Chromatogram Pre-Processing and Multivariate Analysis In Manufacturing Column Performance: A Case Study

Downstream operations in biotechnology, especially chromatography, are the most expensive manufacturing steps. Current practices in manufacturing chromatography may involve some degree of manual data handling and review, rely on experience and lead to delayed results. Moreover, optimizing data handling to improve current manufacturing practices can increase knowledge and efficiency in process monitoring.  Multivariate data analysis (MVDA) tools can contribute to this optimization in several ways, 1) reducing the complexity of data handling, 2) adding  objective statistics measures, 3) standardizing data analysis procedures, and 4)detecting out of specification runs in real time.  MVDA analysis does require pre-processing tools, such as chromatogram alignment, to prepare the data for analysis. In this work, we present a manufacturing case study showing the use of chromatography alignment followed by MVDA in a series of process runs.  This work highlights the methodology to achieve an efficient tool to detect out of specification runs in manufacturing chromatography operations.