Physiologically Based Pharmacokinetic Model of Tyrosine Kinase Inhibitors to Predict Target Site Penetration, with

Suzanne van der Gaag1,2, Tamara Jordens2,3, Maqsood Yaqub1

  • 1Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

Insights

Physiologically based pharmacokinetic (PBPK) modeling accurately predicted osimertinib distribution in non-small cell lung cancer (NSCLC) tissues. This approach aids in precision dosing and evaluating new EGFR-tyrosine kinase inhibitors (TKIs) for NSCLC.

Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Oncology and Cancer Research
  • Medical Imaging and Diagnostics

Background:

  • Osimertinib is a tyrosine kinase inhibitor (TKI) for EGFR-mutated non-small cell lung cancer (NSCLC).
  • Drug distribution heterogeneity impacts osimertinib efficacy, measurable via microdosed radiolabeled drugs and positron emission tomography (PET).
  • Challenges exist in precision dosing due to pharmacokinetic (PK) variations between micro- and therapeutic doses.

Purpose of the Study:

  • To develop and validate a whole-body physiologically based pharmacokinetic (PBPK) model for osimertinib.
  • To predict tissue concentration-time profiles for both microdose and therapeutic doses.
  • To incorporate nonlinear PK processes and target site occupancy into the PBPK model.

Main Methods:

  • A target site PBPK model for osimertinib was developed, building on a prior PBPK model.
  • The model incorporated tissue-specific parameters, linear/nonlinear PK processes, and EGFR-binding dynamics.
  • Model predictions were validated against microdosed [11C]C-osimertinib PET imaging and clinical PK data.

Main Results:

  • The PBPK model accurately predicted osimertinib pharmacokinetics in multiple tissues, including lung tumors.
  • Predictions showed less than a 2-fold error compared to observed PET data across different dose levels.
  • The model successfully captured drug distribution and concentration-time profiles.

Conclusions:

  • PBPK modeling is valuable for predicting osimertinib pharmacokinetics and tissue distribution in NSCLC patients.
  • This approach provides insights into drug distribution and target engagement using microdose PET data.
  • The developed model can aid in optimizing dosing strategies and evaluating novel EGFR-TKIs for NSCLC.

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