Building upon existing selective and secure chemical registration and SAR data sharing capabilities is a new research initiative for selective and secure model sharing. Initial published results (see: �Using open source computational tools for predicting human metabolic stability and additional ADME/Tox properties.� Gupta R, Gifford EM, Liston T, Waller CL, Hohman M, Bunin BA, Ekins S. Drug Metab Dispos, 38: 2083-2090, 2010) have demonstrated that free, open source descriptors and models using CDK with SMARTS keys are statistically equivalent (? = .43) to expensive commercial descriptors and models for ADME/Tox prediction with some of the largest training sets used to date (for 193,000 compounds). Initial efforts are focused on ADME/Tox and Tuberculosis QSAR models, although the approach is extensible to any SAR/QSAR data sets. A call is now open for projects using distributed data sets and corresponding models to accelerate collaborative drug discovery.

Open source QSAR models with IP-sensitive SAR data: POCs in secure online environments for collaborative drug discovery showing CDK with SMARTS keys are statistically equivalent (κ = .43)...and open call for all industry and academic projects

243rd National Meeting (2012)

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