Studies indicate AI-enabled compound management systems can streamline workflows, reduce manual errors, and provide better visibility into experimental and predicted data.
A new system lets researchers build and reprogram phage genomes from digital sequence data, potentially enabling scalable, customizable therapies for drug-resistant bacteria.
Hair loss affects millions, and a new wave of therapies — from drugs to cell-based treatments — could finally offer safe, effective, and lasting solutions.
AI is reshaping early drug discovery, but persistent translational gaps, biological complexity, and validation challenges limit how far machine learning alone can predict human outcomes.
Integrating patient-derived xenografts and organoids can help researchers identify responsive tumor subsets, anticipate resistance, and strengthen translational confidence before clinical testing.