Details

Autor(en) / Beteiligte

• Ketharanathan, Naomi
• Yamamoto, Yumi
• Rohlwink, Ursula K
• Wildschut, Enno D
• Mathôt, Ron A A
• de Lange, Elizabeth C M
• de Wildt, Saskia N
• Argent, Andrew C
• Tibboel, Dick
• Figaji, Anthony A

Titel

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

Ist Teil von

• Journal of neurotrauma, 2019-01, Vol.36 (1), p.111

Ort / Verlag

United States

Erscheinungsjahr

2019

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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 (brain ) morphine concentrations with predicted concentration-time profiles in severe pTBI patients (Glasgow Coma Scale [GCS], ≤8). Plasma and brain 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). Brain samples were obtained by microdialysis. Brain 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 brain concentration-time profiles fell within a 90% prediction interval of microdialysis brain 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.