Patient stratification and personalized medicine are two of the most popular terms in healthcare and life sciences today.
In general they mean individual and group tailoring of therapies and diets depending on patients' genetic make-up and molecular profiling. Many OMICs tests are readily available for DNA, RNA, and protein level testing, but applicability of these assays is very confusing. This is due to the extreme complexity of disease biology and drug response, which often involves alterations in hundreds of genes, of which function and interconnectivity is poorly understood.
Thomson Reuters may help with its state-of-art knowledge base on disease pathology, pathways and protein interactions, systems biology tools. Thomson Reuters has unique experience in predicting therapeutic targets in clinical setting and patient stratification projects with drug companies.
- Sub-gene level biomarker database with powerful filters, search interfaces, and gene parsers will enable identification of the exclusion criteria to eliminate non-responder phenotypes. Biomarkers Graphic >>
- State-of-the-art data analysis algorithms, powerful causal modeling methods and functional descriptor techniques will convey the best results in patient stratification studies. Patient Stratification Study, Virus Graphic >>
- Superior disease-specific pathway maps enhanced by precise cohort specific biomarkers and gain/loss of function annotations will make you ready for personalized medicine era. MetaMiner Pathway Map Graphic >>
- Computational and disease biologists and medical doctors, experienced with cutting edge personalized medicine approaches to help you get the most out of costly patient data and clinical studies. OMICs Report Graphic >>
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