Evidence mapPaperPMID 40430669Full record

ReviewPolymers2025

Next-Generation Hydrogel Design: Computational Advances in Synthesis, Characterization, and Biomedical Applications.

Muhammad Mazhar Fareed, Sergey Shityakov

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Smart Hydrogels in Wearable Electronics for Wound Treatments.Small (Weinheim an der Bergstrasse, Germany) · 2025
    Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. 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

2 authors.

Muhammad Mazhar FareedDepartment of Computer Science, School of Science and Engineering, Università Degli Studi di Verona, 37134 Verona, Italy.
Sergey ShityakovLaboratory of Bioinformatics, Department of Bioinformatics, Biocenter, Würzburg University, 97080 Würzburg, Germany.ORCID 0000-0002-6953-9771

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hydrogels are pivotal in advanced materials, driving innovations in medical fields, such as targeted drug delivery, regenerative medicine, and skin repair. This systematic review explores the transformative impact of in-silico design on hydrogel development, leveraging computational tools such as molecular dynamics, finite element modeling, and artificial intelligence to optimize synthesis, characterization, and performance. We analyze cutting-edge strategies for tailoring the physicochemical properties of hydrogels, including their mechanical strength, biocompatibility, and stimulus responsiveness, to meet the needs of next-generation biomedical applications. By integrating machine learning and computational modeling with experimental validation, this review highlights how in silico approaches accelerate material innovation, addressing challenges and outlining future directions for scalable, personalized hydrogel solutions in regenerative medicine and beyond.

Indexed as

bioinformaticscomputational modelingengineered biological scaffoldshydrogelsin-silico designmachine learningmolecular dynamics simulationrestorative healthcare technologiestargeted therapeutic transport

Identifiers

PMID40430669
PMCPMC12115241

What Socratic 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 Socratic graph.