Evidence map›Paper›PMID 41362451›Full record

ReviewMaterials today. Bio2025

Engineered cellular drug delivery: Strategies and applications.

Juan Lu, Wuxinrui Huang, Beikang Tang, Pu Yang, Jing Tian, Lanjie Lei

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Materials today. Bio, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Juan LuDepartment of Rheumatology and Immunology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Wuxinrui HuangDepartment of Rheumatology and Immunology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Beikang TangDepartment of Rheumatology and Immunology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Pu YangDepartment of Rheumatology and Immunology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Jing TianDepartment of Rheumatology and Immunology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Lanjie LeiKey Laboratory of Artificial Organs and Computational Medicine in Zhejiang Province, Institute of Translational Medicine, Zhejiang Shuren University, Hangzhou, 310015, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-based drug delivery systems (CDDS) offer advantages like biocompatibility and tissue homing. However, it faces challenges owing to the complex physiological environment in the body during drug transport, such as the inhibitory immune microenvironment of tumors and the highly selective blood-brain barrier. Additionally, CDDS has limitations, including poor targeting and uncontrolled drug release. Engineered cellular drug delivery systems (ECDDS) have emerged to overcome these hurdles, providing enhanced target specificity, improved barrier crossing, and precise drug release mechanisms. Customizable through chemical and bioengineering strategies, ECDDS represent a versatile platform for precision medicine. While numerous reviews exist on living cell delivery systems, a focused analysis of ECDDS remains limited. This review bridges that gap by offering a comprehensive analysis of contemporary engineering methods and design approaches for ECDDS. We further examine the

Indexed as

BiomaterialsBiomedical applicationsCell membraneDelivery systemsTargeted therapy

Identifiers

PMID41362451
PMCPMC12681844

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.