Validation Of Chemometric Methods In Determining Betamethasone And Neomycin Levels In Cream Preparations By Ultraviolet Spectrophotometry

Feb 27, 2025 by ADMIN 138 views

Introduction

The combination of betamethasone and neomycin in cream preparations is a crucial aspect of medical practice, and accurate determination of their levels is essential for ensuring the efficacy and safety of these products. In this study, we aimed to validate the chemometric spectrophotometry methods combined with the calibration of multivariate partial least square (PLS) to determine the mixture levels of betamethasone and neomycin in cream preparations. The use of this approach is expected to produce accurate and reliable methods for determining drug levels.

Background

Betamethasone and neomycin are commonly used in cream preparations for various medical conditions. However, the accurate determination of their levels is crucial for ensuring the efficacy and safety of these products. Traditional methods for determining drug levels, such as high-performance liquid chromatography (HPLC), are often time-consuming and require specialized equipment. In contrast, chemometric spectrophotometry methods offer a rapid and cost-effective alternative for determining drug levels.

Methodology

The research method carried out involved the making of a calibration and validation model for each of the 12 synthetic mixtures. Absorbance measurements were carried out at wavelengths between 200 to 400 nm at an interval of 3 Nm. After the measurement, the evaluation results were carried out by paying attention to several parameters, such as the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), coefficient of determination (R²), and root mean square error of prediction (RMSEP).

Results

The results of the analysis show that the relative standard deviations (RSD) for betamethasone and neomycin are 0.93% and 1.73%, respectively. In addition, the value of the percentage of returning for the two compounds is 101.09% and 99.94%, respectively. This shows that the method used in this study has good accuracy.

In the calibration of multivariate PLS, the RMSEC value for betamethasone is 0.0230, and for neomycin is 0.3553. The RMSECV value obtained is 0.7187 for betamethasone and 0.3586 for neomycin, while the RMSEP value is 0.1558 for betamethasone and 0.0820 for neomycin. All of these values are within specified limits, which indicate that the prediction capability of this method is still acceptable and effective for determining levels.

Discussion

The results of this study demonstrate the potential of chemometric spectrophotometry methods combined with the calibration of multivariate PLS for determining the levels of betamethasone and neomycin in cream preparations. The accuracy and reliability of this method are essential for ensuring the efficacy and safety of these products.

The use of chemometric spectrophotometry methods offers several advantages over traditional methods, including rapid analysis times, low costs, and minimal sample preparation requirements. Additionally, this method can be easily automated, making it an attractive option for high-throughput analysis.

Conclusion

In conclusion, the results of this study demonstrate the potential of chemometric spectrophotometry methods combined with the calibration of multivariate PLS for determining the levels of betamethasone and neomycin in cream preparations. The accuracy and reliability of this method are essential for ensuring the efficacy and safety of these products.

Future Directions

The results of this study highlight the need for further research in the development of chemometric spectrophotometry methods for determining drug levels. Future studies should focus on the optimization of the calibration model, the development of new chemometric methods, and the application of this method to other pharmaceutical products.

Implications

The implications of this study are significant, as it demonstrates the potential of chemometric spectrophotometry methods for determining drug levels. This method has the potential to improve the quality of pharmaceutical product control and provide certainty for patients in getting safe and effective therapy.

Recommendations

Based on the results of this study, we recommend the use of chemometric spectrophotometry methods combined with the calibration of multivariate PLS for determining the levels of betamethasone and neomycin in cream preparations. This method has the potential to improve the accuracy and reliability of drug level determination and ensure the efficacy and safety of these products.

Limitations

The limitations of this study include the use of synthetic mixtures and the limited number of samples analyzed. Future studies should focus on the analysis of real-world samples and the optimization of the calibration model.

Future Research Directions

Future research directions should focus on the optimization of the calibration model, the development of new chemometric methods, and the application of this method to other pharmaceutical products. Additionally, the use of this method for determining the levels of other drugs and pharmaceutical products should be explored.

Conclusion

Q: What is the purpose of this study?

A: The purpose of this study is to validate the chemometric spectrophotometry methods combined with the calibration of multivariate partial least square (PLS) to determine the mixture levels of betamethasone and neomycin in cream preparations.

Q: What are the advantages of using chemometric spectrophotometry methods?

A: The advantages of using chemometric spectrophotometry methods include rapid analysis times, low costs, and minimal sample preparation requirements. Additionally, this method can be easily automated, making it an attractive option for high-throughput analysis.

Q: What are the limitations of this study?

A: The limitations of this study include the use of synthetic mixtures and the limited number of samples analyzed. Future studies should focus on the analysis of real-world samples and the optimization of the calibration model.

Q: What are the implications of this study?

A: The implications of this study are significant, as it demonstrates the potential of chemometric spectrophotometry methods for determining drug levels. This method has the potential to improve the quality of pharmaceutical product control and provide certainty for patients in getting safe and effective therapy.

Q: What are the recommendations of this study?

A: Based on the results of this study, we recommend the use of chemometric spectrophotometry methods combined with the calibration of multivariate PLS for determining the levels of betamethasone and neomycin in cream preparations. This method has the potential to improve the accuracy and reliability of drug level determination and ensure the efficacy and safety of these products.

Q: What are the future research directions?

A: Future research directions should focus on the optimization of the calibration model, the development of new chemometric methods, and the application of this method to other pharmaceutical products. Additionally, the use of this method for determining the levels of other drugs and pharmaceutical products should be explored.

Q: What are the potential applications of this method?

A: The potential applications of this method include the determination of drug levels in various pharmaceutical products, such as creams, ointments, and tablets. This method can also be used for the quality control of pharmaceutical products and for the development of new pharmaceutical products.

Q: What are the potential benefits of this method?

A: The potential benefits of this method include improved accuracy and reliability of drug level determination, improved quality of pharmaceutical product control, and improved certainty for patients in getting safe and effective therapy.

Q: What are the potential challenges of this method?

A: The potential challenges of this method include the need for optimization of the calibration model, the development of new chemometric methods, and the application of this method to other pharmaceutical products.

Q: What are the potential future developments of this method?

A: The potential future developments of this method include the use of machine learning algorithms, the development of new chemometric methods, and the application of this method to other pharmaceutical products.

Q: What are the potential implications of this method for the pharmaceutical industry?

A: The potential implications of this method for the pharmaceutical industry include improved accuracy and reliability of drug level determination, improved quality of pharmaceutical product control, and improved certainty for patients in getting safe and effective therapy.

Q: What are the potential implications of this method for patients?

A: The potential implications of this method for patients include improved certainty in getting safe and effective therapy, improved quality of life, and improved health outcomes.

Q: What are the potential implications of this method for healthcare professionals?

A: The potential implications of this method for healthcare professionals include improved accuracy and reliability of drug level determination, improved quality of pharmaceutical product control, and improved certainty for patients in getting safe and effective therapy.

Q: What are the potential implications of this method for regulatory agencies?

A: The potential implications of this method for regulatory agencies include improved accuracy and reliability of drug level determination, improved quality of pharmaceutical product control, and improved certainty for patients in getting safe and effective therapy.