ArticlePeerJ2020
Prediction of human fetal-maternal blood concentration ratio of chemicals.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Psychedelic Drugs Rediscovered-In Silico Study of Potential Fetal Exposure to Analogues of Psychedelic Drugs During Pregnancy.Molecules (Basel, Switzerland) · 2026Article
- Developmental toxicity: artificial intelligence-powered assessments.Trends in pharmacological sciences · 2025Review
- An Integrated Testing Strategy and Online Tool for Assessing Skin Sensitization of Agrochemical Formulations.Toxics · 2024Article
- Organic Sunscreens-Is Their Placenta Permeability the Only Issue Associated with Exposure During Pregnancy? In Silico Studies of Sunscreens' Placenta Permeability and Interactions with Selected Placental Enzymes.Molecules (Basel, Switzerland) · 2024Article
- Organic Sunscreens and Their Products of Degradation in Biotic and Abiotic Conditions-In Silico Studies of Drug-Likeness and Human Placental Transport.International journal of molecular sciences · 2024Article
- Reconfiguring the online tool of SkinSensPred for predicting skin sensitization of pesticides.Journal of pesticide science · 2022Article
- Ensemble learning for predicting ex vivo human placental barrier permeability.BMC bioinformatics · 2022Article
- The Role of the 3Rs for Understanding and Modeling the Human Placenta.Journal of clinical medicine · 2021Review
- A Machine Learning Model to Predict Drug Transfer Across the Human Placenta Barrier.Frontiers in chemistry · 2021Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe measurement of human fetal-maternal blood concentration ratio (logFM) of chemicals is critical for the risk assessment of chemical-induced developmental toxicity. While a few in vitro and ex vivo experimental methods were developed for predicting logFM of chemicals, the obtained experimental results are not able to directly predict in vivo outcomes.
methodsA total of 55 chemicals with logFM values representing in vivo fetal-maternal blood ratio were divided into training and test datasets. An interpretable linear regression model was developed along with feature selection methods. Cross-validation on training dataset and prediction on independent test dataset were conducted to validate the prediction model.
resultsThis study presents the first valid quantitative structure-activity relationship model following the Organisation for Economic Co-operation and Development (OECD) guidelines based on multiple linear regression for predicting in vivo logFM values. The autocorrelation descriptor AATSC1c and information content descriptor ZMIC1 were identified as informative features for predicting logFM. After the adjustment of the applicability domain, the developed model performs well with correlation coefficients of 0.875, 0.850 and 0.847 for model fitting, leave-one-out cross-validation and independent test, respectively. The model is expected to be useful for assessing human transplacental exposure.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.