Evidence map›Paper›PMID 42797159›Full record

ReviewPolymers2026

Shape Memory Polymers as Functional Platforms for Dynamic Tissue Engineering and Regenerative Medical Devices.

Kyubae Lee

Abstract readReview
In one paragraph

Review in Polymers, 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.

Kyubae LeeDepartment of Biomedical Engineering, Gachon University, Seongnam 13120, Republic of Korea.ORCID 0000-0002-1270-8554

Funding

Ministry of Education RS-2023-00247626Ministry of Science and ICT RS-2026-25471006National Research Foundation of Korea RS-2026-25471006
6 · The paper itself

Abstract

Shape memory polymers (SMPs) have emerged as a distinctive class of functional polymers for tissue engineering and regenerative medical devices because they couple programmable shape transformation with the biological, mechanical, and degradation requirements of regenerating tissue. Unlike conventional static scaffolds, SMP-based constructs can be delivered in compact temporary configurations, deployed under clinically relevant stimuli, and recovered into porous, anatomically conformal architectures that mechanically and biologically engage with host tissue. This review provides an engineering-oriented perspective on SMPs as functional polymers, emphasizing how shape recovery alone is insufficient and how regenerative performance emerges from coupled control of polymer chemistry, transition behavior, recovery force, fixity, degradation kinetics, and cytocompatibility. Material platforms ranging from biodegradable polyesters and polyurethanes to hydrogels, natural-polymer composites, and dynamic covalent networks are compared in terms of their ability to support tissue-specific functions including minimally invasive deployment, self-fitting, mechanical conditioning, and staged remodeling. The review further discusses 4D-printed patient-specific architectures and translational barriers, including sterilization, packaging, fatigue, manufacturing reproducibility, and regulatory validation. Together, these perspectives reframe SMPs from shape-recovery materials into integrated regenerative engineering platforms guiding the next generation of dynamic polymeric biomaterials.

Indexed as

4D printingbiodegradable polymersdynamic scaffoldsfunctional polymersminimally invasive implantsregenerative medicineshape memory polymersstimuli-responsive biomaterialstissue engineering

Identifiers

PMID42797159
PMCPMC13611016

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.