Raman Spectroscopy and Feature Selection Partial Least Squares Regression (PLSR) for the Determination of the anti-Diabetic Drugs Vildagliptin and Metformin in Combination Therapy

Analytical Letters, pp. 1–22

Abstract

The present study focused on quantifying the active pharmaceutical ingredients (APIs) metformin and vildagliptin in their fixed-dose combination product using Raman spectroscopy with manual feature selection and partial least squares regression (PLSR). Raman spectroscopy has become an important technique for qualitative and quantitative analysis of pharmaceuticals. This study assesses its potential for analyzing solid dosage combinations of the two anti-diabetic drugs, vildagliptin and metformin. We prepared different solid dosage forms by mixing the APIs with excipients. After gathering and preparing the Raman spectra, these were evaluated by mean plot analysis, principal component analysis (PCA), and manual feature selection-based PLSR. Mean plot analysis of pure APIs and excipients also helped us select the features manually for PLSR. Through the use of multivariate analysis such as PCA or this PLSR approach, the study demonstrates how Raman spectroscopy can accurately measure the concentration of APIs (such as vildagliptin and metformin) with high goodness-of-fit (R2) values (near 0.90). Its low root mean square error of calibration (RMSEC) and root mean square error of validation (RMSEV) for predictions of blind samples showcase its high accuracy for quantitative analysis. These findings make Raman spectroscopy a highly feasible technique for drug formulation analysis, providing a rapid, low-cost alternative to traditional techniques and suggesting that it be more widely adopted in industry quality control and drug development.

Authors 13

1. Arslan Ali

   University of Agriculture Faisalabad

   Affiliation as printed

   Department of Chemistry, University of Agriculture Faisalabad

2. Haq Nawaz corresponding

   University of Agriculture Faisalabad

   Affiliation as printed

   Department of Chemistry, University of Agriculture Faisalabad

3. Muhammad Irfan Majeed corresponding

   University of Agriculture Faisalabad

   Affiliation as printed

   Department of Chemistry, University of Agriculture Faisalabad

4. Nosheen Rashid

   University of Education

   Affiliation as printed

   Department of Chemistry, University of Education, Faisalabad Campus

5. Lamia Abu El Maati

   Princess Nourah bint Abdulrahman University

   Affiliation as printed

   Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University

6. Sahar G. Tawfik

   Princess Nourah bint Abdulrahman University

   Affiliation as printed

   Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University

7. Allah Ditta Aachen Institute for Experimental Molecular Imaging

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital

8. Mohsin Ali

   University of Agriculture Faisalabad

   Affiliation as printed

   Department of Chemistry, University of Agriculture Faisalabad

9. Asmat Ullah

   University of Agriculture Faisalabad

   Affiliation as printed

   Department of Chemistry, University of Agriculture Faisalabad

10. M. Adnan Shahid

    University of Agriculture Faisalabad

    Affiliation as printed

    Department of Chemistry, University of Agriculture Faisalabad

11. Muhammad Muaz Tariq

    University of Agriculture Faisalabad

    Affiliation as printed

    Department of Chemistry, University of Agriculture Faisalabad

12. Javeria Ameen

    University of Education

    Affiliation as printed

    Department of Chemistry, University of Education, Faisalabad Campus

13. Fariha Ghulam Qadir

    University of Agriculture Faisalabad

    Affiliation as printed

    Department of Chemistry, University of Agriculture Faisalabad