Can semantic web technologies enable translational medicine?

Abstract

The success of new innovations and technologies are very often disruptive in nature. At the same time, they enable novel next generation infrastructures and solutions. These solutions often give rise to creation of new commercial markets and/or introduce great efficiencies in the form of efficient processes and the ability to create, organize, share and manage knowledge effectively. This benefits both researchers and practitioners in a given field of activity. In this chapter, we explore the area of Translational Medicine which aims to improve communication between the basic and clinical sciences so that more therapeutic insights may be derived from new scientific ideas - and vice versa. Translation research goes from bench to bedside, where theories emerging from preclinical experimentation are tested on disease-affected human subjects, and from bedside to bench, where information obtained from preliminary human experimentation can be used to refine our understanding of the biological principles underpinning the heterogeneity of human disease and polymorphism(s). Informatics in general and semantic web technologies in particular, has a big role to play in making this a reality. We present a clinical use case and identify critical requirements, viz., data integration, clinical decision support and knowledge maintenance and provenance, which should be supported to enable translational medicine. Solutions based on semantic web technologies for these requirements are also presented. Finally, we discuss research issues motivated by the gaps in the current state of the art in semantic web technologies: (a) The impact of expressive data and knowledge models and query languages; (b) The role played by declarative specifications such as rules, description logics axioms and the associated querying and inference mechanisms based on these specifications; (c) Architectures for data integration, clinical decision support and knowledge management in the context of the application use case.