Drug discovery requires two separate steps: checking whether a drug can bind to a harmful molecule or its receptor, and ...
A team of biochemists at the University of California, Santa Cruz, has developed a faster way to identify molecules in the ...
Advancing proprietary AI discovery of high-bioavailability Oral GLP-1 drug candidates. HOUSTON, Feb. 3, 2026 /PRNewswire/ -- Deep EigenMatics, Inc., a pioneer in high-velocity Artificial Intelligence ...
Digital twins revolutionize drug discovery by integrating AI and biological data, enhancing prediction, trial design, and decision-making in precision medicine.
Explore AI in drug discovery and its journey from promise to proof in 2025 with significant achievements and challenges faced.
Key opportunities in the protein labeling market include increasing demand for site-specific tags in proteomics and drug development, the rise of AI tools for protein structure prediction, and the ...
There’s no doubt that large language models and generative AI tools have taken the world by storm. Their ability to create, ...
Overview AI is speeding up drug discovery by analyzing large biological and chemical data in a short time.Deep learning and AI systems help design new drug mole ...
Figure 1. This figure depicts the four categories of protein druggability target screening tools discussed in this section, which include structure-based methods, sequence-based methods, machine ...
In drug discovery, virtual screening is a fast and cost-effective way of narrowing down vast chemical libraries to identify the most promising hits, reducing synthesis and testing requirements while ...
The global artificial intelligence (AI) in drug discovery market is experiencing rapid expansion, driven by the need to reduce the high costs and long timelines of traditional pharmaceutical ...
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