A new cancer drug candidate has demonstrated the ability to block tumor growth without triggering a common and debilitating side effect.

Machine learning method improves accuracy of inverse protein folding for drug design by University of Sheffield edited by Lisa Lock, reviewed by Robert Egan Editors' notes ...

Designing bioactive molecules with desired properties for specific targets is a longstanding challenge in drug design. We introduce a model called BiAtt-GVAE, which incorporates a conditional to more ...

Debates over AI antibody design terminology have clouded the industry’s shared mission of bringing better therapeutics to the clinic faster.

This new structural and mechanistic understanding of the RAD52-DNA complex may help researchers develop new anti-cancer drugs.

Compute efficient generative AI foundation model for small molecule drug discovery start-up announces funding from leading AI and biotech investors.

Variational AI Announces Oversubscribed $5.5 Million Financing to Launch Foundation Model for Small Molecule Drug Discovery ...

About Variational AI Variational AI is redefining the unit economics of drug discovery through the power of generative AI. The founding machine learning (ML) team comes from leading AI research labs ...

His team harnesses advanced computational technologies, including AI, with the aim of enhancing the discovery, design, optimization and synthesis of small molecules to be developed into innovative ...

PURPOSEWe introduce a novel algorithmic approach to design phase I trials for oncology drug combinations.METHODSOur proposed Toxicity Adaptive Lists Design (TALE) is straightforward to implement, ...