Evidence map›Paper›PMID 40237176›Full record

ArticleBiomaterials science2025

Supervised machine learning for predicting drug release from acetalated dextran nanofibers.

Ryan N Woodring, Elizabeth G Gurysh, Tanvi Pulipaka, Kevin E Shilling, Rebeca T Stiepel, Erik S Pena, Eric M Bachelder, Kristy M Ainslie

Abstract read
In one paragraph

Article in Biomaterials science, 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. Review
  2. Review
  3. Article
  4. Review
  5. Biodegradable nanofibrous scaffolds enhance standard of care for glioblastoma via localized targeted therapy.Journal of controlled release : official journal of the Controlled Release Society · 2025
    Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Modeling Polymeric Drug Release: The Emerging Role of Machine Learning.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
    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

8 authors.

Ryan N WoodringDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.ORCID http://orcid.org/0000-0002-7818-8387
Elizabeth G GuryshDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.ORCID http://orcid.org/0000-0002-2130-5706
Tanvi PulipakaDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.
Kevin E ShillingDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.
Rebeca T StiepelDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.ORCID http://orcid.org/0000-0001-6943-8818
Erik S PenaJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, USA.ORCID http://orcid.org/0000-0002-9204-5155
Eric M BachelderDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.ORCID http://orcid.org/0000-0002-8572-888X
Kristy M AinslieDivision of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at, Chapel Hill, USA. ainsliek@email.unc.edu.ORCID http://orcid.org/0000-0002-1820-8382

Funding

Tunable Temporal Drug Release for Optimized Synergistic Combination Therapy of GlioblastomaR01CA257009 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI AINSLIE, KRISTY M · 2021 to 2025
$1.7M
NCI NIH HHS R01 CA257009
6 · The paper itself

Abstract

Electrospun drug-loaded polymeric nanofibers can improve the efficacy of therapeutics for a variety of implications. By design, these biomaterial platforms can enhance drug bioavailability and site-specific delivery while reducing off-target toxicities when compared to other conventional formulations. By incorporating biocompatible and biodegradable polymers with tunable degradation rates, such as acetalated dextran (Ace-DEX), drug-loaded nanofibers can enhance the safety and efficacy of treatment regimens while improving patient compliance through controlled release. Despite these benefits, clinical translation of electrospun formulations is challenged by labor-intensive

Indexed as

DextransDrug CarriersNanofibersSupervised Machine LearningDrug LiberationMachine LearningDextransDrug Carriers

Identifiers

PMID40237176
PMCPMC12553120

What OpenQuestion holds

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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.