Biopharmaceutical protein products have revolutionized treatment of diseases and are one of the fastest growing segments of the pharmaceutical industry. The production and purification of biopharmaceutical proteins using cellular expression systems is challenging, due to the heterogeneity of the product and complexity of parameters influencing the process. Close monitoring of Critical Quality attributes (CQAs), - attributes of the product itself or impurities that are introduced through the process known to influence efficacy, safety or stability of the final product, - is necessary.
Host cell proteins (HCPs), proteins introduced by the expression system, are especially challenging to monitor and to deplete trough purification, due to a wide range of physicochemical properties like molecular weight or isoelectric points, which can often be similar to the properties of the product. The industrial standard to monitor HCP are enzyme-linked immunosorbent assays (ELISA). These assays are only able to detect immunoreactive HCP species and only give a total quantity. In contrast mass spectrometry (MS) is a non-targeted approach and allows unbiased identification and quantification of HCPs population down to single HCPs. Through monitoring HCP populations within the bioreactor, the understanding of the influence of processing conditions on their distribution and quantity, especially regarding specific HCPs that have been identified as critical for product quality and safety can be assessed.
Here, we present an optimized workflow to monitor and quantify HCP directly from clarified cell culture fluid (CCCF) samples using a DIA bottom-up MS approach.
The developed method is capable of quantifying more than 1000 HCPs from harvest samples including 20 high risk proteins identified as being especially problematic for biopharmaceutical while having improved throughput due to reduction in processing and acquisition time through the implementation of a high temperature digest in combination with a micro-flow LC system and untargeted DIA acquisition on a SCIEX ZenoTOF 7600.
The full workflow as well as unit operations were evaluated for robustness, sensitivity, repeatability and influences on the quantification results.
In addition, we explored the effects of varying standard spike-ins and changes to the data processing pipeline on hi3 absolute quantification methods. Hereby, our results highlight the need for standardization of these approaches for their wider use in an industrial context.
The developed method will be used to investigate changes and differences in HCP population expression during the time course of the production as well as in between bioreactor runs that implement different processing conditions especially feeding strategies.