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.

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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