Simultaneous Qualitative and Quantitative Proteomics Using Tandem Mass Spectrometry
Quantitative proteomics aims to provide large-scale qualitative and quantitative data about every protein in a biological sample. However, drawbacks associated with current techniques can make it difficult to generate the data required. Research scientists have recently developed a new approach that allows highly multiplexed high-resolution MRM quantitation of most of the detectable proteins in a sample in a single analysis.
Quantitative proteomics aims to provide large-scale qualitative and quantitative data about every protein in a biological sample. However, drawbacks associated with current techniques can make it difficult to generate the data required. Research scientists have recently developed a new approach that allows highly multiplexed high-resolution MRM quantitation of most of the detectable proteins in a sample in a single analysis.
AI and GenAI Applications to Help Optimize Purification and Yield of Antibodies From Plasma
October 31st 2024Deriving 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.
