A new study published recently in the American Chemical Society's Journal of Chemical and Information Modeling outlines a method that gives doctors the ability to predict negative or dangerous side effects patients may experience when taking prescription drugs.
The study's authors explain how drug side effects--the fourth-leading cause of death in the U.S. according to an ACS announcement--are not tested accurately. A more cost-effective and viable way to test for side effects would be a computer-based approach, according to the researchers.
In their study, the method used was based on chemical and biological information of ingredients in 658 drugs, which in total have a possible 969 side effects. Using the same approach to identify side effects for uncharacterized molecules, the researchers concluded that their method could unearth side effects early in new drug testing.
The University of California-San Francisco School of Pharmacy, Novartis Institutes for BioMedical Research (NIBR) and SeaChange Pharmaceuticals, Inc., performed a similar study, testing on the negative side effects of prescription drugs and how they can be determined, and published their findings last June. Their computer model predicted negative effects of hundreds of current drugs based on a similar correlation between their chemical structures and molecules that cause side effects.
"This basically gives you a computerized safety panel, so someday, when you're deciding among hundreds of thousands of compounds to pursue, you could run a computer program to prioritize for those that may be safest," Michael Keiser, Ph.D., co-first author of the UCSF paper, said in an announcement.
Last fall, researchers used IBM's Blue Gene supercomputer to simulate a drug inhibiting a target enzyme known to spur the spread of pancreatic cancer. They hope their methods eventually lead to the development of anti-cancer drugs with fewer side effects.
To learn more:
- read the study