Host: The Japanese Society of Toxicology
Name : The 47th Annual Meeting of the Japanese Society of Toxicology
Date : 2020 -
Recently, FDA required that toxicology data be formatted and structured in the Standard Exchange for Nonclinical Data (SEND) model for IND/NDA submissions. The continued growth in the number of toxicology study datasets in SEND format will enable easier information exchange for due diligence, investigation of toxicity profile, cross study analysis and QSAR. The global consortium, “BioCelerate”, developed a SEND-based database (DataCelerate) for nonclinical toxicology data for use by members of the consortium. Shionogi analyzed data from two independent studies submitted to DataCelerate. These two studies were different compounds but designed to have the same pharmacologic target. Interestingly, the same specific target-organ toxicity was observed in both studies were conducted in a different facility. We considered the findings to be a class effect of this drug target. While the above example represents the benefit of cross-study analysis, there are also challenges. For example, animal age data in SEND datasets can be entered as day, week, month or year. The variability in this parameter makes it challenging to employ robust cross-study analysis due to the lack of a standard expression of age. Similar variability in populating variables can also be seen in SEND datasets. Searching across SEND datasets can help to understand a target toxicity profile, and predict toxicity for other compounds in the class. In the future, a large number of SEND datasets in DataCelerate should be a useful resource to predict potential drug target-related clinical adverse events.
