1. New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study
- Author
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Irina Perdivara, Ben Niu, Kim F. Haselmann, St John Skilton, Anthony Leone, Gregory O. Staples, Carsten P. Sønksen, Helena Maria Barysz, Andrew Hanneman, Chun Shao, Rebecca Scott, Anders Lund, Carly Daniels, Michael Jahn, Da Ren, Nunzio Sepe, K. Ilker Sen, Zoran Sosic, David Ripley, Jing Zhen, Margo Wilson, Melissa Alvarez, John G Hoogerheide, Xinbi Li, Harini Kaluarachchi, Josh Woods, Wenqin Ni, Albrecht Gruhler, Keith A. Johnson, Arnd Brandenburg, Kristen Nields, Michelle Busch, Douglas D. Richardson, Yan Wang, Ahmet Cansizoglu, Xiaoxiao Li, Greg W Adams, Simon Letarte, Joe Shambaugh, Hua Yuan, Trina Mouchahoir, Tom Robinson, Xiaoshi Wang, Nancy S. Nightlinger, Alexander Julian Veach, Chris Chumsae, Eric Carlson, Dongdong Wang, Sean Shen, Jing Fang, Wei Wu, Stefano Gotta, Justin B. Sperry, Hirsh Nanda, X. Christopher Yu, Sibylle Heidelberger, Bhumit A. Patel, Jihong Wang, Sean McCarthy, Himakshi Patel, Thomas N. Krogh, Hunter Walker, Olga V. Friese, Daniela Tizabi, Yali Lu, Kristin Boggio, Ernest L. Maynard, Rich Rogers, Ying Zhou, Nick DeGraan-Weber, John E. Schiel, Weibin Chen, Jason C. Rouse, Li Tao, Thomas W. Powers, John Kim, Xu Guo, Bo Yan, Gabriella Leo, Ying Zhang, Oleg V. Borisov, Ying Qing Yu, Martha Stapels, Wael Yared, Yan-Hui Liu, Alan Heckert, Sarah Rogstad, Li Zang, Aaron Ammerman, Li Cao, Benjamin J. Place, Richard Ludwig, Anton V. Manuilov, Andrew Mahan, Andrew Dawdy, Yi Wang, Brian Schmidt, and Peiran Liu
- Subjects
business.industry ,Chemistry ,Process (engineering) ,media_common.quotation_subject ,010401 analytical chemistry ,010402 general chemistry ,01 natural sciences ,0104 chemical sciences ,Peak detection ,Structural Biology ,Process engineering ,business ,Function (engineering) ,Spectroscopy ,media_common - Abstract
The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography-mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.
- Published
- 2021
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