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Queen Mary University of London has initiated a collaborative research project with AstraZeneca to enhance artificial intelligence applications in drug discovery. This project, led by Professor Greg Slabaugh, aims to develop algorithms for integrating various omic data types, including RNA and protein data. The focus is on expediting the drug discovery process by leveraging AstraZeneca's extensive datasets and Queen Mary's machine learning expertise.
The collaboration seeks to create new analytical capabilities that streamline the drug development pipeline, potentially reducing the time and costs associated with bringing new drugs to market. With the project set to begin in January 2025 and last for 30 months, it represents a significant step towards utilizing AI to transform the pharmaceutical landscape. The partnership highlights the importance of combining academic research with industry data to drive innovation in healthcare.
• Collaboration aims to accelerate drug discovery using AI and multimodal data integration.
• AI tools developed will streamline the drug development process and reduce costs.
This term refers to algorithms that combine various types of biological data to enhance analysis and insights.
Omics technologies involve studying different biological data types, such as genomics and proteomics, to understand complex biological systems.
Queen Mary University of London is involved in advancing AI research for drug discovery through academic expertise.
AstraZeneca collaborates with Queen Mary to utilize its multi-omic datasets for enhancing drug discovery processes.
Queen Mary University of London 10month
Queen Mary University of London 10month
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