Computers outperform animal testing for many chemicals

Researchers at Johns Hopkins University and UL have developed a computer algorithm that can accurately predict toxicity for tens of thousands of chemicals, which could greatly reduce animal experimentation. The study was published this month in Toxicological Sciences.

The software uses existing information about the safety of tested compounds, including a chemical’s structure and data obtained from cell and animal tests, to predict the toxicity of untested chemicals, since chemicals with similar molecular structures may have similar effects on human health.

Results from the algorithm were very promising, as they showed “that computational methods, both simple and complex, can provide predictive capacity similar to that of animal testing models and potentially stronger in some domains.”

Dr. Thomas Hartung, whose laboratory led this research, indicated, “Our data shows that we can replace six common tests—which account for 57% of the world’s animal toxicology testing—with computer-based prediction and get more reliable results.” The six tests refer to the toxicological “six-pack” which includes oral, dermal, and inhalation toxicity testing, skin and eye irritation tests, and skin sensitization tests.

This could have a huge impact on animal use, as it is estimated that three to four million animals are used around the world every year for risk testing.

The study also provided additional evidence about the lack of reproducibility of animal tests. Repeated animal tests have been found to be reproducible about 81% of the time, but the computational tool reproduced test results 87% of the time. Dr. Hartung noted this was very important, because regulators want alternatives to be reproducible at a 95% threshold, something that even animal tests aren’t doing.  

In the United States, the National Institute of Environmental Health Sciences is working on validating this alternative toxicity testing method, and regulators in Europe will also be considering accepting it as well. 

We look forward to the potential this technology will have on reducing animal use for the detection of toxic chemicals, and will keep you posted on further developments.

This entry was posted in News and tagged on July 24, 2018.
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