2025-04-03T17:50:10Z
2025-04-03T17:50:10Z
2017-06-08
2025-04-03T17:50:10Z
Tacrolimus (Tac) is a profoundly effective immunosuppressant that reduces the risk of rejection after solid organ transplantation. However, its use is hampered by its narrow therapeutic window along with its highly variable pharmacological (pharmacokinetic [PK] and pharmacodynamic [PD]) profile. Part of this variability is explained by genetic polymorphisms affecting the metabolic pathway. The integration of CYP3A4 and CY3A5 genotype in tacrolimus population-based PK (PopPK) modeling approaches has been proven to accurately predict the dose requirement to reach the therapeutic window. The objective of the present study was to develop an accurate PopPK model in a cohort of 59 kidney transplant patients to deliver this information to clinicians in a clear and actionable manner. We conducted a non-parametric non-linear effects PopPK modeling analysis in Pmetrics®. Patients were genotyped for the CYP3A4∗22 and CYP3A5∗3 alleles and were classified into 3 different categories [poor-metabolizers (PM), Intermediate-metabolizers (IM) or extensive-metabolizers (EM)]. A one-compartment model with double gamma absorption route described very accurately the tacrolimus PK. In covariate analysis, only CYP3A genotype was retained in the final model (Δ-2LL = -73). Our model estimated that tacrolimus concentrations were 33% IC95%[20-26%], 41% IC95%[36-45%] lower in CYP3A IM and EM when compared to PM, respectively. Virtually, we proved that defining different starting doses for PM, IM and EM would be beneficial by ensuring better probability of target concentrations attainment allowing us to define new dosage recommendations according to patient CYP3A genetic profile.
Article
Published version
English
Farmacocinètica; Immunosupressors; Trasplantament renal; Posologia; Pharmacokinetics; Immunosupressive agents; Kidney transplantation; Posology
Frontiers Media
Reproducció del document publicat a: https://doi.org/10.3389/fphar.2017.00358
Frontiers in Pharmacology, 2017, vol. 8, p. 358-364
https://doi.org/10.3389/fphar.2017.00358
cc-by (c) Woillard, J.B. et al., 2017
http://creativecommons.org/licenses/by/4.0/