News|Podcasts|October 31, 2024

AI and GenAI Applications to Help Optimize Purification and Yield of Antibodies From Plasma

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.



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Figure 2. Split injection used to measure triplicate test of MTBE, hexane, o-xylene, and 1-methylnaphthalene comparing different solvents (methanol, methylene chloride) and column insertion distances starting with 0.5 mm, 5.0 mm, 10.0 mm, 15 mm, and 20.0 mm. Methanol had the best performance at the 5.0 mm insertion distance and methylene chloride looked slightly better at the 0.5 mm. We would still recommend not going below the 5.0 mm manufacturer recommended insertion distance.
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