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Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation

Many women take drugs during their pregnancy to treat a variety of clinical conditions. To optimize drug efficacy and reduce fetal toxicity, it is important to determine or predict fetal drug exposure throughout pregnancy. Previously, we developed and verified a maternal-fetal physiologically based...

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Autores principales: Anoshchenko, Olena, Storelli, Flavia, Unadkat, Jashvant D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Pharmacology and Experimental Therapeutics 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626637/
https://www.ncbi.nlm.nih.gov/pubmed/34426410
http://dx.doi.org/10.1124/dmd.121.000538
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author Anoshchenko, Olena
Storelli, Flavia
Unadkat, Jashvant D.
author_facet Anoshchenko, Olena
Storelli, Flavia
Unadkat, Jashvant D.
author_sort Anoshchenko, Olena
collection PubMed
description Many women take drugs during their pregnancy to treat a variety of clinical conditions. To optimize drug efficacy and reduce fetal toxicity, it is important to determine or predict fetal drug exposure throughout pregnancy. Previously, we developed and verified a maternal-fetal physiologically based pharmacokinetic (m-f PBPK) model to predict fetal K(p,uu) (unbound fetal plasma AUC/unbound maternal plasma AUC) of drugs that passively cross the placenta. Here, we used in vitro transport studies in Transwell, in combination with our m-f PBPK model, to predict fetal K(p,uu) of drugs that are effluxed by placental P-glycoprotein (P-gp)—namely, dexamethasone, betamethasone, darunavir, and lopinavir. Using Transwell, we determined the efflux ratio of these drugs in hMDR1-MDCK(cP-gpKO) cells, in which human P-gp was overexpressed and the endogenous P-gp was knocked out. Then, using the proteomics-informed efflux ratio–relative expressive factor approach, we predicted the fetal K(p,uu) of these drugs at term. Finally, to verify our predictions, we compared them with the observed in vivo fetal K(p,uu) at term. The latter was estimated using our m-f PBPK model and published fetal [umbilical vein (UV)]/maternal plasma drug concentrations obtained at term (UV/maternal plasma). Fetal K(p,uu) predictions for dexamethasone (0.63), betamethasone (0.59), darunavir (0.17), and lopinavir (0.08) were successful, as they fell within the 90% confidence interval of the corresponding in vivo fetal K(p,uu) (0.30–0.66, 0.29–0.71, 0.11–0.22, 0.04–0.19, respectively). This is the first demonstration of successful prediction of fetal K(p,uu) of P-gp drug substrates from in vitro studies. SIGNIFICANCE STATEMENT: For the first time, using in vitro studies in cells, this study successfully predicted human fetal K(p,uu) of P-gp substrate drugs. This success confirms that the m-f PBPK model, combined with the ER-REF approach, can successfully predict fetal drug exposure to P-gp substrates. This success provides increased confidence in the use of the ER-REF approach, combined with the m-f PBPK model, to predict fetal K(p,uu) of drugs (transported by P-gp or other transporters), both at term and at earlier gestational ages.
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spelling pubmed-86266372021-12-03 Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation Anoshchenko, Olena Storelli, Flavia Unadkat, Jashvant D. Drug Metab Dispos Articles Many women take drugs during their pregnancy to treat a variety of clinical conditions. To optimize drug efficacy and reduce fetal toxicity, it is important to determine or predict fetal drug exposure throughout pregnancy. Previously, we developed and verified a maternal-fetal physiologically based pharmacokinetic (m-f PBPK) model to predict fetal K(p,uu) (unbound fetal plasma AUC/unbound maternal plasma AUC) of drugs that passively cross the placenta. Here, we used in vitro transport studies in Transwell, in combination with our m-f PBPK model, to predict fetal K(p,uu) of drugs that are effluxed by placental P-glycoprotein (P-gp)—namely, dexamethasone, betamethasone, darunavir, and lopinavir. Using Transwell, we determined the efflux ratio of these drugs in hMDR1-MDCK(cP-gpKO) cells, in which human P-gp was overexpressed and the endogenous P-gp was knocked out. Then, using the proteomics-informed efflux ratio–relative expressive factor approach, we predicted the fetal K(p,uu) of these drugs at term. Finally, to verify our predictions, we compared them with the observed in vivo fetal K(p,uu) at term. The latter was estimated using our m-f PBPK model and published fetal [umbilical vein (UV)]/maternal plasma drug concentrations obtained at term (UV/maternal plasma). Fetal K(p,uu) predictions for dexamethasone (0.63), betamethasone (0.59), darunavir (0.17), and lopinavir (0.08) were successful, as they fell within the 90% confidence interval of the corresponding in vivo fetal K(p,uu) (0.30–0.66, 0.29–0.71, 0.11–0.22, 0.04–0.19, respectively). This is the first demonstration of successful prediction of fetal K(p,uu) of P-gp drug substrates from in vitro studies. SIGNIFICANCE STATEMENT: For the first time, using in vitro studies in cells, this study successfully predicted human fetal K(p,uu) of P-gp substrate drugs. This success confirms that the m-f PBPK model, combined with the ER-REF approach, can successfully predict fetal drug exposure to P-gp substrates. This success provides increased confidence in the use of the ER-REF approach, combined with the m-f PBPK model, to predict fetal K(p,uu) of drugs (transported by P-gp or other transporters), both at term and at earlier gestational ages. The American Society for Pharmacology and Experimental Therapeutics 2021-10 2021-10 /pmc/articles/PMC8626637/ /pubmed/34426410 http://dx.doi.org/10.1124/dmd.121.000538 Text en Copyright © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the CC BY Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Articles
Anoshchenko, Olena
Storelli, Flavia
Unadkat, Jashvant D.
Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation
title Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation
title_full Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation
title_fullStr Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation
title_full_unstemmed Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation
title_short Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation
title_sort successful prediction of human fetal exposure to p-glycoprotein substrate drugs using the proteomics-informed relative expression factor approach and pbpk modeling and simulation
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626637/
https://www.ncbi.nlm.nih.gov/pubmed/34426410
http://dx.doi.org/10.1124/dmd.121.000538
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