Literature DB >> 30019622

Combining Brain Microdialysis and Translational Pharmacokinetic Modeling to Predict Drug Concentrations in Pediatric Severe Traumatic Brain Injury: The Next Step Toward Evidence-Based Pharmacotherapy?

Naomi Ketharanathan1, Yumi Yamamoto2, Ursula K Rohlwink3, Enno D Wildschut1, Ron A A Mathôt4, Elizabeth C M de Lange2, Saskia N de Wildt1,5, Andrew C Argent6, Dick Tibboel1, Anthony A Figaji3.   

Abstract

Evidence-based analgosedation in severe pediatric traumatic brain injury (pTBI) management is lacking, and improved pharmacological understanding is needed. This starts with increased knowledge of factors controlling the pharmacokinetics (PK) of unbound drug at the target site (brain) and related drug effect(s). This prospective, descriptive study tested a pediatric physiology-based pharmacokinetic software model by comparing actual plasma and brain extracellular fluid (brainECF) morphine concentrations with predicted concentration-time profiles in severe pTBI patients (Glasgow Coma Scale [GCS], ≤8). Plasma and brainECF samples were obtained after legal guardian written consent and were collected from 8 pTBI patients (75% male; median age, 96 months [34.0-155.5]; median weight, 24 kg [14.5-55.0]) with a need for intracranial pressure monitoring (GCS, ≤8) and receiving continuous morphine infusion (10-40 μg/kg/h). BrainECF samples were obtained by microdialysis. BrainECF samples were taken from "injured" and "uninjured" regions as determined by microdialysis catheter location on computed head tomography. A previously developed physiology-based software model to predict morphine concentrations in the brain was adapted to children using pediatric physiological properties. The model predicted plasma morphine concentrations well for individual patients (97% of data points within the 90% prediction interval). In addition, predicted brainECF concentration-time profiles fell within a 90% prediction interval of microdialysis brainECF drug concentrations when sampled from an uninjured area. Prediction was less accurate in injured areas. This approach of translational physiology-based PK modeling allows prediction of morphine concentration-time profiles in uninjured brain of individual patients and opens promising avenues towards evidence-based pharmacotherapies in pTBI.

Entities:  

Keywords:  microdialysis; morphine; pediatric; pharmacokinetics; traumatic brain injury

Mesh:

Substances:

Year:  2018        PMID: 30019622     DOI: 10.1089/neu.2017.5588

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  5 in total

1.  Mind the Gaps: Ontogeny of Human Brain P-gp and Its Impact on Drug Toxicity.

Authors:  Jean-Marie Nicolas; Elizabeth C M de Lange
Journal:  AAPS J       Date:  2019-05-28       Impact factor: 4.009

2.  Development of a physiologically-based pharmacokinetic pediatric brain model for prediction of cerebrospinal fluid drug concentrations and the influence of meningitis.

Authors:  Laurens F M Verscheijden; Jan B Koenderink; Saskia N de Wildt; Frans G M Russel
Journal:  PLoS Comput Biol       Date:  2019-06-13       Impact factor: 4.475

3.  Impact of CNS Diseases on Drug Delivery to Brain Extracellular and Intracellular Target Sites in Human: A "WHAT-IF" Simulation Study.

Authors:  Mohammed A A Saleh; Elizabeth C M de Lange
Journal:  Pharmaceutics       Date:  2021-01-13       Impact factor: 6.321

4.  Physiologically based pharmacokinetic/pharmacodynamic model for the prediction of morphine brain disposition and analgesia in adults and children.

Authors:  Laurens F M Verscheijden; Carlijn H C Litjens; Jan B Koenderink; Ron H J Mathijssen; Marcel M Verbeek; Saskia N de Wildt; Frans G M Russel
Journal:  PLoS Comput Biol       Date:  2021-03-04       Impact factor: 4.475

Review 5.  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

  5 in total

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