Personalized medicine · 2026
A population pharmacokinetic model for early follow-up dosing of tacrolimus in Tunisian kidney transplant recipients.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Abderahmene Amani, Francke Marith I, Ammar Meriam, Andrews Louise M, Hesselink Dennis A, Amor Dorra, Sahtout Wissal, Awatif Azzabi, Bouslama Ali, Zellama Dorsaf, Omezzine Asma, De Winter Brenda C M
Аннотация
INTRODUCTION: Tacrolimus is the cornerstone of immunosuppressive therapy in kidney transplantation. However, it exhibits significant pharmacokinetic (PK) variability among patients. Therefore, Population Pharmacokinetic (PopPK) modeling is crucial for personalized tacrolimus treatment. While PopPK models have been extensively developed for transplant patients in Asian and Caucasian populations, it is true that limited data are available for Arab/North-African populations. Thus, our objective was to develop a PopPK model for the Tunisian population to optimize tacrolimus treatment after kidney transplantation.
METHODS: Data on tacrolimus exposure and other patient factors were collected for the first 3 months after kidney transplantation. Genotyping for 6-SNPs was performed. The PK analysis was performed using nonlinear mixed-effects modeling.
RESULTS: A total of 1901 whole-blood pre-dose tacrolimus concentrations (C0) of 196 Tunisian kidney transplant recipients were collected and described using a two-compartment model. CYP3A5*1 carriers had a 1.28-fold higher tacrolimus clearance (CL/F) compared to non-carriers. Higher body mass index (BMI) and lower hematocrit resulted in increased tacrolimus CL/F.
CONCLUSION: In the first 3 months post-transplant, tacrolimus CL/F was significantly influenced by CYP3A5 genotype, BMI, hematocrit, and time after transplantation. The model supports individualized dose adjustment; prospective external validation and a simple dose-adjustment algorithm are warranted to facilitate clinical implementation.
METHODS: Data on tacrolimus exposure and other patient factors were collected for the first 3 months after kidney transplantation. Genotyping for 6-SNPs was performed. The PK analysis was performed using nonlinear mixed-effects modeling.
RESULTS: A total of 1901 whole-blood pre-dose tacrolimus concentrations (C0) of 196 Tunisian kidney transplant recipients were collected and described using a two-compartment model. CYP3A5*1 carriers had a 1.28-fold higher tacrolimus clearance (CL/F) compared to non-carriers. Higher body mass index (BMI) and lower hematocrit resulted in increased tacrolimus CL/F.
CONCLUSION: In the first 3 months post-transplant, tacrolimus CL/F was significantly influenced by CYP3A5 genotype, BMI, hematocrit, and time after transplantation. The model supports individualized dose adjustment; prospective external validation and a simple dose-adjustment algorithm are warranted to facilitate clinical implementation.