Did you know employees in 44% of life sciences companies typically need to draw from 7 or more structured data sources to find answers? And when you add unstructured data to the mix, another 38% also have 7 or more unstructured data repositories where they could find possible answers? That's a lot of data silos to look through, and as much as 36% of an employee's day can be spend looking for information.
In earlier blogs about the value of cognitive search for life sciences companies, we’ve focused on the role it can play in accelerating drug discovery and finding new therapeutic uses for drugs that have received FDA approval. The search technologies that help achieve those goals can also make life sciences sales and marketing smarter and more effective.
As we’ve explained in many blogs and 5-minute guides, a cognitive search platform should combine AI technologies such as natural language processing, machine learning, and knowledge graphing to deliver a contextualized search and discovery experience without compromising security. Those technologies can turn ordinary search into something much more powerful and transformative for any organization.
When life sciences companies develop new drug therapies or biomedical interventions, what typically attracts the most attention is news about the success or failure of clinical trials. But a lot of work goes on behind the scenes before these efforts ever reach the clinical trial stage. In fact, as life sciences companies decide what promising therapies should receive development resources, it’s often rigorous fact finding and research that determines a go or no-go decision.