Tacrolimus updated guidelines through popPK modeling: how to benefit more from CYP3A pre-emptive genotyping prior to kidney transplantation

dc.contributor.author
Hesselink, Dennis A.
dc.contributor.author
Woillard, Jean-Baptiste
dc.contributor.author
Mourad, Michel
dc.contributor.author
Neely, Michael
dc.contributor.author
Capron, Arnaud
dc.contributor.author
van Schaik, Ron H.
dc.contributor.author
van Gelder, Teun
dc.contributor.author
Lloberas Blanch, Núria
dc.contributor.author
Marquet, Pierre
dc.contributor.author
Haufroid, Vincent
dc.contributor.author
Elens, Laure
dc.date.issued
2025-04-03T17:50:10Z
dc.date.issued
2025-04-03T17:50:10Z
dc.date.issued
2017-06-08
dc.date.issued
2025-04-03T17:50:10Z
dc.identifier
1663-9812
dc.identifier
https://hdl.handle.net/2445/220251
dc.identifier
735974
dc.identifier
28642710
dc.description.abstract
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.
dc.format
14 p.
dc.format
application/pdf
dc.language
eng
dc.publisher
Frontiers Media
dc.relation
Reproducció del document publicat a: https://doi.org/10.3389/fphar.2017.00358
dc.relation
Frontiers in Pharmacology, 2017, vol. 8, p. 358-364
dc.relation
https://doi.org/10.3389/fphar.2017.00358
dc.rights
cc-by (c) Woillard, J.B. et al., 2017
dc.rights
http://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Infermeria Fonamental i Clínica)
dc.subject
Farmacocinètica
dc.subject
Immunosupressors
dc.subject
Trasplantament renal
dc.subject
Posologia
dc.subject
Pharmacokinetics
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Immunosupressive agents
dc.subject
Kidney transplantation
dc.subject
Posology
dc.title
Tacrolimus updated guidelines through popPK modeling: how to benefit more from CYP3A pre-emptive genotyping prior to kidney transplantation
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion


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