drug discovery
PulseAugur coverage of drug discovery — every cluster mentioning drug discovery across labs, papers, and developer communities, ranked by signal.
9 day(s) with sentiment data
-
Generative AI advances inorganic compound design, review finds
A review paper published on arXiv analyzes the application of generative AI in the inverse design of inorganic compounds. While generative AI has advanced organic chemistry and drug discovery, its use in inorganic chemi…
-
New ML framework enhances drug discovery screening metrics
Researchers have developed a new machine learning framework to improve performance metric estimation in high-throughput screening (HTS) assays, which are crucial for early-stage drug discovery. The framework addresses t…
-
GFlowNet interpretability study questions learned chemistry in drug discovery models
A new study published on arXiv investigates the interpretability of GFlowNets, a type of AI model used for drug discovery. Researchers developed a framework to analyze SynFlowNet, a GFlowNet trained on drug-likeness, an…
-
New Foundation Model Accelerates Drug Discovery with Accurate ADMET Prediction
Researchers have developed MEGA-CL, a novel foundation model designed to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of small molecules. This graph neural network framewo…
-
New Bayesian Optimization Method RAMBO Tackles Multi-Regime Search Spaces
Researchers have developed a new Bayesian Optimization (BO) method called RAMBO, designed to handle multi-regime search spaces more effectively than standard BO. RAMBO utilizes a Dirichlet Process Mixture of Gaussian Pr…
-
New method injects biokinetic knowledge into neural networks for data-scarce bioprocess modeling
Researchers have developed a novel approach to address data scarcity in bioprocess modeling for drug discovery and biomanufacturing. Their work systematically explores methods for integrating existing biokinetic knowled…
-
Meta AI models power Genesis Mission projects at Lawrence Berkeley Lab
Meta's AI models, including the Segment Anything Model and those built on PyTorch, are being utilized in the initial projects of the Genesis Mission at Lawrence Berkeley National Laboratory. These projects focus on area…
-
Lila Sciences builds AI-powered automated lab for scientific discovery
Lila Sciences is building an automated laboratory designed to function as an AI data center, generating vast amounts of experimentally validated scientific data. Their vision is to create a scientific superintelligence …
-
OpenAI Researcher Eyes $2B Valuation for AI Drug Discovery Startup
Miles Wang, a researcher from OpenAI, is reportedly in discussions to launch a new startup focused on AI-driven drug discovery. The venture is aiming to secure approximately $200 million in funding at a valuation of $2 …
-
AI accelerates drug discovery timelines with protein folding and simulation
Artificial intelligence is significantly speeding up drug discovery by leveraging protein folding and advanced chemical simulations. This technology is reducing the time it takes to identify potential drug candidates, e…
-
AI in Drug Discovery Faces Wall Street's Timeline Mismatch
The integration of artificial intelligence into drug discovery is facing significant hurdles, primarily due to the long timelines and high costs associated with pharmaceutical development. While AI can accelerate certai…
-
New URSA benchmark evaluates AI for drug discovery synthesis planning
Researchers have introduced URSA, a new benchmark framework designed to evaluate retrosynthesis systems in drug discovery. URSA assesses synthetic routes not only for convergence to starting materials but also for chemi…
-
Generative AI and Physics Accelerate Antibiotic Discovery
Researchers are exploring the use of generative AI and physics principles to accelerate the discovery of novel antibiotics. This interdisciplinary approach aims to overcome the growing challenge of antibiotic resistance…
-
Chai Discovery: AI Platform for Advanced Drug and Antibody Design
Chai Discovery is presented as a leading AI platform for drug discovery, antibody design, and biomolecular prediction. The review covers its features, pricing, and pros and cons, aiming to explore its capabilities beyon…
-
NVIDIA BioNeMo Agent Toolkit empowers AI agents in life sciences research
NVIDIA has launched the BioNeMo Agent Toolkit, designed to integrate its accelerated AI capabilities into life sciences research workflows. This toolkit allows AI agents, such as those used in Anthropic's Claude Science…
-
New NMO Benchmark Bridges ML and Nanotechnology with Quantum Simulations · 3 sources tracked
Researchers have introduced the Nanotechnology Molecular Optimization (NMO) Benchmark, a new tool designed to advance machine learning in nanotechnology and materials science. Unlike previous benchmarks focused on drug …
-
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…
-
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…
-
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 …
-
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 …