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Vancomycin is an effective antibiotic used for the treatment of Gram-positive bacterial infections. During the analysis of vancomycin, an unknown impurity at the level of 0.5% was detected by high-performance liquid chromatography (HPLC). To characterize the structure of the impurity, a new two-dimensional preparative liquid chromatography (2D-Prep-LC) method was developed to separate the impurity from the vancomycin sample. After further analysis including liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy, the structure of the unknown impurity was identified as a vancomycin analog in which the N-Methyl-leucine residue on the side chain is replaced by an N-methylmethionine residue. In this study, we established a reliable and efficient method for separating and identifying vancomycin impurities, which will provide a valuable contribution to the field of pharmaceutical analysis and quality control.
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http://dx.doi.org/10.1016/j.jpba.2023.115403 | DOI Listing |
Brief Bioinform
July 2025
Department of Mathematics and Statistics, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 5C2, Canada.
Existing cell type annotation methods face significant hurdles: supervised approaches often fail to differentiate between novel cell types not present in reference data, while unsupervised techniques can suffer from cluster impurity and difficulties in robustly distinguishing multiple distinct unknown cell populations. This critical gap motivated the development of HiCat, a semi-supervised pipeline specifically designed to overcome these limitations. HiCat is a semi-supervised pipeline that integrates both approaches, leveraging reference (labeled) and query (unlabeled) genomic data to simultaneously enhance annotation accuracy for known cell types and improve the discovery and differentiation of novel ones.
View Article and Find Full Text PDFMAbs
December 2025
Analytical Chemistry Group, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA.
Co-formulated antibody cocktails are becoming an increasingly popular therapeutic class; however, they present analytical challenges over traditional single monoclonal antibody (mAb) formulations. One paramount concern is the formation of heteromeric species that have unknown impacts on safety and efficacy. Consequently, effective approaches for identifying and characterizing high-molecular weight (HMW) impurities are critical to the successful development of this therapeutic class.
View Article and Find Full Text PDFToxicol Lett
August 2025
Department of Chemistry, Amity School of Applied Sciences, Amity University Mumbai, Mumbai-Pune Expressway Bhatan, Somathne, Panvel, Mumbai, Maharashtra 410206, India. Electronic address:
Since the adoption of the ICH M7 guidelines in 2014, pharmaceutical industries have been mandated to screen all reagents and chemicals used in drug synthesis for genotoxicity. Genotoxic impurities (GTIs) have the potential to induce mutations in DNA, which may lead to cancer. Unlike routine impurities, the threshold for controlling GTIs is extremely low.
View Article and Find Full Text PDFRapid Commun Mass Spectrom
November 2025
Key Laboratory for Core Technology of Generic Drug Evaluation National Medical Product Administration, Zhejiang Institute for Food and Drug Control, Hangzhou, China.
Rationale: In March 2024, tunlametinib capsules, a Class 1 new drug (referring to active pharmaceutical ingredients and formulations not previously marketed either nationally or globally), were approved in China for treating patients with advanced melanoma and neuroblastoma RAS viral oncogene homologue mutations who experienced disease progression or intolerance to anti-PD-1/PD-L1 therapy. Risk assessment of impurity profiles is essential for drug safety and efficacy in clinical applications. This study characterized impurity profiles in tunlametinib capsules induced by photodegradation.
View Article and Find Full Text PDFJ Proteome Res
August 2025
State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100050, P. R. China.
Host cell proteins (HCPs) are critical process-related impurities in biotherapeutics that threaten drug stability and safety. The substantial dynamic range (>5 orders of magnitude) between therapeutic proteins and residual HCPs often leads to difficulty in detecting high-risk species. Herein, we developed a novel strategy integrating data-dependent acquisition (DDA), parallel reaction monitoring (PRM), and multiple reaction monitoring (MRM) techniques to comprehensively profile and accurately quantify high-risk HCPs.
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