Notably, the paper also includes simulation studies outlining when dDRTC is most effective, positioning it as a practical ...

The DMTA cycle depends on clear data flow, yet most labs still work across disconnected systems. Sean McGee, Director of ...

Researchers from the University of Cincinnati College of Medicine and Cincinnati Children's Hospital have found a new method to increase both speed and success rates in drug discovery. The study, ...

Explore how AI-driven multiomics is reshaping drug discovery and personalized medicine development through innovative data ...

The Computational Analysis of Novel Drug Opportunities (CANDO) platform is a computational approach to make drug discovery faster and less expensive while also being safe and effective. UB researchers ...

This article is based on a poster originally authored by Daniel A. Barr, Mario Öeren, Peter A. Hunt, Jonathan D. Tyzack, Tomáš Chrien, Tamsin E. Mansley and Matthew D. Segall, which was presented at ...

A new imaging-enabled knowledge graph, CardioKG, uses AI to integrate cardiac structure and function with molecular data, ...

Every year, the media informs us that we’re on the cusp of the golden age of something. While the expected trend often comes to fruition, it’s rarely as smooth a process as advertised. Drug discovery ...

In a quest to develop new antiviral drugs for COVID-19 and other diseases, a collaboration led by scientists at The Wertheim UF Scripps Institute has identified a potential new drug against the virus ...

Matthias Trost (left) is a Professor at Newcastle University (UK) with a lab comprising three focuses: method development for proteomics, the application of mass spectrometry in drug discovery and the ...