By Mike May, PhD

Today’s clinicians use recombinant therapeutic proteins, such as monoclonal antibodies, to treat many diseases, from autoimmune disorders to cancer and beyond. Nonetheless, sequence variants (SVs), which create unwanted changes in the therapeutic protein’s amino acids, impede the bioprocessing and safety of these therapies. Pharmaceutical companies and government regulators want that problem solved.

The SV problem is not new. In 2015, Oleg Borisov, PhD, then at Novavax and now analytical development leader at the Bill & Melinda Gates Medical Research Institute, and his colleagues pointed out: “The occurrence of sequence variants contributes to heterogeneity of recombinant protein therapeutics. Establishing a sequence variant profile of a biotherapeutic product is essential in providing proof of its structure, its manufacturing consistency, and the stability of the producing cell line.”

Ongoing issue

Nonetheless, the problem continues to concern bioprocessors. In 2020, Aming Zhang, PhD, then at GSK and now head of analytical develop and quality control at Pyxis Oncology, and his colleagues wrote: “SVs resulting from unintended amino acid substitutions in recombinant therapeutic proteins have increasingly gained attention from both regulatory agencies and the biopharmaceutical industry given their potential impact on efficacy and safety.” Zhang and his colleagues proposed that sequence variants at an amino acid site should be less than 0.1% in a recombinant therapeutic protein.

That’s not much variation, which makes it difficult to detect SVs accurately and quickly during bioprocessing.  As Wei Xu, PhD, director of analytical sciences, biopharmaceuticals R&D, AstraZeneca, and his colleagues wrote in the Journal of the American Society for Mass Spectrometry: “Despite the recent advancements in mass spectrometry hardware and software, it is still quite challenging and time-consuming to detect and identify low-level SVs.” So, these scientists developed a new method of peak detection based on LC-MS/MS. Using this method, Xu and his colleagues concluded that the “workflow identified all SVs reported by conventional data analysis with more than 20-fold increase in speed.”

Undoubtedly, scientists will continue to advance the analytical and computational methods of addressing this needle-in-a-haystack search. The safety and efficacy of recombinant therapeutic proteins depends on it.

Previous articleNovel Strategy Breaks the Protein Separation Bottleneck
Next articleFirst Genetic Marker for Severity, Progression of Multiple Sclerosis Identified