Scaling AAV manufacturing: upstream strategies to reduce cost and risk

By Emmanuelle Cameau and Kelly Cybulski.

Gene therapies have the potential to transform—and in some cases cure—serious genetic diseases. Yet despite accelerated regulatory approvals and growing clinical success, access remains limited. One of the most persistent barriers is the cost and complexity of manufacturing, particularly for therapies based on adeno‑associated virus (AAV) vectors.

As more AAV programs advance toward late‑stage development and commercialization, the industry faces a critical question: How can we scale AAV manufacturing without compounding cost, risk, and variability?

The cost‑of‑dose challenge in gene therapy

Many recently approved gene therapies carry price tags of millions of dollars per dose. Such a cost may be justifiable if only a single dose is needed to treat a patient, and the cost may be less expensive than a lifetime of continued treatment. But the high price tags place significant strain on healthcare systems and limit broad patient access.

Manufacturing plays a central role in the treatment cost. High R&D investment, immature processes, manual operations, limited scalability, and low overall material use all inflate cost of goods (Fig 1). Furthermore, the development costs of all the drugs that didn't make it to market are added to the costs of the drugs that do. And, in some cases, only a small fraction of manufactured vector ultimately reaches the patient, amplifying inefficiency across the process.

Fig 1. Many factors influence and increase the cost per dose of AAV therapeutics.

Why upstream decisions matter more than ever

Upstream manufacturing choices made early in development can have far‑reaching consequences at scale.

Traditional 2D cell culture flatware systems, while familiar, are labor‑intensive and difficult to scale. As production volumes increase, these systems introduce greater risk of contamination and batch‑to‑batch variability. Facility and personnel constraints are another hurdle. At scale, flatware systems often require large footprints (Fig 2) and significant staffing to tend the cultures.

Fig 2. A multi-tray, 2D flatware facility requires a large footprint to grow cells at scale. This model facility occupies 1050 m².

In contrast, scalable and automated, fixed-bed upstream platforms (Fig 3.) offer a path to greater consistency, reduced labor, and more predictable scale‑up. By focusing on process robustness early, developers can avoid costly redevelopment cycles later in clinical or commercial phases.

Fig 3. An automated, fixed-bed bioreactor occupies less space and requires fewer trained personnel. This facility produces the same AAV yield as the facility shown in Figure 2 but occupies just 320 m².

Designing scalability into AAV manufacturing

Successful AAV scale‑up requires more than simply increasing volume. Key parameters, such as power input per volume, oxygen transfer, linear velocity, and media‑to‑surface area ratios, must remain tightly controlled to preserve cell health and vector productivity. When these parameters are properly managed, our scalability studies demonstrated that consistent cell growth, metabolic profiles, and AAV titers can be maintained across multiple production scales. By managing the parameters, you can de‑risk scale‑up while supporting flexible production strategies for different indications, doses, and patient populations.

Supporting flexibility across development stages

Not all gene therapies require the same manufacturing strategy. Differences in disease prevalence, route of administration, and dose (Table 1) demand mean that manufacturing flexibility is essential.

Platforms that enable smooth transitions from bench‑scale to clinical to commercial manufacturing help teams adapt as programs evolve without sacrificing quality or delaying timelines. This flexibility is especially important given the growing number of AAV programs moving concurrently through development pipelines.

Table 1. Examples of the theoretical vector demand in the United States based on number of patients and dose size.

Disease	Number of patients in the US (estimated)	Dose size (estimated)	Maximum vector genomes need (estimated)
Retinitis pigmentosa	100 000	1010–1.2 × 1011 $\frac{\mathrm{vg}}{\mathrm{eye}}$ (local administration)	2.4 × 1016
Wet age-related macular degeneration (AMD)	1 200 000	109–1012 $\frac{\mathrm{vg}}{\mathrm{eye}}$ (local administration)	2.4 × 1018
Severe hemophilia A	6500 (70 kg patient)	4 × 1011–6 × 1013 $\frac{\mathrm{vg}}{\mathrm{kg}}$ (systemic administration)	2.7 × 1019
Duchenne muscular dystrophy	13 000 (50 kg patient)	1013–2 × 1014 $\frac{\mathrm{vg}}{\mathrm{kg}}$ (systemic administration)	1.3 × 1020

Building confidence on the path to commercialization

Ultimately, scaling AAV manufacturing is not just a technical challenge; it's a strategic one. Decisions made upstream influence:

• Speed to clinic and market
• Facility design and footprint
• Labor requirements
• Cost of goods at commercial scale
• Long‑term manufacturing resilience

By prioritizing scalable, automated, and well‑characterized upstream processes, gene therapy developers can move from bench to bedside with greater confidence, while supporting the broader goal of making life‑changing therapies more accessible to patients.