Cargando…
Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study
[Image: see text] The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it lever...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460773/ https://www.ncbi.nlm.nih.gov/pubmed/36018776 http://dx.doi.org/10.1021/jasms.2c00129 |
_version_ | 1784786828625182720 |
---|---|
author | Mouchahoir, Trina Schiel, John E. Rogers, Rich Heckert, Alan Place, Benjamin J. Ammerman, Aaron Li, Xiaoxiao Robinson, Tom Schmidt, Brian Chumsae, Chris M. Li, Xinbi Manuilov, Anton V. Yan, Bo Staples, Gregory O. Ren, Da Veach, Alexander J. Wang, Dongdong Yared, Wael Sosic, Zoran Wang, Yan Zang, Li Leone, Anthony M. Liu, Peiran Ludwig, Richard Tao, Li Wu, Wei Cansizoglu, Ahmet Hanneman, Andrew Adams, Greg W. Perdivara, Irina Walker, Hunter Wilson, Margo Brandenburg, Arnd DeGraan-Weber, Nick Gotta, Stefano Shambaugh, Joe Alvarez, Melissa Yu, X. Christopher Cao, Li Shao, Chun Mahan, Andrew Nanda, Hirsh Nields, Kristen Nightlinger, Nancy Niu, Ben Wang, Jihong Xu, Wei Leo, Gabriella Sepe, Nunzio Liu, Yan-Hui Patel, Bhumit A. Richardson, Douglas Wang, Yi Tizabi, Daniela Borisov, Oleg V. Lu, Yali Maynard, Ernest L. Gruhler, Albrecht Haselmann, Kim F. Krogh, Thomas N. Sönksen, Carsten P. Letarte, Simon Shen, Sean Boggio, Kristin Johnson, Keith Ni, Wenqin Patel, Himakshi Ripley, David Rouse, Jason C. Zhang, Ying Daniels, Carly Dawdy, Andrew Friese, Olga Powers, Thomas W. Sperry, Justin B. Woods, Josh Carlson, Eric Sen, K. Ilker Skilton, St John Busch, Michelle Lund, Anders Stapels, Martha Guo, Xu Heidelberger, Sibylle Kaluarachchi, Harini McCarthy, Sean Kim, John Zhen, Jing Zhou, Ying Rogstad, Sarah Wang, Xiaoshi Fang, Jing Chen, Weibin Yu, Ying Qing Hoogerheide, John G. Scott, Rebecca Yuan, Hua |
author_facet | Mouchahoir, Trina Schiel, John E. Rogers, Rich Heckert, Alan Place, Benjamin J. Ammerman, Aaron Li, Xiaoxiao Robinson, Tom Schmidt, Brian Chumsae, Chris M. Li, Xinbi Manuilov, Anton V. Yan, Bo Staples, Gregory O. Ren, Da Veach, Alexander J. Wang, Dongdong Yared, Wael Sosic, Zoran Wang, Yan Zang, Li Leone, Anthony M. Liu, Peiran Ludwig, Richard Tao, Li Wu, Wei Cansizoglu, Ahmet Hanneman, Andrew Adams, Greg W. Perdivara, Irina Walker, Hunter Wilson, Margo Brandenburg, Arnd DeGraan-Weber, Nick Gotta, Stefano Shambaugh, Joe Alvarez, Melissa Yu, X. Christopher Cao, Li Shao, Chun Mahan, Andrew Nanda, Hirsh Nields, Kristen Nightlinger, Nancy Niu, Ben Wang, Jihong Xu, Wei Leo, Gabriella Sepe, Nunzio Liu, Yan-Hui Patel, Bhumit A. Richardson, Douglas Wang, Yi Tizabi, Daniela Borisov, Oleg V. Lu, Yali Maynard, Ernest L. Gruhler, Albrecht Haselmann, Kim F. Krogh, Thomas N. Sönksen, Carsten P. Letarte, Simon Shen, Sean Boggio, Kristin Johnson, Keith Ni, Wenqin Patel, Himakshi Ripley, David Rouse, Jason C. Zhang, Ying Daniels, Carly Dawdy, Andrew Friese, Olga Powers, Thomas W. Sperry, Justin B. Woods, Josh Carlson, Eric Sen, K. Ilker Skilton, St John Busch, Michelle Lund, Anders Stapels, Martha Guo, Xu Heidelberger, Sibylle Kaluarachchi, Harini McCarthy, Sean Kim, John Zhen, Jing Zhou, Ying Rogstad, Sarah Wang, Xiaoshi Fang, Jing Chen, Weibin Yu, Ying Qing Hoogerheide, John G. Scott, Rebecca Yuan, Hua |
author_sort | Mouchahoir, Trina |
collection | PubMed |
description | [Image: see text] The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment. |
format | Online Article Text |
id | pubmed-9460773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-94607732022-09-10 Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study Mouchahoir, Trina Schiel, John E. Rogers, Rich Heckert, Alan Place, Benjamin J. Ammerman, Aaron Li, Xiaoxiao Robinson, Tom Schmidt, Brian Chumsae, Chris M. Li, Xinbi Manuilov, Anton V. Yan, Bo Staples, Gregory O. Ren, Da Veach, Alexander J. Wang, Dongdong Yared, Wael Sosic, Zoran Wang, Yan Zang, Li Leone, Anthony M. Liu, Peiran Ludwig, Richard Tao, Li Wu, Wei Cansizoglu, Ahmet Hanneman, Andrew Adams, Greg W. Perdivara, Irina Walker, Hunter Wilson, Margo Brandenburg, Arnd DeGraan-Weber, Nick Gotta, Stefano Shambaugh, Joe Alvarez, Melissa Yu, X. Christopher Cao, Li Shao, Chun Mahan, Andrew Nanda, Hirsh Nields, Kristen Nightlinger, Nancy Niu, Ben Wang, Jihong Xu, Wei Leo, Gabriella Sepe, Nunzio Liu, Yan-Hui Patel, Bhumit A. Richardson, Douglas Wang, Yi Tizabi, Daniela Borisov, Oleg V. Lu, Yali Maynard, Ernest L. Gruhler, Albrecht Haselmann, Kim F. Krogh, Thomas N. Sönksen, Carsten P. Letarte, Simon Shen, Sean Boggio, Kristin Johnson, Keith Ni, Wenqin Patel, Himakshi Ripley, David Rouse, Jason C. Zhang, Ying Daniels, Carly Dawdy, Andrew Friese, Olga Powers, Thomas W. Sperry, Justin B. Woods, Josh Carlson, Eric Sen, K. Ilker Skilton, St John Busch, Michelle Lund, Anders Stapels, Martha Guo, Xu Heidelberger, Sibylle