Evidence map›Paper›PMID 42806247›Full record

ReviewPharmaceutical research2026

Engineering Oral Nanoparticles: Navigating Biological Barriers in the Gastrointestinal Tract.

Asly Chua An Wen, Xiancheng Chen, Wenli Zhang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Pharmaceutical 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

3 authors.

Asly Chua An WenDepartment of Pharmaceutics, China Pharmaceutical University, Jiangsu, 210009, PR China.
Xiancheng ChenDepartment of Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, No. 321 Zhongshan Road, Nanjing, Jiangsu Province, 210008, China. chenxiancheng-icu@foxmail.com.
Wenli ZhangDepartment of Pharmaceutics, China Pharmaceutical University, Jiangsu, 210009, PR China. zwllz@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral nanomedicine offers a promising strategy to enhance drug bioavailability, yet engineering strategies are most effectively evaluated not as isolated features but as sequential decision nodes, because a choice at one barrier mechanically constrains the strategy space at the next. This review presents a barrier-sequenced analytical framework that evaluates nanoparticle strategies at each stage by mechanistic causality, oral-specific evidence quality, and downstream design constraint. Within each barrier category, strategies were distinguish and validated by multiple oral in vivo studies from those supported by limited oral data or remaining at the proof-of-concept stage, and identified the physiological boundary conditions (fed versus fasted states, inflammatory disease, and chronic dosing) under which each principle holds. This review further maps how a formulation choice at one barrier mechanically constrains the strategy space at the next, revealing which multi-barrier combinations are compatible and which are antagonistic. Finally, This review assesses physiologically based pharmacokinetic modeling and machine learning against their current data prerequisites, framing them as hypothesis-generating aids with explicit infrastructure gaps rather than decision-grade design engines. By extracting generalizable design principles and their limits, this framework aims to guide mechanism-informed, patient-centered oral nanotherapies.

Indexed as

gastrointestinal barrierslymphatic targetingmucus penetrationmultifunctional nanoparticlesoral drug delivery

Identifiers

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.