Artificial intelligence-driven epigenetic CRISPR therapeutics: a structured multi-domain meta-analysis of therapeutic efficacy, off-target prediction, and gRNA optimization.

CRISPR-based epigenetic editing enables reversible regulation of gene expression without permanent DNA modification. The integration of artificial intelligence (AI) enhances guide RNA (gRNA) design, off-target prediction, and delivery optimization. We conducted a systematic review and meta-analysis (2015-2025) in accordance with PRISMA 2020 guidelines to evaluate the impact of AI on the precision, safety, and therapeutic efficacy of epigenetic CRISPR tools. From 540 screened records, 58 studies met inclusion criteria, of which 41 provided extractable quantitative data for meta-analysis and 17 contributed to qualitative synthesis. Random-effects models, subgroup analyses, and bias assessments were applied. Pooled analyses demonstrated strong positive effects across three domains: therapeutic efficacy (SMD = 1.67), gRNA optimization (SMD = 1.44), and off-target prediction (AUC = 0.79). Publication bias was minimal, and subgroup analyses indicated the strongest impact in therapeutic applications. Deep learning models were consistently associated with higher effect sizes. Qualitative synthesis revealed trends in interpretable AI, omics integration, and delivery innovations, underscoring AI's role in safer and more precise CRISPR editing. Overall, AI significantly improves the precision and therapeutic performance of CRISPR-based epigenetic tools, with the strongest effects observed in therapeutic efficacy, supporting their potential for personalized gene editing.