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Original article
Predicting tacrolimus concentrations in children receiving a heart transplant using a population pharmacokinetic model
  1. Joseph E Rower1,
  2. Chris Stockmann1,
  3. Matthew W Linakis1,
  4. Shaun S Kumar1,
  5. Xiaoxi Liu1,
  6. E Kent Korgenski2,
  7. Catherine M T Sherwin1,3,
  8. Kimberly M Molina4,5
  1. 1 Department of Pediatrics, Division of Clinical Pharmacology, University of Utah School of Medicine, Salt Lake City, Utah, USA
  2. 2 Pediatric Clinical Program, Intermountain Healthcare, Salt Lake City, Utah, USA
  3. 3 Department of Pharmacology and Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
  4. 4 Primary Children’s Hospital, Intermountain Healthcare, Salt Lake City, Utah, USA
  5. 5 Department of Pediatrics, Division of Cardiology, University of Utah School of Medicine, Salt Lake City, Utah, USA
  1. Correspondence to and Dr Joseph E Rower; joseph.rower{at}


Objective Immunosuppressant therapy plays a pivotal role in transplant success and longevity. Tacrolimus, a primary immunosuppressive agent, is well known to exhibit significant pharmacological interpatient and intrapatient variability. This variability necessitates the collection of serial trough concentrations to ensure that the drug remains within therapeutic range. The objective of this study was to build a population pharmacokinetic (PK) model and use it to determine the minimum number of trough samples needed to guide the prediction of an individual’s future concentrations.

Design, setting and patients Retrospective data from 48 children who received tacrolimus as inpatients at Primary Children’s Hospital in Salt Lake City, Utah were included in the study. Data were collected within the first 6 weeks after heart transplant.

Outcome measures Data analysis used population PK modelling techniques in NONMEM. Predictive ability of the model was determined using median prediction error (MPE, a measure of bias) and median absolute prediction error (MAPE, a measure of accuracy). Of the 48 children in the study, 30 were used in the model building dataset, and 18 in the model validation dataset.

Results Concentrations ranged between 1.5 and 37.7 µg/L across all collected data, with only 40% of those concentrations falling within the targeted concentration range (12 to 16 µg/L). The final population PK model contained the impact of age (on volume), creatinine clearance (on elimination rate) and fluconazole use (on elimination rate) as covariates. Our analysis demonstrated that as few as three concentrations could be used to predict future concentrations, with negligible bias (MPE (95% CI)=0.10% (−2.9% to 3.7%)) and good accuracy (MAPE (95% CI)=24.1% (19.7% to 27.7%)).

Conclusions The use of PK in dose guidance has the potential to provide significant benefits to clinical care, including dose optimisation during the early stages of therapy, and the potential to limit the need for frequent drug monitoring.

  • pharmacology
  • therapeutics
  • cardiac surgery
  • pediatrics

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:

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  • Contributors JER performed the data analysis and wrote the manuscript. CS helped design the study and participated in the data analysis. MWL, SSK and XL edited the manuscript and helped with the data analysis. EKK queried the data and was involved in the study design. CMTS and KMM were involved in the study design and edited the manuscript.

  • Competing interests None declared.

  • Ethics approval University of Utah, Intermountain Healthcare and Primary Children’s Hospital Institutional Review Board.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Data used in this manuscript were collected from Intermountain Healthcare, which does not allow any patient data to be shared.

  • Author note Dr Stockmann completed his work on this project before his untimely passing.

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