AOAC International are now accepting nominations for the Harvey W. Wiley and the Fellow of AOAC International awards.
AOAC International are now accepting nominations for the Harvey W. Wiley and the Fellow of AOAC International awards.
The Harvey W. Wiley Award is presented to a scientist (or group of scientists) who has made an outstanding contribution to analytical method development in an area of interest to AOAC International. Nominations for this award must be received no later than 31 January 2017. To obtain a Harvey W. Wiley nomination form click here>>
The Fellow of AOAC International Award recognizes meritorious voluntary services to the Association, increasing the success and prestige of the AOAC. Nominations for this award must be received no later than 15 February 2017. To obtain a Fellow of AOAC nomination form click here>>
For more information about these awards and about AOAC International please click here>>
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.