Director Clinical Pharmacology MIDD Lead

Director Clinical Pharmacology MIDD Lead

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Posted on Dec 16, 2025. Be among the first 25 applicants.

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 sub‑therapeutic 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.

• 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.

• Advanced degree (PhD or Pharm
  
  D and postdoctoral experience preferred) in pharmacometrics, clinical pharmacology, physiological pharmacokinetic and pharmacodynamic based modeling 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…