ReviewMolecular biotechnology2025
The Future of Gene Therapy: A Review of In Vivo and Ex Vivo Delivery Methods for Genome Editing-Based Therapies.
Review in Molecular biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 33 citations in OpenAlex.
- Advanced gene editing technologies for oncology mechanisms, applications, and clinical implementation.Cancer gene therapy · 2026Review
- Clinical pharmacology insights from recent cell and gene therapy approvals relevant to pediatrics.Pediatric research · 2026Review
- CRISPR-Cas9 and next-generation gene editing strategies for therapeutic intervention of neurodegenerative pathways in Alzheimer's disease: a state-of-the-art review.Acta neurologica Belgica · 2026Review
- Extracellular Vesicle-Mediated U1 snRNA Delivery Restores Aberrant Pre-mRNA Splicing in Human Cells.Biomolecules · 2026Article
- Target, silence, replace: a review on RNA-based drugs in modern medicine.Frontiers in cell and developmental biology · 2026Review
- Editorial: Clinical translation and commercialisation of advanced therapy medicinal products, volume II.Frontiers in bioengineering and biotechnology · 2026Article
- Landscape ofMolecular therapy. Methods & clinical development · 2025Article
- Unlocking the role of transcription activator-like effector nuclease (TALENs) and zinc finger nuclease (ZFN) in the treatment of HIV.Molecular biology reports · 2025Review
- Advancing gene editing therapeutics: Clinical trials and innovative delivery systems across diverse diseases.Molecular therapy. Nucleic acids · 2025Review
- Trends and challenges of AAV-delivered gene editing therapeutics for CNS disorders: Implications for neurodegenerative disease.Molecular therapy. Nucleic acids · 2025Review
- Gene therapy of rare diseases as a milestone in medicine - overview of the field and report on initial experiences in Slovenia.Orphanet journal of rare diseases · 2025Review
- Microfluidic Optimization of PEI-Lipid Hybrid Nanoparticles for Efficient DNA Delivery and Transgene Expression.Pharmaceutics · 2025Article
- Development of Lentiviral Packaging Cells and Scale Up of Production to Meet the Growing Demand in Cell and Gene Therapy.Current gene therapy · 2025Review
- Review
- Design of Experiments to Tailor the Potential of BSA-Coated Peptide Nanocomplexes for Temozolomide/p53 Gene Co-Delivery.Pharmaceutics · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of gene therapy based on genome editing has opened up new possibilities for the treatment of human genetic disorders. This field has developed rapidly over the past few decades, some genome editing-based therapies are already in phase 3 clinical trials. However, there are several challenges to be addressed before widespread adoption of gene editing therapy becomes possible. The main obstacles in the development of such therapy are safety and efficiency, so one of the biggest issues is the delivery of genetic constructs to patient cells. Approaches in genetic cargo delivery divide into ex vivo and in vivo, which are suitable for different cases. The ex vivo approach is mainly used to edit blood cells, improve cancer therapy, and treat infectious diseases. To edit cells in organs researches choose in vivo approach. For each approach, there is a fairly large set of methods, but, unfortunately, these methods are not universal in their effectiveness and safety. The focus of this article is to discuss the current status of in vivo and ex vivo delivery methods used in genome editing-based therapy. We will discuss the main methods employed in these approaches and their applications in current gene editing treatments under development.
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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.