Literature DB >> 35281912

Structure-Activity Relationship (SAR) Model for Predicting Teratogenic Risk of Antiseizure Medications in Pregnancy by Using Support Vector Machine.

Liyuan Kang1, Yifei Duan2, Cheng Chen1, Shihai Li1, Menglong Li1, Lei Chen2, Zhining Wen1,3.   

Abstract

Teratogenicity is one of the main concerns in clinical medications of pregnant women. Prescription of antiseizure medications (ASMs) in women with epilepsy during pregnancy may cause teratogenic effects on the fetus. Although large scale epilepsy pregnancy registries played an important role in evaluating the teratogenic risk of ASMs, for most ASMs, especially the newly approved ones, the potential teratogenic risk cannot be effectively assessed due to the lack of evidence. In this study, the analyses are performed on any medication, with a focus on ASMs. We curated a list containing the drugs with potential teratogenicity based on the US Food and Drug Administration (FDA)-approved drug labeling, and established a support vector machine (SVM) model for detecting drugs with high teratogenic risk. The model was validated by using the post-marketing surveillance data from US FDA Spontaneous Adverse Events Reporting System (FAERS) and applied to the prediction of potential teratogenic risk of ASMs. Our results showed that our proposed model outperformed the state-of-art approaches, including logistic regression (LR), random forest (RF) and extreme gradient boosting (XGBoost), when detecting the high teratogenic risk of drugs (MCC and recall rate were 0.312 and 0.851, respectively). Among 196 drugs with teratogenic potential reported by FAERS, 136 (69.4%) drugs were correctly predicted. For the eight commonly used ASMs, 4 of them were predicted as high teratogenic risk drugs, including topiramate, phenobarbital, valproate and phenytoin (predicted probabilities of teratogenic risk were 0.69, 0.60 0.59, and 0.56, respectively), which were consistent with the statement in FDA-approved drug labeling and the high reported prevalence of teratogenicity in epilepsy pregnancy registries. In addition, the structural alerts in ASMs that related to the genotoxic carcinogenicity and mutagenicity, idiosyncratic adverse reaction, potential electrophilic agents and endocrine disruption were identified and discussed. Our findings can be a good complementary for the teratogenic risk assessment in drug development and facilitate the determination of pharmacological therapies during pregnancy.
Copyright © 2022 Kang, Duan, Chen, Li, Li, Chen and Wen.

Entities:  

Keywords:  antiseizure medications; drug safety evaluation; drug-induced teratogenesis; machine learning; structure-activity relationship

Year:  2022        PMID: 35281912      PMCID: PMC8914116          DOI: 10.3389/fphar.2022.747935

Source DB:  PubMed          Journal:  Front Pharmacol        ISSN: 1663-9812            Impact factor:   5.810


  33 in total

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Authors:  Sanjeev V Thomas; Manna Jose; Srividya Divakaran; Prabhakaran Sankara Sarma
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5.  Changes in antiepileptic drug-prescribing patterns in pregnant women with epilepsy.

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10.  Maternal Use of Antiepileptic Agents During Pregnancy and Major Congenital Malformations in Children.

Authors:  Rebecca L Bromley; Jennifer Weston; Anthony G Marson
Journal:  JAMA       Date:  2017-11-07       Impact factor: 56.272

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