• Access to real-world data, collaborative tools and templates can potentially enable greater trial efficiency while aiming to reduce the potential for costly amendments
IBM Watson Health recently unveiled its newest cloud-based technology IBM Study Advance at the 11th Annual Summit for Clinical Ops Executives (SCOPE). The data-driven, study design tool, is designed to optimize clinical trial protocol design by merging automated access to real-world patient population data, standardizing protocol template guidance and providing a collaborative workspace designed to facilitate efficiency.
On average, a single protocol amendment to a Phase III clinical trial can result in approximately $500,000 (USD) in unplanned expenses and an additional 61 days to the project timeline. IBM Study Advance is designed to offer critical insights during the process of study design to help reduce the number of amendments during clinical trials. The tool is designed with an interface to provide access to commercial and claims data from de-identified patient profiles covering 89 million lives from multiple employer-sponsored U.S. healthcare beneficiaries, as well as tools to assess the impact of inclusion and exclusion criteria on the eligible patient population.
“Currently, 80% of trials experience delays in recruiting and one out of four amendments were considered completely avoidable,” said Rob DiCicco, PharmD, Deputy Chief Health Officer, IBM Watson Health. “Breakdowns in the clinical trial process, including issues caused by study design decisions, may potentially delay access to life-changing therapies for patients. IBM Study Advance aims to remove the barriers in clinical development to help researchers efficiently bring necessary therapies to patients.”
Study Advance’s collaborative workspace is designed to allow near real-time collaboration with study design team members who can manage and assign the team to specific sections of the protocol. The workspace is also designed to provide access to standard protocol templates and version control capabilities with complete traceability back to changes, aiming to reduce the average time required to author a clinical trial protocol.
