Evidence map›Paper›PMID 41584419›Full record

ArticleCurrent health sciences journal

Fast HPLC Analysis of Three Antitumor Drugs in Pharmaceutical Dosages.

Monica Denisa Elena Popescu, Costel-Valentin Manda, Johny Neamțu, Andrei Biță, Adela Valeria Neamțu, Simona-Daniela Neamțu, Octavian Croitoru, Daniela Maria Calucică

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

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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

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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

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Monica Denisa Elena PopescuFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.
Costel-Valentin MandaFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.
Johny NeamțuFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.
Andrei BițăFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.
Adela Valeria NeamțuFaculty of Medicine, University of Medicine and Pharmacy of Craiova, Romania.
Simona-Daniela NeamțuFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.
Octavian CroitoruFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.
Daniela Maria CalucicăFaculty of Pharmacy, University of Medicine and Pharmacy of Craiova, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epirubicin, olaparib and ribociclib are three important anti-cancer agents representing distinct classes: an anthracycline (epirubicin), a PARP inhibitor (olaparib) and a CDK4/6 inhibitor (ribociclib). Analytical quantification of these drugs in biological fluids or in dosage forms often uses high-performance or ultra-performance liquid chromatography (HPLC or RP-HPLC), often coupled with ultraviolet (UV) or photo-diode-array detection (PDA), occasionally with mass spectrometric detection (MS). Within this paper, a rapid HPLC method with PDA detection for simultaneous quantitation of these analytes in pharmaceutical dosage forms is presented. The separation was carried out on a Vanquish Core (Thermo Scientific, USA) liquid chromatograph coupled with a PDA detector. Solid Phase Extraction (SPE) using Oasis PRiME HLB® cartridges was employed as sample preparation procedure. Chromatography was performed by using an unconventional porous graphitic carbon column (HypercarbTM); a gradient elution was carried out using a mixture of acetonitrile/tetrahydrofuran. The flow rate of the mobile phase and the injected volume were 1mL/min and 20μL, respectively. The column compartment temperature was set to 60°C. Each chromatographic peak was integrated at its maximum absorption wavelength. Quantification was performed with external standard method. All validation data were assessed according to European Medicines Agency (EMA) Guidelines, regarding stability, limit of detection/quantitation, precision, accuracy and linearity. The presented method was applied in pharmaceutical dosage forms analysis.

Indexed as

Epirubicinolaparibphoto-diode-array detectionporous graphitic carbon columnribociclib

Identifiers

PMID41584419
PMCPMC12831551

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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.