Evidence map›Paper›PMID 37458973›Full record

ArticleDrug delivery and translational research2023

Quality by design (QbD) approach to develop fast-dissolving tablets using melt-dispersion paired with surface-adsorption method: formulation and pharmacokinetics of flurbiprofen melt-dispersion granules.

Sateesh Kumar Vemula, Bhaskar Daravath, Michael Repka

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Article in Drug delivery and translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

3 authors.

Sateesh Kumar VemulaDepartment of Pharmaceutics and Drug Delivery, School of Pharmacy, The University of Mississippi, University, MS, 38677, USA. svemula@olemiss.edu.
Bhaskar DaravathDepartment of Pharmaceutics, GITAM School of Pharmacy, GITAM Deemed to Be University, Rudraram, Patancheru, Sangareddy, Hyderabad, Telangana, India.
Michael RepkaDepartment of Pharmaceutics and Drug Delivery, School of Pharmacy, The University of Mississippi, University, MS, 38677, USA. marepka@olemiss.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing amorphous solid dispersions with good flow properties is always challenging for formulation scientists to convert into tablets. Hence, the present study investigates the impact of the combination of melt-dispersion and surface-adsorption methods to prepare melt-dispersion granules with enhanced dissolution rate and flow properties. This study covers the formulation and pharmacokinetic study of fast-dissolving flurbiprofen tablets using PEG 6000 (hydrophilic carrier) and lactose (adsorbent). Response surface methodology (RSM) using the central composite design (CCD) was used to optimize independent variables like carrier concentrations and adsorbent concentrations, and their interactions with the dependent variables (responses), including solubility, angle of repose, Carr's index, and cumulative % drug release, were investigated. The optimized formulation was selected based on the numerical optimization method and further investigated for FTIR spectroscopy, differential scanning calorimetry, and X-ray diffractometry. Then, the optimized formulation was compressed into tablets and evaluated for both in vitro dissolution and in vivo pharmacokinetics parameters. In vitro dissolution studies revealed that the prepared fast-dissolving tablets released the drug entirely within 15 min (Q

Indexed as

FlurbiprofenAdsorptionAnimalsCalorimetry, Differential ScanningChemistry, PharmaceuticalDrug LiberationRatsSolubilityTabletsFlurbiprofenTabletsDissolution rateFlow propertiesMelt-dispersionResponse surface methodologySurface adsorption

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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.