A Robust, Secure Framework to Effortlessly Bind Distributed Databases and Analysis Tools into Tightly Integrated Translational Drug Discovery Computational Platforms

PROJECT SUMMARY Collaborative Drug DiscoveryIncCDDproposes to develop Cloud Workspaces for Drug Discoverya novel informatics framework that will enable scientists engaged in drug discovery and translation to effortlesslyrobustlyand securely integrate disparate databases and computational tools distributed across multiple systems and vendors into highly efficientcustom tailored computational platformsOur innovative technology will solve a critical problem that hinders drug discovery and translation effortsscientists in this field typically need to combine chemical and biological data from several sourcesrun them through multiple software packages that specialize in different types of analyses and visualizationthen ideally store the results of the analyses together with their underlying experimental dataTodaythis type of integration is difficult and expensive to accomplish and typically fragilecreating a large barrier toiexploiting the rapidly increasing number of highquality public access data repositories andiievaluating promising new analytical tools and strategiesMonolithic platforms offer to solve this problem by bringing everything together under one roofbut they are extremely expensive and they limit flexibilityno package can offer every capabilityThe alternative approachstringing together discrete resourcesevolved during the era of desktop computing and does not translate well to modern cloud based workflows and in particular to the challenges of performing computationally intensive operations that require combining large datasets distributed across remote systemsCloud WorkspacesCWaims to combine the strengths and avoid the weaknesses of these two extremesCW will in essence allow users to easily create their own individualized cloud hosted solutions tailored to their unique requirements and workflowsOur approach offers the performancerobustnessand ease of use of a monolithic software solutionbut without the associated inflexibility and vendor lock inIt offers the flexibility and openness of combining discrete resourcesbut without the associated integration challenges and fragilityand it advances the pipelining approach to embrace cloud based models and to encompass distributed data resources without compromising performance or securityThe Specific Aim for Phaseis to implement a proof of concept CW container environment including bidirectional synchronization of biological and chemical datatransferring only new or modified datawith correct association of chemical identifiersCW will enable scientists to exploit the burgeoning array of public data repositories and sophisticated new computational algorithms and apply them in practice to drug discovery and translation projectsBy eliminating the challenges of installingconfiguringand maintaining softwareCW will allow scientists to quickly explore and adapt new methodologiesConverselythe technology will support new marketing channels and business models for software vendorsenabling faster and broader adoption of advanced techniquesThe market for the technology ranges from academics to small and medium size companies to the large pharmaceutical firms! !PROJECT NARRATIVE The proposed project will create a novel computational framework that will help scientists to fully exploit their own drug discovery research dataaugment their data with datasets that other scientists have contributed to the public domainand apply the best available analytical tools to process these dataThis innovative capability will help to accelerate the discovery and development of novel and improved drugs against a wide range of diseases!