
SAN DIEGO, Dec. 12 (UPI) -- U.S. scientists have created a computational technique that bypasses conventional animal and human drug testing to predict side effects.
Since unexpected side effects account for one third of all drug failures during development, early identification of such adverse effects before drugs are tested in humans is crucial. University of California-San Diego researchers have developed a novel technique using computer modeling to identify potential side effects.
Conventional test methods screen compounds in animal studies in advance of human trials. The UCSD team -- led by Professor Philip Bourne and Lei Xie of the San Diego Supercomputer Center -- uses computational modeling to screen specific drug molecules and compare them with the Protein Data Bank, a worldwide repository that contains tens of thousands of three-dimensional protein structures.
The researchers emphasized their technique still needs to be tested experimentally.
The research is detailed online in the journal PLoS Computational Biology.
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