The average cost of bringing a cell or gene therapy to market has increased to $1.94 billion, according to new analysis, which suggests the complex processes required to make such products are a major driver.

Manufacturing cell and gene therapies is complicated. And, unfortunately for developers, complication is expensive, according to lead author Marco Sabatini, PhD, senior manager of health science and wellness at management consulting firm, EY-Parthenon.

“While the exact drivers for cell and gene R&D cannot be ascertained from SEC reporting alone, we hypothesize that one of the main drivers of the high cost would be the complex and specialized manufacturing processes required to produce such a class of therapies,” he says. “Indeed, making cell and gene therapies often involves the use of high-cost reagents and components. For example, producing the viral vectors used to deliver genetic material requires a highly specialized and complex manufacturing process.”

Sabatini cites autologous cell therapies—T cells harvested from a specific patient that are primed to recognize tumors or diseased cells—as an example where manufacturing processes are likely to account for a substantial proportion of overall costs.

“While cost of goods sold (COGS) estimates for autologous cell therapies like CAR-Ts are seldom reported in the public domain, recent estimates suggest they can range between $100,000 and $300,000 per dosage,” he points out.

Cost reduction

The hypothesis also fits with recent M&A activity in sector as well as developments in the bioprocessing technology space, according to Sabatini.

“There is definitely a lot of innovation from the digital and automation side of things going on. There are a number of dimensions upon which to cut costs relating to manufacture, everything from process optimization to streamlining supply chains,” explains Sabatini.

As an example, Sabatini points to Galapagos’ acquisition of CellPoint and AboundBio last year. At the time, the Belgian biotech said CellPoint’s supply model—which combines the xCellit management software with Lonza’s Cocoon platform—was the motivation.

Sabatini also highlights recent comments by Bristol Myers Squibb (BMS) as evidence developers are using innovative technologies to reduce manufacturing costs. During an R&D presentation in September, BMS said it was using computational science—including artificial intelligence and machine learning—to develop CAR production processes that have “shortened turn-around time” and “lower failure rates.”

The focus on turnaround time is characteristic of industry-wide efforts to address scalability, according to Sabatini, who adds, “Innovation in the space is all around the faster turnaround times to free up capacity, through things like continuous production and faster QC review.”

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