Evidence map›Paper›PMID 35909883›Full record

ArticleFrontiers in medical technology2022

Multiphysics pharmacokinetic model for targeted nanoparticles.

Emma M Glass, Sahil Kulkarni, Christina Eng, Shurui Feng, Avishi Malaviya, Ravi Radhakrishnan

Abstract read
In one paragraph

Article in Frontiers in medical technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Mathematical complexities in radionuclide metabolic modelling: a review of ordinary differential equation kinetics solvers in biokinetic modelling.Journal of radiological protection : official journal of the Society for Radiological Protection · 2024
    Review
  5. Article
  6. 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

6 authors.

Emma M GlassDepartment of Computational Applied Mathematics and Statistics, College of William and Mary, Williamsburg, VA, United States.
Sahil KulkarniDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, United States.
Christina EngDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, United States.
Shurui FengDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States.
Avishi MalaviyaDepartment of Bioengineering, Carnegie Mellon University, Pittsburgh, PA, United States.
Ravi RadhakrishnanDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, United States.

Funding

A physical sciences approach to investigate the role of exosomes in metastatic progressionU01CA250044 · NCI · UNIVERSITY OF PENNSYLVANIA · PI GUO, WEI, RADHAKRISHNAN, RAVI · 2021 to 2025
$3.9M
NCI NIH HHS U01 CA250044
6 · The paper itself

Abstract

Nanoparticles (NP) are being increasingly explored as vehicles for targeted drug delivery because they can overcome free therapeutic limitations by drug encapsulation, thereby increasing solubility and transport across cell membranes. However, a translational gap exists from animal to human studies resulting in only several NP having FDA approval. Because of this, researchers have begun to turn toward physiologically based pharmacokinetic (PBPK) models to guide

Indexed as

biodistributionneural networkphysiologically based pharmacokineticquasi steady-state approximationvascular branching

Identifiers

PMID35909883
PMCPMC9335923

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.