for decision making in clinical development programs
Perform scientific rigor and biological suitability assessment of QSP models and methodologies through establishing a context-driven verification & validation process (reviewing QSP model goals, assumptions, methodology, model code, model outputs, uncertainty quantification)
Advise on dose, regimen and study design to optimize understanding of compound characteristics and variability in exposure and response across all drug development phases.
Provide insights to programs through mechanistic modeling of drug-target-biomarker-disease-patient interaction (QSP modeling)
Identify opportunities to re-use clinical data to extrapolate to untested scenarios, avoiding unnecessary additional clinical trials.