Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women
BackgroundPregnant women represent a vulnerable group in pharmaceutical research due to limited knowledge about drug metabolism and safety of commonly used corticosteroids like prednisone due to ethical and practical constraints. Current preclinical models, including animal studies, fail to accurate...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2025.1528748/full |
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| author | Katja Graf José Martin Murrieta-Coxca Tobias Vogt Sophie Besser Daria Geilen Tim Kaden Tim Kaden Anne-Katrin Bothe Diana Maria Morales-Prieto Behnam Amiri Behnam Amiri Stephan Schaller Ligaya Kaufmann Martin Raasch Ramy M. Ammar Ramy M. Ammar Christian Maass Christian Maass |
| author_facet | Katja Graf José Martin Murrieta-Coxca Tobias Vogt Sophie Besser Daria Geilen Tim Kaden Tim Kaden Anne-Katrin Bothe Diana Maria Morales-Prieto Behnam Amiri Behnam Amiri Stephan Schaller Ligaya Kaufmann Martin Raasch Ramy M. Ammar Ramy M. Ammar Christian Maass Christian Maass |
| author_sort | Katja Graf |
| collection | DOAJ |
| description | BackgroundPregnant women represent a vulnerable group in pharmaceutical research due to limited knowledge about drug metabolism and safety of commonly used corticosteroids like prednisone due to ethical and practical constraints. Current preclinical models, including animal studies, fail to accurately replicate human pregnancy conditions, resulting in gaps in drug safety and pharmacokinetics predictions. To address this issue, we used a three-organ microphysiological system (MPS) combined with a digital twin framework, to predict pharmacokinetics and fetal drug exposure.MethodsThe here shown human MPS integrated gut, liver, and placenta models, interconnected via the corresponding vasculature. Using prednisone as a model compound, we simulate oral drug administration and track its metabolism and transplacental transfer. To translate the generated data from MPS to human physiology, computational modelling techniques were developed.ResultsOur results demonstrate that the system maintains cellular integrity and accurately mimics in vivo drug dynamics, with predictions closely matching clinical data from pregnant women. Digital twinning closely aligned with the generated experimental data. Long-term exposure simulations confirmed the value of this integrated system for predicting the non-toxic metabolization of prednisone.ConclusionThis approach may provide a potential non-animal alternative that could contribute to our understanding of drug behavior during pregnancy and may support early-stage drug safety assessment for vulnerable populations. |
| format | Article |
| id | doaj-art-0eafc3d270d346f1938128e47f9f1647 |
| institution | Kabale University |
| issn | 1663-9812 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj-art-0eafc3d270d346f1938128e47f9f16472025-02-12T07:25:53ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122025-02-011610.3389/fphar.2025.15287481528748Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant womenKatja Graf0José Martin Murrieta-Coxca1Tobias Vogt2Sophie Besser3Daria Geilen4Tim Kaden5Tim Kaden6Anne-Katrin Bothe7Diana Maria Morales-Prieto8Behnam Amiri9Behnam Amiri10Stephan Schaller11Ligaya Kaufmann12Martin Raasch13Ramy M. Ammar14Ramy M. Ammar15Christian Maass16Christian Maass17Dynamic42 GmbH, Jena, GermanyPlacenta Lab, Department of Obstetrics, Jena University Hospital, Jena, GermanyDynamic42 GmbH, Jena, GermanyDynamic42 GmbH, Jena, GermanyDynamic42 GmbH, Jena, GermanyDynamic42 GmbH, Jena, GermanyInstitute of Biochemistry II, Center for Sepsis Control and Care, Jena University Hospital, Jena, GermanyDynamic42 GmbH, Jena, GermanyPlacenta Lab, Department of Obstetrics, Jena University Hospital, Jena, GermanyMPSlabs, ESQlabs GmbH, Saterland, GermanyESQlabs GmbH, Saterland, GermanyESQlabs GmbH, Saterland, GermanyGlobal Medical Affairs, Bayer Consumer Care AG, Basel, SwitzerlandDynamic42 GmbH, Jena, GermanyGlobal R&D, Bayer Consumer Health, Steigerwald Arzneimittelwerk GmbH, Darmstadt, GermanyDepartment of Pharmacology and Toxicology, Faculty of Pharmacy, Kafrelsheikh University, Kafr-El Sheikh, EgyptMPSlabs, ESQlabs GmbH, Saterland, GermanyESQlabs GmbH, Saterland, GermanyBackgroundPregnant women represent a vulnerable group in pharmaceutical research due to limited knowledge about drug metabolism and safety of commonly used corticosteroids like prednisone due to ethical and practical constraints. Current preclinical models, including animal studies, fail to accurately replicate human pregnancy conditions, resulting in gaps in drug safety and pharmacokinetics predictions. To address this issue, we used a three-organ microphysiological system (MPS) combined with a digital twin framework, to predict pharmacokinetics and fetal drug exposure.MethodsThe here shown human MPS integrated gut, liver, and placenta models, interconnected via the corresponding vasculature. Using prednisone as a model compound, we simulate oral drug administration and track its metabolism and transplacental transfer. To translate the generated data from MPS to human physiology, computational modelling techniques were developed.ResultsOur results demonstrate that the system maintains cellular integrity and accurately mimics in vivo drug dynamics, with predictions closely matching clinical data from pregnant women. Digital twinning closely aligned with the generated experimental data. Long-term exposure simulations confirmed the value of this integrated system for predicting the non-toxic metabolization of prednisone.ConclusionThis approach may provide a potential non-animal alternative that could contribute to our understanding of drug behavior during pregnancy and may support early-stage drug safety assessment for vulnerable populations.https://www.frontiersin.org/articles/10.3389/fphar.2025.1528748/fullpregnancyorgan-on-chipcomputational modellingpharmacokineticssafety |
| spellingShingle | Katja Graf José Martin Murrieta-Coxca Tobias Vogt Sophie Besser Daria Geilen Tim Kaden Tim Kaden Anne-Katrin Bothe Diana Maria Morales-Prieto Behnam Amiri Behnam Amiri Stephan Schaller Ligaya Kaufmann Martin Raasch Ramy M. Ammar Ramy M. Ammar Christian Maass Christian Maass Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women Frontiers in Pharmacology pregnancy organ-on-chip computational modelling pharmacokinetics safety |
| title | Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women |
| title_full | Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women |
| title_fullStr | Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women |
| title_full_unstemmed | Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women |
| title_short | Digital twin-enhanced three-organ microphysiological system for studying drug pharmacokinetics in pregnant women |
| title_sort | digital twin enhanced three organ microphysiological system for studying drug pharmacokinetics in pregnant women |
| topic | pregnancy organ-on-chip computational modelling pharmacokinetics safety |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2025.1528748/full |
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