Precision Dosing for Tacrolimus Using Genotypes and Clinical Factors in Kidney Transplant Recipients of European Ancestry

Mahmoud Al-Kofahi, William S. Oetting, David P. Schladt, Rory P. Remmel, Weihua Guan, Baolin Wu, Casey R. Dorr, Roslyn B. Mannon, Arthur J. Matas, Ajay K. Israni, Pamala A. Jacobson

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Genetic variation in the CYP3A4 and CYP3A5 (CYP3A4/5) genes, which encode the key enzymes in tacrolimus metabolism, is associated with tacrolimus clearance and dose requirements. Tacrolimus has a narrow therapeutic index with high intra- and intersubject variability, in part because of genetic variation. High tacrolimus clearance and low trough concentration are associated with a greater risk for rejection, whereas high troughs are associated with calcineurin-induced toxicity. The objective of this study was to develop a model of tacrolimus clearance with a dosing equation accounting for genotypes and clinical factors in adult kidney transplant recipients of European ancestry that could preemptively guide dosing. Recipients receiving immediate-release tacrolimus for maintenance immunosuppression from 2 multicenter studies were included. Participants in the GEN03 study were used for tacrolimus model development (n = 608 recipients) and was validated by prediction performance in the DeKAF Genomics study (n = 1361 recipients). Nonlinear mixed-effects modeling was used to develop the apparent oral tacrolimus clearance (CL/F) model. CYP3A4/5 genotypes and clinical covariates were tested for their influence on CL/F. The predictive performance of the model was determined by assessing the bias (median prediction error [ME] and median percentage error [MPE]) and the precision (root median squared error [RMSE]) of the model. CYP3A5*3, CYP3A4*22, corticosteroids, calcium channel blocker and antiviral drug use, age, and diabetes significantly contributed to the interindividual variability of oral tacrolimus apparent clearance. The bias (ME, MPE) and precision (RMSE) of the final model was good, 0.49 ng/mL, 6.5%, and 3.09 ng/mL, respectively. Prospective testing of this equation is warranted.

Original languageEnglish (US)
Pages (from-to)1035-1044
Number of pages10
JournalJournal of Clinical Pharmacology
Issue number8
Early online dateJan 29 2021
StatePublished - Aug 2021

Bibliographical note

Funding Information:
Support was received by the National Institutes of Health NIAID Genomics of Transplantation (5U19-AI070119) and ARRA supplement (5U19-AI070119).

Publisher Copyright:
© 2021, The American College of Clinical Pharmacology


  • genomics
  • kidney transplant
  • pharmacogenomics
  • population pharmacokinetics
  • tacrolimus

PubMed: MeSH publication types

  • Journal Article
  • Multicenter Study
  • Observational Study
  • Research Support, N.I.H., Extramural


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