Open PHACTS: Semantic Technologies And Drug Discovery

Research and discovery in the life sciences is a pretty complicated business. The complexity of the modern scientific process seems to be a reflection of the intricacies of life and the processes associated with disease and its treatment. Furthermore, as technologies become more advanced, so too does the problem of managing the ever expanding quantity of data being generated.

Currently, pharmaceutical companies expend significant and duplicated efforts aligning and integrating their internal information with public data sources. This process is largely incompatible with large-scale computational approaches and the vast majority of drug discovery sources find it difficult to complicate with eachother.

The typical scientific process produces vast amounts of information that is dispersed and hidden in various data sources (e.g. literature and curated databases). Data-driven life science research, including drug discovery, will increasingly rely on a community of collaborating partners to extract knowledge from these sources to solve complex questions. (1)