Evaluation of pharmacogenomics and hepatic nuclear imaging–related covariates by population pharmacokinetic models of irinotecan and its metabolites

Liu, Zheng; Martin, Jennifer H.; McLachlan, Sue‐Anne; Matera, A; Thompson, Michael A; Jefford, Michael; Hicks, R.; Cullinane, Carleen; Hatzimihalis, Athena; Crowley, Simone; Beale, Philip; Karapetis, Christos Stelios; Price, Timothy; Burge, M.; Michael, Michael

doi:10.1007/s00228-021-03206-w

Cited by 1 publication

(1 citation statement)

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“…In the previous PopPK analysis of irinotecan, the SN38 (a metabolite of irinotecan) concentration was also included to build a combined model, because irinotecan is a prodrug and SN38 showed a 300–1,000 times higher activity than irinotecan ( Berg et al, 2015 ; Adiwijaya et al, 2017 ; Oyaga-Iriarte et al, 2019 ; Brendel et al, 2021 ; Liu et al, 2022 ). In this study, although TQ-B3203 also could be metabolized to produce SN38, the conversion ratio was very low (<5%), and TQ-B3203 mainly existed in the form of the prototype in vivo .…”

Section: Discussionmentioning

confidence: 99%

Population pharmacokinetic analysis of TQ-B3203 following intravenous administration of TQ-B3203 liposome injection in Chinese patients with advanced solid tumors

Yang

Yin

et al. 2023

Front. Pharmacol.

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Background: TQ-B3203 is a novel topoisomerase I inhibitor currently in development for the treatment of advanced solid tumors. Great differences in pharmacokinetic characteristics were found among individuals according to the phase I clinical trial following intravenous administration of TQ-B3203 liposome injection (TLI) in Chinese patients with advanced solid tumors. Thus, it is significant to establish a population pharmacokinetic model to find the key factors and recognize their effect on pharmacokinetic parameters in order to guide individualized administration.Methods: Non-linear mixed effect models were developed using the plasma concentrations obtained from the phase I clinical trial by implementing the Phoenix NLME program. Covariates that may be related to pharmacokinetics were screened using stepwise methods. The final model was validated by goodness-of-fit plots, visual predictive check, non-parametric bootstrap and a test of normalized prediction distribution errors.Results: A three-compartment model with first-order elimination was selected as the best structural model to describe TQ-B3203 disposition adequately. Direct bilirubin (DBIL) and body mass index (BMI) were the two most influential factors on clearance, while lean body weight (LBW) was considered to affect the apparent distribution volume of the central compartment. The population estimations of clearance and central volume were typical at 3.97 L/h and 4.81 L, respectively. Model-based simulations indicated that LBW had a great impact on Cmax, BMI exerted a considerable influence on AUC0-t, and the significance of DBIL on both AUC0-t and Cmax was similarly excellent.Conclusion: The first robust population pharmacokinetic model of TQ-B3203 was successfully generated following intravenous administration of TLI in Chinese patients with advanced solid tumors. BMI, LBW and DBIL were significant covariates that affected the pharmacokinetics of TQ-B3203. This model could provide references for the dose regimen in the future study of TLI.

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