Evidence map›Paper›PMID 29080007›Full record

ArticleLasers in medical science2018

Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

P K Tiwari, S Awasthi, R Kumar, R K Anand, P K Rai, A K Rai

Abstract read
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Article in Lasers in medical science, 2018. 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.

  1. Article
  2. Compositional analysis of copper and iron-based alloys using LIBS coupled with chemometric method.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2024
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

P K TiwariLaser Spectroscopy Research Laboratory, Department of Physics, University of Allahabad, Allahabad, 211002, India.
S AwasthiLaser Spectroscopy Research Laboratory, Department of Physics, University of Allahabad, Allahabad, 211002, India.
R KumarLaser Spectroscopy Research Laboratory, Department of Physics, University of Allahabad, Allahabad, 211002, India.
R K AnandLaser Spectroscopy Research Laboratory, Department of Physics, University of Allahabad, Allahabad, 211002, India.
P K RaiDepartment of Nephrology, N. 10/60-2, Opal Hospital, DLW Road, Kakarmatta, Varanasi, 221004, India.
A K RaiLaser Spectroscopy Research Laboratory, Department of Physics, University of Allahabad, Allahabad, 211002, India. awadheshkrai@rediffmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.

Indexed as

LasersAirAlgorithmsArgonInositolLeast-Squares AnalysisLinear ModelsMultivariate AnalysisPharmaceutical PreparationsPrincipal Component AnalysisSpectrum AnalysisArgonInositolPharmaceutical PreparationsvogliboseLIBSPharmaceutical drugsPLSRVoglibose

Identifiers

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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.