Biotherapeutic QC: Time to Meet MAM

The well-known clinical benefits of biologics come at a price: large molecule drugs are highly complex, leading to analytical challenges throughout the development pipeline – from discovery, through to bioprocessing, quality control and release. Monoclonal antibodies (mAbs) and other complex drug products, such as antibody-drug conjugates (ADCs), must be exhaustively characterized to ensure the safety and efficacy of a batch before release. Even the smallest change or post-translational modification, such as oxidation, deamidation, or glycosylation, has the potential to render the drug batch ineffective, or worse, create negative off-target effects for the patient.

Process development also faces challenges that are unique to the bioproduction environment, which, when combined with technological limitations of selectivity, fluidics and sterility can create an arduous sample analysis process, if the correct methodologies are not carefully chosen.

Characterization of biotherapeutics typically requires multiple labor intensive or time-consuming analytical techniques in offline QC labs; for example, cation-exchange chromatography, imaging capillary isoelectric focusing, and capillary electrophoresis sodium dodecyl sulphate (3). Typically, each technique provides information on only one or possibly a handful of critical quality attributes (CQAs) – and only after significant analysis. 

In my opinion, high-resolution accurate mass (HRAM) mass spectrometry (MS) coupled with high performance separation represents the cutting-edge of biotherapeutic characterization, not only because it offers high-resolution data and impressive levels of sensitivity, but also because it increases confidence in results. Although MS is integral to biopharma R&D processes, its use is still evolving in bioproduction and QC (4). Why? Historically, HRAM MS has required skilled users to operate the instruments, sample processing has been slow and complex, and software hasn’t always been up to scratch. And although HRAM MS certainly results in high resolution data, the fact that it still focuses on single or a handful of attributes makes it difficult to scale up to fit commercial bioprocessing and QC needs (5). Ultimately, these barriers to adoption have been too high to implement in QC and lot release. However, the situation is starting to look very different thanks to new and improved analytical systems and software – and a market place hungry for new solutions.

A relatively new analytical approach that is particularly well suited to biotherapeutics QC  is the multiple attribute method (MAM) – and a number of research papers back its advantages (1). MAM is based upon traditional peptide mapping; the biotherapeutic must first be digested into peptides – a critical step that requires 100 percent sequence coverage, high levels of reproducibility, and minimal process-induced modifications (for example, deamidation). The resulting peptides are separated using liquid chromatography, and detected with HRAM MS, before being processed using software tools. High resolution MS with MAM provides a comprehensive view of the CQAs present in biotherapeutics, down to the individual amino acid sequence of each molecule. Detailed information can then be obtained on post-translational modifications (PTMs), glycoprotein structures, the presence of any sequence variants at extremely low levels, and minute amounts of potential process impurities (2)(4). In short, MAM has the potential to consolidate multiple analyses from QC to batch release, enabling us to work towards consistent biotherapeutic structure from batch to batch, and across the entirety of the process.

For some time, there has been discussion about the need to improve biopharma manufacturing processes, and a common thread is the need for continuous manufacturing and real-time lot release, as alluded to within ICH guidelines (5). To get there, we need effective – and online – analytical methods for process monitoring and data generation. Here, MAM’s ability to simultaneously characterize multiple attributes could provide comprehensive and timely support for the consistent flow of products from continuous processes, assessing quality and ensuring proper control.

Regulators encourage the use of new and improved technologies, but until there is regulatory acceptance of MAM, the technique must run in parallel with existing methods to prove its equivalency and demonstrate its key benefits. There is certainly work ahead, but I do believe it’s time for HRAM MS and MAM to start moving into new areas – in particular, QC. Expanding the use of MS beyond R&D will not only reduce the number of experiments required per sample, but will also save time and resources – and provide increased confidence throughout the development and testing lifecycle.