Kaluarachchi, Harini McCarthy, Sean Kim, John Zhen, Jing Zhou, Ying Rogstad, Sarah Wang, Xiaoshi Fang, Jing Chen, Weibin Yu, Ying Qing Hoogerheide, John G. Scott, Rebecca Yuan, Hua J Am Soc Mass Spectrom [Image: see text] The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment. American Chemical Society 2022-08-26 2022-09-07 /pmc/articles/PMC9460773/ /pubmed/36018776 http://dx.doi.org/10.1021/jasms.2c00129 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Mouchahoir, Trina Schiel, John E. Rogers, Rich Heckert, Alan Place, Benjamin J. Ammerman, Aaron Li, Xiaoxiao Robinson, Tom Schmidt, Brian Chumsae, Chris M. Li, Xinbi Manuilov, Anton V. Yan, Bo Staples, Gregory O. Ren, Da Veach, Alexander J. Wang, Dongdong Yared, Wael Sosic, Zoran Wang, Yan Zang, Li Leone, Anthony M. Liu, Peiran Ludwig, Richard Tao, Li Wu, Wei Cansizoglu, Ahmet Hanneman, Andrew Adams, Greg W. Perdivara, Irina Walker, Hunter Wilson, Margo Brandenburg, Arnd DeGraan-Weber, Nick Gotta, Stefano Shambaugh, Joe Alvarez, Melissa Yu, X. Christopher Cao, Li Shao, Chun Mahan, Andrew Nanda, Hirsh Nields, Kristen Nightlinger, Nancy Niu, Ben Wang, Jihong Xu, Wei Leo, Gabriella Sepe, Nunzio Liu, Yan-Hui Patel, Bhumit A. Richardson, Douglas Wang, Yi Tizabi, Daniela Borisov, Oleg V. Lu, Yali Maynard, Ernest L. Gruhler, Albrecht Haselmann, Kim F. Krogh, Thomas N. Sönksen, Carsten P. Letarte, Simon Shen, Sean Boggio, Kristin Johnson, Keith Ni, Wenqin Patel, Himakshi Ripley, David Rouse, Jason C. Zhang, Ying Daniels, Carly Dawdy, Andrew Friese, Olga Powers, Thomas W. Sperry, Justin B. Woods, Josh Carlson, Eric Sen, K. Ilker Skilton, St John Busch, Michelle Lund, Anders Stapels, Martha Guo, Xu Heidelberger, Sibylle Kaluarachchi, Harini McCarthy, Sean Kim, John Zhen, Jing Zhou, Ying Rogstad, Sarah Wang, Xiaoshi Fang, Jing Chen, Weibin Yu, Ying Qing Hoogerheide, John G. Scott, Rebecca Yuan, Hua Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study |
title | Attribute Analytics
Performance Metrics from the MAM
Consortium Interlaboratory Study |
title_full | Attribute Analytics
Performance Metrics from the MAM
Consortium Interlaboratory Study |
title_fullStr | Attribute Analytics
Performance Metrics from the MAM
Consortium Interlaboratory Study |
title_full_unstemmed | Attribute Analytics
Performance Metrics from the MAM
Consortium Interlaboratory Study |
title_short | Attribute Analytics
Performance Metrics from the MAM
Consortium Interlaboratory Study |
title_sort | attribute analytics
performance metrics from the mam
consortium interlaboratory study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460773/ https://www.ncbi.nlm.nih.gov/pubmed/36018776 http://dx.doi.org/10.1021/jasms.2c00129 |
work_keys_str_mv | AT mouchahoirtrina attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT schieljohne attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT rogersrich attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT heckertalan attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT placebenjaminj attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT ammermanaaron attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT lixiaoxiao attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT robinsontom attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT schmidtbrian attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT chumsaechrism attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT lixinbi attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT manuilovantonv attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT yanbo attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT staplesgregoryo attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT renda attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT veachalexanderj attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wangdongdong attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT yaredwael attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT sosiczoran attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wangyan attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT zangli attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT leoneanthonym attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT liupeiran attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT ludwigrichard attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT taoli attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wuwei attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT cansizogluahmet attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT hannemanandrew attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT adamsgregw attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT perdivarairina attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT walkerhunter attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wilsonmargo attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT brandenburgarnd attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT degraanwebernick attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT gottastefano attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT shambaughjoe attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT alvarezmelissa attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT yuxchristopher attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT caoli attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT shaochun attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT mahanandrew attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT nandahirsh attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT nieldskristen attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT nightlingernancy attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT niuben attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wangjihong attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT xuwei attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT leogabriella attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT sepenunzio attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT liuyanhui attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT patelbhumita attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT richardsondouglas attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wangyi attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT tizabidaniela attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT borisovolegv attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT luyali attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT maynardernestl attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT gruhleralbrecht attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT haselmannkimf attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT kroghthomasn attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT sonksencarstenp attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT letartesimon attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT shensean attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT boggiokristin attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT johnsonkeith attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT niwenqin attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT patelhimakshi attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT ripleydavid attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT rousejasonc attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT zhangying attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT danielscarly attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT dawdyandrew attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT frieseolga attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT powersthomasw attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT sperryjustinb attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT woodsjosh attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT carlsoneric attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT senkilker attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT skiltonstjohn attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT buschmichelle attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT lundanders attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT stapelsmartha attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT guoxu attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT heidelbergersibylle attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT kaluarachchiharini attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT mccarthysean attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT kimjohn attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT zhenjing attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT zhouying attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT rogstadsarah attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT wangxiaoshi attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT fangjing attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT chenweibin attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT yuyingqing attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT hoogerheidejohng attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT scottrebecca attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy AT yuanhua attributeanalyticsperformancemetricsfromthemamconsortiuminterlaboratorystudy |