This case study demonstrates how a leading Medical Information team used artificial intelligence to elevate its medical content strategy with data-driven insight.
A Medical Information team sought to explore the potential for Artificial Intelligence (AI) to accelerate the detection of approved medical content needs for their newly approved asset.
Download the Standard Response Letter Gap Analysis PDF to see the process.
Using Sorcero’s cognitive technology, an internal Gap Analysis project was divided into three phases:
Sorcero utilized Ingestum, our unified content ingestion framework, to ingest and transform multiple data and document types into a uniform format. Three categories of internal data relevant to the drug in focus were ingested and unified for AI enrichment. All sources of data were unstructured and heterogeneous in format.
The Sorcero advanced AI enrichment process established accurate links between Standard Response Letters and Insight data points that contained high degrees of similarity in (1) language and (2) meaning. The enriched data populated the Sorcero omnichannel analytics platform with AI-augmented insights to drive strategy.
Download the Medical Information Case Study PDF to learn more about the gap analysis.
Medical Information teams are relying on Language Intelligence to generate evidence and respond to internal and external feedback in near real-time. Pharmaceutical companies can ingest, enrich, and analyze heterogeneous and unstructured data in one unified dashboard - providing HCPs and patients with the most accurate data and information available.
Download the Standard Response Letter Gap Analysis Case Study PDF here.