CHARLOTTESVILLE, Virginia, June 23, 2015 /PRNewswire/ —
Biovista Inc. today announced the publication of data from research it carried out in collaboration with the FDA and Israeli HMO Clalit, focusing on the prediction of risk factors related to targeted diseases. The research, published in the American Diabetes Association journal Diabetes Care, identifies hypothyroidism as a risk factor for new-onset Diabetes Mellitus, associated with the use of statins, the widely-used class of cholesterol-lowering drugs.
The study was conducted in two phases. In the first phase big data analytics of biomedical data was carried out in order to identify, rank and select highly probable risk factors for the development of statin-associated Diabetes Mellitus. In the second phase, the most prominent risk factor was confirmed in an observational cohort study using large electronic medical record (EMR) data sets.
The Pubmed abstract is available at http://www.ncbi.nlm.nih.gov/pubmed/26070591
“Next-generation drug discovery and therapy development efforts can benefit from the application of cutting-edge knowledge discovery technologies using Artificial Intelligence and Big Data analytics on molecules, mechanisms of action, and electronic medical records, as validated by the results we published,” said Aris Persidis, President of Biovista. “We believe this work is important because of the heightened need to better assess the benefit/risk profile of drugs. Predicting clinical outcomes and risk factors can be usefully applied in developing targeted therapies, designing clinical trials as well as helping create better-differentiated products with enhanced therapeutic and commercial prospects.” Dr. Persidis added.
About Biovista’s Clinical Outcome Search Space (COSS) technology platform.
The Big Data analytics were carried out using Biovista’s COSStechnology. COSSintegrates Big Data and artificial intelligence (AI) technologies to correlate over 270,000 clinical outcomes known to medicine, including risk factors, against any gene, drug or combination. This enables the linking of pre-clinical experimental data directly with potential clinical outcomes. COSSis used for systematic drug repositioning and intellectual property generation, and also to identify adverse events, differentiating the causes of adverse events among a drug or the underlying disease.
Biovista is a privately held biotechnology company that finds novel uses for drugs and assesses their benefit/risk profile using mechanism-of-action big data analytics. http://www.biovista.com