Comparison of predictions of developmental toxicity for compounds of solvent data set

We have considered a series of 235 compounds technically classified as solvents. Chemically, they belong to different classes. Their potential developmental toxicity was evaluated using two models available on platform VEGA HUB; model CAESAR and the Developmental/ Reproductive Toxicity library (PG) model. Models provide beside the prediction of developmental toxicity additional information on similar compounds from models' training sets. In the report, first, we compare the predictions. Second, the sets of similar compounds have been used to implement the clustering scheme. The Kohonen artificial neural network method has been applied as a clustering method. The clusters obtained have been discussed for both models.