Using Big Data to Predict Toxicity of Chemicals Can Save Animals

There is a large amount of available data that can be used to predict chemical toxicity without carrying out animal tests, thanks to international data-sharing projects. The enormous volume of these databases makes it difficult to use conventional data-analysis tools when processing them. Recent advances in big-data analytics, however, provide new methods for predictions of chemical toxicity.
Recently, experts gathered at the Indian Institute of Technology Delhi for a national event, “Breaking Barriers through Bioinformatics and Computational Biology.” They shared information on the latest development in computational biology.
PETA India described how companies could use big data to reduce animal testing. It also asked private and government organizations to use big-data analytics methods. A PETA India poster discussed the disadvantages of traditional animal-based methods to determining the toxicity of chemicals, the progress on data-sharing, and how data in public repositories can be used to make models that can predict the toxicity level of chemical compounds. The steps that regulatory and government authorities can take to adopt big data and reduce animal testing were also discussed.
According to PETA India’s Dr. Rohit Bhatia, using big advanced data analytics approach to predict toxicity save money, time, and lives of many animals.
References
http://www.petaindia.com/blog/big-data-approach-can-predict-toxicity-chemicals-save-thousands-animals/
https://www.eurekalert.org/pub_releases/2017-07/pfte-bda073117.php

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