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Team TFS
Team TFS
hcpHere at Thermo Fisher Scientific our mission is to enable our customers to make the world healthier, cleaner and safer. Ultimately our aim is to help our customers accelerate life sciences research, solve complex analytical challenges, improve patient diagnostics, deliver medicines to market and increase laboratory productivity. Our mission is central to everything we do but despite this I remain surprised by all the little ways in which this mission can be realised.

This was the case when reading a recent application note detailing the Easy, fast and reproducible analysis of host cell protein (HCP) in monoclonal antibody preparations, which was generated in partnership with the National Institute for Bioprocessing Research and Training.

Biopharmaceutical drugs are produced by recombinant DNA-technology using a non-human host cell. Host cell proteins (HCPs) are process-related impurities, expressed by the host cell. The majority of these proteins are removed via various purification and polishing steps but some may still be present at very low concentrations in the final drug product, possibly interfering with the product activity and/or stability, and potentially compromising patient safety. For these reasons regulators such as the FDA and EMA, require that biopharmaceuticals must be analysed and purified to reduce HCPs to an acceptable level. This level varies and is determined on a case-by-case basis.

Traditionally, process-specific enzyme linked immunosorbent assays (ELISAs) and protein gel blots have been the most popular method for HCP detection. Unfortunately both of these analytical techniques use a semi-quantitative approach that is targeting only a small set of expected proteins. This is bearing the risk of missing any unexpected or unknown protein that might still be present in the final drug product. In addition, these types of assays can be prone to underestimating the amount of HCPs.

LC-MS/MS based HCP analysis methods provide a powerful approach to facilitate both quantitative and qualitative analysis at the required levels of sensitivity.

Lean more in this recent application note:


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