Evidence map›Paper›PMID 26225236›Full record

ArticleCPT: pharmacometrics & systems pharmacology2015

Physiologically Based Pharmacokinetic Modeling of Fluorescently Labeled Block Copolymer Nanoparticles for Controlled Drug Delivery in Leukemia Therapy.

M J Gilkey, V Krishnan, L Scheetz, X Jia, A K Rajasekaran, P S Dhurjati

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  9. Imaging-based characterization of convective tissue properties.International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group · 2020
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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.

M J GilkeyDepartment of Chemical and Biomolecular Engineering, University of Delaware Newark, Delaware, USA.
V KrishnanDepartment of Materials Science and Engineering, University of Delaware Newark, Delaware, USA ; Nemours Biomedical Research, A I DuPont Hospital for Children Wilmington, Delaware, USA.
L ScheetzDepartment of Biomedical Engineering, University of Delaware Newark, Delaware, USA.
X JiaDepartment of Materials Science and Engineering, University of Delaware Newark, Delaware, USA ; Department of Biomedical Engineering, University of Delaware Newark, Delaware, USA ; Department of Biological Sciences, Center for Translational Cancer Research, University of Delaware Newark, Delaware, USA.
A K RajasekaranDepartment of Materials Science and Engineering, University of Delaware Newark, Delaware, USA ; Department of Biological Sciences, Center for Translational Cancer Research, University of Delaware Newark, Delaware, USA ; Lankenau Institute for Medical Research Wynnewood, Pennsylvania, USA.
P S DhurjatiDepartment of Chemical and Biomolecular Engineering, University of Delaware Newark, Delaware, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A physiologically based pharmacokinetic (PBPK) model was developed that describes the concentration and biodistribution of fluorescently labeled nanoparticles in mice used for the controlled delivery of dexamethasone in acute lymphoblastic leukemia (ALL) therapy. The simulated data showed initial spikes in nanoparticle concentration in the liver, spleen, and kidneys, whereas concentration in plasma decreased rapidly. These simulation results were consistent with previously published in vivo data. At shorter time scales, the simulated data predicted decrease of nanoparticles from plasma with concomitant increase in the liver, spleen, and kidneys before decaying at longer timepoints. Interestingly, the simulated data predicted an unaccounted accumulation of about 50% of the injected dose of nanoparticles. Incorporation of an additional compartment into the model justified the presence of unaccounted nanoparticles in this compartment. Our results suggest that the proposed PBPK model can be an excellent tool for prediction of optimal dose of nanoparticle-encapsulated drugs for cancer treatment.

Identifiers

PMID26225236
PMCPMC4394613

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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.