Pharmacokinetic Model of Drug Interaction of Tacrolimus with Combined Administration of CYP3A4 Inhibitors Voriconazole and Clarithromycin After Bone Marrow Transplantation
European Journal of Drug Metabolism and Pharmacokinetics, ISSN: 2107-0180, Vol: 49, Issue: 6, Page: 763-771
2024
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Background and Objectives: A pharmacokinetic model has been developed to quantify the drug–drug interactions of tacrolimus with concentration-dependent inhibition of cytochrome P450 (CYP) 3A4 from voriconazole and clarithromycin based on the CYP3A5 and CYP2C19 genotypes. Methods: This retrospective study recruited unrelated bone marrow transplant recipients receiving oral tacrolimus concomitantly with voriconazole and clarithromycin. The published population pharmacokinetic model that implemented genotypes of CYP3A5 (tacrolimus) and CYP2C19 (voriconazole) was integrated. The tested CYP3A4 inhibition models (Sigmoid efficacy maximum [E], E, log-linear, and linear) were a function of competitive inhibition of voriconazole and mechanism-based inhibition of clarithromycin in a virtual enzyme compartment. Results: The total tacrolimus trough concentrations were 119 points, with a median of 4.3 (range: 2.0–9.9) ng/mL (n = 3). The final model comprised the Sigmoid E model for voriconazole and clarithromycin, which depicted time-course alterations in tacrolimus concentration and clearance when given voriconazole and clarithromycin. Conclusions: These findings could facilitate the model-informed precision dosing of tacrolimus after unrelated bone marrow transplant.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85204622797&origin=inward; http://dx.doi.org/10.1007/s13318-024-00915-2; http://www.ncbi.nlm.nih.gov/pubmed/39313741; https://link.springer.com/10.1007/s13318-024-00915-2; https://dx.doi.org/10.1007/s13318-024-00915-2; https://link.springer.com/article/10.1007/s13318-024-00915-2
Springer Science and Business Media LLC
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