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Johns Hopkins Bloomberg School of Public HealthCAAT

Big Data and AI

Alexandra Maertens

Coordinator: Alexandra Maertens (

Last year we had two successful meetings as well as several publications demonstrating the potential for a “21st century” read-across based on a big-data approach, machine learning, and the larger data sets available through ECHA. We intend to continue spearheading efforts to improve the scientific rigor of read across, develop better chemical similarity metrics, to combine biological data with chemoinformatics, and develop novel algorithms to classify chemicals. We are collaborating with several teams and plan to make our data and software packages public. 

This coming year, we hope to build on the success of the previous meetings with a satellite meeting held to coincide with the 2017 Society of Toxicology meeting in Baltimore, which will expand our discussion of the regulatory acceptance of read-across, focusing on increasing the transparency and consistency of read-across as well as dealing with uncertainty. This meeting will include not only US and European regulatory agencies but also Australia and Asia.