Evidence map›Paper›PMID 41516809›Full record

ReviewPolymers2025

Four-Dimensional Printing of Shape Memory Polymers for Biomedical Applications: Advances in DLP and SLA Manufacturing.

Raj Kumar Pittala, Marc Anthony Torres, Neha Reddy, Sara Swank, Melanie Ecker

Abstract readReview
In one paragraph

Review in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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.

Raj Kumar PittalaDepartment of Biomedical Engineering, University of North Texas, Denton, TX 76203, USA.ORCID 0009-0005-2916-1718
Marc Anthony TorresDepartment of Biomedical Engineering, University of North Texas, Denton, TX 76203, USA.ORCID 0009-0006-1162-4128
Neha ReddyTexas Academy of Mathematics and Science, University of North Texas, Denton, TX 76203, USA.
Sara SwankDepartment of Biomedical Engineering, University of North Texas, Denton, TX 76203, USA.ORCID 0009-0008-2392-7059
Melanie EckerDepartment of Biomedical Engineering, University of North Texas, Denton, TX 76203, USA.ORCID 0000-0002-0603-6683

Funding

U.S. National Science Foundation 2237510
6 · The paper itself

Abstract

Shape memory polymers (SMPs) represent an innovative class of materials that possess programmed, reversible shape-changing capabilities in response to external stimuli. The recent emergence of SMPs' advanced manufacturing, specifically 4D printing, has created exceptional opportunities for use in biomedical engineering. This review presents a critical synthesis of the latest advances in the chemistry, biomedical applications, manufacturing strategies, and clinical translation of SMPs, highlighting vat photopolymerization techniques, such as stereolithography (SLA) and digital light processing (DLP). Notably, 4D-printed SMPs can promote spatiotemporally controlled architectures, and applications include minimally invasive implants, dynamic tissue scaffolds, and multifunctional drug delivery. This paper focuses on recent advances in resin design, multi-responsive and nanocomposite resins, AI-guided material discovery, and emerging biocompatible and biodegradable formulations, while outlining current roadblocks to clinical implementation, including cytotoxicity, sterilization, regulatory compliance, and device shelf-life. Our goal is to elucidate the relationship between material design, processing, and biomedical performance to inform researchers of potential future directions for 4D-printed SMPs and next-generation, patient-centered medical devices.

Indexed as

4D-printingbiomedical applicationsDLPshape memory polymers (SMPs)SLAsmart materials

Identifiers

PMID41516809
PMCPMC12787484

What OpenQuestion holds

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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.