To visualize the chemical space of the compounds in the Epi Food Chemical Database, we generated a tdistributed stochastic neighbor embedding (t-SNE). This technique involves nonlinearly reducing dimensions by creating Gaussian probability distributions across high-dimensional space and then utilizing them to enhance a Student t-distribution within a lower-dimensional space through optimization. The lower dimensional space conserves pairwise similarities from the original higher dimensional space, resulting in clustering within the embedding space without a notable loss of the structural information.