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Physiologically-based pharmacokinetic modeling of nilotinib for drug-drug interactions, pediatric patients, and pregnancy and lactation #529

Open AndreDlm opened 11 months ago

AndreDlm commented 11 months ago

https://pubmed.ncbi.nlm.nih.gov/37909674/ Liu XI, Leong R, Burckart GJ, Dallmann A. Physiologically-based pharmacokinetic modeling of nilotinib for drug-drug interactions, pediatric patients, and pregnancy and lactation. J Clin Pharmacol. 2023 Nov 1. doi: 10.1002/jcph.2379. Epub ahead of print. PMID: 37909674.

Abstract Nilotinib is a second generation BCR-ABL tyrosine kinase inhibitor for the treatment of Philadelphia chromosome positive chronic myeloid leukemia in both adult and pediatric patients. The pharmacokinetics (PK) of nilotinib in specific populations such as pregnancy and lactation people remain poorly understood. Therefore, the objectives of the current study were to develop a physiologically-based pharmacokinetic (PBPK) model to predict nilotinib PK in virtual drug-drug interaction (DDI) studies, as well as in pediatric, pregnant, and lactating populations. The nilotinib PBPK model was built in PK-Sim® which is part of the free and open-source software Open Systems Pharmacology (OSP). The observed clinical data for the validation of the nilotinib models were obtained from the literature. The model reasonably predicted nilotinib concentrations in the adult population, the DDIs between nilotinib and rifampin or ketoconazole in the adult population, as well as the PK in the pediatric, pregnant, and lactating populations, although in the latter two populations plasma concentrations were slightly underestimated. The ratio of predicted vs observed PK parameters for the adult model ranged from 0.71-1.11 for AUC and 0.55-0.95 for Cmax. For the DDI, the predicted AUCR and CmaxR fell within the Guest criterion. The current study demonstrated the utility of using PBPK modeling to understand the mechanistic basis of PK differences between adults and special populations, such as pediatrics, and pregnant and lactating individuals, indicating that this technology can potentially inform or optimize dosing conditions in specific populations.

Keywords: drug-drug interactions; lactation; nilotinib; pediatrics; physiologically-based pharmacokinetics; pregnancy.

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