drug discovery
PulseAugur coverage of drug discovery — every cluster mentioning drug discovery across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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Space emerges as a new frontier for medical research and drug discovery
A new era in medical research may be dawning with the potential use of space as a laboratory. This shift could unlock novel approaches to drug discovery and development by leveraging the unique conditions found beyond Earth.
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New active learning method tackles complex Boltzmann distributions
Researchers have developed a new Gaussian Process-based acquisition function called AB-SID-iVAR for active learning problems. This method addresses the challenge of learning an unknown function under a self-induced Bolt…
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AI Saves Pharma Billions in Operations, But Drug Discovery Impact Lags
Artificial intelligence has generated significant cost savings for pharmaceutical companies, particularly in manufacturing and back-office operations, amounting to billions of dollars. However, AI's impact in the crucia…
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Digital Twin AI to Boost Pharma Production Efficiency by 40% by 2026
Digital twin technology, enhanced by AI, is projected to significantly boost pharmaceutical production efficiency by up to 40% by 2026. While its impact on early-stage drug discovery is still limited, the primary gains …
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Jon Stokes to lecture on AI's role in accelerating antibiotic discovery
Jon Stokes is scheduled to deliver a lecture on May 28th focused on the application of AI in accelerating antibiotic discovery. The event, hosted by LED3hub, aims to foster a discussion about the realistic potential and…
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MAMMAL AI architecture accelerates biomedical discovery and drug development
Researchers have introduced MAMMAL, a novel multi-modal architecture designed for biomedical discovery. This system integrates molecular data with language models to accelerate research in areas like drug discovery and …
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AI research advances planning, drug discovery, and data extraction
Researchers have developed a new method for generating dual-target molecules, which are designed to interact with two protein targets simultaneously. This approach, called CombiMOTS, uses a Pareto Monte Carlo Tree Searc…