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

  • Pharmacogenetics
  • Published:
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Abstract

Background

Body surface area (BSA)–based dosing of irinotecan (IR) does not account for its pharmacokinetic (PK) and pharmacodynamic (PD) variabilities. Functional hepatic nuclear imaging (HNI) and excretory/metabolic/PD pharmacogenomics have shown correlations with IR disposition and toxicity/efficacy. This study reports the development of a nonlinear mixed-effect population model to identify pharmacogenomic and HNI-related covariates that impact on IR disposition to support dosage optimization.

Methods

Patients had advanced colorectal cancer treated with IR combination therapy. Baseline blood was analysed by Affymetrix DMET™ Plus Array and, for PD, single nucleotide polymorphisms (SNPs) by Sanger sequencing. For HNI, patients underwent 99mTc-IDA hepatic imaging, and data was analysed for hepatic extraction/excretion parameters. Blood was taken for IR and metabolite (SN38, SN38G) analysis on day 1 cycle 1. Population modelling utilised NONMEM version 7.2.0, with structural PK models developed for each moiety. Covariates include patient demographics, HNI parameters and pharmacogenomic variants.

Results

Analysis included (i) PK data: 32 patients; (ii) pharmacogenomic data: 31 patients: 750 DMET and 22 PD variants; and (iii) HNI data: 32 patients. On initial analysis, overall five SNPs were identified as significant covariates for CLSN38. Only UGT1A3_c.31 T > C and ABCB1_c.3435C > T were included in the final model, whereby CLSN38 reduced from 76.8 to 55.1%.

Conclusion

The identified UGT1A3_c.31 T > C and ABCB1_c.3435C > T variants, from wild type to homozygous, were included in the final model for SN38 clearance.

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Funding

Funding support by the (1) Australian National Health and Medical Research Council (Grant No. 628564) and (2) the Pathways to Cancer Freedom Grant, Cancer Council NSW 2018, Australia.

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Wrote manuscript: Zheng Liu, Jennifer Martin, Winston Liauw, Sue-Anne McLachlan, Emma Link, Anetta Matera, Michael Jefford, Rod J Hicks, Carleen Cullinane, Athena Hatzimihalis, Ian Campbell, Phillip J Beale, Christos S Karapetis, Timothy Price, Mathew E. Burge, Michael Michael. Designed research: Zheng Liu, Jennifer Martin, Ian Campbell, Rod J Hicks, Michael Michael. Performed research: Zheng Liu, Jennifer Martin, Winston Liauw, Sue-Anne McLachlan, Emma Link, Anetta Matera, Michael Thompson, Michael Jefford, Rod J Hicks, Carleen Cullinane, Athena Hatzimihalis, Ian Campbell, Simone Crowley, Phillip J Beale, Christos S Karapetis, Timothy Price, Mathew E. Burge, Michael Michael. Analysed data: Zheng Liu, Jennifer Martin, Emma Link, Michael Thompson, Ian Campbell, Simone Crowley, Athena Hatzimihalis, Michael Michael. Contributed analytical tools: Zheng Liu, Jennifer Martin, Michael Thompson, Rod J Hicks, Athena Hatzimihalis, Ian Campbell, Simone Crowley, Michael Michael.

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Correspondence to Michael Michael.

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Liu, Z., Martin, J.H., Liauw, W. et al. Evaluation of pharmacogenomics and hepatic nuclear imaging–related covariates by population pharmacokinetic models of irinotecan and its metabolites. Eur J Clin Pharmacol 78, 53–64 (2022). https://doi.org/10.1007/s00228-021-03206-w

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