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Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study.


ABSTRACT: 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.

SUBMITTER: Mouchahoir T 

PROVIDER: S-EPMC9460773 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study.

Mouchahoir Trina T   Schiel John E JE   Rogers Rich R   Heckert Alan A   Place Benjamin J BJ   Ammerman Aaron A   Li Xiaoxiao X   Robinson Tom T   Schmidt Brian B   Chumsae Chris M CM   Li Xinbi X   Manuilov Anton V AV   Yan Bo B   Staples Gregory O GO   Ren Da D   Veach Alexander J AJ   Wang Dongdong D   Yared Wael W   Sosic Zoran Z   Wang Yan Y   Zang Li L   Leone Anthony M AM   Liu Peiran P   Ludwig Richard R   Tao Li L   Wu Wei W   Cansizoglu Ahmet A   Hanneman Andrew A   Adams Greg W GW   Perdivara Irina I   Walker Hunter H   Wilson Margo M   Brandenburg Arnd A   DeGraan-Weber Nick N   Gotta Stefano S   Shambaugh Joe J   Alvarez Melissa M   Yu X Christopher XC   Cao Li L   Shao Chun C   Mahan Andrew A   Nanda Hirsh H   Nields Kristen K   Nightlinger Nancy N   Niu Ben B   Wang Jihong J   Xu Wei W   Leo Gabriella G   Sepe Nunzio N   Liu Yan-Hui YH   Patel Bhumit A BA   Richardson Douglas D   Wang Yi Y   Tizabi Daniela D   Borisov Oleg V OV   Lu Yali Y   Maynard Ernest L EL   Gruhler Albrecht A   Haselmann Kim F KF   Krogh Thomas N TN   Sönksen Carsten P CP   Letarte Simon S   Shen Sean S   Boggio Kristin K   Johnson Keith K   Ni Wenqin W   Patel Himakshi H   Ripley David D   Rouse Jason C JC   Zhang Ying Y   Daniels Carly C   Dawdy Andrew A   Friese Olga O   Powers Thomas W TW   Sperry Justin B JB   Woods Josh J   Carlson Eric E   Sen K Ilker KI   Skilton St John SJ   Busch Michelle M   Lund Anders A   Stapels Martha M   Guo Xu X   Heidelberger Sibylle S   Kaluarachchi Harini H   McCarthy Sean S   Kim John J   Zhen Jing J   Zhou Ying Y   Rogstad Sarah S   Wang Xiaoshi X   Fang Jing J   Chen Weibin W   Yu Ying Qing YQ   Hoogerheide John G JG   Scott Rebecca R   Yuan Hua H  

Journal of the American Society for Mass Spectrometry 20220826 9


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 ha  ...[more]

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