A Little Blood Goes A Long Way
A new technique, using liquid chromatography-mass spectrometry (LC-MS), has now made it easier for scientists and researchers to obtain any information they need from very small amounts of blood.
A new technique, using liquid chromatography-mass spectrometry (LC-MS), has now made it easier for scientists and researchers to obtain any information they need from very small amounts of blood.
The technique, which was developed by a group of researchers from the University of Colorado led by anesthesiologist Jeffry Galinkin, uses a new method of screening miniscule amounts of dried blood for chemicals.
This new method will reportedly solve the current problem that researchers have faced with obtaining a sufficient amount of blood from infants to test for chemicals. According to Galinkin, drug dosing guides for infants is the primary priority for the researchers, however it is only one of many possible applications of the technique, which include diagnosing HIV or tuberculosis, and even testing for banned substances in athletes.
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.
