A team of toxicologists has just unveiled a digital chemical safety screening tool that could greatly reduce the need for six tests on common animals. These tests represent almost 60% of the estimated 3 to 4 million animals that are used annually in risk tests worldwide.
The tool has been built on a massive database of molecular structures and existing safety data. This tool appears to match and sometimes improve animal test results on matters such as skin sensitization and eye irritation. However, there are limitations … The method is not able to reliably assess the risk of a chemical causing cancer. Nor is it clear the willingness of regulatory agencies to take an approach other than testing on animals.
Still, “We’re really excited about the potential of this model,” says toxicologist Nicole Kleinstreuer, deputy director of a center evaluating alternatives to animal testing at the National Institute of Environmental Health Sciences (NIEHS) in Durham, Carolina. from North. Kleinstreuer, who was not involved in the work, adds that using “big data … to build predictive models is an extremely promising way to reduce and replace animal testing.”
Most developed nations require new chemicals to enter the commercial circuit. The substances must pass some safety tests. However, the traditional practice of exposing rabbits, rats and other animals to chemicals to assess risks faces growing public objections and cost concerns , helping to drive the search for alternatives. In the United States, the Environmental Protection Agency (EPA) has been supporting research into new ways to evaluate chemicals through programs like the Toxicity Forecaster (ToxCast). And in 2016, Congress passed an updated chemical safety law, the Toxic Substances Control Act (TSCA), which directs federal regulators to take steps to reduce the number of animals companies use to test compounds for safety .
One approach is to use what is already known about the safety of existing compounds to predict the risks posed by new chemicals with similar molecular structures without using living things.
In 2016, a team led by Thomas Hartung of the Johns Hopkins University Bloomberg School of Public Health in Baltimore, Maryland, took a step toward that goal by gathering test data on 9,800 chemicals regulated by the European Agency for Substances and Preparations. Chemicals (ECHA) in Helsinki. They then showed that chemicals with similar structures can have similar health effects , such as being irritants.
Hertung’s team of toxicologists have gone one step further, expanding their database to 10 million chemical structures by adding information from the public PubChem database and the US National Toxicology Program. They then compared the structures. and toxicological properties of each possible pair of compounds in your database creating a vast map of similarity that groups compounds by structure and effect. Finally, they tested the model: they asked him to predict the toxicological profile of a randomly chosen chemical by linking it to similar “neighbors” on the map, and he compared the results with six real-life animal tests of the compound.
Better results have been obtained than with animal tests
On average, the computational tool reproduced the animal test results 87% of the time . That’s better than animal testing can do. Reviewing the existing literature, Hartung’s group found that repeated animal testing replicated past results only 81% of the time, on average. “This is an important finding,” Hartung said, because regulators often expect alternative methods to animal testing to be reproducible at the 95% threshold, a standard that even animal testing does not meet.
“Our data shows that we can replace six common tests, which account for 57% of animal toxicology tests in the world , with computer-based predictions and get more confident results,” Hartung said. “And it could help eliminate duplication of effort,” he added. The team found, for example, that 69 chemicals were each tested at least 45 times separately using the so-called Draize rabbit test, a method that involves placing a chemical in the rabbit’s eye and has received significant public opposition. .
The detection method has weaknesses. Although it can predict simple effects like irritation, more complex points like cancer are out of reach , says Mike Rasenberg, who heads ECHA’s Computational Assessment and Diffusion unit. “This will not be the end of animal testing ,” he predicts, “but it is a useful concept for analyzing simple toxicity.”
Europe is expected to accept the new system without problem
The question now is how regulators will view the method. Rasenberg believes that European regulators will accept it for simple endpoints because it meets the validation criteria for so-called quantitative structure-activity relationship models.
In the United States, the NIEHS center is working on method validation. And once it is complete, EPA “will be able to review the evaluation results to determine how and if they can be used to report chemicals evaluated under TSCA,” officials said in a statement. “If the assessment is favorable, these types of models could be used in conjunction with other tools such as ToxCast to report hazards at the detection level or classify / prioritize large amounts of substances.”
Hartung says he hopes the detection method will also be of interest to countries preparing to implement new chemical laws, such as Turkey and South Korea.
Meanwhile, the researchers have partnered with Northbrook, Illinois-based Underwriters Laboratories to make the tool available to companies that want to analyze products before submitting them for regulatory review.
