4.7 Article

Evaluation of the analytical performances of two Raman handheld spectrophotometers for pharmaceutical solid dosage form quantitation

Journal

TALANTA
Volume 214, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.talanta.2020.120888

Keywords

Raman handheld spectrophotometer; Quantitative performances; Accuracy profile method validation; Uniformity of dosage unit; Pharmaceutical tablets

Funding

  1. European funds of regional development (FEDER)
  2. Walloon Region of Belgium
  3. Walloon Region of Belgium in the framework of the Vibra4Fake project [7517]
  4. National Fund for Scientific Research, FNRS-F.R.S. [1.A030.17 - FC6921]

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This paper addresses the issue of pharmaceutical solid dosage form quantitation using handheld Raman spectrophotometers. The two spectrophotometers used are designed with different technologies: one allows getting a more representative sampling with the Orbital Raster Scanning technology and the other one allows setting acquisition parameters. The goal was to evaluate which technology could provide the best analytical results. Several parameters were optimized to get the lowest prediction error in the end. The main objective of this study was to evaluate if this kind of instrument would be able to identify substandard medicines. For that purpose, two case-study were explored. At first, a full ICH Q2 (R1) compliant validation was performed for moderate Raman scatterer active pharmaceutical ingredient (API) in a specific formulation. It was successfully validated in the +/- 15% relative total error acceptance limits, with a RMSEP of 0.85% (w/w). Subsequently, it was interesting to evaluate the influence of excipients when the API is a high Raman scatterer. For that purpose, a multiformulation model was developed and successfully validated with a RMSEP of 2.98% (w/w) in the best case. These two studies showed that thanks to the optimization of acquisition parameters, Raman handheld spectrophotometers methods were validated for two different case-study and could be applied to identify substandard medicines.

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