Application of Mass Spectrometry Techniques in the Characterization and Quantitative Analysis of Therapeutic Protein Drugs in Veterinarian
Therapeutic protein drugs have evolved into a crucial branch of drug research and development.Due to their remarkable clinical efficacy and safety profile,they have become the preferred choice for treating conditions like cancer and autoimmune disorders.Therapeutic protein drugs produced through in vitro cell expression are often highly complex.Therefore,it is essential to establish a series of quality analysis and standards to ensure consistency and safety during the development and production processes.Mass spectrometry technology,known for its high sensitivity,excellent selectivity,specificity and high throughput capabilities,has been widely employed in the development of small molecule drugs.It has also emerged as a vital tool for the quality analysis of therapeutic protein drugs,contributing to structural characterization,post-translational modification assessment,quantitative analysis,impurity analysis and interaction studies.This article offers a comprehensive overview of protein analysis through mass spectrometry,including ionization techniques,dissociation methods and mass analyzers.Moreover,it delves into the sample preparation and methodologies for protein structural characterization and post-translational modification analysis such as glycosylation and disulfide bonds.The article also explores techniques for protein quantification via mass spectrometry,covering sample pre-processing and standard analytical procedures.Moreover,it also provides an outline of general strategies for characterizing and quantifying antibody-drug conjugate(ADC)and application in other way.By comprehensively exploring these topics,this article aims to provide valuable insights and reference to advance veterinary therapeutic protein drug research and development through mass spectrometry technology.
therapeutic protein drugsmass spectrometry techniquesquality control and evaluationquantitative analysis
万方数据
维普
