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PBPK Modeling Approach to Predict the Behavior of Drugs Cleared by Metabolism in Pregnant Subjects and Fetuses.
Le Merdy, Maxime; Szeto, Ke Xu; Perrier, Jeremy; Bolger, Michael B; Lukacova, Viera.
Afiliação
  • Le Merdy M; Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA 93534, USA.
  • Szeto KX; Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA 93534, USA.
  • Perrier J; PhinC Development, 36 Rue Victor Basch, 91300 Massy, France.
  • Bolger MB; Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA 93534, USA.
  • Lukacova V; Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA 93534, USA.
Pharmaceutics ; 16(1)2024 Jan 10.
Article em En | MEDLINE | ID: mdl-38258106
ABSTRACT
This study aimed to develop a physiologically based pharmacokinetic (PBPK) model that simulates metabolically cleared compounds' pharmacokinetics (PK) in pregnant subjects and fetuses. This model accounts for the differences in tissue sizes, blood flow rates, enzyme expression levels, plasma protein binding, and other physiological factors affecting the drugs' PK in both the pregnant woman and the fetus. The PBPKPlus™ module in GastroPlus® was used to model the PK of metoprolol, midazolam, and metronidazole for both non-pregnant and pregnant groups. For each of the three compounds, the model was first developed and validated against PK data in healthy non-pregnant volunteers and then applied to predict the PK in the pregnant groups. The model accurately described the PK in both the non-pregnant and pregnant groups and explained well the differences in the plasma concentration due to pregnancy. When available, the fetal plasma concentration, placenta, and fetal tissue concentrations were also predicted reasonably well at different stages of pregnancy. The work described the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for metabolically cleared compounds.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article