How Automation Is Improving AAV Purification for Gene Therapy Development

The use of adeno-associated viruses (AAVs) as vectors for gene therapy delivery and other therapeutics is growing fast, driven by innovations in treatments for genetic disorders as well as neurological, metabolic, and ophthalmic diseases. The AAV market will only become stronger, thanks to technological advances, such as the ability to increase vector tropism with capsid engineering and the ability to improve transduction efficiency with novel transgene cassettes. Hence, the market for AAVs is expected to grow at a compound annual growth rate of more than 40% to reach $107.2 billion by 2035.¹

This growth of the AAV market is fueling the demand for advanced purification technologies. As powerful as AAVs are for gene therapy delivery, they can be inefficient at packaging their nucleic acid cargo, resulting in only a small fraction of viral capsids carrying the gene of interest. Purification workflows help developers enrich the content of full capsids to levels necessary for safe gene therapy, typically greater than 85%, depending on the tropism required.² Purification is also essential for ridding AAVs of endotoxins, so they are safe for injecting into patients.³

Density gradient ultracentrifugation (DGUC) is commonly seen as the gold standard for purification of full capsids with consistent yields of 90% or higher purity of full capsids by cesium chloride (CsCl)–based methods. DGUC is also largely serotype and genotype independent; it does not require optimization when using a different serotype or engineered variant unless the density of capsids is significantly altered. The cost of scaling up DGUC methods is also cheaper than orthogonal methods to achieve the same quality.

The challenge for AAV developers is that current DGUC workflows require several manual steps, which make AAV purification by DGUC an open system vulnerable to human error. What’s more, DGUC is a manual purification process that is perceived as time-consuming and often difficult for early-career scientists to master.

Automating steps in DGUC can help overcome these challenges. By simplifying preparation methods, automation in DGUC minimizes variability in purification processes, while at the same time reducing processing time from as many as 3 days to under 1 day.

How should automation be implemented?

Automating step density gradient setup

The first step in purifying AAVs with ultracentrifugation is to set up a 15% to 60% w/v iodixanol step-density gradient, which separates AAV capsids from other cellular material while enriching full capsid content into a narrow band. This setup is traditionally a manual process that requires filling up to 8 to 12 tubes, often with 4 to 5 layers of material per tube, which therefore can be variable and error-prone. The tubes are loaded into a rotor and capped before being placed into the centrifuge.

Automation can greatly simplify the setup of step-density gradients. Automated DGUC technology can calculate flow rates and mixing ratios to generate continuous, consistent step gradients. Automated reagent preparation, gradient dispensing, and tube sealing further improve the efficiency of purification preparation. In one study, researchers measured recovery of viral genomes and found that the 2 methods were comparable. However, hands-on time was 5 minutes with the automated method vs 31 minutes for the manual method.⁴

Automating continuous density gradient setup

Continuous CsCl density gradients are used as a polishing step in purifying AAVs with ultracentrifugation to achieve consistently high purity of full capsids. These gradients, however, require long ultracentrifugation run times (16 hours or more) to generate the linear gradient and then separate the particles. Studies have shown that automated DGUC streamlines purification workflows, yielding similar results in less time. In one study, an automated system was used to preform and dispense continuous density gradients between predefined upper- and lower-limit densities, using CsCl and nanopure water as the diluent. A separate set of tubes were manually filled. The automation-prepared tubes were centrifuged for 4 hours, and the manually prepared tubes were centrifuged for 20 hours to allow the density gradient to form.

Samples from 3 different auto-dispensed tubes showed consistency in density distribution and a close match to the targeted continuous gradient. Hands-on time was 5 minutes for the automated process vs 14 minutes for the manual process. When tested with AAV, full-capsid purification efficiency was 90% with the automated process, resulting in a run time of 5 hours, which represents an estimated time savings of 75%.⁵

Challenges exist with using DGUC for purification, including scalability. DGUC is batch based, making it significantly more challenging to perform on large sample sizes than the other widely used purification method, chromatography. That being said, DGUC may be better suited than chromatography for small-volume projects aimed at assessing potential gene therapy candidates. Chromatography requires resins, which are specific to AAV serotypes. DGUC, on the other hand, is serotype agnostic. This characteristic allows researchers to purify multiple AAV serotypes in a single rotor, eliminating the need to optimize resins for each serotype and then purify each one separately. This further reduces the purification time.

What are the benefits beyond time savings?

Cutting the time required for AAV purification from 3 days to under 1 day offers several benefits for labs. With shorter ultracentrifugation run times, labs can get more use and throughput out of their instruments, which, in turn, can help them manage costs.

Automating DGUC preparation also reduces the training required to get young researchers comfortable with AAV purification. Training processes for manual DGUC workflows are rigorous and can take up to 6 weeks, sometimes more. With automation, inexperienced users can start running density gradients with as little as 15 minutes of training. This time savings also helps control costs.

The future of AAV purification is bright, with technology developers continually seeking new ways to deploy automation. For example, robots may be able to be deployed to recover samples after centrifugation. Automating the handoff between DGUC and other processes, such as filtration and chromatography, is another possibility.

Ultimately, what matters in AAV purification is not necessarily the specific technology at play but rather its ability to solve problems for researchers. In addition, it goes without saying that automation benefits patients as well. By improving the efficiency of purification workflows, researchers can assess the viability of the AAVs they’re developing much faster than they could before, which in turn can help speed novel therapies to the patients who need them.

About the author

Balasubramanian Venkatakrishnan, PhD, is a staff application scientist at Beckman Coulter Life Sciences and an AAV structural virologist by training.

References

1. Adeno-Associated Virus Gene Therapy Market Size, Epidemiology, In-Market Drugs Sales, Pipeline Therapies, and Regional Outlook 2025-2035. IMARC Group. Accessed October 6, 2025. https://www.imarcgroup.com/adeno-associated-virus-gene-therapy-market
2. Mietzsch M, Eddington C, Jose A, et al. Improved genome packaging efficiency of adeno-associated virus vectors using rep hybrids. J Virol. 2021;95(19):e00773-21. doi:10.1128/JVI.00773-21
3. Wright JF. Product-related impurities in clinical-grade recombinant AAV vectors: characterization and risk assessment. Biomedicines. 2014;2(1):80-97. doi:10.3390/biomedicines2010080
4. Reducing variability and hands-on time in viral vector purification using the OptiMATE gradient maker. Beckman Coulter Life Sciences. Accessed October 6, 2025. https://www.beckman.com/resources/reading-material/application-notes/reducing-variability-and-hands-on-time-in-viral-vector-purification
5. Rapid, automated purification of adeno-associated virus using the OptiMATE gradient maker. Beckman Coulter Life Sciences. Accessed October 6, 2025. https://www.beckman.com/resources/reading-material/application-notes/rapid-automated-purification-of-adeno-associated-virus-using-the-optimate-gradient-maker