Pharmacogenomics and personalized medicine
By massively speeding up the rate at which genes can be sequenced, Next Generation Sequencing (NGS) promises to revolutionize applied markets like diagnostics, drug discovery, biomarker discovery, agriculture & animals research, and personalized medicine.
I2E puts these practical applications within reach. It can dramatically shorten the time needed to analyze the data, providing a detailed and focused gene profile for the genotype, variants, mutations and phenotype under investigation.
For over a decade, FDA CDER has been urging the adoption of pharmacogenomics strategies and the pursuit of targeted therapies. Personalized medicine holds out the prospect of lower variability of drug response, improved safety, and increased treatment efficacy.
Key to this is the increased application of NGS across the drug discovery and development pathway; for example, in target evaluation, patient stratification and clinical profiling.
Biological interpretation of NGS output is highly time-consuming: mostly a manual process of literature searching and annotation of the gene results.
This can be accelerated with I2E. It can be used to collate a comprehensive gene profile, with key biological annotation from combination of sources (e.g. MEDLINE, PubMed Central, OMIM, NIH Grants).
Use of extensive ontologies and its advanced linguistic analytics, along with pattern- and rule-based approaches for mutation and genetic information (e.g. SNPs, CNV, indels, nucleotide or amino acid substitutions) means that I2E can extract the most up-to-date published knowledge for a gene profile, including:
- Expression information
- Protein-Compound interactions
- Protein-Protein interactions
- Key opinion leaders for the gene or disease area
To find out more:
Read our blog on pharmacogenomics across the drug discovery pipeline or read our application note on the power of text mining for precision medicine research.
Watch our webinars on I2E for pharmacogenomics and personalized medicine:
Text Mining at Sanofi for Genotype-Phenotype Associations in Multiple Sclerosis
In this webinar we discuss how Sanofi used Linguamatics I2E natural language processing (NLP) text mining solution was for literature mining to annotate the association of human leukocyte antigen (HLA) alleles with diseases and drug hypersensitivity as part of a multiple sclerosis (MS) biomarker discovery project.
A Systematic Examination of Gene-Disease Associations Through Text Mining Approaches
At Shire, I2E is used for systematic examination of gene-disease associations. In this webinar, Madhusudan Natarajan will discuss the value of text analytics for disease severity and genotype-phenotype association, focused on Hunter Syndrome. This rare disease, also known as Mucopolysaccharidosis II, is caused by an X-linked deficiency in iduronate-2-sulfatase.
Advanced Text Analytics within Pharmacogenomics and Personalized Medicine - I2E for NGS Annotation
This webinar will show how I2E can be used to collate a comprehensive gene profile, with key biological annotation from a combination of sources like MEDLINE, OMIM and NIH Grants.