Peptide mapping (PM) is a vital technique in biopharmaceutical industry. The fingerprint obtained helps to qualitatively confirm host stability as well as verify primary structure, purity and integrity of the target protein. Yet, in-solution digestion followed by tandem mass spectrometry is not suitable as a routine quality control test. It is time consuming and requires sophisticated, expensive instruments and highly skilled operators. In an attempt to enhance the fuctionality of PM and extract multi-dimentional data about various critical quality attributes and comparability of biosimilars, coupling of PM generated using immobilized trypsin followed by HPLC-UV to principal component analysis (PCA) is proposed. Recombinant human growth hormone (rhGH); was selected as a model biopharmaceutical since it is available in the market from different manufacturers and its PM is a well-established pharmacopoeial test. Samples of different rhGH biosimilars as well as degraded samples: deamidated and oxidized were subjected to trypsin digestion followed by RP-HPLC-UV analysis. PCA of the entire chromatograms of test and reference samples was then conducted. Comparison of the scores of samples and investigation of the loadings plots clearly indicated the applicability of PM-PCA for: i) identity testing, ii) biosimilarity assessment and iii) stability evaluation. Hotelling’s T² and Q statistics were employed at 95% confidence level to measure the variation and to test the conformance of each sample to the PCA model, respectively. Coupling of PM to PCA provided a novel tool to identify peptide fragments responsible for variation between the test and reference samples as well as evaluation of the extent and relative significance of this variability. Transformation of conventional PM that is largely based on subjective visual comparison into an objective statiscally-guided analysis framework should provide a simple and economic tool to help both manufacturers and regulatory authorities in quality and biosimilarity assessment of biopharmaceuticals.

肽图分析（PM）是生物制药行业中的一项至关重要的技术。获得的指纹有助于定性确认宿主的稳定性，并验证靶蛋白的一级结构，纯度和完整性。然而，在溶液中消解后进行串联质谱法不适合作为常规质量控制测试。这是耗时的，并且需要复杂，昂贵的仪器和高技能的操作员。为了增强PM的功能性并提取有关各种关键质量属性和生物仿制药可比性的多维数据，提出了使用固定化胰蛋白酶和HPLC-UV生成的PM与主成分分析（PCA）的耦合方法。重组人生长激素（rhGH）；由于其在市场上可从不同的制造商处获得，并且其PM是一项完善的药典测试，因此被选择为生物制药的典范。将不同的rhGH生物仿制药样品以及降解的样品（脱酰胺和氧化的样品）进行胰蛋白酶消化，然后进行RP-HPLC-UV分析。然后对测试样品和参考样品的整个色谱图进行PCA分析。样品得分的比较和负载曲线的研究清楚地表明了PM-PCA在以下方面的适用性：i）身份测试，ii）生物相似性评估和iii）稳定性评估。Hotelling的T 然后对测试样品和参考样品的整个色谱图进行PCA分析。样品得分的比较和负载曲线的研究清楚地表明了PM-PCA在以下方面的适用性：i）身份测试，ii）生物相似性评估和iii）稳定性评估。Hotelling的T 然后对测试样品和参考样品的整个色谱图进行PCA分析。样品得分的比较和负载曲线的研究清楚地表明了PM-PCA在以下方面的适用性：i）身份测试，ii）生物相似性评估和iii）稳定性评估。Hotelling的T在95％置信水平下使用²和Q统计量来分别测量变化和测试每个样本与PCA模型的一致性。PM与PCA的耦合提供了一种新颖的工具，可识别负责测试样品与参考样品之间变异的肽片段，以及评估该变异程度和相对重要性的方法。传统的PM（主要基于主观视觉比较）转变为客观的，稳定的，指导性的分析框架，应该提供一种简单且经济的工具，以帮助制造商和监管机构双方对生物药品进行质量和生物相似性评估。