When: Tuesday 8 December, 2020
Time: 11:00am EST; 8:00am PST; 4:00pm GMT; 5:00pm CET
Duration: 60 minutes
Drug safety is of critical importance, at all stages in drug discovery, development and delivery. Across the whole span, safety-relevant data is being both generated and sought from unstructured text – from internal safety reports, scientific literature, individual case safety reports, clinical investigator brochures, patient forums, social media, conference abstracts.
Intelligent search across these hundreds of thousands of pages can provide the information for key decision support. Many of our customers are using the power of Linguamatics Natural Language Processing (NLP) platform to transform the unstructured text into actionable structured data that can be rapidly visualized and analysed, at every stage through the safety lifecycle of a drug. This webinar will present an overview of customer success stories, to show best practice use of this Artificial Intelligence (AI) technology to advance drug safety.
What will you learn?
- How natural language processing (NLP) text mining can extract structured data from unstructured text in scientific papers, clinical trial databases, internal safety reports, FDA drug labels, and more.
- How big pharma access internal data silos and external data sources for safety decision making. Use cases include Merck for preclinical toxicology reports and Agios Pharmaceuticals for clinical safety
Who should attend?
Anyone with an interest in getting better value from their textual information, and integrating diverse data sets to provide knowledge relevant to drug safety and risk prediction.
Specifically, informaticians, information professionals, researchers, with responsibility for:
- Risk profiles for targets in early drug discovery
- Preclinical and clinical drug safety
- Safety assessment across pipeline