Associate Director, PBPK-PD Translational Modeling, DMPK
GSK
August 18, 2026
Remote friendly (Stevenage, England, United Kingdom)
United States
Clinical Research and Development
Position Summary
- Develop and apply mechanistic PBPK-PD models for oligonucleotide therapeutics and antibody-drug conjugates, translating in vitro and preclinical data into predictions of tissue exposure, target engagement, and pharmacological effects in patients.
- Provide PBPK-PD expertise to support target validation, modality selection, human dose prediction, and PK/PD strategies from early discovery through first-in-human.
- Integrate PBPK-PD, QSP, and AI-enabled modelling to enable data-informed candidate selection and development decisions.
Working arrangement
- Hybrid (UK or US): typically 2–3 days/week on-site; flexible per business needs/policy.
Responsibilities
- Build, qualify, and apply mechanistic whole-body PBPK-PD models for siRNA, ASO, and conjugated oligonucleotides.
- Build/apply ADC PBPK models covering antibody disposition, target expression/internalization, DAR distribution/deconjugation, linker stability, payload release, intratumoral penetration, and bystander effects.
- Deliver human efficacious dose projections (translate preclinical PK/PD into dose, regimen, duration) with explicit uncertainty.
- Define and communicate project-level PK/PD modelling strategies; apply PBPK-PD + QSP earlier in discovery.
- Partner with Discovery, Biology, Chemistry, Toxicology, Bioanalysis, and Clinical Pharmacology to embed model-informed drug discovery/development (MID3) and define quantitative candidate selection criteria.
- Apply AI/tech-enabled modelling frameworks; engage stakeholders and represent DMPK modelling in meetings/forums.
- Publish and present results externally.
Basic Qualifications (Required)
- PhD in pharmacokinetics, pharmaceutical sciences, engineering, systems pharmacology, applied mathematics, statistics, or related quantitative discipline.
- Strong industry/equivalent experience developing/applying mechanistic PBPK and/or PK-PD models; proficiency in PBPK/systems platforms (e.g., Simcyp, SimBiology/MATLAB).
- Experience delivering human PK and efficacious dose predictions and translational PK/PD assessments.
- Demonstrated ability to apply AI/tech-enabled modelling frameworks.
Preferred Qualifications
- Experience modelling oligonucleotides and antibody-drug conjugates/bioconjugates.
- Track record implementing MID3 to accelerate therapeutics and improve portfolio decisions.
- Collaborative, effective communicator in a multidisciplinary matrix with accountability for timely delivery.
How to apply
- Submit CV and a short cover letter describing a recent PBPK-PD or translational modelling project: what you modelled, decisions supported, and lessons learned.
- Develop and apply mechanistic PBPK-PD models for oligonucleotide therapeutics and antibody-drug conjugates, translating in vitro and preclinical data into predictions of tissue exposure, target engagement, and pharmacological effects in patients.
- Provide PBPK-PD expertise to support target validation, modality selection, human dose prediction, and PK/PD strategies from early discovery through first-in-human.
- Integrate PBPK-PD, QSP, and AI-enabled modelling to enable data-informed candidate selection and development decisions.
Working arrangement
- Hybrid (UK or US): typically 2–3 days/week on-site; flexible per business needs/policy.
Responsibilities
- Build, qualify, and apply mechanistic whole-body PBPK-PD models for siRNA, ASO, and conjugated oligonucleotides.
- Build/apply ADC PBPK models covering antibody disposition, target expression/internalization, DAR distribution/deconjugation, linker stability, payload release, intratumoral penetration, and bystander effects.
- Deliver human efficacious dose projections (translate preclinical PK/PD into dose, regimen, duration) with explicit uncertainty.
- Define and communicate project-level PK/PD modelling strategies; apply PBPK-PD + QSP earlier in discovery.
- Partner with Discovery, Biology, Chemistry, Toxicology, Bioanalysis, and Clinical Pharmacology to embed model-informed drug discovery/development (MID3) and define quantitative candidate selection criteria.
- Apply AI/tech-enabled modelling frameworks; engage stakeholders and represent DMPK modelling in meetings/forums.
- Publish and present results externally.
Basic Qualifications (Required)
- PhD in pharmacokinetics, pharmaceutical sciences, engineering, systems pharmacology, applied mathematics, statistics, or related quantitative discipline.
- Strong industry/equivalent experience developing/applying mechanistic PBPK and/or PK-PD models; proficiency in PBPK/systems platforms (e.g., Simcyp, SimBiology/MATLAB).
- Experience delivering human PK and efficacious dose predictions and translational PK/PD assessments.
- Demonstrated ability to apply AI/tech-enabled modelling frameworks.
Preferred Qualifications
- Experience modelling oligonucleotides and antibody-drug conjugates/bioconjugates.
- Track record implementing MID3 to accelerate therapeutics and improve portfolio decisions.
- Collaborative, effective communicator in a multidisciplinary matrix with accountability for timely delivery.
How to apply
- Submit CV and a short cover letter describing a recent PBPK-PD or translational modelling project: what you modelled, decisions supported, and lessons learned.