<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study explores biosensor technology, focusing on its application in drug detection through advanced quantitative analysis methods: partial least squares (PLS) and probabilistic principal component analysis (PPCA). We developed a rapid quantitative calibration model using azure A, B, and C—metabolites of pefloxacin mesylate and methylene blue— demonstrated through surface-enhanced Raman spectroscopy. The findings highlight the superior accuracy of PLS and PPCA in predicting drug concentrations, with pefloxacin mesylate detection deviations maintained between 0.24%-0.98% and 0.35%-1.02%, respectively. PLS proved to be slightly more effective. This study confirms the potential of biosensor technology in ensuring drug safety, offering substantial support for public health protection and regulatory compliance.</p>
</abstract>

This study explores biosensor technology, focusing on its application in drug detection through advanced quantitative analysis methods: partial least squares (PLS) and probabilistic principal component analysis (PPCA). We developed a rapid quantitative calibration model using azure A, B, and C—metabolites of pefloxacin mesylate and methylene blue— demonstrated through surface-enhanced Raman spectroscopy. The findings highlight the superior accuracy of PLS and PPCA in predicting drug concentrations, with pefloxacin mesylate detection deviations maintained between 0.24%-0.98% and 0.35%-1.02%, respectively. PLS proved to be slightly more effective. This study confirms the potential of biosensor technology in ensuring drug safety, offering substantial support for public health protection and regulatory compliance.

Effective application of biosensor analytical techniques in drug testing

Department of Criminal Investigation in Gansu Police Vocational College

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Effective application of biosensor analytical techniques in drug testing"}

This study explores biosensor technology, focusing on its application in drug detection through advanced quantitative analysis methods: partial least squares...

Effective application of biosensor analytical techniques in drug testing

Online veröffentlicht: 01. Apr. 2024

Seitenbereich: -

Eingereicht: 22. Jan. 2024

Akzeptiert: 27. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0695

Schlüsselwörter
Partial least squares, Probabilistic principal component analysis, Biosensor technology, Drug detection

© 2024 Zhiwei Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Effective application of biosensor analytical techniques in drug testing

Online veröffentlicht: 01. Apr. 2024

Seitenbereich: -

Eingereicht: 22. Jan. 2024

Akzeptiert: 27. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0695

SchlüsselwörterPartial least squares, Probabilistic principal component analysis, Biosensor technology, Drug detection

© 2024 Zhiwei Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Partial least squares, Probabilistic principal component analysis, Biosensor technology, Drug detection