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Humans are exposed to tens of thousands of chemicals over the course of a lifetime, yet there remains inadequate data on the potential harmful effects of these substances on human health. Using quantitative high-throughput screening (qHTS), we can test these compounds for potential toxicity in a more efficient and cost-effective way compared to traditional animal studies. Tox21 has developed a library of ~10,000 chemicals (Tox21 10K) comprising one-third approved and investigational drugs and two-thirds environmental chemicals. In this study, the Tox21 10K was screened in a qHTS format against a panel of 70 cell-based assays with 213 readouts covering a broad range of biological pathways. Activity profiles were compared with chemical structure to assess their ability to differentiate drugs from environmental chemicals, and structure was found to be a better predictor of which chemicals are likely to be drugs. Drugs and environmental chemicals were further analyzed for diversity in structure and biological response space and showed distinguishable, but not distinct, responses in the Tox21 assays. Inclusion of other targets and pathways to further diversify the biological response space covered by these assays is likely required to better evaluate the safety profile of drugs and environmental chemicals to prioritize for in-depth toxicological studies.

Tens of thousands of chemicals with poorly understood biological properties are released into the environment each day. High-throughput screening (HTS) is potentially a more efficient and cost-effective alternative to traditional toxicity tests. Using HTS, one can profile chemicals for potential adverse effects and prioritize a manageable number for more in-depth testing. Importantly, it can provide clues to mechanism of toxicity. The Tox21 program has generated >50 million quantitative high-throughput screening (qHTS) data points. A library of several thousands of compounds, including environmental chemicals and drugs, is screened against a panel of nuclear receptor (NR) and stress response (SR) pathway assays. The National Center for Advancing Translational Sciences (NCATS) has organized an international data challenge in order to “crowd-source” data and build predictive toxicity models. This Challenge asks a “crowd” of researchers to use these data to elucidate the extent to which the interference of biochemical and cellular pathways by compounds can be inferred from chemical structure data. The data generated against the Tox21 library served as the training set for this modeling Challenge. The competition attracted participants from 18 different countries to develop computational models aimed at better predicting chemical toxicity. The winning models from nearly 400 model submissions all achieved >80% accuracy. Several models exceeded 90% accuracy, which was measured by area under the receiver operating characteristic curve (AUC-ROC). Combining the winning models with the knowledge already gained from Tox21 screening data are expected to improve the community's ability to prioritize novel chemicals with respect to potential human health concern.