Host Cell Protein Analysis for Biopharmaceuticals

Introduction:

Host cell proteins (HCPs) are the most important process-related impurity in recombinant biopharmaceuticals, ie proteins produced in bacteria, yeast, and mammalian cell lines. Limited by current purification techniques, low levels (1 to 100 ppm) of host cell proteins (HCPs) may still remain in the purified biotherapeutics, even after a series of purifications. The ppm-level residual host cell proteins may effect drug safety and efficacy and cause adverse effects in patients, and can impact stability of the drug substance by proteolytic activity, so they are required to be identified and quantified as part of drug safety evaluation, by the regulatory agencies.

In order to avoid clinical failures of your drug product, it is desperately needed to learn as much qualitative and quantitative information about host cell proteins in your samples as possible. Identification and quantification of host cell proteins allow risk evaluation of each individual host cell protein, and facilitate development of the manufacturing process to remove HCPs of concern.

Usually the HCP assay can be achieved by 2D Electrophoresis, Western Blot and ELISA. After efficient separation of the biotherapeutics with electrophoresis, the host cell proteins could be identified and quantified with antiserum or polyclonal antibodies. LC-MS/MS, as a powerful analytical technique, has been introduced for HCP profiling as a revolutionary technology in recent years.

Biotherapeutics regulatory agencies (FDA, EMA, etc) are increasingly aware of the importance of mass spectrometry as an orthogonal method to ELISA for host cell protein analysis as described in the European and US Pharmacopeia.

Omics Technologies has been developing and providing HCP analysis services in the following areas:

1) Host cell protein analysis for biotherapeutics manufacturing pipeline optimization:

  ➢Identification of HCPs in each manufacturing step
  ➢Physical and Chemical properties of each HCP (poly-peptide sequence, molecular weight, pI, hydrophobicity, PTMs,)
  ➢Evaluate HCPs between manufacturing steps and identify/test the best protocol for HCP clearance

2) Host cell protein analysis for biotherapeutics products

  ➢Identification of HCPs in GMP batches, incorporated as a QC step for your product
  ➢Documentation of HCP detection and clearance for PAT and process validation
  ➢Absolute and relative quantification of specific HCPs, as accurate as protein copy number per ug product, eg. 1.3 million HCP protein copies per ug product.

3) Characterization and in-depth study of host cell protein of concern

  ➢Identification and quantification of HCPs of potential concern in drug substance
  ➢Characterization of your desired features of the identified HCPs
  ➢Development of the protocol to monitor and clear the HCPs based on your particular request

The protein therapeutics are separated with 1D/ 2D electrophoresis, and then visualized by Coomassie brilliant blue or sliver staining, and then digested into peptides by in-gel digestion for mass spectrometry analysis. Meanwhile, the protein therapeutics can be in-solution digested directly for nanoLC-ESI-LTQ/Orbitrap system. The contaminant proteins can be detected by database searching through numerous commercial softwares and can be de novo sequenced by our new PEAKS studio and Q module software platform. Omics Technologies can help you select the best methods based on your biopharmaceuticals and FDA's guidelines.






Sample types we accept:

1, Customized sample types (please contact us to discuss)


Please refer to our Omics Technologies Proteomics Sample Preparation and Shipping Guidelines for instructions on how to prepare your samples with less contamination for Mass Spectrometry Analysis.

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MyProt™-HCP

  • *Service Price will be quoted based on your desired service contents and the number of fractions you want to analyze. Please contact us to discuss.
  • Please note, the number of fractions you request determines the depth of analysis, total number of identified proteins and coverage (confidence) of identified proteins. Here is an example of how the number of fractions afffects your data's quality.

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