Knowledgent has a deep heritage in helping Life Sciences Organization utilize Big Data technology to further their Data and Analytics initiatives and derive critical insights for the business.

Case Study: Improving Patient Care for a Major Life Sciences R&D Organization

Multiple Sclerosis is a chronic neurological disease for which there is no cure. MS is estimated to affect approximately 400,000 people in the US , and 2.1 million worldwide. MS is believed to be caused by a combination of genetic, environmental, infectious and autoimmune factors.

Knowledgent implemented advanced analytics to comb through a series of over 2,000 genetic and environmental factors that might lead to multiple sclerosis (MS) symptoms. The analytics helped the researchers fine tune their aim and match the speed of analysis with the rate of data coming into their systems with a goal to demystify why the disease progresses more rapidly in some patients and get those insights back to other researchers, so they can find new treatments.

Case Study: Big Data Innovation for a Biotech Organization

This Biotech had no shared vision for Big Data and Analytics, and Senior management did not understand if the activities already underway were the right ones. There was no consensus as to the value of Big Data initiatives within the business, and conflicting views and priorities resulted in organizational inertia and confusion.

Knowledgent customized our framework to the client, to understand their Big Data need and potential impact. We facilitated a Big Data workshop that developed a shared, prioritized set of high-value initiatives and developed a high-level action plan to move initiatives from concept to implementation.

Knowledgent clearly established the value of Big Data to the business and unified the understanding across Senior Management of Big Data’s potential and its priority. We identified opportunities to reduce cost, improve timeliness, and gain market advantage utilizing Big Data and Analytics and formulated a vision for Big Data and its use – the beginnings of a Big Data Strategy.

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