Current Highlight from October 28, 2016
Model for Prediction of Estrogenic Activity in Sunscreen Product Ingredients
Scientists from FDA's NCTR and CDER developed a computational model to predict the estrogen receptor binding activity of sunscreen product ingredients. As proof of principle, the consensus model was applied to 32 chemicals used in sunscreen products. The model, which consists of two NCTR-developed Decision Forest models built on two different training sets, predicted estrogenic activity for seven of the 32 chemicals―five of which were confirmed by previously published data. The model has potential for use as a risk-assessment tool when available scientific data is inadequate and represents advancement in the characterization of estrogenic activity in widely used consumer products such as sunscreens. This publication is now available online at International Journal of Environmental Research and Public Health.
For more information, please contact Huixiao Hong, Ph.D., Division of Bioinformatics and Biostatistics, FDA/NCTR or Diego Rua, Ph.D., Division of Nonprescription Drug Products, FDA/CDER.
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