Watson for Drug Discovery has seven modules that mirror the questions, steps and processes researchers follow in a drug discovery process.
Researchers start with a candidate list, such as a group of diseases, compounds, genes, or drugs they’d like to narrow down for further testing. Watson for Drug Discovery helps predict or define relationships among them through the various modules. Depending on your research project, you may use one, two or all modules at different times and multiple ways.
The modules are different, complementary lenses on a core central repository of knowledge from millions of medical articles, abstracts, patents, drugs, conditions and genes/proteins. You may also connect your own proprietary knowledge stores to Watson Drug Discovery for analysis.
The IBM Watson cognitive platform, trained with healthcare and life sciences knowledge, uses natural language processing to understand contextual meanings in this wealth of data and identify connections. This cognitive platform can also help generate new hypotheses by predicting potential relationships not already known.
Results come as interactive visualizations that show the connections and relationships. These dynamic visuals help you make sense of large volumes of data and detect the signal in the noise to generate new insights.