Literature DB >> 24526611

Determination of the most influential sources of variability in tacrolimus trough blood concentrations in adult liver transplant recipients: a bottom-up approach.

Cécile Gérard1, Jeanick Stocco, Anne Hulin, Benoit Blanchet, Céline Verstuyft, François Durand, Filomena Conti, Christophe Duvoux, Michel Tod.   

Abstract

Tacrolimus, an immunosuppressant drug, presents a narrow therapeutic window and a large pharmacokinetic variability with poor correlation between drug dosing regimen and blood concentration. The objective was to identify predictive factors influencing tacrolimus trough concentrations (C0) using a bottom-up approach. A physiologically based pharmacokinetic (PBPK) model of tacrolimus was proposed, taking into account the body weight, the proportion of fat (P(fat)), hematocrit, lipid fraction of organs, typical intrinsic clearance (CLi(typ)), CYP3A5 genotype of liver donor, plasma unbound fraction of tacrolimus (fu(p)), and concomitant drugs (CYP3A4 inhibitors). For the evaluation of the PBPK model, mean C0 and concentrations 2 h after oral dose of tacrolimus were compared with those from 66 liver transplant recipients included in a multicentric pharmacokinetic study and were found very close. Tacrolimus concentration profiles were simulated in a virtual population defined by a set of covariate values similar to those from the real population. The sensitivity of tacrolimus C0 with respect to each covariate has been tested to identify the most influential ones. With the range of covariate values tested, the impact of each covariate on tacrolimus C0 may be ranked as follows: fu(p), CLi(typ), bioavailability, body weight, hematocrit, CYP3A5 polymorphism, P(fat), and CYP3A4 inhibitory drug-drug interactions. Values for initial dosing regimen of tacrolimus in order to reach a C0 of 10 ng/ml at day 5 (assuming a constant dosing schedule) as a function of CYP3A5 donor genotype and patient's hematocrit and body weight are proposed.

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Year:  2014        PMID: 24526611      PMCID: PMC4012056          DOI: 10.1208/s12248-014-9577-8

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  57 in total

1.  Correlation of tacrolimus levels in peripheral blood mononuclear cells with histological staging of rejection after liver transplantation: preliminary results of a prospective study.

Authors:  Arnaud Capron; Jan Lerut; Dominique Latinne; Jacques Rahier; Vincent Haufroid; Pierre Wallemacq
Journal:  Transpl Int       Date:  2011-10-08       Impact factor: 3.782

2.  Comparison of predicted body fat percentage from anthropometric methods and from impedance in university students.

Authors:  Marta Arroyo; Ana M Rocandio; Laura Ansotegui; Hector Herrera; Itziar Salces; Esther Rebato
Journal:  Br J Nutr       Date:  2004-11       Impact factor: 3.718

3.  The effect of graft function on FK506 plasma levels, dosages, and renal function, with particular reference to the liver.

Authors:  K Abu-Elmagd; J J Fung; M Alessiani; A Jain; R Venkataramanan; V S Warty; S Takaya; S Todo; W D Shannon; T E Starzl
Journal:  Transplantation       Date:  1991-07       Impact factor: 4.939

4.  FK-506, a novel immunosuppressant isolated from a Streptomyces. II. Immunosuppressive effect of FK-506 in vitro.

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

5.  Population pharmacokinetic and pharmacogenomic analysis of tacrolimus in pediatric living-donor liver transplant recipients.

Authors:  Masahide Fukudo; Ikuko Yano; Satohiro Masuda; Maki Goto; Miwa Uesugi; Toshiya Katsura; Yasuhiro Ogura; Fumitaka Oike; Yasutsugu Takada; Hiroto Egawa; Shinji Uemoto; Ken-ichi Inui
Journal:  Clin Pharmacol Ther       Date:  2006-10       Impact factor: 6.875

6.  FK-506, a novel immunosuppressant isolated from a Streptomyces. I. Fermentation, isolation, and physico-chemical and biological characteristics.

