Evidence map›Paper›PMID 41234295›Full record

ReviewBioactive materials2026

Next-generation smart ophthalmic biomaterials: From passive response to active interaction and closed-loop control.

Pengbo Zhang, Yan Nie, Xiaofang Wang, Xibo Zhang, Longqian Liu

Abstract readReview
In one paragraph

Review in Bioactive materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. 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

5 authors.

Pengbo ZhangDepartment of Ophthalmology, West China Hospital, Sichuan University, Chengdu, China.
Yan NieDepartment of Ophthalmology, West China Hospital, Sichuan University, Chengdu, China.
Xiaofang WangState Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Xibo ZhangDepartment of Ophthalmology, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, Sichuan, China.
Longqian LiuDepartment of Ophthalmology, West China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ophthalmic biomaterials are undergoing a rapid transition from inert implants to intelligent, adaptive systems that respond to the spatiotemporal complexity of ocular disease. Conventional materials provide structural support and baseline biocompatibility but rarely adapt to the evolving ocular microenvironment shaped by biochemical and biomechanical cues. Recent advances have delivered stimuli-responsive platforms that release therapeutics or modulate mechanics in response to stimuli such as pH, temperature, enzymatic activity, or mechanical strain. Yet most current strategies remain reactive or preprogrammed, lacking closed-loop, autonomous control. Here we present an evolutionary framework for ophthalmic biomaterials, tracing the shift from passive structures to interactive and emerging closed-loop systems that integrate sensing, on-board decision-making, and actuation. We synthesize advances across the first three generations, delineate core design principles, functional transitions, and clinical implementations, and highlight systems-level integration challenges. Finally, we identify critical opportunities and design principles for intelligent, self-adaptive platforms, providing a conceptual basis for the rational design of next-generation, closed-loop ocular therapies.

Identifiers

PMID41234295
PMCPMC12607147

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.