Defining a Clinical and R&D Data Strategy for a Gene Therapy Company
Clarkston Consulting recently partnered with a biotech client on a clinical and R&D strategy. Read a synopsis of the project below or download the full clinical R&D data strategy case study.
A global biotechnology company on a mission to engineer solutions for rare diseases was facing challenges across R&D with their data orchestration to empower exploratory analyses and to better leverage a wide array of existing data assets. With a primary focus on research at the forefront of gene therapy, RNA-targeted exon skipping, and gene editing, the client’s data ecosystem and needs were rapidly evolving as the business launched new commercial products and continued to gather positive data for its late-stage clinical trials.
The company’s R&D leadership saw an opportunity to drive further flexibility, speed, and orchestration of their data to drive faster insights and even better patient outcomes. The R&D organization had an aspiration to better leverage a broad array of R&D data, including pre-clinical, clinical, and operational data in a way that would make it easier, faster, and less complex to derive the insights necessary to drive even more value for patients and the business.
Download the Clinical and R&D Data Strategy Case Study Here
Clarkston performed 50+ working sessions across R&D leaders to understand how the company was storing, generating, processing, and using clinical and non-clinical data. Through the discovery process, the team identified 40+ business challenges and crafted recommendations to optimize their current landscape and define how R&D data processes could be holistically managed and aggregated to facilitate effective and efficient ways to derive value from the data across multiple functional areas and data sources.
Ultimately, Clarkston Consulting provided the company with a short-term and long-term strategy meant to realize the benefit of transformed data orchestration within R&D. Clarkston’s recommendations and roadmap are helping the client achieve and sustain exploratory analyses that were not possible before by building the foundation to systematically ingest data and develop reports with dynamic dashboards and visuals to view data at the patient level.
