Multi-Attribute Method for Quality Control of Therapeutic Proteins

Area of Science:

• Analytical Chemistry
• Biotechnology
• Pharmaceutical Science

Background:

• High-resolution mass spectrometry (MS) and semi-automated software advancements drive the adoption of MS-based methods for therapeutic protein quality control (QC).
• The multi-attribute method (MAM) is a proposed MS-based approach offering potential benefits over conventional QC techniques like CEX, HILIC, and CE-SDS.
• The established use of MS in cGMP environments for QC is limited, necessitating the exploration of new scientific and regulatory considerations.

Purpose of the Study:

• To address scientific and regulatory questions surrounding the implementation of the multi-attribute method (MAM) for therapeutic protein QC in current Good Manufacturing Practice (cGMP) settings.
• To provide a framework for evaluating MAM for both new and existing protein products.
• To identify and suggest approaches for overcoming challenges associated with MAM adoption.

Main Methods:

• The study categorizes implementation questions into four key areas: risk assessment, method validation, New Peak Detection (NPD) capabilities, and comparisons with conventional methods.
• A perspective-based approach is used to outline considerations and suggest solutions for each identified aspect.
• The focus is on practical implementation within a cGMP framework.

Main Results:

• Key considerations for MAM implementation include comprehensive risk assessment, rigorous method validation, understanding the specifics of New Peak Detection (NPD), and direct comparisons to established QC methods.
• Potential issues and challenges are identified across these areas.
• Guidance is offered to facilitate the successful integration of MAM into cGMP workflows.

Conclusions:

• Successful implementation of MAM in cGMP requires careful attention to risk assessment, validation, NPD functionality, and comparative analyses.
• Addressing these aspects proactively will support the reliable use of MAM for therapeutic protein QC.
• This perspective serves as a guide for navigating the complexities of adopting advanced MS-based analytical strategies in pharmaceutical manufacturing.