Explore AI in drug discovery and its journey from promise to proof in 2025 with significant achievements and challenges faced.

Developing high-quality, safe, and effective drugs is a complex process that requires varied scientific skills and stringent regulatory assessments. Drug development is a process that spans many years ...

UM researchers have developed a deep learning model to predict compound protein interactions. GraphBAN is an inductive graph-based approach. The model is all about discovering new drug candidates in ...

The biggest challenge in drug development is that the process is not an even balance of hit or miss – it is overwhelmingly miss, with around 90% of drugs never making it beyond clinical trials. As a ...

The world of medicine has taken a significant leap forward with the first AI-generated drug entering clinical trials. This breakthrough has the potential to revolutionize drug discovery, transforming ...

LIGAND-AI is a flagship project of the Target 2035 initiative, funded by the Innovative Health Initiative, a public-private partnership (PPP) between the European Union and the European life science ...

TOKYO--(BUSINESS WIRE)--Elix, Inc. (CEO: Shinya Yuki / Headquarters: Tokyo; hereinafter “Elix”) is pleased to announce that its AI drug discovery platform, Elix ...

Artificial intelligence and machine learning are being embedded in every aspect of the drug discovery and development process. In the preclinical stages, for example, companies are using advanced AI ...

Explore the impact of AI in drug discovery as 2026 promises critical clinical results and industry transformations.

Traditionally, developing a new drug takes many years and requires a massive financial investment, often involving significant risk and a high likelihood of failure. AI models trained on extensive ...