Collaborative Drug Discovery, Inc. (CDD) proposes to create an innovative software module that will help biologists to quickly and easily encode their plain-text biological assay protocols into formats suitable for computational processing. The software will enable scientists engaged in early stage drug discovery to automatically identify, sort and compare datasets across research groups;efficiently and properly document experimental procedures;and formulate assay project workflow strategies and schema to transition pure research efforts into effective translational projects. In order to encourage adoption, the software will integrate seamlessly into preclinical data management platforms (such as CDD's), prioritize intuitive ease of use by scientists who are not informatics experts, harmonize with existing laboratory workflows, minimize the extra effort of annotation, and deliver clear and immediate benefits to the user as part of an integrated experience. This combination of new capabilities and extreme ease of use will accelerate translational drug discovery efforts by empowering software platforms that bridge the divide between biologists and medicinal chemists to apply sophisticated tools - long available on the chemistry side - for the first time also to the biological side, and thus across both domains. Existing software can already easily connect screening results to chemical structures. This new platform will further connect these data to the purpose and methodology of the screens.
Specific aims for Phase 1 include: 1. Prototype a novel annotation engine that interactively encodes assay protocols using an expressive ontology. The software will query the user when necessary to capture knowledge that cannot be inferred automatically from the text, but will respect the value of the user's time and impose a minimal burden. 2. Show a clear, qualitative improvement in annotation accuracy compared with fully automated approaches. 3. Demonstrate sorting and comparing datasets within the CDD database based on encoded assay descriptors. 4. Evaluate other benefits enabled by assay encoding, and prioritize the features to be implemented in Phase 2.
The proposed project will create novel computational tools that will help researchers to translate new experimental discoveries into the development of novel and improved drugs against a wide range of diseases. These tools will particularly benefit networks of researchers working on diseases that leading pharmaceutical companies have largely ignored because they are not perceived as highly profitable opportunities, despite the fact that in many cases they afflict millions of people.
