Design and analyze an in silico cohort for your next market analysis, R&D, or real world evidence (RWE) project from our database of 3M+ de-identified EMRs. Nashville Biosciences guides your scientists through the process of curating and analyzing custom controlled cohorts. Applications include synthetic control arms for clinical trials, natural history studies, trial recruitment optimization and comparative effectiveness analyses.
Overlay BioVU®’s existing 2M+ marker genotype data onto your in silico cohort, or generate new molecular data from DNA, Blood, plasma and other research-grade biospecimens collected through BioVU®. Nashville Biosciences can facilitate whole genome/exome sequencing, genotyping, and other omics analyses, as well as a range of bioinformatics services, providing custom R&D pipelines for rich molecular analyses. Example applications include variant, target and biomarker identification and validation.
Leverage decades of real world clinical history and linked genotype data from BioVU® to uncover genetic associations between drug targets and disease phenotypes and identify novel therapeutic indications and adverse event risks. Nashville Biosciences leverages the power of pheWAS™ to help pharma and biotech companies with pre-clinical planning, portfolio prioritization, drug rescue and repositioning, and lifecycle extension.
The NashBio™ Technology
Introduction to BioVU®
An Unparalleled Resource for Improving Human Health
BioVU® is a bio-bank of de-identified longitudinal medical records and DNA extracted from discarded blood samples collected during routine clinical care designed to enable exploration of the relationships among genetic variation, disease susceptibility and variable drug responses.
The NashBio™ Technology
Introduction to PheWAS™
Creating News Means of Diagnosing, Treating and Preventing Disease
Drug discovery traditionally has been approached by attempting to identify the genes or targets underlying the disease of interest and then identifying a molecule that interacts with that target. With this approach, we don’t always understand the disease process or how the drug target is implicated in the disease. The pursuit of new targets is also difficult.
The pheWAS™ approach increases the probability of R&D success by leveraging natural genetic ‘experiments’ within human DNA. We use small mutations naturally present in each and every human genome, and correlate those mutations to the full disease landscape. This ‘target-first’ approach allows us to map out diseases that may be treated by a new drug or potential sides effects that may occur.