A New Computational Technique Predicts Side-Effects Of A Major Cancer Drug

Researchers at the University of California San Diego have developed a novel computer technique to search for the side effects of major pharmaceuticals. The study, reported November 30 in PLoS Computational Biology relates to a class of drugs known as Select Estrogen Receptor Modulators (SERMs), which includes tamoxifen, the most prescribed drug in the treatment of breast cancer. Unexpected side effects account for one-third of all drug development failures and result in drugs being pulled from the market. Typically drugs are tested using an experimental method which aims to identify off-target proteins that cause side effects. The team in this study, led by Drs. Philip Bourne and Lei Xie, propose a computational modeling approach. If broadly successful the approach could shorten the drug development process and reduce costly recalls.

A New Computational Technique Predicts Side-Effects Of A Major Cancer Drug