Nancy L. Allbritton Wins Ralph N. Adams Award
Nancy L. Allbritton of the University of Washington in Seattle is the 2020 winner of the Ralph N. Adams Award in Bioanalytical Chemistry, which is presented by the Pittsburgh Conference. The award recognizes significant contributions to the field of bioanalytical chemistry, broadly defined.
Nancy L. Allbritton of the University of Washington in Seattle is the 2020 winner of the Ralph N. Adams Award in Bioanalytical Chemistry, which is presented by the Pittsburgh Conference. The award recognizes significant contributions to the field of bioanalytical chemistry, broadly defined.
Allbritton is the Frank & Julie Jungers Dean of Engineering at the University of Washington in Seattle, a position she took in November 2019 following 12 years on the faculty of the University of North Carolina at Chapel Hill (UNC) and North Carolina State University (NC State), where she was the Kenan Distinguished Professor. Her research has focused on using principles and techniques from engineering, chemistry, physics, and materials science to develop enabling technologies and platforms for biomedical research and clinical care.
After receiving her B.S in physics from Louisiana State University, her M.D. from John Hopkins University, and her PhD from the Massachusetts Institute of Technology, with a postdoctoral fellowship at Stanford University.
Allbritton’s most recent research has focused on multiplexed single-cell assays, microfabricated platforms for high-content cytometry combined with cell sorting, and microengineered stem-cell-based systems for recapitulating human organ-level function. Her work has resulted in over 180 full-length journal publications and patents and led to 15 commercial products, and has been funding by more than $60 million in grants since 2000
Allbritton is a Fellow of the American Association for the Advancement of Science, the American Institute for Medical & Biological Engineering, and the National Academy of Inventors. Among other awards, she is a 2015 recipient of the National Institutes of Health (NIH) Director’s Transformative Award for her pioneering work in building functional microscale replicas of the digestive tract, the 2016 recipient of the American Chemical Society (ACS) Award in Chemical Instrumentation, the 2017 Edward Kidder Graham Leadership Award, and the 2017 recipient of the UNC “Inventor of the Year” Award. She is highly recognized for her work, with more than 270 invited speaking engagements at both national and international venues.
An interview with Allbritton on her work on separations-based chemical cytometry can be read in a free downloadable ebook available on the LCGC website.
A Dream Come True: Separation Science at Analytica
November 6th 2024At Analytica this year, an oral session titled “A Dream Comes True: Fantastic News from Analytical Chemistry” focused on cutting-edge techniques in separation science in Hall 5 of the International Congress Center Munich (ICM) International Congress Center Munich (ICM).
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.
