ReviewMethods in molecular biology (Clifton, N.J.)2027
Overview of Delivery Methods for Gene Editing.
Review in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The clinical success of CRISPR-based interventions depends primarily on the efficient delivery of editing components into target cells. While base and prime editing have refined genomic precision, achieving therapeutic efficacy requires specialized vehicles that can navigate systemic circulation, escape endosomes, and ensure cell-specific entry. Delivery platforms are traditionally categorized into viral and nonviral systems. Viral vectors, namely adeno-associated vectors (AAV), lentiviral vectors, and adenoviral vectors, employ evolved mechanisms to achieve high transduction efficiency and predictable biodistribution, yet remain constrained by immunogenicity and the risk of insertional mutagenesis. In contrast, nonviral approaches, including synthetic nanoparticles and physical methods, offer superior scalability and transient expression profiles, reducing long-term genomic risks. Next-generation platforms such as virus-like particles (VLPs), engineered extracellular vesicles (EVs), and functionalized nanoparticles have emerged to bridge this gap. These hybrid systems synergize the entry efficiency of viral proteins with the low-immunogenicity profiles of synthetic carriers. Ultimately, the optimal delivery method is determined by the CRISPR cargo format and target cell characteristics, balancing safety, immunogenicity, and scalability. This chapter emphasizes that the strategic selection of a delivery vehicle must be harmonized with the specific cargo and the unique biological requirements of the target tissue to ensure therapeutic success.
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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.