Challenges for Measuring Immunogenicity of AAV-based Gene Therapies
Since gene therapy products work by introducing genetic material into the cell, scientists need a way to deliver DNA, RNA, or nuclease to the target tissue and cells. The delivery systems that carry the genetic material are referred to as vectors.
Viral-based or vector-based gene therapies may hold the key to treating a wide range of human diseases. Of course, these versatile and complex tools aren’t without their challenges. A primary obstacle in the development and efficacy of these therapies is the host immune and inflammatory responses that may limit the ability of the gene therapy to successfully reach target cells and deliver the genetic payload.
The risk of generating immunogenicity against the virus and vector used in gene therapy is a safety risk for patients, and therefore according to FDA, the pre-existing immunity are one of the major challenges that must be addressed by finding novel strategies to reduce immunogenicity of gene therapy product.
The impact of immune responses and inflammation may pose a safety risk to patients and may also limit product efficacy. Thus, there is a need for thorough characterization of the immunogenicity of gene therapy products in order to better understand the impact and better design future gene therapy vectors.
Challenges of Measuring Humoral Immunogenicity for AAV-based Gene Therapies
Characterization of the immune response against viral vector-based gene therapies, in particular adeno-associated viruses (AAV), is currently a hot topic in the industry. The role of pre-existing antibodies against AAV and their impact on efficacy is not clearly understood and, therefore, requires additional data and experience to better guide decision-making for sponsors developing these therapies.
Anti-drug antibody (ADA) assays that are specific for the individual AAV serotypes and natural history studies that provide data on the frequency of individuals with pre-existing antibodies are key tools to provide context to both non-clinical and clinical studies. There have been differences identified in the frequency of positive individuals based on age, geographic location and disease state. High-quality, sensitive assays for detecting these antibodies are essential for collecting data.
While there are no current regulatory guidance documents specifically for immunogenicity of gene therapies, much can be leveraged from the 2019 FDA Guidance on Immunogenicity. Currently, the expectations for ADA assays to assess AAV-specific antibodies is patterned after that guidance document. Sensitivity targets and performance criteria that are used for other biotherapeutics, such as monoclonal antibodies, are also applied to AAV-specific ADA assays. There are some specific challenges that have to be overcome such as the identification of positive control antibodies and the establishment of a proper cutpoint when there is such a high frequency of positive individuals due to environmental exposure.
Typically, ADA assay cutpoints are set using minimally 50 individuals. However, in cases where you may have to eliminate 40-70% of individuals as outliers due to pre-existing antibodies, far more individuals may need to be screened than the typical 50. There are also open discussions as to whether the sponsor’s specific capsid loaded with payload should be used or if commercially available “empty” capsids will suffice. There is currently a draft white paper that represents a team of individuals from biotech, pharma, CROs and regulatory agencies who have assembled recommendations for these assays.
Along with humoral immunogenicity, cellular immune responses are also of great interest. Typical approaches involve using tools like ELISpot to measure the production of cytokines by cells, such as circulating lymphocytes, when stimulated with peptides derived from the viral vector.
While a consensus for these assays is beginning to form, there is still much to learn about the relationship of these results with the larger picture of safety and efficacy. In particular, the role of pre-existing antibodies as inclusion/exclusion criteria has yet to be clearly defined. As the field gains experience built around data from robust assays, we will continue to learn and evolve our thinking on the impact and relevance of these pre-existing antibodies.
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