Physiologically Based Pharmacokinetic Modelling to Predict Imatinib Exposures in Cancer Patients with Renal Dysfunction: A Case Study

Author:

Rowland Yeo Karen1,Hatley Oliver1ORCID,Small Ben G.1ORCID,Johnson Trevor N.1

Affiliation:

1. Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK

Abstract

Imatinib is mainly metabolised by CYP3A4 and CYP2C8 and is extensively bound to α-acid glycoprotein (AAG). A physiologically based pharmacokinetic (PBPK) model for imatinib describing the CYP3A4-mediated autoinhibition during multiple dosing in gastrointestinal stromal tumor patients with normal renal function was previously reported. After performing additional verification, the PBPK model was applied to predict the exposure of imatinib after multiple dosing in cancer patients with varying degrees of renal impairment. In agreement with the clinical data, there was a positive correlation between AAG levels and imatinib exposure. A notable finding was that for recovery of the observed data in cancer patients with moderate RI (CrCL 20 to 39 mL/min), reductions of hepatic CYP3A4 and CYP2C8 abundances, which reflect the effects of RI, had to be included in the simulations. This was not the case for mild RI (CrCL 40 to 50 mL/min). The results support the finding of the clinical study, which demonstrated that both AAG levels and the degree of renal impairment are key components that contribute to the interpatient variability associated with imatinib exposure. As indicated in the 2020 FDA draft RI guidance, PBPK modelling could be used to support an expanded inclusion of patients with RI in clinical studies.

Publisher

MDPI AG

Subject

Pharmaceutical Science

Reference30 articles.

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3. European Medicines Agency (2015). Guideline on the Evaluation of the Pharmacokinetics of Medicinal Products in Patients with Decreased Renal Function, European Medicines Agency.

4. Design and conduct considerations for studies in patients with impaired renal function;Ravenstijn;Clin. Transl. Sci.,2021

5. Modeling and predicting drug pharmacokinetics in patients with renal impairment;Yeo;Expert Rev. Clin. Pharmacol.,2011

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