Job Description

The Clinical Pharmacology and Quantitative Medicine (CPQM) group at GSK is a newly established organization dedicated to becoming a Centre of Excellence in Model-Informed Drug Development (MIDD). CPQM uniquely integrates expertise in clinical pharmacology, digital medicine, translational imaging, and mechanistic and systems modeling.


Under the strategic leadership of the MIDD Head, the MIDD team drives strategy and innovation in clinical pharmacology and quantitative medicine. This function is essential for advancing GSK's MIDD capabilities, efficiency, and impact, with a strong focus on respiratory, immunology, inflammation, hepatology,


neurodegeneration, and emerging areas within the Respiratory, Immunology &


Inflammation Research Unit (RIIRU). The MIDD team is responsible for leading the development and execution of comprehensive therapeutic or sub-therapeutic area MIDD evidence strategies across RIIRU.

Job Purpose

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The MIDD Lead is a scientific and strategic leader who applies modelling and simulation to inform drug development decisions. The MIDD Lead is responsible for leading the development and implementation of MIDD evidence strategies, serving as an advanced technical and subject matter expert for a therapeutic or subtherapeutic area within RIIRU. This role oversees integration and leads on the delivery of advanced modelling and simulation approaches, building-on or extending model-informed clinical pharmacology strategies. Emphasis is placed on incorporating disease-level data and novel digital and imaging endpoints to inform asset and mechanism-level decision-making. This role integrates advanced pharmacometrics approaches, alongside systems pharmacology, biostatistics, and data science to optimize dosing, clinical trial design, regulatory strategy, and go/no-go decisions. The role supports optimization and promotion of the effective use of established M&S methodologies (including MBMA and disease progression modelling) and the integration of emerging technologies (including AI/ML and SciML). A key objective is to ensure CPQM delivers robust and transparent MIDD evidence to de-risk and accelerate programs supporting both internal and regulatory decision-making. The Lead will advocate for and advise on optimizing regulatory MIDD strategies to accelerate the delivery of transformative therapies to patients. Collaboration is central to this role, requiring close partnership with AI/ML lead & experts within the MIDD team, Clinical Pharmacology Modelling & Simulation (CPMS), Quantitative Systems Pharmacology (QSP), digital, imaging, and biomarker teams within CPQM, as well multiple functions (e.g., Biostatistics, Clinical/Medical, Translation Sciences, Epidemiology) across RIIRU and GSK.

Key Responsibilities:

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Design & Execute MIDD Strategies:

Drive optimal use of MIDD approaches, associated data plans and model evaluation strategies, to inform disease-, program-, and business-level decisions. Develop and implement robust evidence strategies within RIIRU, advancing MIDD Evidence frameworks and documentation standards to de-risk and accelerate programs, optimizing internal and regulatory strategies to deliver transformative therapies.

Technical Expertise:

Act as a subject matter expert for modeling and simulation (M&S) for a (sub)-therapeutic area serving as a contributor and technical coach. Lead development of the more technically challenging M&S plans, analyses, and reports. Contribute to regulatory interactions involving quantitative evidence, ensuring clear communication of modeling assumptions, rigor in alignment with the impact on decision-making.

Optimize & Innovate:

Promote effective use of current M&S methodologies (e.g., MBMA, disease progression modeling) and integrate with emerging technologies (AI/ML, SciML). Develop good practices, training, and wider adoption strategies.

Shape Future Methods:

Collaborate with global CPMS, academic partners, and external experts to develop scalable methodologies aligned with RIIRU needs.

Cross-Functional Partnerships:

Build strong networks across AI/ML, CPMS, QSP, biomarkers, digital, imaging, biostatistics, clinical, and real-world data teams to embed advanced modeling into decision-making frameworks.

External Engagement:

Enhance external profile through publications, conferences, and contributions to scientific and regulatory communities in MIDD, pharmacometrics, QSP, and AI/ML integration.

Why you?

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Basic Qualifications:

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Advanced degree (PhD or PharmD and Postdoctoral experience preferred) in pharmacometrics, Clinical pharmacology, Physiological Pharmacokinetic and Pharmacodynamic based modelling or related quantitative disciplines QSP. A deep understanding and examples of successful application of various M&S methods and software used in MIDD (e.g., population PK/PD, exposure-response, MBMA and disease progression modeling) and demonstration of their and their effective use in clinical development and regulatory decision making. An advanced understanding of relevant regulatory and ICH guidelines across major markets related to the design of clinical studies and drug development strategy with particular emphasis on the role of MIDD. An advanced understanding of appropriate regulatory and ICH guidelines across major markets in the design of clinical studies and drug development strategy with particular emphasis on the role of MIDD. Ability to quickly attain the therapeutic or sub-therapeutic area literacy sufficient to implement and communicate the MIDD strategy to clinical experts 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

Preferred Qualifications:

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A strong knowledge of and experience applying MIDD in RIIRU-relevant disease areas with knowledge of the Hepatology disease area an additional advantage. Hands-on use of AI/ML and application to MIDD M&S methods. Hands-on PBPK and/or QSP skills
#LI-GSK*


If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $180,675 to $301,125. The US salary ranges take into account a number of factors including work location within the US market, the candidate's skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases - to impact health at scale.



People and patients around the world count on the medicines and vaccines we make, so we're committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.



GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.



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