Literature DB >> 31820437

Utilizing Pediatric Physiologically Based Pharmacokinetic Models to Examine Factors That Contribute to Methadone Pharmacokinetic Variability in Neonatal Abstinence Syndrome Patients.

Brooks T McPhail1,2, Chie Emoto1,3, Tsuyoshi Fukuda1,3, Dawn Butler4, Jason R Wiles5, Henry Akinbi3,6, Alexander A Vinks1,3.   

Abstract

Chronic intrauterine exposure to psychoactive drugs often results in neonatal abstinence syndrome (NAS). NAS is the symptomatic drug withdrawal in newborns that generally occurs after in utero chronic opioid exposure. Methadone is an opioid analgesic commonly prescribed for pharmacologic management of NAS. It exhibits high pharmacokinetic (PK) variability. The current study used physiologically based PK modeling to predict the PK profile of methadone in 20 newborns treated for NAS. The physiologically based PK simulations adequately predicted the PK profile of the clinical data for 45% of the patients. Sensitivity analyses were conducted to explore contributing factors to methadone PK variability. The data suggest that P450 enzymatic activity impacts the clearance of methadone in virtual adults and neonates, while the contribution of cardiac output may be negligible. Understanding maturational and/or pharmacogenetic changes in cytochrome P450 enzymatic activity may further explain the large PK variability of methadone in newborns with NAS and will help individualized treatment.
© 2019, The American College of Clinical Pharmacology.

Entities:  

Keywords:  CYP450; PBPK model; cardiac output; methadone; neonatal abstinence syndrome (NAS); neonates

Mesh:

Substances:

Year:  2019        PMID: 31820437      PMCID: PMC7336467          DOI: 10.1002/jcph.1538

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  51 in total

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Authors:  D Raistrick; A Hay; K Wolff
Journal:  BMJ       Date:  1996-10-12

2.  Meta-analysis of hepatic cytochrome P450 ontogeny to underwrite the prediction of pediatric pharmacokinetics using physiologically based pharmacokinetic modeling.

Authors:  Vijay V Upreti; Jan L Wahlstrom
Journal:  J Clin Pharmacol       Date:  2015-10-09       Impact factor: 3.126

3.  Regulatory experience with physiologically based pharmacokinetic modeling for pediatric drug trials.

Authors:  R Leong; M L T Vieira; P Zhao; Y Mulugeta; C S Lee; S-M Huang; G J Burckart
Journal:  Clin Pharmacol Ther       Date:  2012-05       Impact factor: 6.875

4.  Cohort Analysis of a Pharmacokinetic-Modeled Methadone Weaning Optimization for Neonatal Abstinence Syndrome.

Authors:  Eric S Hall; Jareen Meinzen-Derr; Scott L Wexelblatt
Journal:  J Pediatr       Date:  2015-10-21       Impact factor: 4.406

Review 5.  Similarities and differences in gastrointestinal physiology between neonates and adults: a physiologically based pharmacokinetic modeling perspective.

Authors:  Guo Yu; Qing-Shan Zheng; Guo-Fu Li
Journal:  AAPS J       Date:  2014-09-03       Impact factor: 4.009

Review 6.  Methadone--metabolism, pharmacokinetics and interactions.

Authors:  Anna Ferrari; Ciro Pio Rosario Coccia; Alfio Bertolini; Emilio Sternieri
Journal:  Pharmacol Res       Date:  2004-12       Impact factor: 7.658

Review 7.  Methadone: a review of its pharmacokinetic/pharmacodynamic properties.

Authors:  M J Garrido; I F Trocóniz
Journal:  J Pharmacol Toxicol Methods       Date:  1999-10       Impact factor: 1.950

8.  Steady-state pharmacokinetics of (R)- and (S)-methadone in methadone maintenance patients.

Authors:  D J Foster; A A Somogyi; K R Dyer; J M White; F Bochner
Journal:  Br J Clin Pharmacol       Date:  2000-11       Impact factor: 4.335

Review 9.  Human Ontogeny of Drug Transporters: Review and Recommendations of the Pediatric Transporter Working Group.

Authors:  K L R Brouwer; L M Aleksunes; B Brandys; G P Giacoia; G Knipp; V Lukacova; B Meibohm; S K Nigam; M Rieder; S N de Wildt
Journal:  Clin Pharmacol Ther       Date:  2015-09       Impact factor: 6.875

Review 10.  Why has model-informed precision dosing not yet become common clinical reality? lessons from the past and a roadmap for the future.

Authors:  A S Darwich; K Ogungbenro; A A Vinks; J R Powell; J-L Reny; N Marsousi; Y Daali; D Fairman; J Cook; L J Lesko; J S McCune; Caj Knibbe; S N de Wildt; J S Leeder; M Neely; A F Zuppa; P Vicini; L Aarons; T N Johnson; J Boiani; A Rostami-Hodjegan
Journal:  Clin Pharmacol Ther       Date:  2017-04-04       Impact factor: 6.875

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  2 in total

Review 1.  Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development.

Authors:  Kefei Wang; Kun Jiang; Xiaoyi Wei; Yulan Li; Tiejie Wang; Yang Song
Journal:  AAPS PharmSciTech       Date:  2021-07-26       Impact factor: 3.246

Review 2.  Clinical pharmacology and dosing regimen optimization of neonatal opioid withdrawal syndrome treatments.

Authors:  Fei Tang; Chee M Ng; Henrietta S Bada; Markos Leggas
Journal:  Clin Transl Sci       Date:  2021-05-01       Impact factor: 4.689

  2 in total

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