Site Name: USA - Pennsylvania - Upper Providence, UK - Hertfordshire - Stevenage
Posted Date: Oct 26 2023
We are seeking a Director- level Quantitative Systems Pharmacology candidate 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 develop a deeper understanding of physiological systems and disease mechanisms within and across therapeutic areas. 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 multidisciplinary 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; develop a deep disease understanding and knowledge base.
Create a collaboration framework with internal and external experts in the development and application of these models.
Learn and apply emerging modeling and simulation methodologies with a view to enhance clinical program efficiency and investment decision quality; collaborate with external field-leading teams for methodology application.
Promote model-informed drug discovery & development (MID3) strategies and approaches by publishing in peer-reviewed journals and presenting at scientific conferences.
Develop a strategy for QSP integration and identify key points of impact into the workflow of clinical drug development.
Explore and build new QSP opportunities and synergies in combining QSP approaches with other computational groups including human genetics and functional genomics.
Provide both scientific and strategic expertise across multiple (non-oncology) therapeutic areas to facilitate, develop and deliver quantitative support for decision making in critical clinical development program questions, as well as contribute to design and execution of quantitative mechanistic models to support clinical programs.
Providing the scientific rigor and biological suitability 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).
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 (MIDD), 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).
Assess impact of DDI’s and special populations on drug exposure to inform label (using in silico PBPK modeling approaches where possible).
Undertake early comparative benchmarking of compound activity relative to competitors and the target medicine profile using model-based meta-analysis (MBMA).
Identify opportunities to re-use clinical data to extrapolate to untested scenarios, avoiding unnecessary additional clinical trials.
Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:
Must have a doctoral degree such as MD and/or PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with strong background in the application of mathematical and statistical methods.
Demonstrated experience (5 years or more) in developing and applying QSP approaches to drug discovery and development programs in the pharmaceutical industry.
Must have deep understanding of theory, principles, and 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 systems
Computational fluency and extensive, hands-on 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.
Preferred Qualifications:
If you possess the following characteristics and experience, would be a huge plus:
Ability to learn new areas of biological sciences and build on solid foundation of quantitative skills to develop mechanistically-sound PK-PD models.
Understanding of PK-PD principles and commonly applied models
Ability to translate, condense, summarize outcomes of modeling and simulation analyses into information that can be understood and invested by project teams
Ability to keep up-to-date with and propose the implementation of scientific and technological developments in the area of mechanistic PK-PD
Good listener and ability to effectively interact with colleagues with a variety of backgrounds.
Self-directed, independent, and highly motivated researcher who excels in a collaborative, multi-disciplinary team environment.
#LI-GSK
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why Us?
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 – as an organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030.
Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We’re committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.
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. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.
Important notice to Employment businesses/ Agencies
GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements. For more information, please visit GSK’s Transparency Reporting For the Record site.