GSK
Associate Director, Quantitative Systems Pharmacology Lead
GSK, Waltham, Massachusetts, United States, 02254
Site Name:
USA - Massachusetts - WalthamPosted Date:
Sep 13 2024
We are seeking an
Associate Director level, Quantitative Systems Pharmacology Lead
for our Clinical Pharmacology Modelling and Simulation (CPMS) department.
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. We are seeking 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.
A successful candidate comes with passion and curiosity and works collaboratively in multidisciplinary teams and with QSP modelers internally and externally.
Role 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 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.
CPMS 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.
Basic Qualifications:
PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with experience in the application of mathematical and statistical methods.
2 or more years of experience in Pharma Life Science Biomedical industry developing and applying QSP approaches to drug development programs.
Experience working with the theory, principles, statistical aspects of mathematical modeling and simulation.
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.
Preferred Qualifications:
Demonstrated collaborative ways of working and able to work successfully in matrix teams.
Ability to effectively communicate and interact with key stakeholders, medical professionals and senior leadership.
Ability to learn new areas of biological sciences and build on a solid foundation of quantitative skills.
#LI-GSK
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns.
If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles.
#J-18808-Ljbffr
USA - Massachusetts - WalthamPosted Date:
Sep 13 2024
We are seeking an
Associate Director level, Quantitative Systems Pharmacology Lead
for our Clinical Pharmacology Modelling and Simulation (CPMS) department.
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. We are seeking 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.
A successful candidate comes with passion and curiosity and works collaboratively in multidisciplinary teams and with QSP modelers internally and externally.
Role 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 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.
CPMS 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.
Basic Qualifications:
PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with experience in the application of mathematical and statistical methods.
2 or more years of experience in Pharma Life Science Biomedical industry developing and applying QSP approaches to drug development programs.
Experience working with the theory, principles, statistical aspects of mathematical modeling and simulation.
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.
Preferred Qualifications:
Demonstrated collaborative ways of working and able to work successfully in matrix teams.
Ability to effectively communicate and interact with key stakeholders, medical professionals and senior leadership.
Ability to learn new areas of biological sciences and build on a solid foundation of quantitative skills.
#LI-GSK
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns.
If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles.
#J-18808-Ljbffr