Evidence map›Paper›PMID 31146485›Full record

ArticleCancers2019

In Vivo Evaluation of Dual-Targeted Nanoparticles Encapsulating Paclitaxel and Everolimus.

Loujin Houdaihed, James Christopher Evans, Christine Allen

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 33% of its field
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

9 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Article
  3. Development of constitutively synergistic nanoformulations to enhance chemosensitivity in T-cell leukemia.Journal of controlled release : official journal of the Controlled Release Society · 2023
    Article
  4. Review
  5. Article
  6. Review
  7. Cancer Nanomedicine.Cancers · 2020
    Article
  8. Synergistic drug combinations for a precision medicine approach to interstitial glioblastoma therapy.Journal of controlled release : official journal of the Controlled Release Society · 2020
    Article
  9. 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

3 authors at 1 institution in 1 country.

Loujin HoudaihedLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2, Canada. loujin.houdaihed@mail.utoronto.ca.
James Christopher EvansLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2, Canada. james.evans@utoronto.ca.
Christine AllenLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2, Canada. cj.allen@utoronto.ca.
University of Toronto · CA

Funding

Canadian Institutes of Health Research Doctoral Research AwardCanadian Institutes of Health Research MOP325013Centre for Pharmaceutical Research CPO Award
6 · The paper itself

Abstract

A synergistic combination of paclitaxel (PTX) and everolimus (EVER) can allow for lower drug doses, reducing the toxicities associated with PTX, while maintaining therapeutic efficacy. Polymeric nanoparticles (NPs) of high stability provide opportunities to modify the toxicity profile of the drugs by ensuring their delivery to tumor at the synergistic ratio while limiting systemic drug exposure and the toxicities that result. The current study goal is to study the in vivo fate of human epidermal factor receptor 2 (HER2) and epidermal growth factor receptor (EGFR) dual-targeted PTX+EVER-loaded NPs (Dual-NPs) in an MDA-MB-231-H2N BC tumor-bearing mouse model. The pharmacokinetic parameters, plasma area under the curve (AUC) and half-life (t

Indexed as

breast cancerdrug combinationdual-targetingeverolimusnanoparticlespaclitaxel

Identifiers

PMID31146485
PMCPMC6628352
OpenAlexW2947563175

What OpenQuestion 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 OpenQuestion graph.