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Data on validation using accuracy profile of HPLC-UV method.

Ahmed M Ibrahim¹, Hassan A M Hendawy¹, Wafaa S Hassan²

¹National Organization for Drug Control and Research, P.O. Box 29, Cairo, Egypt.

|April 18, 2019

Summary

This study optimizes High-Performance Liquid Chromatography-Ultraviolet (HPLC-UV) methods using Six Sigma principles for analyzing ascorbic acid, paracetamol, and guaifenesin. The data supports enhanced accuracy and reliability in pharmaceutical analysis.

Keywords:

Accuracy profile Ascorbic acid Guaifenesin HPLC Paracetamol

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Area of Science:

Analytical Chemistry
Pharmaceutical Analysis
Quality Management

Background:

High-Performance Liquid Chromatography-Ultraviolet (HPLC-UV) is a critical technique in pharmaceutical analysis.
Method optimization is essential for ensuring accurate and reliable analytical results.
Six Sigma methodology offers a data-driven approach to process improvement and quality control.

Purpose of the Study:

To present raw data from HPLC-UV analysis of ascorbic acid (AS), paracetamol (PA), and guaifenesin (GU).
To detail the application of a Six Sigma quality approach for optimizing HPLC-UV methods.
To provide data supporting the validation of the optimized analytical method.

Main Methods:

HPLC-UV analysis was performed on ascorbic acid, paracetamol, and guaifenesin.
Calibration standards were prepared at six concentration levels (25-150%) and measured in triplicate daily.
Validation standards were prepared at four concentration levels (25-150%) and measured in quintuplicate daily over three series.

Main Results:

Raw HPLC-UV data for AS, PA, and GU are provided.
The study outlines the preparation and measurement protocols for calibration and validation standards.
Data collection involved daily preparation and triplicate/quintuplicate measurements to ensure robustness.

Conclusions:

The presented data supports the optimization of HPLC-UV methods using Six Sigma.
The methodology ensures reliable quantification of ascorbic acid, paracetamol, and guaifenesin.
This approach enhances the quality and efficiency of pharmaceutical analysis.