2019
DOI: 10.1021/acs.analchem.9b03808
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Multi-Attribute Method for Quality Control of Therapeutic Proteins

Abstract: Recent advances in high resolution mass spectrometry (MS) instrumentation and semi-automated software have led to a push toward the use of MS-based methods for quality control (QC) testing of therapeutic proteins in a cGMP environment. The approach that is most commonly being proposed for this purpose is known as the multi-attribute method (MAM). MAM is a promising approach that provides some distinct benefits compared to conventional methods currently used for QC testing of protein therapeutics, such as CEX, … Show more

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Cited by 93 publications
(124 citation statements)
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“…Mass spectrometry (MS) is now recognized as a major tool in protein structural characterization [5] and requested for example in ICH Q6B guideline (https://www.ich.org/page/search-index-ich-guidelines). Recent advances in high resolution MS instrumentation and have even led to the use of MS-based methods for quality control testing in a current Good Manufacturing Practice environment [6,7]. The continuous evolution of separative techniques and MS hyphenation enhances protein mixtures understanding and is widely applicable in mAbs assessments [8][9][10].…”
Section: Introductionmentioning
confidence: 99%
“…Mass spectrometry (MS) is now recognized as a major tool in protein structural characterization [5] and requested for example in ICH Q6B guideline (https://www.ich.org/page/search-index-ich-guidelines). Recent advances in high resolution MS instrumentation and have even led to the use of MS-based methods for quality control testing in a current Good Manufacturing Practice environment [6,7]. The continuous evolution of separative techniques and MS hyphenation enhances protein mixtures understanding and is widely applicable in mAbs assessments [8][9][10].…”
Section: Introductionmentioning
confidence: 99%
“…antibody screening | high throughput | intact protein mass spectrometry | electrospray U nambiguous characterization of analytes from complex matrices with high content information in a label-free format continues to expand the application of mass spectrometry (MS) in drug discovery (1)(2)(3). With the need for high accuracy, sensitivity, and selectivity, the rapidly improving MS instrumentations are emerging at the forefront of analyzing analytes with limited alternative assays for biologics developability (4)(5)(6), biotransformation, and high-throughput screening (HTS).…”
mentioning
confidence: 99%
“…The U.S. FDA recently reported that nearly all protein therapeutic biologics license applications approved between 2000 and 2015 used mass spectrometry for the characterization of drug substance and impurities (Rogstad et al, 2017). Liquid chromatography‐mass spectrometry (LC‐MS) based multiattribute methods for simultaneous monitoring of the glycan profile, charge variants, and purity of biotherapeutics was first reported by Rogers et al (2015), and has since gained significant utility in bioprocess development (Rogstad et al, 2019). As multiattribute LC‐MS methods can measure multiple CQAs in a single run, it eliminates the need for typical chromatographic tests such as hydrophilic interaction liquid chromatography for glycan profiling, cation exchange chromatography for charge variant analysis, and reduced capillary electrophoresis for purity analysis.…”
Section: Process Analytical Technologiesmentioning
confidence: 99%
“…Due to the technological maturation of on‐column trypsin digestion technologies and advanced sampling techniques such as the μSI System® from FIAlab®, it is now feasible to monitor product quality attributes such as glycans and other posttranslational modifications in an on‐line fashion (Toth, Kuklenyik, Morris, & Barr, 2019). Despite the aforementioned attractive features of LC‐MS based multi‐CQA monitoring tools, there are unique challenges associated with these systems, including the complexity of the technology, complicated method life cycle management, and method validation complications with new peak detection (Rogstad et al, 2019).…”
Section: Process Analytical Technologiesmentioning
confidence: 99%