The U.S. Food and Drug Administration (FDA) and pharmaceutical companies are very interested in system-wide drug effects, explained Subramaniam. "In the coming decade, researchers, drug developers and clinicians will use systems biology to discover exactly which drug-induced functional changes are related to therapeutic efficacy and which are unrelated to efficacy," said Subramaniam.

The side effects of statins-a class of cholesterol-lowering drugs-provide an example of the kinds of non-therapeutic effects that researchers hope to uncover during the drug development process. "These are the kinds of problems we believe we can identify early on, by taking a system-wide approach," said Subramaniam.

The team's systems biology approach could also help doctors quickly determine if a specific patient is likely to respond to a drug, based on their personal gene expression profile and basic phenotypic information. In the new study, the researchers uncovered markers for identifying which patients will respond to TZD treatment with improved insulin sensitivity-and which patients will not respond.

Methodologies developed in Subramaniam's lab make it possible to say what is and is not significant from mountains of gene expression data.

"This study is built on our variance modeling approach. Gene expression gives you thousands of transcription data points, and we devised a way to tease out what is significant and what is not significant. We are looking at gene expression profiles and their relevance to function," said Gene Hsiao, a Ph.D. candidate in bioengineering at UCSD and an author on the PNAS paper.

"I think this is one of the first successful examples of 'systems medicine'-which is the application of systems biology to medicine," said Subramaniam, who explained that this systems approach can be applied to many other diseases and drugs. His team is currently investigating both cell death and stem cell differentiation using similar strategies.

Source: University of California - San Diego