A Reversed-Phase HPLC Column for the Separation and Characterization of Peptides Using LC-UV-MS

Learn how effective non-targeted analysis in soil samples is enabled through high resolution accurate mass in combination with intelligent data processing from Compound Discoverer.

Hear from Associate Professor Douglas Walker at Emory University on how GC Orbitrap MS has advanced their capability in exposomics research.

Deriving antibodies from plasma products involves several steps, typically starting from the collection of plasma and ending with the purification of the desired antibodies. These are: plasma collection; plasma pooling; fractionation; antibody purification; concentration and formulation; quality control; and packaging and storage. This process results in a purified antibody product that can be used for therapeutic purposes, diagnostic tests, or research. Each step is critical to ensure the safety, efficacy, and quality of the final product. Applications of AI/GenAI in many of these steps can significantly help in the optimization of purification and yield of the desired antibodies. Some specific use-cases are: selecting and optimizing plasma units for optimized plasma pooling; GenAI solution for enterprise search on internal knowledge portal; analysing and optimizing production batch profitability, inventory, yields; monitoring production batch key performance indicators for outlier identification; monitoring production equipment to predict maintenance events; and reducing quality control laboratory testing turnaround time.

Scientists from the Massachusetts Institute of Technology, the University of Washington, and other leading institutions took the stage at the Eastern Analytical Symposium to accept awards and share insights into their research.

After collecting dried blood spots from preterm infants with gestational age (GA) of less than 32 weeks within 24 hours after birth, researchers used liquid chromatography-tandem mass spectrometry (LC–MS/MS) to perform targeted measurements of metabolites to identify differential metabolites in preterm infants with bronchopulmonary dysplasia and uncovering circulating biomarkers for the early prediction of this chronic lung disease.