TechnologyThe CombinatoRx drug discovery engine has identified many promising new drug candidates, perhaps just the beginning to harness the potential of this previously untapped and renewable source of novel therapeutics. cHTS™ - Evaluating Drug CombinationsBuilding on the belief that synergistic drugs could transform medicine, the CombinatoRx drug discovery engine (cHTS™) evaluates the potential of possible drug combinations and elucidates new mechanisms to treat diseases. Our scientific efforts here are empowered by the vast number of different combination opportunities. Through these screens, CombinatoRx:
CombinatoRx has already applied its cHTS™ technology to screen millions of combinations against proven models of a disease. This drug discovery process has yielded thousands of pairs of drugs which in preclinical studies exhibit a therapeutic effect against a model for a target disease when applied in combination, even though neither drug is indicated for such disease on its own. CombinatoRx has also discovered pairs of drugs where preclinical studies suggest the effectiveness or safety of one drug in its primary disease indication may be improved by combining it with another drug that, on its own, is not indicated for that disease. Multiple Filters Yield the Most Robust PossibilitiesOur integrated database and analysis technology enables the selection and characterization of combination drug hits generated by cHTS™ for further research and development. CombinatoRx deploys the technology to identify synergistic combinations of drugs and other small molecules whose active pharmaceutical ingredients have desirable chemical, pharmacological and therapeutic properties. Dose Matrix GenerationIn order to identify and analyze potentially valuable combination effects, cHTS™ generates a dose matrix for each chemical combination capturing the combined activity of two compounds over a broad range of single agent concentrations. cHTS™ is capable of generating hundreds of thousands of data points per day in order to efficiently screen in a dose matrix format. Dose matrix data requires specialized analyses. Data is collected and merged in similar dose matrices before quantitatively benchmarking them to expected combination response patterns. The comparison models are useful in determining the novelty of a combination therapy or to gain insight into the biological mechanism of action of a drug combination. Using these tools, combinations are analyzed, quantitatively scored and visualized in a comprehensive combination effect report, which provides links to available internal and external data on the combination and its constituent compounds. In Silico TestingBefore proceeding into animal studies, new combinations first pass in silico tests, where candidate compounds are compared against a database that aggregates published safety and pharmacology information and data about the compounds in our library. This in silico step ensures, to the extent possible based on published information, that the active pharmaceutical ingredients have profiles that:
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