Iterative LC-MS/MS Exclusion for Low-Abundance HCP Detection
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Solution Overview
Problem
Current methods for identifying and quantifying host cell proteins (HCPs) in therapeutic protein development face challenges in achieving robust, unbiased, and sensitive analysis, particularly due to the high dynamic range of protein abundance and interference from abundant drug substance peptides, which limits the detection of low-abundance HCPs.
Innovation Solution
The implementation of an automated precursor ion exclusion (PIE) acquisition method, termed HCP-Automated Iterative MS (HCP-AIMS), which uses direct digestion samples and iterative tandem mass spectrometry to exclude previously fragmented precursor ions, allowing for deeper identification and quantitation of low-abundance HCPs without enrichment, combined with high-throughput UHPLC analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional LC-MS/MS methods are used for HCP identification, then fast and unbiased HCP identification can be achieved, but sensitive protein identification and accurate protein quantitation are compromised due to interference from abundant drug substance peptides
Solution Approach 1:
The patent extracts and excludes the interfering abundant precursor ions (drug substance peptides) from the mass spectrometry analysis by creating an exclusion list based on the known drug substance sequence. This allows the mass spectrometer to focus on detecting and quantifying low-abundance HCP peptides without interference from the dominant drug substance signals, thereby resolving the contradiction between identification speed and quantitation accuracy.
Solution Approach 2:
The patent performs preliminary identification of drug substance peptides and creates an exclusion list before conducting the actual HCP quantitation analysis. This preliminary action enables the subsequent analysis to automatically exclude interfering ions, allowing both fast identification and accurate quantitation of HCPs to be achieved simultaneously.
2Measurement precision
If enrichment methods are used to detect low-abundance HCPs, then detection sensitivity is improved, but analysis time and process complexity increase
Solution Approach 1:
The patent replaces the mechanical/enzymatic enrichment process with a computational/exclusion-based approach. Instead of using physical methods to concentrate HCPs before analysis, the system uses software-based precursor ion exclusion to filter out interfering signals during direct LC-MS/MS analysis of digested samples, achieving high sensitivity without the time-consuming enrichment steps.
3Productivity
If direct digestion samples are analyzed without exclusion methods, then high-throughput analysis is maintained, but low-abundance HCPs cannot be detected due to interference from abundant peptides
Solution Approach 1:
The patent extracts the interfering abundant precursor ions from the complex digest sample by creating a dynamic exclusion list based on the drug substance sequence. This allows direct digestion samples to be analyzed at high throughput while simultaneously enabling detection of low-abundance HCPs that would otherwise be masked by the dominant drug substance peptides.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables sensitive and robust HCP identification and quantitation to a detection limit of about 10 ppm or lower, facilitating high-throughput analysis and ensuring the quality and safety of therapeutic protein products by effectively mitigating the risk of problematic HCPs.
Implementation Method 1
subjecting the sample to a chromatography column to obtain a chromatographic elution peak
Implementation Method 2
performing a tandem mass spectrometry analysis by performing a data-dependent acquisition cycle across the chromatographic elution peak
Implementation Method 3
performing a tandem mass spectrometry analysis by performing a data-dependent acquisition cycle
Data Source
AI summary
The present disclosure generally pertains to methods of identifying and quantitating host cell proteins (HCPs) in therapeutic protein development. In particular, the present invention generally pertains to methods of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for unbiased identification and sensitive quantitation of HCPs in therapeutic protein development.