drug discovery
PulseAugur coverage of drug discovery — every cluster mentioning drug discovery across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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New chemical reaction database launched to boost AI drug discovery
A new, extensive database of chemical reactions has been launched, aiming to accelerate AI-driven drug discovery. This resource is designed to provide researchers with a comprehensive tool for exploring and predicting c…
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New ML frameworks boost protein-ligand binding affinity prediction
Two new machine learning frameworks, RicciBind and CPES, have been introduced for predicting protein-ligand binding affinity, a crucial step in drug discovery. RicciBind utilizes Ricci curvature and optimal transport to…
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New RAG Benchmark Launched for Drug Discovery PPIs
Researchers have introduced RAGPPI, a new benchmark designed to evaluate Retrieval-Augmented Generation (RAG) systems for identifying the biological impacts of protein-protein interactions (PPIs) in drug discovery. The …
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New AI method boosts drug property prediction accuracy
Researchers have developed a new pretraining framework called Probabilistic Contrastive Pretraining (PCP) to enhance the prediction of ADME properties crucial for drug discovery. This method combines chemistry-specific …
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AI drug discovery review tackles fairness in DRL models
A new review paper published on arXiv synthesizes definitions and metrics for fairness in deep reinforcement learning (DRL) applied to drug discovery. The research focuses on how dataset composition, reward design, and …
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Diffusion models fine-tuned for drug discovery with RL and genotype conditioning
Two new research papers propose advanced methods for using diffusion models in drug discovery. The first, FTDiff, employs reinforcement learning to fine-tune diffusion models for generating molecules with specific drug-…
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AI Agent TRACE Enhances Drug Discovery Lead Optimization
Researchers have developed TRACE, a novel agent that utilizes LLM reasoning for molecular lead optimization in drug discovery. Unlike previous methods that optimize in a single step, TRACE treats tool selection as a seq…
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Decision Trees Enhance LLMs for Molecular Property Prediction
Researchers have developed a new method called TreeKD to improve the accuracy of large language models (LLMs) in molecular property prediction, a crucial task in drug discovery. TreeKD works by distilling knowledge from…
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New framework enables AI agents to conduct atomistic research
Researchers have developed AtomisticSkills, an open-source framework designed to enable AI coding agents to perform complex atomistic research across materials science, chemistry, and drug discovery. This framework orga…
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LLMs evaluated for advanced chemistry tasks with new benchmarks
Researchers have developed new benchmarks and methods to evaluate and enhance Large Language Models (LLMs) for chemistry-related tasks. One approach, Speak-to-Structure (S^2-Bench), focuses on open-domain molecule gener…
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AI Revolutionizes Life Sciences, Accelerating Drug Discovery and Genomics
Artificial intelligence is revolutionizing the life sciences, impacting areas from drug discovery to genomic analysis. AI-powered research is enhancing both the speed and precision of breakthroughs in biology and medici…
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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…