New Approaches to Cell and Gene Therapy Manufacturing Needed to Meet Demand
Pictured: Sterile viles/Courtesy, iStock, Neznam
Finding reliable methods to manufacture their products is a challenge for companies specializing in cell or gene therapies. Unlike traditional small molecule or antibody drugs, these medicines involve various specialized components that must be intricately woven together through complex and costly processes.
“Cell therapies are particularly challenging to manufacture due to the fact that they are personalized medicines that are currently being manufactured in manual and labor-intensive processes for each patient individually,” Fabian Gerlinghaus, CEO of Cellares, a cell therapy manufacturer, told BioSpace. “The technology that was never intended for commercial manufacturing is not ‘fit-for-purpose’ and requires open manufacturing steps resulting in high costs, high process failure rates and the inability of manufacturers to meet commercial-scale patient demand.”
This stands as a significant challenge to the rising number of cell and gene therapies in development, with the surge in demand often surpassing the capacity of large contract manufacturers. Gerlinghaus said bottlenecks in manufacturing could specifically be caused by supply chain constraints and labor shortages. The result is waitlists that can extend for one to two years.
“This can impact the company negatively by … potentially disappointing the patient community waiting for that drug to get into the clinic,” Claire Aldridge, chief strategy officer at Form Bio, told BioSpace.
Such challenges can be particularly acute for startups with limited resources, Gerlinghaus said. Recent approvals for cell and gene therapies have primarily been obtained by large pharma or biotech companies that have made substantial investments in manufacturing, he said.
“Manufacturing delays are particularly challenging to young companies due to limited cash reserves and runway. For cell therapy biotechs, any delay in manufacturing is effectively a delay in reaching the next value inflection point that would enable the next financing.”
Not only does this challenge the potential commercialization of these products once they reach the market, but it can often delay clinical testing, Aldridge said.
“If the manufacturing run does not generate enough doses or fails completely, that puts the entire development process at risk.”
New Approaches to Manufacturing
Next-gen manufacturers address these challenges in several ways. First, considering manufacturing from the start is pivotal, Aldrige said.
“Determining the manufacturability score for a particular drug product early on is key because it is much harder to make changes to them once you are too far along in the development path.”
Gerlinghaus advised that cell and gene therapy manufacturing needs to adopt fully automated, closed and integrated technologies. These solutions allow manufacturers to scale up and increase patient access to these life-saving therapies.
One approach to automation is to incorporate AI technologies. As in many other industries, AI is an attractive option in cell and gene manufacturing for its potential to save costs, compute variables and streamline processes.
“AI makes it easier to make things more powerful and to do less, of some things, fewer experiments to get to the same place,” William Whitford, a biotechnology product and process development expert now with Arcadis DPS Group, told BioSpace.
AI computes nearly unlimited variables with ease, making connections between variables, finding efficiencies and synthesizing data that would otherwise be costly in terms of time and money, Whitford said.
Aldridge agreed that AI would be key for the manufacturing of cell and gene therapy. “We are at a place where the technologies, including machine learning and generative AI, have developed to a point where they can help scientists with their trickiest problems,” she said. “We’ll always need the judgment of our scientific community, but these tools can narrow down the areas of interest and accelerate breakthroughs. It’s time to use the power of AI and ML to get them out.”