It’s well-known that clinical trials are one of the most expensive parts of the drug development process. Addressable bottlenecks include improving access to knowledge for protocol design such as site selection, assessment schedules, eligibility criteria, and more. As well as clinical trial design, data extraction from clinical literature is also useful for other applications such as competitive intelligence.
Such extraction, usually done manually, is often tedious and error-prone. Linguamatics NLP is a valuable technology for extracting and synthesizing the high value information that is found in unstructured text. In this webinar, we discuss the benefits of text analytics and natural language processing over internal and external clinical trial data to optimize clinical trial design and gain knowledge from legacy data.