Senior Scientist, Biopharmaceutics Modelling & Simulation (PBBM/PBPK)

SRG; Stone Cross; On-site; GBP 70,000 - 110,000; Full time

Job summary

SRG is seeking a Senior Scientist with PBPK and PBBM expertise to support drug product development. You will apply mechanistic modelling to predict in vivo performance, considering drug properties, formulation and physiology to guide development decisions.

You will collaborate with multidisciplinary teams, calibrate models, and contribute to regulatory submissions and scientific publications. Strong emphasis on model-informed drug development and innovation.

Qualifications

• PhD or MSc in a pharmaceutical sciences related field.
• Demonstrated PBPK/PBBM expertise and pharmacometrics experience.
• Strong understanding of oral absorption, dissolution and PK principles.

Responsibilities

• Develop, verify and apply PBBM and PBPK models using industry-standard software.
• Predict oral absorption, bioavailability, dissolution and formulation bridging.
• Perform model calibration, sensitivity analyses and uncertainty assessments.
• Collaborate with lab scientists to design in vitro studies for model support.
• Support dissolution method development and in vitro–in vivo links.
• Communicate modelling outcomes via reports, presentations and regulatory documents.
• Contribute to innovations in modelling methods, automation and AI/ML approaches.

Skills

PBPK modelling

PBBM modelling

Pharmacokinetics

Mechanistic modelling

Model-informed drug development

Oral absorption

Dissolution

Simcyp

GastroPlus

PK-Sim

Education

PhD in Pharmaceutical Sciences

MSc in Biopharmaceutics or Pharmacokinetics

Tools

Simcyp

GastroPlus

PK-Sim

Job description

Are you an experienced scientist with expertise in Physiologically Based Pharmacokinetic (PBPK) and Physiologically Based Biopharmaceutics Modelling (PBBM)? We are looking for a highly motivated Senior Scientist to support the development and optimization of innovative drug products across all stages of development.

In this role, you will apply mechanistic modelling and simulation approaches to predict and understand the impact of drug substance properties, formulation design, physiology, and clinical variables on in vivo performance and patient outcomes. You will collaborate with multidisciplinary teams to support model-informed drug development and regulatory decision-making.

Key Responsibilities:

• Develop, verify, and apply PBBM and PBPK models using industry-standard software platforms.
• Predict and assess oral absorption, food effects, bioavailability, formulation bridging, dissolution and particle size specifications, and virtual bioequivalence.
• Perform model calibration, sensitivity analyses, scenario testing, and uncertainty assessments to support development decisions.
• Collaborate with laboratory scientists to design and interpret in vitro studies supporting model development and verification.
• Support the development of clinically relevant dissolution methods and in vitro-in vivo relationships.
• Communicate modelling outcomes through technical reports, presentations, regulatory documents, and scientific publications.
• Contribute to innovations in modelling methodologies, automation, and AI/ML-driven predictive approaches.

Required Qualifications;

• PhD or MSc in Pharmaceutical Sciences, Biopharmaceutics, Pharmacokinetics, Pharmacometrics, Chemical Engineering, or a related discipline.
• Demonstrated expertise in PBPK, PBBM, pharmacometrics, mechanistic modelling, or model-informed drug development.
• Strong understanding of oral absorption, dissolution, permeability, biopharmaceutics, and pharmacokinetics.
• Experience with modelling software such as Simcyp, GastroPlus, PK-Sim, or equivalent platforms.
• Proven ability to apply modelling approaches to solve pharmaceutical development challenges.
• Excellent scientific communication and stakeholder engagement skills.

Preferred Qualifications;

• Experience supporting regulatory submissions involving PBPK or PBBM analyses.
• Experience with virtual bioequivalence and clinically relevant dissolution specifications.
• Programming experience with Python, R, MATLAB, or similar scientific tools.
• Knowledge of machine learning and data science applications in pharmaceutical development.
• Experience across a range of drug modalities, including poorly soluble compounds, enabling formulations, peptides, or complex dosage forms.