March 2025

A new paper, “Data-driven federated learning in drug discovery with knowledge distillation”, was recently published in Nature Machine Intelligence, the leading journal for Machine Learning and AI. It explores the potential for federated learning to advance drug discovery through secure, collaborative research, representing a major step forward in privacy-preserving machine learning.   What is Federated […]

At Lhasa we know that there are many challenges involved in carrying out risk assessments for drug substances and drug products, to ultimately ensure a safe and effective product for patients. Forced degradation studies are essential in pharmaceutical development to assess drug stability and ensure product quality and safety. These studies help identify degradation pathways,