High Throughput Screening (HTS) studies provide the community with rich toxicology information that has the potential to be integrated into toxicity research. A general question raised from the current big data scenario is what is the usage of a toxicity bioassay (normally refers to a specific binding target) to the studies of more complicated toxicity phenomena (e.g. animal toxicity). To answer this challenge, the goal of this project was to develop novel computational approaches that use data on a single bioassay as the probe to search and reveal all the relevant information in the public big data pool. Compared to the existing data management and sharing projects, the approach developed in this study is the first to take the advantage of chemical toxicity big data and apply it to animal toxicity evaluations.