Spectrophotometric methods for determination of naringin, amlodipine, and nifedipine using chemometric techniques

Vishala Rani Baraily; Jithendar Reddy  Mandhadi; Bhupendra  Shrestha

doi:10.69857/joapr.v13i3.1107

Authors

Vishala Rani Baraily Assam down town University, Panikhaiti, Guwahati, Assam, 781026, India
Jithendar Reddy Mandhadi Assam down town University, Panikhaiti, Guwahati, Assam, 781026, India
Bhupendra Shrestha Himalayan Pharmacy Institute, Majhitar, East Sikkim 737136, India

DOI:

https://doi.org/10.69857/joapr.v13i3.1107

Keywords:

Chemometrics, Naringin, Nifedipine, Amlodipine, UV-spectroscopy, Orthogonal partial least squares (OPLS)

Abstract

Background: Chemometrics articulates statistical and mathematical aspects to analyse the effectiveness of chemical data, playing a pivotal role in spectroscopy. Among all the chemometrics techniques, this study utilizes the Orthogonal partial least squares (OPLS) model for the simultaneous analysis of naringin, amlodipine, and nifedipine, a well-established calcium channel blocker. Naringin, a citrus flavonoid exhibiting notable pharmacological activities. Methodology: This research employs UV-visible spectrophotometry in conjunction with the OPLS method for both calibration and prediction sets in simultaneous studies of Amlodipine–Naringin and Nifedipine–Naringin, aiming to develop a precise model for measuring drug concentrations. A linear dynamic range of 5-20 µg/mL was achieved for standard solutions, while calibration sets were developed using factorial designs. Result and Discussion: The OPLS model had significant predictive performance with R²values within the range of 0.9947-0.9976 for calibration and 0.9947-0.9985 for prediction, and low root mean square error of cross validation (RMSECV) values of 0.6191- 0.4353 for NIF-NAR, and 0.3978- 0.4418 for AML-NAR, indicating robust model performance. The model validation process, using Hotelling’s T2 test, DModx, established no significant outliers, and permutation analysis validated the model’s reliable fit. The recovery studies showed values close to 100%, thus verifying the effectiveness of the methodology. Conclusion: The research demonstrated OPLS (Orthogonal Partial Least Squares) as a powerful solution for resolving overlapping spectral data, providing high-precision drug analysis with minimal interference. The development of chemometrics methods demonstrated efficiency and precision in pharmaceutical analysis while also offering cost-effectiveness for quality control and formulation development.

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