Latest App Notes & Case Studies

This case study highlights how EU-OPENSCREEN implemented a fully automated workflow for compound dissolution, aliquoting, storage and plate reformatting, meeting the scale and speed of modern screening demands.

This application note presents a next-generation approach to drug discovery - combining AI-guided structural design with rapid, automated digital microfluidics-based screening workflows that optimize protein expression. Researchers can obtain purifi

This application note highlights a complete extraction-to-analysis method that offers the exceptional sensitivity and robust quantitation needed to analyze nine nitazene analogs and brorphine in DBS samples.

This application note explores how researchers successfully combined AI with advanced multiplexed gene synthesis to design and validate novel single-domain antibodies with atomic-level precision.

In this application note, discover how mass photometry can be used to analyze the fragmentation and aggregation of therapeutic antibodies in response to stressors like light, pH variations, and peroxide exposure.

In this technical note, we explore datasets captured through mass photometry and size exclusion chromatography (SEC), comparing how they characterize the aggregation levels in different biosimilar antibodies

This app note explores a how single multi-capillary, high-throughput platform can be used to perform both these techniques, enabling complex biotherapeutics to be rapidly and thoroughly characterized.

This application note highlights the successful 5-fold scale-up of a high-cell density E. coli process from an established 200 L stainless steel fermenter to a 1000 L single-use system.

This app note highlights the advantages of electron-activated dissociation (EAD) in identifying oxidative metabolites of the molecular glue, mezigdomide.

This application note highlights a LC-MS/MS method that leverages advanced sample preparation and next-generation detection technology to achieve high sensitivity and accuracy while minimizing sample volume requirements.