Gene Network Sciences receives SBIR

Company to continue development of its VisualHeart modeling software for predicting the cardiac effects of medications.

Lisa Espenschade
CAMBRIDGE, Mass.—Gene Network Sciences (GNS) recent­ly received a Phase II Small Business Innovation Research (SBIR) grant to continue devel­opment of its VisualHeart mod­eling software for predicting the cardiac effects of medications. The National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) made the three-year, $1.6 million award.
 
Colin Hill, GNS CEO, says VisualHeart discovers and vali­dates mechanisms by which compounds affect the electrical activity of the heart and induce cardiac arrhythmias, thus pro­viding toxicity screening meth­ods for use before late-stage clinical trials. "That's of utmost importance to increasing clini­cal trial success rates," he says. "Part of that goes toward help­ing our pharmaceutical partners really make the best use of their experimental data." Hill hopes GNS will be the first company capable of predicting arrhyth­mias in silico.
 
VisualHeart combines data on drugs' effects at the molecular/ion channel level with compu­tational methods, tapping into experimental ECG results from Dr. Robert Gilmour of Cornell University and Dr. Charles Antzelevitch of the Masonic Medical Research Laboratory (MMRL) plus a commercial partnership with IBM's Blue Gene super­computing project.
 
"One of the key aspects of [the VisualHeart] approach," says Hill, "is the extreme use of supercomputing to enable accurate prediction of drugs that affect drug-induced arrhythmia. That's really some­thing no-one else has taken to this level." Hill says VisualHeart leverages Blue Gene's architec­ture and massive scale, enabling GNS to attempt new modeling approaches.
 
Hill expects successful work under the grant to give GNS opportunities to position itself as a partner for pharmaceutical companies and the FDA. "I think ultimately GNS wants to be the one-stop shop for pharmaceutical companies that need to increase their abilities to predict which compounds will make it through clinical trials," says Hill. "This kind of approach is very timely to an industry that really can't con­tinue to afford taking those kinds of risks, especially when there are technologies that allow them to remediate that risk."
 
Dr. Jennie Larkin, pro­gram director of the Advanced Technologies and Surgery Branch Division of Cardiovascular Diseases at the NHLBI, also sees good com­mercial potential for GNS, thanks to an outstanding business plan and interesting science. The NIH currently funds computational modeling efforts in various medi­cal areas with the hope of develop­ing more user-friendly tools. "You need to be able to make it usable by the actual researchers for it to have full impact," says Larkin. She sees GNS's combination of risk assess­ment and computational tech­niques as a "fabulous win."
 
GNS's other research, says Hill, goes beyond the heart into disease-agnostic work that uses another platform, called Network Inference Engine, to explore mole­cules under millions of conditions. That platform has broader appli­cations including cancer, diabetes, and infectious disease and also uses IBM technology to reverse-engineer raw experimental data into usable information on drug action.
 
"It's satisfying to see that these rather cutting-edge approaches are now becoming more widely accepted in the industry and the marketplace," says Hill. He hopes more pharmaceutical companies will make efforts to utilize the data they generate to understand drug mechanisms while improving the chances of bringing medicines to market. "We're focused on that goal with them," he says. GNS announced in June a joint agree­ment with Murex Pharmaceuticals for using computer-based models in developing cancer therapies; other alliances include Novartis and Johnson & Johnson.

Lisa Espenschade

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