Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability

Area of Science:

• Pharmacokinetics and Pharmacodynamics
• Computational Biology
• Biotechnology

Background:

• Inter-individual variability in drug pharmacokinetics (PK) poses challenges for effective therapeutic use.
• Monoclonal antibodies (mAbs) like trastuzumab exhibit significant PK variability, necessitating predictive models.
• Physiologically-based pharmacokinetic (PBPK) models offer mechanistic insights into drug disposition.

Purpose of the Study:

• To develop and validate a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying PK variability.
• To identify and quantify key biological factors contributing to inter-individual variability in trastuzumab PK.
• To demonstrate the utility of the popPBPK framework in predicting observed PK variability in clinical trials.

Main Methods:

• Development of a PBPK model incorporating mechanistic sources of variability for trastuzumab.
• Sensitivity analyses (local and global) to identify and quantify the impact of five key variability parameters.
• Generation of virtual populations and adaptation of parameters to predict variability in four experimental trials.

Main Results:

• Identified five key factors influencing trastuzumab PK variability: HER2 concentration, convective flow, endocytic transport, complex degradation, and shed HER2.
• Membrane-bound HER2 concentration ([Formula: see text]) was critical for tissue distribution, while clearance variability was mainly driven by endocytic transport ([Formula: see text]).
• The popPBPK framework, incorporating literature-based variability in key parameters, accurately predicted observed inter-individual variability in trastuzumab PK across four trials.

Conclusions:

• The developed popPBPK framework successfully quantifies and predicts pharmacokinetic variability.
• Key biological parameters, beyond anthropometrics, are crucial for accurate prediction of drug variability.
• This approach provides a robust tool for understanding the mechanistic basis of PK variability for mAbs and other drugs.