Purpose: To establish a physiologically-based pharmacokinetic (PBPK) model for analyzing the factors associated with side effects of irinotecan by using a computer-based virtual clinical study (VCS) because many controversial associations between various genetic polymorphisms and side effects of irinotecan have been reported.
Methods: To optimize biochemical parameters of irinotecan and its metabolites in the PBPK modeling, a Cluster Newton method was introduced. In the VCS, virtual patients were generated considering the inter-individual variability and genetic polymorphisms of enzymes and transporters.
Results: Approximately 30 sets of parameters of the PBPK model gave good reproduction of the pharmacokinetics of irinotecan and its metabolites. Of these, 19 sets gave relatively good description of the effect of UGT1A1 *28 and SLCO1B1 c.521T>C polymorphism on the SN-38 plasma concentration, neutropenia, and diarrhea observed in clinical studies reported mainly by Teft et al. (Br J Cancer. 112(5):857-65, 20). VCS also indicated that the frequency of significant association of biliary index with diarrhea was higher than that of UGT1A1 *28 polymorphism.
Conclusion: The VCS confirmed the importance of genetic polymorphisms of UGT1A1 *28 and SLCO1B1 c.521T>C in the irinotecan induced side effects. The VCS also indicated that biliary index is a better biomarker of diarrhea than UGT1A1 *28 polymorphism.
Keywords: Cluster Newton method; inter-individual variability; irinotecan(CPT-11); neutropenia; physiologically-based pharmacokinetic modeling; virtual clinical study.