<scp>AAV</scp> Gene Therapy Drug Development and Translation of Engineered Ocular and Neurotropic Capsids: A Systematic Review Using Natural Language Processing

Natural AAV serotypes often lack specificity and efficiency, leading to off-target effects and a low therapeutic index. To overcome these limitations of naturally occurring serotypes, there has been a keen interest in the field to engineer novel capsids to enhance tissue and cell-specific targeting, resulting in a high number of published literature reports over the past few years. To ensure a systematic review and illustrate advances in engineered capsids that enhance specificity and efficiency, we used Natural Language Processing with Linguamatics i2E to identify neurotropic and ocular AAV capsids tested in non-human primates. By querying PubMed abstracts for specific mentions of AAVs, administration routes, and organ/tissue/species, we obtained 5907 hits, refined through an optimized process to 36 relevant and unique abstracts. Notable findings include numerous novel capsids summarized by route of administration: (1) systemic administration, targeting the central nervous system (e.g., AAV-PHP.eB, AAV X1.1, and AAV.PAL2), (2) direct central nervous system injection (e.g., AAV2.Retro, Olig001, and AAV2.1A), and (3) ocular administration (e.g., AAV.44.9 (E531D), rAAV2tYF, and Anc80L65). Such engineered capsids exhibit enhanced tissue specificity, improved pharmacokinetics and pharmacodynamics, or reduced off-target effects compared to the parent serotypes. Our study provides insight into state-of-the-art translational and drug-development considerations for engineered neurotropic and ocular capsids. We also highlight the effectiveness of Natural Language Processing and Large Language Models as tools in identifying and characterizing engineered neurotropic and ocular AAV capsids to summarize this rapidly growing class of drugs and area of therapeutics.