SynthesisClinical and translational science2025
AAV Gene Therapy Drug Development and Translation of Engineered Ocular and Neurotropic Capsids: A Systematic Review Using Natural Language Processing.
Synthesis in Clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- AAV Gene Therapy Drug Development and Translation of Engineered Ocular and Neurotropic Capsids: A Systematic Review Using Natural Language Processing.Clinical and translational science · 2025Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.