Evidence map›Paper›PMID 42373735›Full record

ReviewGene therapy2026

Recent advancements in improving cross-species applicability of bioengineered AAV capsids.

Haolai Pan, Nianci Li, Jieyu Qi, Renjie Chai

Abstract readReview
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In one paragraph

Review in Gene therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Haolai Pan *Department of Radiology, Zhuhai People's Hospital, The Affiliated Hospital of Beijing Institute of Technology, Advanced Technology Research Institute, School of Life Science, Beijing Institute of Technology, Beijing, China.
Nianci Li *Department of Otolaryngology Head and Neck Surgery, Zhongda Hospital, State Key Laboratory of Digital Medical Engineering, Jiangsu Provincial Key Laboratory of Critical Care Medicine, School of Life Sciences and Technology, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China.
Jieyu QiDepartment of Radiology, Zhuhai People's Hospital, The Affiliated Hospital of Beijing Institute of Technology, Advanced Technology Research Institute, School of Life Science, Beijing Institute of Technology, Beijing, China. qijieyu@bit.edu.cn.
Renjie ChaiDepartment of Radiology, Zhuhai People's Hospital, The Affiliated Hospital of Beijing Institute of Technology, Advanced Technology Research Institute, School of Life Science, Beijing Institute of Technology, Beijing, China. renjiec@seu.edu.cn.ORCID 0000-0002-3885-543X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adeno-associated virus (AAV) is widely accepted as a delivery vector for in vivo gene therapy due to its relatively low immunogenicity, minimal toxicity, sustained efficacy, and broad tropism. However, its unpredictable cross-species applicability remains a troublesome hurdle for broader clinical applications. Thus, designing novel AAV capsids with enhanced cross-species applicability is urgently needed. In this review, we present AAV bioengineering methods, including rational design, directed evolution, and artificial intelligence-based design, with the goal of creating novel AAV variants that are translatable to humans. Using representative examples, we also evaluate how each method addresses key species-dependent barriers-receptor usage, intracellular trafficking, immune recognition, and toxicity-that critically determine cross-species translatability.

Indexed as

BioengineeringDependovirusGenetic VectorsGene Transfer TechniquesAnimalsCapsid ProteinsGenetic TherapyHumansCapsid Proteins

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.