Evidence map›Paper›PMID 18998202›Full record

ArticlePharmaceutical research2009

Design of biodegradable nanoparticles for oral delivery of doxorubicin: in vivo pharmacokinetics and toxicity studies in rats.

D R Kalaria, G Sharma, V Beniwal, M N V Ravi Kumar

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Article in Pharmaceutical research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
–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

50 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

D R KalariaDepartment of Pharmaceutics, National Institute of Pharmaceutical Education and Research (NIPER), S. A. S. Nagar, 160 062, Punjab, India.
G Sharma
V Beniwal
M N V Ravi Kumar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDoxorubicin, a potent anticancer drug associated with cardiotoxicity and low oral bioavailability, was loaded into nanoparticles with a view to improve its performance.

methodsDoxorubicin loaded PLGA nanoparticles were prepared by a double emulsion method. The pH dependent stability of nanoparticles in simulated fluids was evaluated. DSC and XRD studies were carried out in order to ascertain the nature of doxorubicin in formulations in conjunction with accelerated stability studies. The in vitro release was investigated in phosphate buffer. The pharmacokinetic and toxicity studies were conducted in rats.

resultsNanoparticles had an average size of 185 nm, with 49% entrapment at 10% w/w of polymer. The particles displayed good pH dependent stability in the pH range 1.1-7.4. DSC and XRD studies revealed the amorphous nature of doxorubicin in nanoparticles and the accelerated stability studies revealed the integrity of formulations. Initial biphasic release (20%) followed by a sustained release (80%) for 24 days was observed under in vitro conditions. The doxorubicin loaded nanoparticles demonstrated superior performance in vivo as evident by enhanced bioavailability and lower toxicity.

conclusionsTogether, the data indicates the potential of doxorubicin loaded nanoparticles for oral chemotherapy. Further, these formulations could be explored for new indications like leishmaniasis.

Indexed as

Drug DesignAdministration, OralAnimalsAntibiotics, AntineoplasticBiocompatible MaterialsBiological AvailabilityCalorimetry, Differential ScanningDoxorubicinDrug CarriersDrug StabilityFemaleHydrogen-Ion ConcentrationLactic AcidNanoparticlesParticle SizePolyglycolic AcidAntibiotics, AntineoplasticBiocompatible MaterialsDoxorubicinDrug CarriersLactic AcidPolyglycolic AcidPolylactic Acid-Polyglycolic Acid Copolymer

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Registered trials

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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.