title: Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in renal transplant recipients on a new once-daily formulation.
abstract: OBJECTIVE
  Advagraf is a new extended-release once-daily formulation of tacrolimus, a potent immunosuppressant widely used in renal transplantation. The aims of his study were (i) to develop a population pharmacokinetic model for once-daily tacrolimus in adult renal transplant patients; and (ii) to develop a Bayesian estimator able to reliably estimate individual pharmacokinetic parameters and exposure indices.
  
  
  METHODS
  Full pharmacokinetic profiles obtained from 41 adult renal transplant patients who had been switched from ciclosporin to a single daily dose of the new once-daily tacrolimus formulation for more than 6 months were analysed. Tacrolimus concentrations were measured using validated turbulent flow chromatography-tandem mass spectrometry methods. Population parameters were computed using nonlinear mixed-effect modelling software (NONMEM Version VI). The patients were randomly divided into (i) a model-building test group (n = 29); and (ii) a validation group (n = 12). Population pharmacokinetic analysis was performed to estimate the effects on tacrolimus pharmacokinetics of demographic characteristics (sex, bodyweight, age), drug interaction with prednisolone, laboratory test results (the haematocrit, haemaglobin level and serum creatinine level) and cytochrome P450 (CYP) 3A5 (CYP3A5) genetic polymorphism. The population pharmacokinetic model was further refined by taking into account all of the data from the 41 patients, and the final model was validated using a bootstrap and a visual predictive check. For Bayesian estimation, the best limited-sampling strategy was determined on the basis of the D-optimality criterion and validation performed in the validation group.
  
  
  RESULTS
  The trapezoidal area under the whole-blood concentration time curve from 0 to 24 hours (AUC(24)) of tacrolimus varied by up to 50% for the same trough concentration value. The pharmacokinetics of once-daily tacrolimus were well described by a two-compartment model combined with an Erlang distribution to describe the absorption phase. The CYP3A5 genotype was the only covariate retained in the final model. The apparent clearance of tacrolimus was 2-fold higher in expressers (with the CYP3A5*1/*1 and CYP3A5*1/*3 genotypes) than in non-expressers (with the CYP3A5*3/*3 genotype). This factor explained around 25% of the interindividual variability in the apparent clearance. A posteriori Bayesian estimation allowed accurate prediction of the AUC(24) of once-daily tacrolimus, using just three sampling times (0, 1 and 3 hours post-dose) with a nonsignificant mean bias of 0.7% (range 16-20%) and good precision (root mean square error 9%).
  
  
  CONCLUSIONS
  Population pharmacokinetic analysis of once-daily tacrolimus in renal transplant recipients resulted in identification of the CYP3A5*1/*3 genotype as a significant covariate on the apparent clearance of tacrolimus, and the design of an accurate maximum a posteriori Bayesian estimator based on three blood concentration measurements and this covariate. Such a tool could be helpful for comparing different exposure indices or different target levels. It could contribute to improvement of the efficacy and tolerability of once-daily tacrolimus in some patients.
authors.affiliation: INSERM Unit 850, Limoges University and CHU Limoges, Limoges, France.
authors.forename: Khaled
authors.initials: K
authors.lastname: Benkali
authors.forename: Lionel
authors.initials: L
authors.lastname: Rostaing
authors.forename: Aurélie
authors.initials: A
authors.lastname: Premaud
authors.forename: Jean-Baptiste
authors.initials: JB
authors.lastname: Woillard
authors.forename: Franck
authors.initials: F
authors.lastname: Saint-Marcoux
authors.forename: Saik
authors.initials: S
authors.lastname: Urien
authors.forename: Nassim
authors.initials: N
authors.lastname: Kamar
authors.forename: Pierre
authors.initials: P
authors.lastname: Marquet
authors.forename: Annick
authors.initials: A
authors.lastname: Rousseau
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D001499:Bayes Theorem; D003577:Cytochrome P-450 Enzyme System / Q000235:genetics; D003692:Delayed-Action Preparations / Q000008:administration & dosage; D005260:Female; D005838:Genotype; D006801:Humans; D007166:Immunosuppressive Agents / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D016030:Kidney Transplantation; D008297:Male; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D008954:Models, Biological; D020641:Polymorphism, Single Nucleotide; D016559:Tacrolimus / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*
chemical_list: D003692:Delayed-Action Preparations; D007166:Immunosuppressive Agents; D003577:Cytochrome P-450 Enzyme System; C473667:cytochrome P-450 CYP3A45; D016559:Tacrolimus
references.citation: Clin Pharmacokinet. 1995 Dec;29(6):404-30
references.pmid: 8787947
references.citation: Ther Drug Monit. 2009 Apr;31(2):187-97
references.pmid: 19258929
references.citation: Clin Pharmacol Ther. 2006 Jul;80(1):51-60
references.pmid: 16815317
references.citation: J Am Soc Nephrol. 2005 Jun;16(6):1839-48
references.pmid: 15800121
references.citation: J Pharmacokinet Biopharm. 1981 Aug;9(4):503-12
references.pmid: 7310648
references.citation: Clin Chem Lab Med. 2006;44(10):1192-8
references.pmid: 17032130
references.citation: Clin Pharmacokinet. 2005;44(12):1317-28
references.pmid: 16372829
references.citation: Transplant Proc. 1999 Nov;31(7A):21S-24S
references.pmid: 10576037
references.citation: Ther Drug Monit. 2009 Apr;31(2):139-52
references.pmid: 19177031
references.citation: Am J Transplant. 2007 Mar;7(3):595-608
references.pmid: 17217442
references.citation: Clin Pharmacol Ther. 2002 Dec;72(6):660-9
references.pmid: 12496747
references.citation: Transplant Proc. 2009 Jul-Aug;41(6):2115-7
references.pmid: 19715848
references.citation: Basic Clin Pharmacol Toxicol. 2008 Dec;103(6):546-52
references.pmid: 19067682
references.citation: Drugs. 2007;67(13):1944-5
references.pmid: 17722963
references.citation: Am J Transplant. 2007 Jun;7(6):1609-15
references.pmid: 17511684
references.citation: Clin Pharmacokinet. 2009;48(12):805-16
references.pmid: 19902988
references.citation: Comput Methods Programs Biomed. 1999 Apr;59(1):19-29
references.pmid: 10215174
references.citation: Clin Pharmacokinet. 2004;43(14):1055-7
references.pmid: 15530133
references.citation: Transplantation. 2007 Jun 27;83(12):1648-51
references.pmid: 17589351
references.citation: Transplant Proc. 2005 Mar;37(2):1211-3
references.pmid: 15848672
references.citation: Transplant Proc. 2005 Mar;37(2):867-70
references.pmid: 15848559
references.citation: Ther Drug Monit. 2004 Feb;26(1):23-30
references.pmid: 14749545
references.citation: J Clin Pharmacol. 2001 May;41(5):542-51
references.pmid: 11361051