Evidence map›Paper›PMID 31429126›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2019

Using Large Datasets to Understand Nanotechnology.

Kalina Paunovska, David Loughrey, Cory D Sago, Robert Langer, James E Dahlman

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Adaptation of mesenchymal stromal cells to culture on collagen-based bioscaffold.Journal of materials science. Materials in medicine · 2026
    Article
  3. Review
  4. Article
  5. Pooled Nanoparticle Screening Using a Chemical Barcoding Approach.Angewandte Chemie (International ed. in English) · 2025
    Article
  6. Review
  7. Review
  8. Self-Reporting Therapeutic Protein Nanoparticles.ACS applied materials & interfaces · 2024
    Article
  9. Review
  10. Nucleic acid-based drugs for patients with solid tumours.Nature reviews. Clinical oncology · 2024
    Review
  11. Review
  12. High-throughput screens identify a lipid nanoparticle that preferentially delivers mRNA to human tumors in vivo.Journal of controlled release : official journal of the Controlled Release Society · 2023
    Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Drug delivery systems for RNA therapeutics.Nature reviews. Genetics · 2022
    Review
  18. Review
  19. Review
  20. 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.

Kalina PaunovskaWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory School of Medicine, Atlanta, GA, 30332, USA.
David LoughreyWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory School of Medicine, Atlanta, GA, 30332, USA.
Cory D SagoWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory School of Medicine, Atlanta, GA, 30332, USA.
Robert LangerDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
James E DahlmanWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory School of Medicine, Atlanta, GA, 30332, USA.ORCID https://orcid.org/0000-0001-7580-436X

Funding

Research Training Program Plan on Cell and Tissue Engineering (CTEng)T32GM008433 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI GARCIA, ANDRES J · 1991 to 2021
$7.1M
T32 Research Training Program in ImmunoEngineeringT32EB021962 · NIBIB · GEORGIA INSTITUTE OF TECHNOLOGY · PI JULIA E BABENSEE · 2017 to 2026
$1.9M
Bayer Hemophilia Awards Program (AGE DTD)Cystic Fibrosis Research Foundation DAHLMA15XX0Georgia TechNIBIB NIH HHS T32 EB021962NIGMS NIH HHS T32 GM008433NIH/NIGMS-sponsored T32EB021962NIH/NIGMS-sponsored T32GM008433Parkinson's Disease Foundation PDF-JFA-1860
6 · The paper itself

Abstract

Advances in sequencing technologies have made studying biological processes with genomics, transcriptomics, and proteomics commonplace. As a result, this suite of increasingly integrated techniques is well positioned to study drug delivery, a process that is influenced by many biomolecules working in concert. Omics-based approaches can be used to study the vast nanomaterial chemical space as well as the biological factors that affect the safety, toxicity, and efficacy of nanotechnologies. The generation and analysis of large datasets, methods to interpret them, and dataset applications to nanomaterials to date, are demonstrated here. Finally, new approaches for how sequencing-generated datasets can answer fundamental questions in nanotechnology based drug delivery are proposed.

Indexed as

Databases, FactualAnimalsDrug Delivery SystemsHigh-Throughput Nucleotide SequencingHumansNanotechnologybig datadrug deliverynanotechnologynext-generation sequencing

Identifiers

PMID31429126
PMCPMC6810779

What OpenQuestion holds

Textmetadata
LicenceTDM
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.