Big data beats animal testing for finding toxic chemicals - Futurity

You are free to share this article under the Attribution 4.0 International license. Scientists may be able to better predict the toxicity of new chemicals through data analysis than with standard tests on animals, according to a new study. The researchers say they developed a large database of known chemicals and then used it to map the toxic properties of different chemical structures. They then showed they could predict the toxic properties of a new chemical compound with structures similar to a known chemical, and do it more accurately than with an animal test. "A new pesticide, for example, might require 30 separate animal tests, costing the sponsoring company about $20 million…" The most advanced toxicity-prediction tool the team developed was on average about 87 percent accurate in reproducing consensus animal-test-based results across nine common tests, which account for 57 percent of the world's animal toxicology testing.