Physiologically Based Pharmacokinetic Modeling Framework to Predict Neonatal Pharmacokinetics of Transplacentally Acquired Emtricitabine, Dolutegravir, and Raltegravir.


Journal

Clinical pharmacokinetics
ISSN: 1179-1926
Titre abrégé: Clin Pharmacokinet
Pays: Switzerland
ID NLM: 7606849

Informations de publication

Date de publication:
06 2021
Historique:
accepted: 12 12 2020
pubmed: 3 2 2021
medline: 16 10 2021
entrez: 2 2 2021
Statut: ppublish

Résumé

Little is understood about neonatal pharmacokinetics immediately after delivery and during the first days of life following intrauterine exposure to maternal medications. Our objective was to develop and evaluate a novel, physiologically based pharmacokinetic modeling workflow for predicting perinatal and postnatal disposition of commonly used antiretroviral drugs administered prenatally to pregnant women living with human immunodeficiency virus. Using previously published, maternal-fetal, physiologically based pharmacokinetic models for emtricitabine, dolutegravir, and raltegravir built with PK-Sim/MoBi Neonatal physiologically based pharmacokinetic models generally captured the initial plasma concentrations after delivery but underestimated concentrations in the terminal phase. The mean percentage error for predicted plasma concentrations was - 71.5%, - 33.8%, and 76.7% for emtricitabine, dolutegravir, and raltegravir, respectively. A sensitivity analysis suggested that the activity of organic cation transporter 2 and uridine diphosphate glucuronosyltransferase 1A1 during the first postnatal days in term newborns is ~11% and ~30% of that in adults, respectively. These findings demonstrate the general feasibility of applying physiologically based pharmacokinetic models to predict washout concentrations of transplacentally acquired drugs in newborns. These models can increase the understanding of pharmacokinetics during the first postnatal days and allow the prediction of drug exposure in this vulnerable population.

Sections du résumé

BACKGROUND AND OBJECTIVE
Little is understood about neonatal pharmacokinetics immediately after delivery and during the first days of life following intrauterine exposure to maternal medications. Our objective was to develop and evaluate a novel, physiologically based pharmacokinetic modeling workflow for predicting perinatal and postnatal disposition of commonly used antiretroviral drugs administered prenatally to pregnant women living with human immunodeficiency virus.
METHODS
Using previously published, maternal-fetal, physiologically based pharmacokinetic models for emtricitabine, dolutegravir, and raltegravir built with PK-Sim/MoBi
RESULTS
Neonatal physiologically based pharmacokinetic models generally captured the initial plasma concentrations after delivery but underestimated concentrations in the terminal phase. The mean percentage error for predicted plasma concentrations was - 71.5%, - 33.8%, and 76.7% for emtricitabine, dolutegravir, and raltegravir, respectively. A sensitivity analysis suggested that the activity of organic cation transporter 2 and uridine diphosphate glucuronosyltransferase 1A1 during the first postnatal days in term newborns is ~11% and ~30% of that in adults, respectively.
CONCLUSIONS
These findings demonstrate the general feasibility of applying physiologically based pharmacokinetic models to predict washout concentrations of transplacentally acquired drugs in newborns. These models can increase the understanding of pharmacokinetics during the first postnatal days and allow the prediction of drug exposure in this vulnerable population.

Identifiants

pubmed: 33527213
doi: 10.1007/s40262-020-00977-w
pii: 10.1007/s40262-020-00977-w
pmc: PMC9334904
mid: NIHMS1821147
doi:

Substances chimiques

Heterocyclic Compounds, 3-Ring 0
Oxazines 0
Piperazines 0
Pyridones 0
Raltegravir Potassium 43Y000U234
dolutegravir DKO1W9H7M1
Emtricitabine G70B4ETF4S

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

795-809

Subventions

Organisme : NICHD NIH HHS
ID : HHSN275201800001C
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI068632
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI068616
Pays : United States
Organisme : NICHD NIH HHS
ID : T32 HD087969
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI106716
Pays : United States
Organisme : NICHD NIH HHS
ID : HHSN275201800001I
Pays : United States

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Auteurs

Xiaomei I Liu (XI)

Division of Clinical Pharmacology, Children's National Hospital, 10430 Owen Brown Road, Columbia, Maryland, 21044, USA. rph5862@gmail.com.
Division of Infectious Diseases, Children's National Hospital, Washington, DC, USA. rph5862@gmail.com.

Jeremiah D Momper (JD)

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, USA.
Pediatric Department, School of Medicine, Rady Children's Hospital San Diego, La Jolla, CA, USA.

Natella Y Rakhmanina (NY)

Division of Infectious Diseases, Children's National Hospital, Washington, DC, USA.
Elizabeth Glaser Pediatric AIDS Foundation, Washington, DC, USA.

Dionna J Green (DJ)

Office of Pediatric Therapeutics, US Food and Drug Administration, Silver Spring, MD, USA.

Gilbert J Burckart (GJ)

Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA.

Tim R Cressey (TR)

PHPT/IRD 174, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.

Mark Mirochnick (M)

School of Medicine, Boston University, Boston, MA, USA.

Brookie M Best (BM)

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, USA.
Pediatric Department, School of Medicine, Rady Children's Hospital San Diego, La Jolla, CA, USA.

John N van den Anker (JN)

Division of Clinical Pharmacology, Children's National Hospital, 10430 Owen Brown Road, Columbia, Maryland, 21044, USA.
Division of Pediatric Pharmacology and Pharmacometrics, University Children's Hospital Basel, University of Basel, Basel, Switzerland.

André Dallmann (A)

Bayer AG, Clinical Pharmacometrics, Leverkusen, Germany.

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Classifications MeSH