Pharma organizations have an ever-increasing amount of data that can be used in drug discovery. With 80% of all data in unstructured formats, organizations need innovative technologies to untap the potential value of these data streams. Deploying natural language processing (NLP) at scale is key to greatly increasing data access and data insights.
Join us to learn how NLP can help improve the speed-to-insight generation 10-100X. We’ll cover how we’re using the latest AI/ML technologies and several examples of how our clients, such as Roche and Sanofi, are utilizing our platform. We’ll go over a variety of use cases including:
Constantinos Katevatis is Associate Director, R&D NLP at Linguamatics, an IQVIA company. He is responsible for developing the strategic vision of Linguamatics’ product portfolio and business development for R&D and clinical operations in the pharma and biotech industries. Constantinos has experience and expertise in NLP-centric data extraction and data management across the pharma product life cycle. Before joining the life science industry, Constantinos completed a doctorate on DNA-based medical devices.
Peng Zhang is a Senior Application Scientist who provides NLP solutions for extracting information from unstructured data such as scientific literatures, electronic medical records and real world evidences. Before joining Linguamatics, he had >10 years’ experience of text-mining and informatics in pharmaceutical and biotechnology R&D setting.