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The AAPS Journal

, 21:68 | Cite as

Population Pharmacokinetic Modeling in the Presence of Missing Time-Dependent Covariates: Impact of Body Weight on Pharmacokinetics of Paracetamol in Neonates

  • Wojciech KrzyzanskiEmail author
  • Sarah F. Cook
  • Melanie Wilbaux
  • Catherine M. T. Sherwin
  • Karel Allegaert
  • An Vermeulen
  • John N. van den Anker
Research Article

Abstract

Body weight is the primary covariate in pharmacokinetics of many drugs and dramatically changes during the first weeks of life of neonates. The objective of this study is to determine if missing body weights in preterm and term neonates affect estimates of model parameters and which methods can be used to improve performance of a population pharmacokinetic model of paracetamol. Data for our analysis were obtained from previously published studies on the pharmacokinetics of intravenous paracetamol in neonates. We adopted a population model of body weight change in neonates to implement three previously introduced methods of handling missing covariates based on data imputation, likelihood function modification, and full random effects modeling. All models were implemented in NONMEM 7.4, and population parameters were estimated using the FOCE method. Our major finding was that missing body weights minimally affect population estimates of pharmacokinetic parameters but do affect the covariate relationship parameters, particularly the one describing dependence of clearance on body weight. None of the tested methods changed estimates of between-subject variability nor impacted the predictive performance of the model. Our analysis shows that a modeling approach towards handling missing covariates allows borrowing information gathered in various studies as long as they target the same population. This approach is particularly useful for handling time-dependent missing covariates.

KEY WORDS

full random effects model missing covariates paracetamol pediatric population 

Notes

Acknowledgments

Authors acknowledge Elaine Williams from Children’s National Health System, Washington, DC, for her support in data collection.

Funding Information

This work was supported by a fellowship from Janssen Research & Development, a division of Janssen Pharmaceutica N.V. (WK), the Agency for Innovation by Science and Technology in Flanders (IWT) Safepedrug grant number IWT/SBO 130033 (KA, AV), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD060543) (JvdA).

Supplementary material

12248_2019_331_MOESM1_ESM.docx (17.4 mb)
ESM 1 (DOCX 17821 kb)

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Copyright information

© American Association of Pharmaceutical Scientists 2019

Authors and Affiliations

  • Wojciech Krzyzanski
    • 1
    Email author
  • Sarah F. Cook
    • 1
  • Melanie Wilbaux
    • 2
  • Catherine M. T. Sherwin
    • 3
  • Karel Allegaert
    • 4
    • 7
  • An Vermeulen
    • 5
  • John N. van den Anker
    • 6
    • 8
  1. 1.Department of Pharmaceutical SciencesUniversity at BuffaloBuffaloUSA
  2. 2.Paediatric Pharmacology and PharmacometricsUniversity of Basel Children’s Hospital (UKBB)BaselSwitzerland
  3. 3.Division of Clinical Pharmacology, Department of PediatricsUniversity of Utah School of MedicineSalt Lake CityUSA
  4. 4.Department of Development and RegenerationKU LeuvenLeuvenBelgium
  5. 5.Janssen Research & Development, a Division of Janssen Pharmaceutica N.V.BeerseBelgium
  6. 6.Division of Clinical PharmacologyChildren’s National Health SystemWashingtonUSA
  7. 7.Department of Pediatrics, Division of NeonatologyErasmus MC Sophia Children’s HospitalRotterdamthe Netherlands
  8. 8.University of Basel Children’s HospitalBaselSwitzerland

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