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.