AUC Analysis for AAV Characterization

What is AAV Vector?

AAV vectors are small, non-pathogenic viruses that have been modified to deliver therapeutic genes to target cells. They are composed of a protein capsid that encapsulates the viral genome. AAV vectors are attractive for gene therapy due to their ability to efficiently transduce a wide range of cell types, long-term gene expression capabilities, and favorable safety profile.

What is AUC Analysis?

Analytical Ultracentrifugation (AUC) analysis is a powerful analytical technique that utilizes ultracentrifugation to separate particles based on their sedimentation properties. AUC can provide high-resolution characterization of AAV vectors by separating different populations of vectors present in a sample based on their sedimentation coefficients (S-values). This allows for the quantification and characterization of intact, empty, and partially filled AAV vectors.

Characterization of recombinant adeno-associated virusCharacterization of recombinant adeno-associated virus (Gimpel et al., 2021)

Utilizing AUC Platform for AAV Vector Analysis

AUC analysis services for AAV vector characterisation are provided by Creative Proteomics. AUC analysis makes use of a specific platform to characterize AAV vectors in high-resolution. Modern ultracentrifuges with cutting-edge detection systems make up the platform. Based on their sedimentation coefficients, these tools are intended to offer accurate separation and measurement of AAV vector populations.

  • Ultracentrifuges: To successfully separate AAV vector populations for AUC analysis, ultracentrifuges with large centrifugal forces are required. These ultracentrifuges spin quickly, usually between 40,000 and 150,000 times per minute (RPM), which effectively sediments vectors within the material.
  • Detection Systems: The AUC platform incorporates cutting-edge detection systems to record and process the sedimentation data produced by the study. Based on the sedimentation coefficients of the AAV vectors, these devices use optical sensors to monitor the sedimentation process and offer real-time information on the spread of AAV vectors. High-resolution density profiles are created using the information gathered by the detection devices, allowing for the quantification and characterisation of various vector populations.

Advantages of AUC Analysis for AAV Vector Characterization

High Resolution: When characterizing AAV vectors, AUC analysis offers resolution that is unmatched. In accordance with their sedimentation coefficients (S-values), it can precisely distinguish between various vector populations. This makes it possible to precisely quantify and characterize whole, empty, and partially filled vectors. With the use of high-resolution data from the AUC analysis, researchers can precisely determine the vector quality.

Purity Assessment: By quantifying the distribution of vectors across different S-values, it enables researchers to assess the proportion of intact and non-functional vectors in a sample. This information is vital for optimizing vector production processes and ensuring that the final product meets the desired specifications. AUC analysis can identify potential impurities or contaminants that may impact the therapeutic efficacy of the vectors.

Shell-to-Core Ratio: The proportion of undamaged vectors and their prospective functional capacity are directly related by this ratio, which is a crucial characteristic. Researchers can precisely measure the intact vectors and assess their integrity using AUC analysis. Researchers can increase the effectiveness of AAV vectors and raise the general success of gene therapy treatments by improving the shell-to-core ratio.

Physical Property Characterization: AUC analysis provides insights into the physical properties of AAV vectors, such as size distribution and density. These parameters are crucial for understanding the behavior of vectors during the production and purification processes. By monitoring size distribution, researchers can optimize vector production methods to increase the yield of intact vectors. Density information helps in the identification of different vector populations and aids in ensuring batch-to-batch consistency.

Matrix Independence: AUC does not require considerable sample preparation or matrix-based separations, in contrast to certain other approaches. By getting rid of any potential interferences or artifacts that can result from matrix interactions, this enables more accurate and trustworthy analysis. In order to ensure data accuracy and reduce the possibility of erroneous interpretations, AUC offers a direct examination of AAV vectors in their natural condition.

The AUC provides high-resolution AAV sample analysis information that enables quantitative identification of hollow, solid, partially solid particles and aggregates. Contact us to learn more.


  1. Gimpel, Andreas L., et al. "Analytical methods for process and product characterization of recombinant adeno-associated virus-based genetherapies." Molecular Therapy-Methods & Clinical Development 20 (2021): 740-754.
* This service is for RESEARCH USE ONLY, not intended for any clinical use.