This is a breakthrough development that could reduce the need for tests which, as well as considered unethical by many, are expensive, time-consuming and often inaccurate.
The computer-based system – called Read-Across-based Structure Activity Relationship (RASAR) – offers an alternative approach to animal testing by using artificial intelligence to analyze a database on chemical safety that contains the results of 800,000 tests on 10,000 different chemicals.
The Financial Times reports that “the computer has mapped out previously unknown relationships between molecular structure and specific types of toxicity, such as the effect on the eyes, skin or DNA.”
RASAR has achieved an 87% accuracy in predicting chemical toxicity, compared to 81% in animal tests. The results were published in the journal Toxicological Sciences, and the system’s lead designer, Thomas Hartung, a professor at Johns Hopkins University in Baltimore, presented the findings at the EuroScience Open Forum in France last week.
Companies that produce chemical compounds would eventually be able to access RASAR, which will be made available to the public. When formulating something like a new pesticide, the manufacturer could pull up information about various chemicals without having to test them individually and involve unnecessary duplicate testing.
RASAR has similarities to the Human Toxicology Project Consortium which is also working to build a database of information about chemicals, based on results from toxicity and exposure tests and predictive computer programs. This approach is called Pathway-Based Toxicology, and its goal is to make animal testing obsolete while offering better predictions about chemicals’ reactions in the human body.