Screening Strategies in Drug Discovery – News and Features

Structure verification by NMR is a vital task in drug discovery but can be slow and subjective. This article explores how ASV transforms it into a scalable, consistent and reliable process.

To be able to study ALS-linked neuroinflammation in the lab, researchers generated “spinal microtissues” containing motor neurons and immune cells from ALS patients' stem cells.

This article explores how AI is transforming precision medicine by streamlining drug discovery, improving patient stratification and treatment prediction, and accelerating clinical trials while highlighting challenges around data quality.

This article explores how generative chemistry accelerates drug design, identifies novel compounds and complements traditional computational tools.

Researchers have identified several uncharacterized chromatin factors and a gene that are involved in DNA repair.

Researchers have identified a small molecule that can selectively block cell death. The findings lay the groundwork for next-generation neuroprotective drugs for degenerative conditions, which currently have no cure or treatments.

Phenotypic screening has re-emerged as a powerful strategy for identifying drugs based on their observable effects. Discover how phenotypic screening accelerates drug discovery, supports drug repurposing and enables novel therapeutic breakthroughs.

Scientists have designed new drug frameworks that selectively target CYP3A4, one of the most critical CYP proteins. Structural insights from this work offer a roadmap for future drug developers to better evaluate drug interactions.

Drug discovery efforts have expanded beyond the traditional approaches of small molecules and antibodies to include cells. This article explores the use of microfluidic methods for high-throughput screening of cell-based drug products.

In this interview, Sebastiaan J. Trietsch, Chief Technology Officer at MIMETAS, discusses how microphysiological systems are advancing drug discovery through scalable human-relevant models and AI integration.