Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Webinar: Accelerating drug discovery by building and turning high-quality data into actionable insights
Posted on April 6th, 2020 by Rosalind Sankey in Chemistry
Drug discovery is a time-consuming and costly process (and all the more costly because it’s time-consuming). One of the hopes of the era of Big Data has been that having access to a wealth of scientific information could help speed the discovery process. However, the data itself has proven to come with many challenges. Medicinal chemists like myself are often frustrated in our attempts to integrate and work with disparate and unstructured sets of data.
I will join Min Lu, Ph.D. from Merck & Co. in presenting a webinar on April 28 covering our recent research in relation to accelerating drug discovery with high-quality data – and we think our findings will be of interest to many chemists.
More about our topic: Structuring data in discovery chemistry
The prioritization of hits from large compound lists for further follow-up is a challenging task for medicinal chemists. During this step of drug discovery, multiple parameters such as synthetic accessibility, target specificity, physicochemical properties and potential toxicities, in addition to desired biological activity, must be considered simultaneously. Increasing amounts of biological data are accumulating in the pharmaceutical industry and published literature (e.g. journals and patents).
However, data does not equal actionable information, and guidelines for appropriate data capture, harmonization, integration, mining and visualization need to be established to fully harness its potential. In our work, we describe ongoing efforts to structure data in the area of discovery chemistry. We are integrating complementary data from both internal and external data sources (Reaxys) into one, and will demonstrate how this well-curated database facilitates compound set design, tool compound selection, target deconvolution in phenotypic screening, and predictive model building (e.g. target prediction).
Early in the discovery process, chemists select a subset of compounds for further research, often from many viable candidates. These decisions determine the success of a discovery campaign, and ultimately what kind of drugs are developed and marketed to the public.
Join us for the webinar to learn more
In this webinar coming up on April 28 at 10am EST, we will present our findings in the context of complex problem solving and decision theory, and discuss the implications on drug discovery. To join us, please register here.
R&D Solutions for Pharma & Life SciencesWe're happy to discuss your needs and show you how Elsevier's Solution can help.
Senior Product Manager, Reaxys
- Ontologies – what do they have to do with pharma research?
- Reaxys User Day 2022: Researcher secrets in the spotlight
- Taking on the Net Zero challenge at the government level
- Elsevier and LG: Turning data into action
- Pharma can now track the most relevant patent info – fast and at scale