OBJECTIVE: To investigate the population pharmacokinetics of tacrolimus in an adult liver transplant cohort using routine drug monitoring data and to identify patient characteristics that influence pharmacokinetic parameters. METHODS: Tacrolimus pharmacokinetics was studied in 37 adult patients using a population approach performed with NONMEM. RESULTS: A one-compartment open model with linear absorption and elimination adequately described the data. The apparent clearance (CL) was approximately zero in the immediate post-operative days (PODs) and then rapidly increased as a function of POD to reach a plateau. This was modelled as a sigmoid relationship with the characteristic parameters CL(max) (plateau), TCL(50) (time to obtain 50% of the plateau) and gamma (coefficient of sigmoidicity). This clearance model was thought to describe the hepatic function regeneration after transplantation. Typical population estimates (percentage inter-individual variability) of CL(max), TCL50, and gamma and apparent distribution volumes (V) were 36 l/h (43%), 6.3 days (33%), and 4.9 l and 1870 l (49%), respectively. The CL(max) was negatively related to plasma albumin, and TCL50 was positively related to aspartate amino transferase (ASAT). Bayesian estimations performed at different POD times indicated that acceptable precisions in individual pharmacokinetic predictions could be obtained after the 15th POD. CONCLUSION: Tacrolimus clearance modelling showed that there was a large variation in individual CL estimates up to the 15th day post-surgery. After this period, the mean error resulting from the Bayesian estimation was strongly decreased and this estimation method could be applicable and should limit tacrolimus monitoring.
OBJECTIVE: To investigate the population pharmacokinetics of tacrolimus in an adult liver transplant cohort using routine drug monitoring data and to identify patient characteristics that influence pharmacokinetic parameters. METHODS:Tacrolimus pharmacokinetics was studied in 37 adult patients using a population approach performed with NONMEM. RESULTS: A one-compartment open model with linear absorption and elimination adequately described the data. The apparent clearance (CL) was approximately zero in the immediate post-operative days (PODs) and then rapidly increased as a function of POD to reach a plateau. This was modelled as a sigmoid relationship with the characteristic parameters CL(max) (plateau), TCL(50) (time to obtain 50% of the plateau) and gamma (coefficient of sigmoidicity). This clearance model was thought to describe the hepatic function regeneration after transplantation. Typical population estimates (percentage inter-individual variability) of CL(max), TCL50, and gamma and apparent distribution volumes (V) were 36 l/h (43%), 6.3 days (33%), and 4.9 l and 1870 l (49%), respectively. The CL(max) was negatively related to plasma albumin, and TCL50 was positively related to aspartate amino transferase (ASAT). Bayesian estimations performed at different POD times indicated that acceptable precisions in individual pharmacokinetic predictions could be obtained after the 15th POD. CONCLUSION:Tacrolimus clearance modelling showed that there was a large variation in individual CL estimates up to the 15th day post-surgery. After this period, the mean error resulting from the Bayesian estimation was strongly decreased and this estimation method could be applicable and should limit tacrolimus monitoring.
Authors: David W Holt; Victor W Armstrong; Andrea Griesmacher; Raymond G Morris; Kimberly L Napoli; Leslie M Shaw Journal: Ther Drug Monit Date: 2002-02 Impact factor: 3.681
Authors: F C Grenier; J Luczkiw; M Bergmann; S Lunetta; M Morrison; D Blonski; K Shoemaker; M Kobayashi Journal: Transplant Proc Date: 1991-12 Impact factor: 1.066
Authors: W J Sandborn; G M Lawson; T J Cody; M K Porayko; J E Hay; G J Gores; J L Steers; R A Krom; R H Wiesner Journal: Hepatology Date: 1995-01 Impact factor: 17.425
Authors: T Kino; H Hatanaka; S Miyata; N Inamura; M Nishiyama; T Yajima; T Goto; M Okuhara; M Kohsaka; H Aoki Journal: J Antibiot (Tokyo) Date: 1987-09 Impact factor: 2.649
Authors: T Kino; H Hatanaka; M Hashimoto; M Nishiyama; T Goto; M Okuhara; M Kohsaka; H Aoki; H Imanaka Journal: J Antibiot (Tokyo) Date: 1987-09 Impact factor: 2.649
Authors: R Venkataramanan; L M Shaw; L Sarkozi; R Mullins; J Pirsch; G MacFarlane; D Scheller; D Ersfeld; M Frick; W E Fitzsimmons; M Virji; A Jain; K L Brayman; A Shaked Journal: J Clin Pharmacol Date: 2001-05 Impact factor: 3.126
Authors: L Bäckman; M Nicar; M Levy; D Distant; C Eisenstein; T Renard; R Goldstein; B Husberg; T A Gonwa; G Klintmalm Journal: Transplantation Date: 1994-02-27 Impact factor: 4.939
Authors: M Yasuhara; T Hashida; M Toraguchi; Y Hashimoto; M Kimura; K Inui; R Hori; Y Inomata; K Tanaka; Y Yamaoka Journal: Transplant Proc Date: 1995-02 Impact factor: 1.066
Authors: Itziar Oteo; John C Lukas; Nerea Leal; Elena Suarez; Andres Valdivieso; Mikel Gastaca; Jorge Ortiz de Urbina; Rosario Calvo Journal: Eur J Clin Pharmacol Date: 2012-06-03 Impact factor: 2.953
Authors: V Guy-Viterbo; A Scohy; R K Verbeeck; R Reding; P Wallemacq; Flora Tshinanu Musuamba Journal: Eur J Clin Pharmacol Date: 2013-04-16 Impact factor: 2.953