Ian Blair of the University of Pennsylvania (Philadelphia, Pennsylvania) will preside over six Monday morning oral sessions on Metabolomics: New MS Technologies and Applications. The sessions will take place today between 8:30 a.m. and 10:10 a.m. in the Theater.
The first presentation, starting at 8:30 a.m. will be by Tao Huan of the University of Alberta (Edmonton, Canada). The title of Huan’s talk is “DnsID: a Metabolite Standards Library for Automated Identification of Dansylated Amine- and Phenol-containing Metabolites in Metabolomics. Huan and colleagues developed a metabolite standards library with a built-in function of retention time calibration. Currently, the library consists of 285 human metabolites (amines and phenols) with mz, RT, and MS-MS fragmentation information.
Mirriam Sindelar of Weill Medical College of Cornell (New York, New York) will follow with at talk at 8:50 a.m. titled “The Human Plasma REDOXOME: A Broad Compendium Of Oxidative Stress Biomarkers.” Oxidative stress is a contributing factor to many chronic diseases, for example, atherosclerosis, chronic obstructive lung disease, rheumatoid arthritis, diabetes, and chronic inflammation. In order to determine the status of oxidative stress from patient-derived serum samples, Sindelar and colleagues developed a metabolomics platform that broadly identifies markers for oxidative stress.
At 9:10, Gregory Hamm, of ImaBiotech, MS Imaging Department (Loos, France) will present “Metabolic Changes and Oxidative Stress Pathways in a Novel Patient-Derived IDH1-R132H Mutant Oligodendroglioma Xenograft Assessed by Mass Spectrometry Imaging.” Following the recent discovery in the field of brain tumors of a mutation in the enzyme isocitrate dehydrogenase in low-grade gliomas and secondary glioblastomas, Hamm and colleagues addressed the differential metabolic profile of IDH1 mutant versus IDH1 wildtype gliomas. They investigated metabolic profiling by mass spectrometry imaging to provide specific molecular distributions in different anatomical compartments of tissue sections by correlation with histology.
Next, at 9:30 a.m., Danijel Djukovic of the University of Washington Medicine (Seattle, Washington) will give a talk called “Highly Reproducible and Robust LC–MS-MS Assay for Targeted Profiling of 180 Metabolites Using a Single HILIC Chromatography Method.” Djukovic and colleagues, noting that a major difficulty in targeted LC–MS-MS metabolomics is achieving a well-resolved chromatographic separation of a large number of metabolite species with different chemical and physical properties on a single analytical column, describe a highly reproducible and robust targeted HILIC LC–MS-MS assay for the relative quantitation of 180 metabolites across most major metabolic pathways using a single chromatography method.
Following Djukovic at 9:50 a.m., Nathaniel Snyder of Drexel University (Philadelphia, Pennsylvania) will present “Simultaneous Targeted Quantification and Untargeted Metabolomics of Meconium Steroid Content.” Djukovic and colleagues investigated the molecular composition of meconium, which is the first stool of a newborn, in both a targeted manner to examine specific steroids as well as a simultaneous untargeted lipidomics approach.
The final presentation starts at 10:10 a.m. and will be given by Petia Shipkova of Bristol Myers Squibb (Princeton, New Jersey). Shipkova will present “Effect of Controlled Diet on Biomarker Measurements in the Clinic.” Shipkova and colleagues created a study designed to evaluate the effect of standardized diets on the metabolome of healthy volunteers enrolled in a clinical trial.
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.