Director, CPMS Oncology

GSK•Durham, NC

3d•$188,100 - $313,500•Hybrid

About The Position

We have an exciting opportunity at GSK for a highly motivated and experienced Director to join our team supporting the Oncology Clinical Pharmacology Modelling and Simulation (CPMS) department within Oncology Translational Medicine. This role focuses on delivering CPMS quantitative excellence to development programs, helping to inform and accelerate the development of innovative oncology therapies by ensuring they reach the right patients, at the right dose, and at the right time. GSK provides a supportive environment for scientists who are aspiring to learn, to contribute and to make impact on business decisions through innovation, expertise, and influence. As a Director, CPMS Oncology, you will be part of a science driven group delivering clinical pharmacology and modelling & simulation excellence to research and development programs. You’ll have the opportunity to work on antibody drug conjugates, biologics and small molecules in the Oncology therapeutic area. CPMS responsibilities generally start post-candidate selection with accountability occurring from approximately 6 months prior to FTIH through to life cycle management.

Requirements

PhD in Quantitative Clinical Pharmacology and Pharmacometrics disciplines (e.g., pharmacology, engineering or statistics) and experience in using modeling/simulation to solve practical problems in industry or academia. PharmD or Master’s degree in the same disciplines with an additional 3 years of relevant experience may be considered.
5+ years of utilizing and leveraging population PK and exposure-response modelling in drug development; and verifiable proficiency in pharmacometric tools NONMEM or R.
3+ years of experience in planning, performing, and reporting model-based analysis of clinical data per industry and regulatory standards.

Nice To Haves

Oncology drug development experience
Knowledge of or ability to quickly learn disease biology, mechanisms, trial design, endpoints and treatment paradigms in oncology
Solid experience with advanced pharmacometric approaches such as mechanistic PKPD modelling, longitudinal disease modeling, model-based meta-analysis, or adaptive dosing simulations
Ability to keep up-to-date with and propose the implementation of new modeling approaches to inform drug development
Experience with AI/ML tools and applications in pharmacometrics
Demonstrated aptitude for productive collaboration in a multi-discipline team, using effective communication and taking personal accountability for timely delivery of results
Clear evidence of ability to make sound judgement in complex situations and adapt to changing business needs by prioritizing multiple tasks
Experience in the design, analysis, interpretation and reporting of Clinical Pharmacology studies per industry and regulatory standards
Passion for quantitative clinical pharmacology and desire to innovate for better outcome
Experience working with senior stakeholders in a cross functional environment
Excellent interpersonal skills with strong oral/written communication and presentation skills
Strong track record of implementation of Model-Informed Drug Discovery and Development (MID3) approaches to accelerate patient access to novel therapies and to expand therapeutic indications of marketed drugs

Responsibilities

Defining and executing model-based development strategies for oncology projects
Planning, conducting and reporting of population PK and exposure-response analyses, simulation-based trial design and dose selection
Presenting strategy and defending outcome of model-based approaches to internal governance boards and regulatory agencies
Contributing to clinical program design, trial protocols, analysis plans, study reports and regulatory submissions
Writing or reviewing clinical pharmacology components of regulatory documents and responses such that GSK products are rapidly and efficiently approved with optimum labelling (with regards to the clinical pharmacology, modelling and simulation contents)
Interacting with line and middle management, staff and external contacts on a functional, strategic and tactical level
Applying innovative methods such as drug-disease modeling, longitudinal exposure-response analysis, model-based meta-analysis, quantitative systems pharmacology and AI/ML informed analyses to enhance data use and trial efficiency
Implementing best practices, trends, lessons learned from internal and external sources to further clinical pharmacology modelling and simulation contributions to R&D pipeline
Promoting model-informed drug discovery and development through external collaboration, journal publication and conference presentation