ReviewBiotechnology and bioengineering2026
Development and Integrated Application of the Multi-Attribute Method (MAM) in Quality Control of Biotechnological Drugs.
Review in Biotechnology and bioengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Development and Integrated Application of the Multi-Attribute Method (MAM) in Quality Control of Biotechnological Drugs.Biotechnology and bioengineering · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The multi-attribute method (MAM) is an integrated peptide mapping strategy based on liquid chromatography-mass spectrometry (LC-MS) technology. It enables precise quantification and dynamic tracking of multiple site-specific modifications in a single analysis, significantly enhancing the efficiency and depth of biopharmaceutical quality control. Notably, its integrated application across process development, process monitoring, and product release has driven a paradigm shift from a "single-attribute, single-method" approach to a "multi-attribute, integrated-method" approach in quality control. This review systematically summarizes the technical principles, optimization strategies, and application progress of MAM by integrating recent research cases of complex therapeutic proteins (e.g., monoclonal antibodies and Fc fusion proteins), with a focus on specific strategies and practical paths of MAM in workflow automation, new peak detection (NPD) optimization, intact multi-attribute method (iMAM), and the integration of complementary technologies. The objective is to provide a valuable reference for the standardization and industrial application of MAM in biotechnological drug quality control. Although MAM is expected to become a core analytical tool for biopharmaceutical quality control, its widespread industrial application remains constrained by key challenges, including insufficient method robustness, incomplete standardization, and variable regulatory acceptance. Notably, a significant stride in regulatory acceptance has been made with the recent implementation of the United States Pharmacopeia (USP) General Chapter < 1060 > , which establishes the first official framework for MAM. Beyond this regulatory milestone, future efforts should focus on advancing automated platform development, creating intelligent data algorithms, and strengthening cross-disciplinary collaboration to further promote the systematic integration and standardized application of MAM throughout the full lifecycle quality management of biotechnological drugs.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.