External evaluation of population pharmacokinetic models of imatinib in adults diagnosed with chronic myeloid leukaemia.

AIMS: Imatinib is considered the standard first-line treatment in newly diagnosed patients with chronic-phase myeloid leukaemia (CML). Several imatinib population pharmacokinetic (popPK) models have been developed. However, their predictive performance has not been well established when extrapolated to different populations. Therefore, this study aimed to perform an external evaluation of available imatinib popPK models developed mainly in adult patients, and to evaluate the improvement in individual model-based predictions through Bayesian forecasting computed by each model at different treatment occasions. METHODS: A literature review was conducted through PubMed and Scopus to identify popPK models. Therapeutic drug monitoring data collected in adult CML patients treated with imatinib was used for external evaluation, including prediction- and simulated-based diagnostics together with Bayesian forecasting analysis. RESULTS: Fourteen imatinib popPK studies were included for model-performance evaluation. A total of 99 imatinib samples were collected from 48 adult CML patients undergoing imatinib treatment with a minimum of one plasma concentration measured at steady-state between January 2016 and December 2020. The model proposed by Petain et al showed the best performance concerning prediction-based diagnostics in the studied population. Bayesian forecasting demonstrated a significant improvement in predictive performance at the second visit. Inter-occasion variability contributed to reducing bias and improving individual model-based predictions. CONCLUSIONS: Imatinib popPK studies developed in Caucasian subjects including α1-acid glycoprotein showed the best model performance in terms of overall bias and precision. Moreover, two imatinib samples from different visits appear sufficient to reach an adequate model-based individual prediction performance trough Bayesian forecasting.

[Pharmacogenetics in oncology]. / Farmacogenética en oncología.

Pharmacogenetics studies the relationship between genetic polymorphisms and individual responses to drugs. In recent years, there has been a great progress in our knowledge of the effects of drug-metabolizing enzymes and molecular target genetic polymorfisms on cancer chemotherapy. Pharmacogenetics focuses on the prediction of drug efficacy and toxicity based on a patient's genetic profile with routinely applicable genetic tests to select the most appropriate medication at optimal doses for each individual patient. Two years ago the FDA approved one genetic test to detect patients with increased risk of severe toxicity associated with irinotecan therapy. There have also been commercialized genetic chips to genotyping two cytochrome P450 enzymes at the same time. Prospectively, stratifying patients based on genotype may identify subpopulations likely to experience severe toxicity or to derive benefit from a particular treatment strategy, helping us move toward the ultimate goal of individualized therapy. In this review, we describe the clinical effects of polymorphisms that may influence cancer chemotherapy.