The aim of this project is to create an environment which enables new biomarker tests, based on molecular pathology techniques, to be developed. These can then be used to stratify patients, to allow more accurate diagnosis or prediction of the best treatments to use. The initial focus will be on people who suffer from inflammatory disease (psoriasis, rheumatoid arthritis and lupus), given the availability of a large number of patient samples for these diseases. Text mining will be employed to carry out automated semantic analysis of various “unstructured” textual information sources thet may contain information that is relevant to the development of biomarker tests, including biomedical literature and electronic health records. Given that each of these sources constitutes vast numbers of documents, information contained within them may be hidden and easily overlooked. TM techniques will be used in a number of ways to enhance the ease and efficiency with which unstructured textual information sources can be exploited to support the development of biomarker tests.

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