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Our Offerings

While each project we undertake with our partners is unique, we have already deployed our analytic expertise and the breadth of data contained in BioVU® in a number of different ways. In addition to the offerings and examples listed below, we are also open to exploring new ways to leverage BioVU® to improve human health – please contact us at to discuss further.


Indication Exploration

Nashville Biosciences’ scientists have combined pheWAS™ with a wide range of other data resources to guide pharmaceutical R&D in multiple different settings, including early stage target assessment, portfolio prioritization, mid-stage indication expansion, repositioning of drugs that failed clinical trial and generic repurposing.

Personalized Medicine

Nashville Biosciences’ scientists have used the clinical and genetic data in BioVU® to retrospectively analyze a wide range of patients cohorts for pharmaceutical and diagnostics clients, including patients with the same disease, patients taking the same medication or patients with the same genotype, or to generate new data through BioVU®’s capabilities to collect blood plasma samples.

Example Projects

The Nashville Biosciences team has served multiple clients across the life science spectrum on a wide range of projects, from early stage target prioritization, to target deep dives and cohort analysis and screening.

Below are examples of how we integrated BioVU® data with a diverse set of external resources and assembled the best answer possible to our clients’ requests.

Early Stage Target Prioritization

The Challenge

A top twenty pharmaceutical company was looking to prioritize 23 early stage targets, including both internal and partnered programs. The goal was to utilize pheWAS™ and BioVU® to identify disease phenotypes that represented possible indications, and prioritize them based on the strength of evidence and fit with the company’s focus areas.

The Approach

Nashville Biosciences identified 17 targets with existing SNP genotype data and scored associated disease phenotypes for each target by pheWAS™ stats, biological plausibility, market attractiveness and competitive intensity.

The Solution

The Nashville Biosciences team rapidly identified validating and novel disease hypotheses for all targets and ranked the targets into three priority categories based on aggregate scoring. Upon a thorough understanding of the client’s therapeutic focus areas, we selected 4 targets for further deep dive review.

Target Disease Deep Dives

The Challenge

Initial promising hypotheses for novel target – disease links were identified via pheWAS™. The Nashville Biosciences team conducted deep dives into all available clinical & scientific evidence to assess these hypotheses before our client moved to in vitro biological testing.

The Approach

Nashville Biosciences selected and chart reviewed cohorts of patients identified via pheWAS™ to refine the disease diagnosis and specify clinical features of the patient cohort. We then used an extensive review of published literature and other databases to build a mechanistic hypothesis and designed experiments to test it.

The Solution

Nashville Biosciences is currently working through target-disease deep dives for several early clients. This approach has been used by Vanderbilt colleagues to assess 10+ target-disease concepts now in various stages of experimental testing at Vanderbilt University.

Cohort Analysis and Screening

The Challenge

A top ten pharmaceutical company was looking to develop a novel therapy for poorly diagnosed and treated diseases. Our objective was to use electronic medical records (EMR) to identify disease and disease-protected cohorts with common static and longitudinal risk factors for sequencing and new variant identification.

The Approach

Nashville Biosciences partnered with the client to developed EMR mining logic to assess project feasibility. From there, we worked to identify and validate patients for both cohorts (i.e., based on structured EMR data and de-identified chart review).

The Solution

While this project is currently in progress, the feasibility assessment is complete, and we are working on cohort identification & validation. The use of retrospective data (i.e., for long-term longitudinal variables) and banked DNA samples greatly reduces total study time.