Clinical Pharmacokinetics

, Volume 57, Issue 5, pp 625–636 | Cite as

Population Pharmacokinetics and Optimal Sampling Strategy for Model-Based Precision Dosing of Melphalan in Patients Undergoing Hematopoietic Stem Cell Transplantation

  • Kana Mizuno
  • Min Dong
  • Tsuyoshi Fukuda
  • Sharat Chandra
  • Parinda A. Mehta
  • Scott McConnell
  • Elias J. Anaissie
  • Alexander A. Vinks
Original Research Article



High-dose melphalan is an important component of conditioning regimens for patients undergoing hematopoietic stem cell transplantation. The current dosing strategy based on body surface area results in a high incidence of oral mucositis and gastrointestinal and liver toxicity. Pharmacokinetically guided dosing will individualize exposure and help minimize overexposure-related toxicity.


The purpose of this study was to develop a population pharmacokinetic model and optimal sampling strategy.


A population pharmacokinetic model was developed with NONMEM using 98 observations collected from 15 adult patients given the standard dose of 140 or 200 mg/m2 by intravenous infusion. The determinant-optimal sampling strategy was explored with PopED software. Individual area under the curve estimates were generated by Bayesian estimation using full and the proposed sparse sampling data. The predictive performance of the optimal sampling strategy was evaluated based on bias and precision estimates. The feasibility of the optimal sampling strategy was tested using pharmacokinetic data from five pediatric patients.


A two-compartment model best described the data. The final model included body weight and creatinine clearance as predictors of clearance. The determinant-optimal sampling strategies (and windows) were identified at 0.08 (0.08–0.19), 0.61 (0.33–0.90), 2.0 (1.3–2.7), and 4.0 (3.6–4.0) h post-infusion. An excellent correlation was observed between area under the curve estimates obtained with the full and the proposed four-sample strategy (R 2 = 0.98; p < 0.01) with a mean bias of −2.2% and precision of 9.4%. A similar relationship was observed in children (R 2 = 0.99; p < 0.01).


The developed pharmacokinetic model-based sparse sampling strategy promises to achieve the target area under the curve as part of precision dosing.


Compliance with Ethical Standards


This work was supported by the University of Arkansas for Medical Sciences (EJA) and the University of Arkansas for Medical Sciences Medical Research Endowment (SM). In addition, this work was supported in part by funding from a National Institutes of Health grant [5T32HD069054] (MD).

Conflict of interest

Kana Mizuno, Min Dong, Tsuyoshi Fukuda, Sharat Chandra, Parinda A. Mehta, Scott McConnell, Elias J. Anaissie, and Alexander A. Vinks have no conflicts of interest directly relevant to the content of this study.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Supplementary material

40262_2017_581_MOESM1_ESM.pdf (467 kb)
Supplementary material 1 (PDF 466 kb)


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Kana Mizuno
    • 1
  • Min Dong
    • 1
    • 5
  • Tsuyoshi Fukuda
    • 1
    • 5
  • Sharat Chandra
    • 2
    • 5
  • Parinda A. Mehta
    • 2
    • 5
  • Scott McConnell
    • 3
  • Elias J. Anaissie
    • 4
  • Alexander A. Vinks
    • 1
    • 5
  1. 1.Division of Clinical PharmacologyCincinnati Children’s Hospital Medical CenterCincinnatiUSA
  2. 2.Division of Bone Marrow Transplantation and Immune DeficiencyCincinnati Children’s Hospital Medical CenterCincinnatiUSA
  3. 3.AlkermesWalthamUSA
  4. 4.University of Cincinnati Cancer Institute, College of MedicineUniversity of CincinnatiCincinnatiUSA
  5. 5.Department of Pediatrics, College of MedicineUniversity of CincinnatiCincinnatiUSA

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