success story

Making clinical trial data come alive

A comprehensive cognitive computing framework
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challenge
During the clinical trial cycles, enormous amount of data is generated at each stage. The pharma leader wanted to leverage technology and cognitive computing to analyze the large volumes of data, help generate insights regarding rationale for failed clinical studies, and leverage that to monitor studies going forward. Analytical insights will allow them to predict failures early, take corrective action or terminate the studies and save costs.
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process
Given the nuanced and ambiguous nature of this project, we ran a series of natural language processing and machine learning based functional and technical experiments (each ranging from a few hours to few days) and documented those results to understand opportunities, feasibility and limitations of what could be accomplished.
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solution
We leveraged the ‘signal extraction framework’ to mine the right insights determining the success or failure of a clinical trial, from a large unstructured set of data. We employed a disease area-specific clinical trial success framework to develop detailed compound profiles and interpret the signal. Using the insights from this, we developed a dashboard wherein our client could look at the summary profile of each candidate in the clinical study or any competitor compounds.
Nagarro showed great transparency in outlining their approach, clearly communicated the methods used, gave their assessment and results to our challenging questions, and a dashboard containing the results of the sentiment analysis…This is a fairly new and developing technology and therefore we had the need to describe the approach, thank-you for that.
Client Sponsor
Innovation and entrepreneurship incubator lead for the client

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