Director, Quantitative Clinical Pharmacology

Key Skills

Aartificial intelligence, Agile methodologies, Data science techniques, Design, Effective communication skills, Employee life cycle, Leadership Skill, Machine learning techniques, Mathematical modeling

Job Description

You will be expected to play a critical role in driving integration of end-to-end model-informed drug discovery and development. In addition, you will be accountable to define, coordinate and defend Clinical Pharmacology Modelling & Simulation development strategies for disease & therapeutics of interest at senior level meetings, and provide expert input into the clinical pharmacology evidence generation and integrated evidence plans. CPMS responsibilities and accountabilities generally commence at candidate selection with preparations of first time in human trials, and continue through to filing, registration, and market expansion.

Main responsibilities and accountabilities also include:

• Establish or guide mathematical model development to understand disease, its progression, and drug action to prevent, treat and cure diseases; conduct meta-analyses as appropriate to generate knowledge through data re-use; conduct simulations to assess trial design performance
• Define and execute a co-ordinated scientific and technical strategy (18-24 months planning horizon) with demonstrated ability to co-ordinate outputs from several expertise areas to determine strategy
• Build and utilize mechanistic 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 bench biologists, data scientists, computational biologists, clinicians and other partner line colleagues to inform research and development programs and improve our understanding of disease mechanisms
• 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
• 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
• Implement best practices, trends, lessons learned from internal and external sources to further clinical pharmacology modelling and simulation contributions to R&D pipeline
• Ability to interact with line and middle management, staff and external contacts on a functional, strategic and tactical level
• Represent CPMS on various internal advisory boards, companywide initiatives and/or leadership teams
• Promote transparency and communicate R&D achievements through publications in appropriate scientific journals

Why you?

Basic Qualifications:

We are looking for a professional with these required skills to achieve our goals:

• PhD, MD, or PharmD with experience in clinical pharmacology, modelling and simulation in pharmaceutical research and development

• Five or more years of experience in mechanistic mathematical modeling to apply to clinical questions in drug development
• Five or more years of experience in clinical pharmacokinetics, modelling/simulation and drug development to solve practical problems in pharmaceutical industry

Preferred Qualifications:

• Strong drive and learning agility to build knowledge on a drug-disease system, symptom progression, standard of care, and trial design
• 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 working with senior stakeholders in a cross functional environment
• Strong track record of implementation of Model-Informed Drug Discovery and Development (MIDD) approaches to accelerate patient access to novel therapies and to expand therapeutic indications of marketed drugs

Why GSK?

We’re combining the power of genetic and genomic insights into what causes disease, with the speed and scale of artificial intelligence and machine learning (AI/ML) to make better predictions about who a treatment might work for, and why. We believe this powerful combination of data and technology holds the key to fundamentally transforming medical discovery for the better, improving R&D success rates and shaping how even the most challenging diseases, like neurological conditions and cancer, can be both prevented and treated.​

In 2021 we delivered four major product approvals: Cabenuva for HIV, Jemperli for endometrial cancer, Xevudy for COVID-19 and Apretude, our new long-acting medicine for HIV prevention.