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<p>Tacrolimus is a narrow therapeutic index drug with wide intrapatient and interpatient pharmacokinetic variability and cytochrome P450 3A5 (<i>CYP3A5</i>) genotype-guided dosing recommendations. This review aimed to evaluate population pharmacokinetic models and dosing algorithms across all treatment settings that analyzed the influence of <i>CYP3A5</i> genotypic variation plus additional clinical covariates on tacrolimus pharmacokinetics. These effects were mathematically translated and summarized to provide a comparison between models. Changes in apparent clearance warranting tacrolimus dose adjustments were assessed and summarized by relative magnitude and direction. Sixty-eight tacrolimus population pharmacokinetic models were included in this review, including 55 developed for adults and 38 for kidney transplant recipients. The most frequently retained covariates on tacrolimus clearance were <i>CYP3A5</i> genotype (88%), body size (29%), hematocrit (29%), and days since transplant (28%). The median fold increase in apparent clearance, across all treatments, was 1.64 for CYP3A5 normal and intermediate metabolizer patients compared to poor metabolizer patients. As days since transplant increased, median tacrolimus apparent clearance increased in liver (<i>n</i>&#xa0;=&#xa0;6) and lung transplant (<i>n</i>&#xa0;=&#xa0;2) models but decreased early post-transplant and then subsequently increased in kidney transplant models (<i>n</i>&#xa0;=&#xa0;11). Concomitant administration of tacrolimus with -azole antifungals or Wuzhi capsules was associated with reduced tacrolimus apparent clearance (38% and 31%, respectively), while corticosteroids were associated with a 23% increase in apparent clearance. Based on our analysis, a substantial tacrolimus dose increase (≥&#xa0;75%) is required for CYP3A5 normal and intermediate metabolizer patients compared with poor metabolizer patients. Ultimately, these findings can be used to determine optimal personalized tacrolimus doses across a variety of disease states and treatment types.</p>

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A Review of Population Pharmacokinetic Models and Dosing Algorithms Assessing the Influence of CYP3A5 Genotype and Other Clinical Covariates on Tacrolimus Pharmacokinetics

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Riley M. Randolph,
  • Sara Jubas,
  • Li Gong,
  • Raman Venkataramanan,
  • Dhrita Khatri,
  • Pamala A. Jacobson,
  • David Metz,
  • Daniel J. Crona

摘要

Tacrolimus is a narrow therapeutic index drug with wide intrapatient and interpatient pharmacokinetic variability and cytochrome P450 3A5 (CYP3A5) genotype-guided dosing recommendations. This review aimed to evaluate population pharmacokinetic models and dosing algorithms across all treatment settings that analyzed the influence of CYP3A5 genotypic variation plus additional clinical covariates on tacrolimus pharmacokinetics. These effects were mathematically translated and summarized to provide a comparison between models. Changes in apparent clearance warranting tacrolimus dose adjustments were assessed and summarized by relative magnitude and direction. Sixty-eight tacrolimus population pharmacokinetic models were included in this review, including 55 developed for adults and 38 for kidney transplant recipients. The most frequently retained covariates on tacrolimus clearance were CYP3A5 genotype (88%), body size (29%), hematocrit (29%), and days since transplant (28%). The median fold increase in apparent clearance, across all treatments, was 1.64 for CYP3A5 normal and intermediate metabolizer patients compared to poor metabolizer patients. As days since transplant increased, median tacrolimus apparent clearance increased in liver (n = 6) and lung transplant (n = 2) models but decreased early post-transplant and then subsequently increased in kidney transplant models (n = 11). Concomitant administration of tacrolimus with -azole antifungals or Wuzhi capsules was associated with reduced tacrolimus apparent clearance (38% and 31%, respectively), while corticosteroids were associated with a 23% increase in apparent clearance. Based on our analysis, a substantial tacrolimus dose increase (≥ 75%) is required for CYP3A5 normal and intermediate metabolizer patients compared with poor metabolizer patients. Ultimately, these findings can be used to determine optimal personalized tacrolimus doses across a variety of disease states and treatment types.