Since its clinical introduction in 1998, the topoisomerase I inhibitor irinotecan has been widely used in the treatment of solid tumors, including colorectal, pancreatic, and lung cancer. Irinotecan therapy is characterized by several dose-limiting toxicities and large interindividual pharmacokinetic variability. Irinotecan has a highly complex metabolism, including hydrolyzation by carboxylesterases to its active metabolite SN-38, which is 100- to 1000-fold more active compared with irinotecan itself. Several phase I and II enzymes, including cytochrome P450 (CYP) 3A4 and uridine diphosphate glucuronosyltransferase (UGT) 1A, are involved in the formation of inactive metabolites, making its metabolism prone to environmental and genetic influences. Genetic variants in the DNA of these enzymes and transporters could predict a part of the drug-related toxicity and efficacy of treatment, which has been shown in retrospective and prospective trials and meta-analyses. Patient characteristics, lifestyle and comedication also influence irinotecan pharmacokinetics. Other factors, including dietary restriction, are currently being studied. Meanwhile, a more tailored approach to prevent excessive toxicity and optimize efficacy is warranted. This review provides an updated overview on today’s literature on irinotecan pharmacokinetics, pharmacodynamics, and pharmacogenetics.

A pharmacokinetically guided individualized dosing algorithm was successfully applied and evaluated. The dosing algorithm led to patients being treated at dosages ranging from 400 to 1,800 mg daily. Further studies are needed to show a benefit of individualized dosing on clinical outcomes, such as progression-free survival. Clin Cancer Res; 22(23); 5738-46. ©2016 AACRSee related commentary by Ornstein and Rini, p. 5626.

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A popPK model for pazopanib was developed that illustrated the complex absorption process, the non-linear dose-concentration relationship, the high inter-patient and intra-patient variability, and the first-order decay of pazopanib concentration over time. The developed popPK model can be used in clinical practice to screen covariates and guide therapeutic drug monitoring.

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