Environmental Health & Safety

UNC Improves System For Predicting New Product Risk

By Chemical Processing Staff

Nov 18, 2016

The approach used by regulators to initially screen new chemical products for toxic effects is wrong almost half the time, according to scientists at the University of North Carolina at Chapel Hill. They have proposed an improvement that could reportedly increase accuracy to as much as 85%, saving millions of dollars and years of development time for new drugs and other products while improving safety.

Regulatory agencies, such as the U.S. Food and Drug Administration and the Environmental Protection Agency, that are charged with evaluating new drugs and other chemical products rely on an initial screening of a product’s molecular structure, according to UNC Chapel Hill. Any groups of atoms that are believed to be linked to chemical toxicity trigger a structural alert. A product that generates a structural alert is sent back for more testing.

Researchers led by Alex Tropsha, K. H. Lee Distinguished Professor at the UNC Eshelman School of Pharmacy, determined that structural alerts are accurate in predicting toxicity only about 50% to 60% of the time. They developed a computational approach that uses statistical analysis to determine how trustworthy an alert is. Their improvement reportedly augments the simple-but-often-wrong thumbs up or thumbs down currently provided.

“A lot of chemicals are incorrectly identified as potentially toxic even though in the end they are not toxic and that could have been predicted,” Tropsha says.  “Companies are forced to run a lot of unnecessary and costly experiments, and because companies run these checks themselves before submitting their products to regulators, there are products that never see the light of day because they are flagged as toxic when they are not.”

By layering a technique called quantitative structure-activity relationship, or QSAR, modeling over the existing alerts system, the UNC-Chapel Hill researchers are able to account for the structure of the entire chemical molecule and assign a numerical value to the chance that an alert is accurate. Tropsha’s group plans to make their system freely available to regulators and scientists as web-based computer software.

For more information, visit: www.unc.edu