Evidence map›Paper›PMID 40820463›Full record

ArticleCurrent pharmaceutical design2026

Formulation and

Faiza Naureen, Yasar Shah, Maqsood Ur Rehman, Reem M Alnemari

Abstract read
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In one paragraph

Article in Current pharmaceutical design, 2026. 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

4 authors.

Faiza NaureenDepartment of Pharmacy, Abdul Wali Khan University Mardan, Mardan, Khyber-Pakhtunkhwa, Pakistan.
Yasar ShahDepartment of Pharmacy, Abdul Wali Khan University Mardan, Mardan, Khyber-Pakhtunkhwa, Pakistan.
Maqsood Ur RehmanDepartment of Pharmacy, University of Malakand, Chakdara, Pakistan.
Reem M AlnemariDepartment of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif University, P.O Box 11099, Taif, Saudi Arabia.

Funding

Taif University, Saudi Arabia TU-DSPP-2025-10
6 · The paper itself

Abstract

introductionCrizotinib, an inhibitor of the epidermal growth factor receptor (EGFR) tyrosine kinase, holds significant potential for the treatment of lung cancer. However, its toxicities present a major challenge to its clinical use. To enhance the targeted delivery of Crizotinib to lung tumors, polymeric-based nanoparticles were developed.

methodsCrizotinib-loaded polymeric nanoparticles were prepared using a nano-precipitation method, incorporating stearic acid as the lipid, polyethylene glycol as the polymer, and Tween 80 as the surfactant. Key formulation parameters were optimized to achieve high-quality nanoparticles.

resultsThe optimized formulation exhibited a mean particle size of 142 nm, a zeta potential of -31.9 mV, an entrapment efficiency of 82.35%, and an DISCUSSION: crizotinib nano-formulations were assessed for a variety of physicochemical and in vitro characterization. Five different formulations were designed and optimized on the basis of Particle size, Zeta potential, %EE, and

conclusionThis nanotechnology approach offers a promising targeted drug delivery system for Crizotinib, characterized by small particle size, high encapsulation efficiency (EE), and optimal in vitro drug release.

Indexed as

Antineoplastic AgentsCarcinoma, Non-Small-Cell LungCrizotinibLung NeoplasmsNanoparticlesPolymersProtein Kinase InhibitorsPyrazolesPyridinesApoptosisCell Line, TumorCell ProliferationCell SurvivalDrug Delivery SystemsDrug LiberationDrug Screening Assays, AntitumorAntineoplastic AgentsCrizotinibPolymersProtein Kinase InhibitorsPyrazolesPyridinesCrizotinibin vitro drug releaselung cancerpolymeric nanoparticlessmall cell lung carcinoma (NSCLC)targeted drug delivery

Identifiers

PMID40820463

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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.