Researchers use I2E to understand which genes or other entities are potential biomarkers for particular diseases, and search and extract key information on interactions with various compounds.
According to our customers, I2E reduces time spent on query development by up to 85%; and better queries improve search: for example, literature review can be reduced from 3-4 weeks, to just 7-10 days.
I2E adds value in the hunt for new biomarkers within drug discovery and development.
Biomarkers can be defined as naturally occurring molecules, genes, or characteristics by which a particular pathological or physiological process, disease, etc. can be identified. There are two major types of biomarkers: biomarkers of exposure, which are used in risk prediction and safety/toxicity assessment; and biomarkers of disease, which are used in screening and diagnosis and monitoring of disease progression.
These biomarkers can take different forms, e.g. enzymes with varying activity, changes in expression levels of particular genes, or the presence or absence of individual metabolites. The flexibility of I2E allows the user to search for any of these data types and to find relationships between known or novel markers, and diseases, mutations, drugs and more.
Merck Use Case for Biomarker Discovery
Researchers at Merck used I2E and other tools to discover potential novel biomarkers and phenotypes for diabetes and obesity, from PubMed, clinical trial data, and internal Merck research documents.
Trugenberger et al. (2013): "Discovery of novel biomarkers and phenotypes by semantic technologies”. BMC Bioinformatics; 14:51
Sanofi Use case for Multiple Sclerosis (MS) biomarker discovery
Sanofi established a workflow for whole exome sequencing-based HLA typing and analysis that identified more than 400 HLA alleles. They used the Linguamatics I2E platform to analyze and search the literature to annotate the association of the HLA alleles with diseases and drug hypersensitivity.