Mount Sinai develops AI that can predict which drugs cause birth defects

Researchers from New York City-based Mount Sinai Health System have created an artificial intelligence model that can predict which existing medicines and preclinical compounds may cause congenital disabilities.

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Data scientists at the Icahn School of Medicine at Mount Sinai created the model, dubbed “knowledge gap,” to assess the relationship between birth defects, genes and drugs, according to a July 17 press release from Mount Sinai. 

Researchers used data produced from the NIH Common Fund programs and datasets from birth defect associations, ReproTox-KG and a semi-supervised learning, to assess approximately 30,000 preclinical small molecule drugs and their potential of crossing the placenta and inducing birth defects. 

The analysis found “500 birth-defect/gene/drug cliques,” that could potentially explain molecular mechanisms that could cause drug-induced birth defects.

Researchers warned that the findings are preliminary and that additional research is needed to further validate this. 

The full study was published July 17 in Communications Medicine.

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