Franc Andreu1,2, Helena Colom2, Laure Elens3,4, Teun van Gelder5,6,4, Ronald H N van Schaik6,4, Dennis A Hesselink5,4, Oriol Bestard1, Joan Torras1, Josep M Cruzado1, Josep M Grinyó1, Nuria Lloberas7. 1. Laboratory 4122, Nephrology Service and Laboratory of Experimental Nephrology, University of Barcelona, Campus Bellvitge, Pavelló de Govern, Feixa Llarga, s/n, L'Hospitalet de Llobregat, 08907, Barcelona, Spain. 2. Biopharmaceutics and Pharmacokinetics Unit, Department of Pharmacy and Pharmaceutical Technology Department, School of Pharmacy, University of Barcelona, Barcelona, Spain. 3. Department of Integrated PharmacoMetrics, PharmacoGenomics and PharmacoKinetics (PMGK), Louvain Drug Research Institute (LDRI), Université Catholique de Louvain (UCL), Brussels, Belgium. 4. Department of Clinical Chemistry, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 5. Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 6. Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 7. Laboratory 4122, Nephrology Service and Laboratory of Experimental Nephrology, University of Barcelona, Campus Bellvitge, Pavelló de Govern, Feixa Llarga, s/n, L'Hospitalet de Llobregat, 08907, Barcelona, Spain. nlloberas@ub.edu.
Abstract
BACKGROUND: Single nucleotide polymorphisms (SNPs) in the CYP3A5 and CYP3A4 genes have been reported to be an important cause of variability in the pharmacokinetics of tacrolimus in renal transplant patients. The aim of this study was to merge all of the new genetic information available with tacrolimus pharmacokinetics to generate a more robust population model with data from renal transplant recipients. METHODS: Tacrolimus exposure data from 304 renal transplant recipients were collected throughout the first year after transplantation and were simultaneously analyzed with a population pharmacokinetic approach using NONMEM® version 7.2. RESULTS: The tacrolimus whole-blood concentration versus time data were best described by a two-open-compartment model with inter-occasion variability assigned to plasma clearance. The following factors led to the final model, which significantly decreased the minimum objective function value (p < 0.001): a new genotype cluster variable combining the CYP3A5*3 and CYP3A4*22 SNPs defined as extensive, intermediate, and poor metabolizers; the standardization of tacrolimus whole blood concentrations to a hematocrit value of 45%; and age included as patients <63 years versus patients ≥63 years. External validation confirmed the prediction ability of the model with median bias and precision values of 1.17 ng/mL (95% confidence interval [CI] -3.68 to 4.50) and 1.64 ng/mL (95% CI 0.11-5.50), respectively. Simulations showed that, for a given age and hematocrit at the same fixed dose, extensive metabolizers required the highest doses followed by intermediate metabolizers and then poor metabolizers. CONCLUSIONS: Tacrolimus disposition in renal transplant recipients was described using a new population pharmacokinetic model that included the CYP3A5*3 and CYP3A4*22 genotype, age, and hematocrit.
BACKGROUND: Single nucleotide polymorphisms (SNPs) in the CYP3A5 and CYP3A4 genes have been reported to be an important cause of variability in the pharmacokinetics of tacrolimus in renal transplant patients. The aim of this study was to merge all of the new genetic information available with tacrolimus pharmacokinetics to generate a more robust population model with data from renal transplant recipients. METHODS:Tacrolimus exposure data from 304 renal transplant recipients were collected throughout the first year after transplantation and were simultaneously analyzed with a population pharmacokinetic approach using NONMEM® version 7.2. RESULTS: The tacrolimus whole-blood concentration versus time data were best described by a two-open-compartment model with inter-occasion variability assigned to plasma clearance. The following factors led to the final model, which significantly decreased the minimum objective function value (p < 0.001): a new genotype cluster variable combining the CYP3A5*3 and CYP3A4*22 SNPs defined as extensive, intermediate, and poor metabolizers; the standardization of tacrolimus whole blood concentrations to a hematocrit value of 45%; and age included as patients <63 years versus patients ≥63 years. External validation confirmed the prediction ability of the model with median bias and precision values of 1.17 ng/mL (95% confidence interval [CI] -3.68 to 4.50) and 1.64 ng/mL (95% CI 0.11-5.50), respectively. Simulations showed that, for a given age and hematocrit at the same fixed dose, extensive metabolizers required the highest doses followed by intermediate metabolizers and then poor metabolizers. CONCLUSIONS:Tacrolimus disposition in renal transplant recipients was described using a new population pharmacokinetic model that included the CYP3A5*3 and CYP3A4*22 genotype, age, and hematocrit.
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