When: Thursday, October 25, 2018
Time: 8:00 - 9:00am (PST) | 11:00am - 12noon (EDT) | 4:00 - 5:00pm (BST) | 5:00 - 6:00pm (CEST)
Length: 1 hour
Reliable prediction of potential ‘on-target’ and ‘off-target’ Adverse Drug Reactions (ADRs) for new drugs in development is a goal in early discovery. This webinar will present an integrated systems pharmacology approach using a combination of bioinformatics tools, including Metabase, I2E, and OpenVigil. We wanted to assess potential safety liabilities of a new drug, by understanding the landscape of information about other drug therapies that target proteins in the same pathway.
To accomplish this, high quality annotated databases supported with text and data analytics and visual descriptive techniques were used to collate information about upstream and downstream proteins in a pathway along with tissue distributions. In addition, clinical information for other drugs and their ADRs known to interact with the proteins in that same pathway were integrated. A target gene was selected for a proof-of-concept evaluation to test this systems pharmacology pathway approach, with the aim to complement and inform additional safety assessments to conduct during drug development.
Malika Mahoui, PhD, Senior Research Scientist-IT, Eli Lilly and Company
Malika Mahoui is a Senior Research Scientist at Elli Lilly and Company. She Holds a PhD in Computer Science and an MPH in public health. Previously she held several academic positions at universities including her more recent faculty position with the School of Informatics at IUPUI. Her current research interests lie in the areas of data and text mining applied to health.
Jane Z. Reed, Head of Life Science, Linguamatics
Jane Reed is Head of Life Science at Linguamatics. She is responsible for developing the strategic vision for Linguamatics’ growing product portfolio and business development in the life science domain. Jane has extensive experience in life science informatics. She worked for more than 15 years in vendor companies supplying data products, data integration and analysis, and consultancy to pharma and biotech—with roles at Instem, BioWisdom, Incyte, and Hexagen. Before moving into the life science industry, Jane worked in academia with post-docs in genetics and genomics.
What will you learn?
- How natural language processing (NLP) text mining can extract structured data from unstructured text in scientific papers, clinical trial databases, FDA drug labels
- How Lilly used a variety set of applications (including I2E, Metabase, OpenVigil) to extract and integrate the most up-to-date published knowledge for drug targets and associated adverse events, to provide potential risk liability predictions.
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:
- Drug safety
- Target selection, target prioritisation
- Systems pharmacology