By Nick Pittman, Magnus Wetterhall, and Scott Berger, Ph.D., Waters Corporation
The implementation of attribute-based analysis of biopharmaceuticals by LC-MS is now largely accepted by development organizations as a natural extension of the use of LC-MS for product characterization. Broader acceptance is hampered by concerns surrounding the cost of scaled implementation of LC-MS-based assays, as well as the challenge inherent to developing streamlined workflows and platform-based methods for implementing these capabilities without requiring significant organizational changes.
These concerns are balanced by increasing regulatory encouragement to adopt a more modernized and precise approach to biopharmaceutical analytics 1,2. Still, the challenge of justifying the capital and operational costs of LC-MS analysis can be difficult, and many organizations are hoping that the replacement of multiple conventional/traditional assays by MAM will provide not only better data to bolster their decisions, but to realize cost savings in the long run. This transition also requires organizations to carefully vet these technologies and techniques in order to determine the right partners, workflows, and personnel needed to ensure an MAM LC-MS platform is fit for their products, sites, and teams. Much of this work involves understanding the potential pitfalls that have been experienced by innovators and early adopters of MAM, as well as the rationale on how to avoid them.