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.
Magnetic molecularly imprinted polymer extraction with liquid chromatography-high resolution mass spectrometry (LC–HRMS) finds patulin in store-bought juice.
In this fifth part of " Conversations with Michael Dong," a series on fundamentals of HPLC in pharmaceutical analysis, LCGC International’s "Perspectives in HPLC" column editor discusses how to overcome challenges with reversed-phase chromatography in drug analysis.
This week on Chromatography Online, leading experts shared practical insights with LCGC International on sustainable affinity methods, siRNA impurity profiling, nontarget screening, peptide tech transfer, and AI in separation science.