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デジタル研究開発
A structured framework to achieve AI maturity for your scientific data
Scientific R&D teams face real barriers to AI adoption. Learn how structured data, expert collaboration, and the Triangle of Success framework drive meaningful AI maturity.
Shifting climate, spreading insects: The rising burden of vector-borne diseases
Vector-borne diseases are spreading to new regions as climate change intensifies, and public health systems need more treatment options to limit the impacts.
How AI-driven analysis can accelerate drug discovery
Spiro[2.3]hexanes are an example of promising yet challenging scaffold structures for new drug compounds. By using AI-powered predictive analytics with CAS BioFinder, researchers more efficiently identified candidates for validation.