Evidence map›Paper›PMID 38867526›Full record

ArticleCurrent drug delivery2025

2

Mohamed T Elsebay, Mohammad H Alyami, Hamad S Alyami, Mohammad Amjad Kamal, Noura G Eissa, Gehan F Balata, Hanan N El-Nahas

Abstract read
PubMed Publisher
In one paragraph

Article in Current drug delivery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Mohamed T ElsebayDepartment of Pharmaceutics, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt.
Mohammad H AlyamiDepartment of Pharmaceutics, College of Pharmacy, Najran University, Najran 66462, Saudi Arabia.
Hamad S AlyamiDepartment of Pharmaceutics, College of Pharmacy, Najran University, Najran 66462, Saudi Arabia.
Mohammad Amjad KamalJoint Laboratory of Artificial Intelligence in Healthcare, Institutes for Systems Genetics and West China School of Nursing, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-0088-0565
Noura G EissaDepartment of Pharmaceutics, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt.
Gehan F BalataDepartment of Pharmaceutics, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt.
Hanan N El-NahasDepartment of Pharmaceutics, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt.

Funding

Deanship of Graduate Studies and Scientific Research at Najran University NU/GP/MRC/13/112-1
6 · The paper itself

Abstract

introductionDesloratadine, a second-generation antihistaminic drug, is poorly watersoluble and requires amelioration of the dissolution rate to improve its pharmacokinetics properties.

methodThis study investigated the impact of polymer, surfactant types, and concentration on the particle size, zeta potential, and dissolution efficiency of nanosuspensions formulated through the solvent antisolvent precipitation method. To optimize the delivery of Desloratadine nanosuspension, we used Minitab software and a 4-factor, 2-level full factorial design. Physicochemical properties and drug release studies were conducted to evaluate the suggested nanosuspension formulations. The optimization goals included minimizing particle size and zeta potential while maximizing dissolution efficiencies.

resultThe selected optimal nanosuspension demonstrated favourable values, including a particle size of 478.63 ± 15.67 nm, a zeta potential of -36.24 ± 3.21 mV, and dissolution efficiencies in double distilled water and buffer of 90.29 ± 3.75 % and 93.70 ± 3.67 %, respectively. The optimized formulation was subjected to additional analysis using X-ray powder diffraction (XPRD), scanning and transmission electron microscopy (SEM and TEM), and Fourier-transform infrared spectroscopy (FTIR).

conclusionThe optimized nanosuspension formulation also underwent further studies under optimal lyophilization conditions, revealing the effectiveness of mannitol as a cryoprotectant at a concentration of 8%.

Indexed as

Histamine H1 Antagonists, Non-SedatingLoratadineNanoparticlesChemical PrecipitationChemistry, PharmaceuticalDrug CompoundingDrug LiberationParticle SizeSolubilitySolventsSurface-Active AgentsSuspensionsdesloratadineHistamine H1 Antagonists, Non-SedatingLoratadineSolventsSurface-Active AgentsSuspensionscryoprotectantdeliverydesloratadinedrug dissolutionfactorial design.Nanosuspension

Identifiers

What OpenQuestion holds

Textmetadata
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.