Technical considerations for the implementation of the Multi-Attribute-Method by mass spectrometry in a Quality Control laboratory.

Large molecule protein therapeutics have steadily grown and now represent a significant portion of the overall pharmaceutical market. These complex therapies are commonly manufactured using cell culture technology. Sequence variants (SVs) are undesired minor variants that may arise from the cell culture biomanufacturing process that can potentially affect the safety and efficacy of a protein therapeutic. SVs have unintended amino acid substitutions and can come from genetic mutations or translation errors. These SVs can either be detected using genetic screening methods or by mass spectrometry (MS). Recent advances in Next-generation Sequencing (NGS) technology have made genetic testing cheaper, faster, and more convenient compared to time-consuming low-resolution tandem MS and Mascot Error Tolerant Search (ETS)-based workflows which often require ~6 to 8 weeks data turnaround time. However, NGS still cannot detect non-genetic derived SVs while MS analysis can do both. Here, we report a highly efficient Sequence Variant Analysis (SVA) workflow using high-resolution MS and tandem mass spectrometry combined with improved software to greatly reduce the time and resource cost associated with MS SVA workflows. Method development was performed to optimize the high-resolution tandem MS and software score cutoff for both SV identification and quantitation. We discovered that a feature of the Fusion Lumos caused significant relative under-quantitation of low-level peptides and turned it off. A comparison of common Orbitrap platforms showed that similar quantitation values were obtained on a spiked-in sample. With this new workflow, the amount of false positive SVs was decreased by up to 93%, and SVA turnaround time by LC-MS/MS was shortened to 2 weeks, comparable to NGS analysis speed and making LC-MS/MS the top choice for SVA workflow.

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A Highly Efficient Workflow for Detecting and Identifying Sequence Variants in Therapeutic Proteins with a High Resolution LC-MS/MS Method

The multi-attribute method (MAM), a liquid chromatography-mass spectrometry (LC-MS)-based peptide mapping method, has gained increased interest and applications in the biopharmaceutical industry. MAM can, in one method, provide targeted quantitation of multiple site-specific product quality attributes, as well as new peak detection. In this review, we focus on the scientific and regulatory considerations of using MAM in product quality attribute monitoring and quality control (QC) of therapeutic proteins. We highlight MAM implementation challenges and solutions with several case studies, and provide our perspective on the opportunities to use MS in QC for applications other than standard peptide mapping-based MAM.

Benjamin Nathan Moore

Papers

A Robust Purity Method for Biotherapeutics Using New Peak Detection in an LC-MS-Based Multi-Attribute Method.

A Highly Efficient Workflow for Detecting and Identifying Sequence Variants in Therapeutic Proteins with a High Resolution LC-MS/MS Method