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March 3, 2026Scientific ReportsOpen Access

Artificial intelligence versus traditional approaches in multicomponent spectral analysis

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Authors

NFNesma M. FahmyROReem H. ObaydoHLHayam M. Lotfy

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Overview

Compares AI-assisted methods for spectral analysis to traditional techniques, suggesting enhanced efficiency in pharmaceutical mixtures.

Key Points

  • This research aims to evaluate the effectiveness of AI-assisted methods in spectrophotometric analysis compared to traditional approaches.
  • Applied established protocols for analyzing Clioquinol and Gentamicin in pharmaceutical mixtures.
  • Developed two novel approaches: MAN-[DD-DDE] and AUTO-[DD-DD] for analyzing ternary mixtures.
  • Used software for generating calibration curves and regression equations to assess accuracy and precision.
  • Evaluated sustainability of methods using MA Tool (2025) across different criteria.
  • Linear working ranges for TOL, BETA, and CC were established, with LODs of 0.09 µg/mL for CLIO and 0.26 µg/mL for CC.
  • AI-driven methods matched accuracy and reproducibility of traditional methods while reducing subjective input.
  • Achieved a Whiteness Score of 60.9% through AI-assisted analysis, suggesting greener workflows.

Cite This Study

Fahmy et al. (2026) studied this question.

synapsesocial.com/papers/69a67ec3f353c071a6f0a262https://doi.org/10.1038/s41598-026-39433-3
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