Gene therapy firms face manufacturing and regulatory challenges that slow development and limit patient access. The good news is that new technologies have the potential to resolve many of these difficulties.

The science underpinning gene therapy is well established. The aim is to provide working copies of proteins whose functions are missing in patients as a result of inherited mutations. These copies are coded by nucleic acids that are introduced into target cells.

What is less well established is how to go about making gene therapies at scale, according to Cenk Sumen, PhD, CSO at cell engineering company, MaxCyte.

“We don’t currently have standardized, automated factories to mass produce these valuable therapeutic products. The industry is extremely regulated, with perhaps the highest compliance burdens and costs of any industry.

“Talent and skills are in short supply, and making these therapies to serve all patients requires tremendous specialized knowledge about cells and molecules. Patients struggle to gain access and hospitals aren’t always equipped to administer them.”

This lack of standardization and manufacturing talent is reflected in gene therapy prices, according to Sumen.

“Gene therapies are valuable because they are extremely difficult to make. It can take an estimated 50–100 PhD level scientists to make a single dose of product. Imagine how expensive a five-star meal would cost if 50–100 of the world’s best star chefs worked on it together.”

“Gene therapies, and cell therapies for that matter, are essentially luxury products; we just don’t call them that due to the socialized nature of the global healthcare industry,” he says.


Solving these difficulties will make gene therapies cheaper to manufacture and, Sumen says, allow more patients to benefit. Technology will play a vital role in driving this change.

“Analytics need to improve, and the regulatory agencies need to evolve, but there are certainly technologies available to miniaturize and automate the sampling and testing at microliter volumes and thousands of samples.

“We need developers to plan with the scale in mind and investors to have the patience to support large-scale automation initiatives.”

And artificial intelligence technology is likely to play a major role in helping gene therapy developers automate manufacturing.

“We can use AI to operate some of the bioprocessing steps, optimize settings, and aid discovery by sifting through large data stacks to find key parameters. Machine learning can be used to correlate disparate data sources and trained to recognize certain patterns much faster than groups of human brains.

“The ideal application in gene therapy production is likely to enable groups of experts and AI/ML systems to work in harmony to develop affordable, scalable therapies for the future.”

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