Leveraging network biology to drive drug discovery
Network biology has become a powerful approach for academic research and drug discovery, bringing together OMICs data, pathway and network prior knowledge databases, and tools for OMICs data analysis. Significant effort is being invested in OMICs data generation, and major databases exist with manually curated network and pathway information to guide analysis. However, OMICs data and the supporting network resources require advanced computational methods to drive scientific discovery.
Clarivate is leading a pre-competitive consortium of pharmaceutical companies known as Computational Biology Methods for Drug Discovery (CBDD). The program is focused on implementing state-of-the-art approaches for network and pathway analysis of all types of OMICs datasets to help accelerate innovation. CBDD’s 17 member companies include Pfizer, Novartis, Sanofi, Janssen, Takeda, Roche, BMS, Merck KGaA, Eli Lilly, and AstraZeneca, among others. To date, more than 300 algorithms have been evaluated and 59 algorithms implemented.
Join our experts in this webinar to better understand the scope, experience and focus of the CBDD consortia and how this can be leveraged in government, non-profit and academic research.
Key areas of discussion will provide critical learnings, including:
- How leading pharmaceutical companies are leveraging network and pathway algorithms to elucidate disease mechanisms and drive drug target and biomarker discovery
- How systems biology tools that combine data with prior knowledge uncover insights from WGS, GWAS, RNA-Seq, and single cell data that can’t be made from data or knowledge alone
- How algorithms developed in the consortium can help advance cutting-edge research in your organization
- Which algorithms are optimal depending on research goal(s)