Precision Lipid Management in the Era of Biotechnology and Artificial Intelligence: From Gene Editing to Smart Drug...

Hyperlipidemia is a major modifiable contributor to atherosclerotic cardiovascular disease (ASCVD). Despite statins as first-line therapy, residual cardiovascular risk, treatment intolerance, and genetic dyslipidemias highlight the need for innovative strategies.

This narrative review critically evaluates emerging biotechnology- and artificial intelligence (AI)-enhanced approaches for hyperlipidemia, emphasizing translational maturity, clinical applicability, and regulatory implications.

A structured literature search of PubMed/MEDLINE, Scopus, and Web of Science Core Collection was conducted to identify relevant evidence published primarily between January 2015 and February 2025. The review methodology, including the approximate literature search yield, is described in the Methods section. Evidence was synthesized across three developmental tiers: preclinical and early clinical gene-editing strategies; clinically established or late-stage therapies, including PCSK9 monoclonal antibodies and inclisiran; and early translational or conceptual platforms involving nanotechnology, microbiome modulation, and AI-assisted treatment optimization.

PCSK9 monoclonal antibodies provide substantial LDL-C reduction and established cardiovascular outcome benefits, whereas inclisiran offers durable LDL-C lowering with infrequent dosing, although definitive cardiovascular outcomes evidence remains pending. CRISPR-based approaches may enable durable lipid regulation but remain constrained by delivery efficiency, off-target effects, immunogenicity, and long-term safety concerns. Nanoparticle-based delivery, microbiome-targeted interventions, and AI-driven prediction and treatment optimization are promising, but clinical translation is limited by biological variability, standardization challenges, insufficient external validation, algorithmic bias, data-governance concerns, and workflow integration barriers.

Biotechnology and AI are reshaping precision lipid management. Successful translation will require long-term safety and outcomes validation, reproducible delivery platforms, cost-effectiveness, equitable implementation, and adaptive regulatory frameworks.