Evidence map›Paper›PMID 42213349›Full record

ReviewDrug delivery and translational research2026

Strategies for engineering biomimetic lipoproteins to improve drug delivery efficiency and tumor therapy.

Yuchen He, Naibo Yin, Zhiwen Zhang, Guo-Liang Lu, Jingyuan Wen

Abstract readReview
PubMed Publisher
In one paragraph

Review in Drug delivery and translational research, 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

5 authors.

Yuchen HeSchool of Pharmacy, Faculty of Medical and Health Sciences, the University of Auckland, Auckland, 1023, New Zealand.
Naibo YinSchool of Pharmacy, Faculty of Medical and Health Sciences, the University of Auckland, Auckland, 1023, New Zealand.
Zhiwen ZhangSchool of Pharmacy, Fudan University, Shanghai, China. zhangzhiwen@fudan.edu.cn.
Guo-Liang LuAuckland Cancer Society Research Centre, Faculty of Medical and Health Sciences, the University of Auckland, Auckland, 1023, New Zealand. gl.lu@auckland.ac.nz.
Jingyuan WenSchool of Pharmacy, Faculty of Medical and Health Sciences, the University of Auckland, Auckland, 1023, New Zealand. j.wen@auckland.ac.nz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer treatment remains limited by key challenges, including poor drug biodistribution, restricted tumor penetration, and severe systemic toxicity. Lipoprotein nanoparticles (LPNs) have emerged as promising platforms for drug delivery, addressing these obstacles. Their inherent biocompatibility, small size, and natural ability to interact with specific cellular receptors make them ideal candidates for targeted cancer therapy. This review presents recent advances in the design of LPNs to improve the precision and efficiency of anti-tumor drug delivery. We investigate how these smart nanoparticles enhance the therapeutic performance of three primary treatment modalities: chemotherapy, immunotherapy, and emerging nucleic acid-based therapies. This comprehensive review summarizes current strategies in the field and offers forward-looking insights into future innovations in LPN drug delivery systems (DDSs) for cancer therapy.

Indexed as

Cancer treatmentChemotherapyDrug deliveryImmunotherapyLipoproteinNucleic acids drugs

Identifiers

PMID42213349

What OpenQuestion 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 OpenQuestion graph.