Evidence map›Paper›PMID 42599575›Full record

ReviewTherapeutic innovation & regulatory science2026

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

Esra Palabiyik

Abstract readReview
PubMed Publisher
In one paragraph

Review in Therapeutic innovation & regulatory science, 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

1 author.

Esra PalabiyikDepartment of Molecular Biology and Genetics, Ağrı İbrahim Çeçen University, Ağrı, Turkey. epalabiyik@agri.edu.tr.ORCID http://orcid.org/0000-0002-3066-1921

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperlipidemia 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.

objectiveThis narrative review critically evaluates emerging biotechnology- and artificial intelligence (AI)-enhanced approaches for hyperlipidemia, emphasizing translational maturity, clinical applicability, and regulatory implications. METHODS AND SCOPE: 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. RESULTS AND IMPLICATIONS: 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.

conclusionBiotechnology 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.

Indexed as

Artificial intelligenceCRISPR-Cas9Gene therapyGut microbiomeHyperlipidemiaNanoparticlesPCSK9 inhibitors

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.