Evidence map›Paper›PMID 26809005›Full record

ReviewJournal of controlled release : official journal of the Controlled Release Society2016

Engineering nanolayered particles for modular drug delivery.

Santiago Correa, Erik C Dreaden, Li Gu, Paula T Hammond

Abstract readReview
In one paragraph

Review in Journal of controlled release : official journal of the Controlled Release Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Designing the Next Generation of Biomaterials through Nanoengineering.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  5. Article
  6. Review
  7. Article
  8. Charge-Stabilized Nanodiscs as a New Class of Lipid Nanoparticles.Advanced materials (Deerfield Beach, Fla.) · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. A predictive microfluidic model of human glioblastoma to assess trafficking of blood-brain barrier-penetrant nanoparticles.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
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

4 authors.

Santiago CorreaKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Erik C DreadenKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Li GuKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Paula T HammondKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States; Institute for Soldier Nanotechnologies, Massachusetts Institute of Technology, Cambridge, MA 02139, United States. Electronic address: hammond@mit.edu.

Funding

Stochastic gene expression in differentiation and developmentDP1CA174420 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI VAN OUDENAARDEN, ALEXANDER · 2012 to 2012
$832k
LbL Nanotechnologies for Synergistic Therapy of Advanced Ovarian CarcinomaF32EB017614 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI DREADEN, ERIK CHRISTOPHER · 2013 to 2014
$102k
NCI NIH HHS DP1 CA174420NIBIB NIH HHS F32 EB017614
6 · The paper itself

Abstract

Layer-by-layer (LbL) based self-assembly of nanoparticles is an emerging and powerful method to develop multifunctional and tissue responsive nanomedicines for a broad range of diseases. This unique assembly technique is able to confer a high degree of modularity, versatility, and compositional heterogeneity to nanoparticles via the sequential deposition of alternately charged polyelectrolytes onto a colloidal template. LbL assembly can provide added functionality by directly incorporating a range of functional materials within the multilayers including nucleic acids, synthetic polymers, polypeptides, polysaccharides, and functional proteins. These materials can be used to generate hierarchically complex, heterogeneous thin films on an extensive range of both traditional and novel nanoscale colloidal templates, providing the opportunity to engineer highly precise systems capable of performing the numerous tasks required for systemic drug delivery. In this review, we will discuss the recent advancements towards the development of LbL nanoparticles for drug delivery and diagnostic applications, with a special emphasis on the incorporation of biostability, active targeting, desirable drug release kinetics, and combination therapies into LbL nanomaterials. In addition to these topics, we will touch upon the next steps for the translation of these systems towards the clinic.

Indexed as

AnimalsDrug CarriersGene Transfer TechniquesHumansNanoparticlesParticle SizePharmaceutical PreparationsSurface PropertiesTechnology, PharmaceuticalTheranostic NanomedicineDrug CarriersPharmaceutical PreparationsActive targetingBiomaterialsClinical translationColloid chemistryCombination therapyControlled releaseDiagnosticsDrug deliveryGene deliveryLayer-by-layerNanoparticlesPolymer engineeringScalable synthesisShelf lifeTheranostics

Identifiers

PMID26809005
PMCPMC6450096

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.