Gene Network Sciences (GNS) has announced that the company has won a Phase II Small Business Innovation Research Grant (SBIR) from the National Heart, Lung, and Blood Institute of the National Institutes of Health.
The three-year, $1.6 million grant will be used to further develop VisualHeart, the company's cardiac modeling software platform.
VisualHeart incorporates data on a drug's effect at the molecular/ion channel level into a mechanistic simulation of cardiac electrical activity to determine proarrhythmic markers and mechanism of action.
The technology is designed to improve risk assessment of new drug candidates in clinical trials by simulating a drug's effect on the electrocardiogram (ECG), including the long QT index.
A fundamental problem facing safety pharmacologists is the translation of results from one experimental model, such as a HERG screen, into more complicated systems, such as action potential assays or whole animal experiments.
"We've developed our technology using a 'model-agnostic' approach, which allows us to quickly translate results between assays involving different systems, and to incorporate and build on the solid foundation of work done by heart modeling pioneers," said Dr. Jeffrey Fox, vice president of research at GNS and the principal investigator of the grant.
"By using this technology, pharmaceutical companies will save money by efficiently focusing their data collection efforts."
Central to the GNS methodology is the combination of experimental data and computational methods. As part of the grant, the company will collaborate with Dr. Robert Gilmour of Cornell University and Dr. Charles Antzelevitch of the Masonic Medical Research Laboratory to generate the necessary experimental data.
GNS will also collaborate with IBM, who has agreed to contribute Blue Gene supercomputing power and expertise to the project.
The GNS VisualHeart platform generates proarrhythmic markers by quantifying a drug's effect on ion channels, action potential (AP), and ECG output. The platform will help identify specific, quantitative hypotheses for the mechanism of action by which a drug may alter the cardiac AP and ECG.
The platform will determine these deliverables by using ion current data to generate data-driven models of cardiac ion currents. These models will be incorporated into myocyte models that can predict the drug's effect on the cardiac AP.
AP data can also be used to validate and refine the models. Finally, the myocyte models will be embedded into a model of electrical wave propagation in the ventricle that can predict a drug's effect on the ECG.
"Initiatives such as the FDA's Critical Path highlight the importance of risk reduction as medical discoveries become new products. Our platform helps fulfill mandates such as this, providing a way for pharmaceutical companies to speed safer drugs to market," said Colin Hill, CEO of Gene Network Sciences.
In 2005, GNS received three cardiac-related Phase I SBIR grants from the NIH. These grants helped to: develop the simulation platform for creating data-driven computer models of cardiac electrophysiology; streamline data integration; and extend GNS technology to include models of key cardiac signaling networks.
In 2004, a team from GNS, Cornell and UCSD won a $2 million, four-year Bioengineering Research Grant from the NIH to characterize ion channels via a computer model of the canine ventricle.