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

dc.contributor.authorHesselink, Dennis A.
dc.contributor.authorWoillard, Jean-Baptiste
dc.contributor.authorMourad, Michel
dc.contributor.authorNeely, Michael
dc.contributor.authorCapron, Arnaud
dc.contributor.authorvan Schaik, Ron H.
dc.contributor.authorvan Gelder, Teun
dc.contributor.authorLloberas Blanch, Núria
dc.contributor.authorMarquet, Pierre
dc.contributor.authorHaufroid, Vincent
dc.contributor.authorElens, Laure
dc.date.accessioned2025-04-03T17:50:10Z
dc.date.available2025-04-03T17:50:10Z
dc.date.issued2017-06-08
dc.date.updated2025-04-03T17:50:10Z
dc.description.abstractTacrolimus (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.extent14 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec735974
dc.identifier.issn1663-9812
dc.identifier.pmid28642710
dc.identifier.urihttps://hdl.handle.net/2445/220251
dc.language.isoeng
dc.publisherFrontiers Media
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3389/fphar.2017.00358
dc.relation.ispartofFrontiers in Pharmacology, 2017, vol. 8, p. 358-364
dc.relation.urihttps://doi.org/10.3389/fphar.2017.00358
dc.rightscc-by (c) Woillard, J.B. et al., 2017
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Infermeria Fonamental i Clínica)
dc.subject.classificationFarmacocinètica
dc.subject.classificationImmunosupressors
dc.subject.classificationTrasplantament renal
dc.subject.classificationPosologia
dc.subject.otherPharmacokinetics
dc.subject.otherImmunosupressive agents
dc.subject.otherKidney transplantation
dc.subject.otherPosology
dc.titleTacrolimus updated guidelines through popPK modeling: how to benefit more from CYP3A pre-emptive genotyping prior to kidney transplantation
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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