ArticleCPT: pharmacometrics & systems pharmacology2026
Precision Dosing of Tacrolimus in Liver Transplantation: Integrating Donor-Recipient CYP3A5 Pharmacogenomics and Drug Interactions.
Article in CPT: pharmacometrics & systems pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Tacrolimus dosing in liver transplantation is complicated by a narrow therapeutic index and high CYP3A5 genetic variability. While saturable Michaelis-Menten kinetics can explain nonlinearities, identifying saturable parameters from routine clinical data remains challenging. This study aimed to determine the optimal structural model and develop a precision dosing algorithm. A population pharmacokinetic analysis was conducted in 114 patients, yielding 1989 observations. CYP3A5 genotypes were determined for both recipients and donors. Using Phoenix NLME, we rigorously compared linear versus Michaelis-Menten elimination structures. Stepwise covariate modeling was conducted to quantify the impact of genetic, physiological, and pharmacological factors, followed by Monte Carlo simulations to optimize dosing. A conventional two-compartment model adequately described the data without requiring a Michaelis-Menten structure. The combined CYP3A5 genotype exhibited a distinct stepwise reduction in apparent clearance from the homozygous expressor to the non-expressor group. Fluconazole emerged as a major inhibitor, reducing clearance by 33%, whereas prednisolone showed modest induction. Hemoglobin displayed a significant inverse relationship with clearance. Crucially, incorporating the daily dose as a covariate on clearance effectively captured the apparent nonlinear disposition. Simulations confirmed that fluconazole-treated patients require substantially lower doses (1.5-3.0 mg every 12 h) compared with fluconazole-free patients (2.5-7.0 mg every 12 h). A dose-dependent two-compartment model offers a basis for model-informed dose selection, addressing reported nonlinearities through physiological covariates. We provide a model-informed dosing algorithm that accounts for combined recipient/donor genetics and drug interactions, which may improve target attainment in liver transplant populations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.