Director - Quantitative Systems Pharmacology

Role Summary

Director - Quantitative Systems Pharmacology, leading the QSP/QST efforts within CPQM to advance Model-Informed Drug Discovery and Development for GSK’s Respiratory, Inflammation and Immunology portfolio.

Responsibilities

• Build and/or guide mathematical model development to understand disease, its progression, and drug action; conduct simulations to assess trial design performance
• Apply mechanistic models of biological, physiological, and pathophysiological processes to evaluate disease pathways and progression, as well as drug candidates or treatment modalities
• Develop and/or utilize state-of-the-art mathematical tools including inverse-problem modelling, simulation, scientific ML and/or statistical techniques to gain insight into causal relationships among system components and drug–target–biomarker–disease–patient interactions
• Define and execute a coordinated scientific and technical strategy (18–24 months) coordinating outputs from multiple expertise areas
• Work closely with biologists, clinicians, clinical pharmacologists, pharmacometricians, statisticians, AIML, imaging, biomarker and other partners to inform R&D programs and improve understanding of disease mechanisms
• Implement best practices and lessons learned to advance clinical pharmacology modelling and simulation contributions to the R&D pipeline
• Create a collaboration framework with internal and external experts for model development and application
• Learn and apply emerging modeling and simulation methodologies to enhance program efficiency and decision quality; collaborate with leading external teams
• Interact effectively with line and middle management, staff and external contacts on strategic and tactical levels
• Represent QSP CPQM on internal advisory boards and leadership teams
• Promote transparency and communicate R&D achievements through publications in scientific journals

Qualifications

• PhD, MD, or PharmD with experience in mechanistic modelling and simulation and systems biology for pharmaceutical R&D
• Substantial experience in mechanistic mathematical modeling, inverse problem modeling and simulation, and/or scientific machine learning for pre-clinical and/or clinical drug development
• Strong ability to learn a drug-disease system quickly and drive design decisions
• Proven collaboration skills in a multi-disciplinary team with accountability for timely results
• Ability to make sound judgments in complex, changing environments and prioritize multiple tasks
• Experience working with senior stakeholders in a cross-functional environment
• Track record of implementing MIDD approaches to accelerate patient access to therapies and expand indications

Skills

• Quantitative systems pharmacology and quantitative systems toxicology modeling
• Mechanistic modeling, inverse problem solving, simulation
• Scientific ML, AIML, statistical methodologies
• Cross-functional collaboration, strategic planning, and stakeholder engagement
• Model-informed drug discovery and development (MIDD) applications

Education

• PhD, MD, or PharmD in a relevant field; additional training in pharmacometrics or related disciplines is a plus