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

7.  FK506 trough levels in whole blood and plasma in liver transplant recipients. Correlation with clinical events and side effects.

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

8.  Impact of cytochrome p450 3A5 genetic polymorphism on tacrolimus doses and concentration-to-dose ratio in renal transplant recipients.

Authors:  Eric Thervet; Dany Anglicheau; Barry King; Marie-Hélène Schlageter; Bruno Cassinat; Philippe Beaune; Christophe Legendre; Ann K Daly
Journal:  Transplantation       Date:  2003-10-27       Impact factor: 4.939

9.  Forecasting of blood tacrolimus concentrations based on the Bayesian method in adult patients receiving living-donor liver transplantation.

Authors:  Masahide Fukudo; Ikuko Yano; Sachio Fukatsu; Hideyuki Saito; Shinji Uemoto; Tetsuya Kiuchi; Koichi Tanaka; Ken-ichi Inui
Journal:  Clin Pharmacokinet       Date:  2003       Impact factor: 6.447

Review 10.  Mechanisms of clinically relevant drug interactions associated with tacrolimus.

Authors:  Uwe Christians; Wolfgang Jacobsen; Leslie Z Benet; Alfonso Lampen
Journal:  Clin Pharmacokinet       Date:  2002       Impact factor: 6.447

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  8 in total

Review 1.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

Review 2.  Carbapenem-Resistant Enterobacteriaceae in Solid Organ Transplantation: Management Principles.

Authors:  Olivia Smibert; Michael J Satlin; Anoma Nellore; Anton Y Peleg
Journal:  Curr Infect Dis Rep       Date:  2019-06-10       Impact factor: 3.725

3.  Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach.

Authors:  Tom M Nanga; Thao T P Doan; Pierre Marquet; Flora T Musuamba
Journal:  Br J Clin Pharmacol       Date:  2019-12-17       Impact factor: 4.335

4.  Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation.

Authors:  Kalluri Thishya; Kiran Kumar Vattam; Shaik Mohammad Naushad; Shree Bhushan Raju; Vijay Kumar Kutala
Journal:  PLoS One       Date:  2018-04-05       Impact factor: 3.240

5.  Unbound Plasma, Total Plasma, and Whole-Blood Tacrolimus Pharmacokinetics Early After Thoracic Organ Transplantation.

Authors:  Maaike A Sikma; Erik M Van Maarseveen; Claudine C Hunault; Javier M Moreno; Ed A Van de Graaf; Johannes H Kirkels; Marianne C Verhaar; Jan C Grutters; Jozef Kesecioglu; Dylan W De Lange; Alwin D R Huitema
Journal:  Clin Pharmacokinet       Date:  2020-06       Impact factor: 6.447

6.  A Theoretical Physiologically-Based Pharmacokinetic Approach to Ascertain Covariates Explaining the Large Interpatient Variability in Tacrolimus Disposition.

Authors:  Chie Emoto; Trevor N Johnson; David Hahn; Uwe Christians; Rita R Alloway; Alexander A Vinks; Tsuyoshi Fukuda
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-03-07

7.  Predictive engines based on pharmacokinetics modelling for tacrolimus personalized dosage in paediatric renal transplant patients.

Authors:  Manuel Prado-Velasco; Alberto Borobia; Antonio Carcas-Sansuan
Journal:  Sci Rep       Date:  2020-05-05       Impact factor: 4.379

8.  Pharmacokinetics of Once-Daily Extended-Release Tacrolimus Tablets Versus Twice-Daily Capsules in De Novo Liver Transplant.

Authors:  Derek A DuBay; Lewis Teperman; Kimi Ueda; Andrew Silverman; William Chapman; Angel E Alsina; Carmelina Tyler; Daniel R Stevens
Journal:  Clin Pharmacol Drug Dev       Date:  2019-01-22
  8 in total

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