Published: November 12, 2011 r2011 American Chemical Society 278 dx.doi.org/10.1021/ci2003297 | J. Chem. Inf. Model. 2012, 52, 278–284 ARTICLE pubs.acs.org/jcim DEGAS: Sharing and Tracking Target Compound Ideas with External Collaborators Man-Ling Lee,* Ignacio Aliagas, Jennafer Dotson, Jianwen A. Feng, Alberto Gobbi, and Timothy Heffron Genentech Inc., South San Francisco, California 94080, United States ’ INTRODUCTION Modern small molecule drug discovery poses many chal- lenges. Before a compound is selected for clinical studies, many properties need to be optimized, such as activity, selectivity, and safety. The process is a multiparameter optimization in which many compounds have to be made and evaluated in regards to all their properties. Each compound synthesis and testing is asso- ciated with costs in terms of time, resources, and money. Another major challenge is that today drug discovery is often conducted by geographically separated teams. Decision making is compli- cated by difficulties in communication and by the differences in time zones. Improving the collaborative decision process and reducing the cycle time have an impact on the likelihood of success and the cost of a drug discovery project. A number of pharmaceutical companies have presented their compound profiling applications in the past. The features of these applications vary greatly. The most common features are: • enumeration of combinatorial libraries 1À4 • computation of physicochemical properties and ADME/ Tox models 1À5 • graphical data analysis 1À5 • access to in-house databases and reagent management systems 1,2,4 The applications let users evaluate and prioritize compounds based on their properties and chemical structure. Some provide access to in-house reagent inventories to support synthesis planning. A complementary approach to support decision making is to assemble expert knowledge in knowledge management systems. Astra Zeneca and Actelion adopted Wiki-technology for their applications CODD 6 and ActWiki, 7 respectively. PFAKT 8 from Pfizer and ROCK 9 from Roche were implemented from scratch to meet the specific requirements for knowledge submission, revision, processing, and presentation. The knowledge captured varies widely by application: CODD and PFAKT focus on capturing compound-specific knowledge and the status of virtual compounds, while ActWiki and ROCK focus on capturing more general medicinal chemistry knowledge. Knowledge management and compound profiling applica- tions help to foster collaborative teamwork. However, with members of a drug discovery team operating from different sites, the aspect of instant sharing has become important. Several publications describe software applications which help sharing information and coordinating efforts. Microsoft’s SharePoint 10 has become a popular framework for shared content management. This framework lets team members share documents on the web. Examples include C-ME 11 and OnePoint. 12 Collaborative Drug Discovery (CDD) has developed a proprietary web platform. It aims at bringing scientists from all over the world together using concepts from social networking. 13 A significant number of the small molecule drug discovery projects at Genentech are collaborations with external partners in which Genentech scientists interact closely with scientists at the collaborating sites. To facilitate transparent decision making, we have introduced DEGAS 14 to the internal and external users. Target compound ideas are entered and are instantly available to all other team members. The DEGAS compound identifier provides a short unique name that can be used when referring to specific compounds in discussions. Team members at the dif- ferent sites make joint decisions on which molecules should be synthesized. They also need to track synthesis progress. Storing Special Issue: 2011 Noordwijkerhout Cheminformatics Received: July 16, 2011 ABSTRACT: To minimize the risk of failure in clinical trials, drug discovery teams must propose active and selective clinical candidates with good physicochemical properties. An additional challenge is that today drug discovery is often conducted by teams at different geographical locations. To improve the collaborative decision making on which compounds to synthe- size, we have implemented DEGAS, an application which enables scientists from Genentech and from collaborating external partners to instantly access the same data. DEGAS was implemented to ensure that only the best target compounds are made and that they are made without duplicate effort. Physicochemical properties and DMPK model predictions are computed for each compound to allow the team to make informed decisions when prioritizing. The synthesis progress can be easily tracked. While developing DEGAS, ease of use was a particular goal in order to minimize the difficulty of training and supporting remote users.