Biopharma Hungry for GLP-1 Receptor Agonist Manufacturing Skills

Demand for engineers with GLP-1 receptor agonist (RA) manufacturing skills is increasing as the market for the popular anti-obesity drugs continues to grow, according to Ireland’s NIBRT, which has set up a training course to help meet the need.

The new course will cover biosynthetic and chemical production routes for peptide-based therapies as well as quality, regulatory, and supply chain considerations.

John Milne, PhD, NIBRT’s director of bioprocess training, tells GEN that development of the course was prompted by predictions about the substantial growth worldwide for GLP-1 receptor agonists over the next decade.

“These medicines have evolved quickly from niche drugs to treat diabetes when first launched to, now, blockbuster status for addressing type 2 diabetes, obesity, and cardiovascular health.

“Ireland can continue to play its part with respect to the ongoing and future manufacturing of these therapeutics, building on the track record of manufacturing sites, such as Lilly’s campus in Kinsale, which has contributed greatly to the global supply of its own GLP-1 RA portfolio.”

Ireland’s critical role in GLP-1 RA production was underlined in March when Novo Nordisk said it would make an oral version of Wegovy at its campus in Athlone, County Westmeath.

Such investments also helped convince NIBRT Ireland was an ideal location for a dedicated training course, Milne says.

“Building on the undoubted interest that exists in these therapeutics and helping trainees to contextualize these treatments from both a medical and a manufacturing perspective were important in our decision.”

Chemistry and biotech

Making GLP-1 RAs is a complex undertaking involving synthetic chemistry and protein expression, both of which will be covered by the new course, Milne says.

“Currently, the largest class of approved treatments globally are peptide-based GLP-1 RAs where the active target peptide is chemically synthesized, coupled to a long chain fatty acid with the resulting material being purified using chromatographic and filtration operations, prior to formulation and final filling.

“In other products, the active peptide can also be manufactured using recombinant technologies by expressing the active peptide in a cell-based system such as yeast cells or mammalian cells, followed by subsequent purification and formulation,” he says.

More recently, developers have advanced oral peptide- and non-peptide-based GLP-1 RAs—notably Eli Lilly’s Foundayo—which has further expanded the skill set production engineers require, according to Milne.

“In general terms, there is some overlap in the skill sets required to manufacture GLP-1 RAs, but there are also some obvious nuances specific to GLP-1 RAs. As an example, most GLP-1 analogues approved to date are administered by injection and hence are manufactured using similar fill and finish platforms and processes that are seen for other traditional biologic medicines.

“With the upsurge in manufacturing demand globally, there will undoubtedly be more facilities constructed by innovator companies and indeed more contract manufacturing organizations partnering with industry to address supply constraints.  New personnel will be needed, and sites will need to be repurposed to manufacture these products, in what will be a very competitive market space,” he adds.

Efficiency

Predictably, in such an environment, manufacturers are looking at ways of making production more efficient, Milne says, citing automation and AI as examples.

“Both automation and AI are becoming increasingly important with respect to improving capacity, quality, and reducing costs. As with most biomanufacturing operations, automation is fundamental to commercial GLP-1 production.

“Most commercial peptide synthesis systems are now fully automated and would include real-time process monitoring and control systems. This helps maintain GMP compliance, improve reproducibility, and robustness.”

He continues, “AI adoption is less mature but is growing across biomanufacturing, and a future state where AI will be applied in process optimization, continuous manufacturing, creating digital twins, automated quality monitoring, and supporting predictive maintenance is likely to emerge.”

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