研究目的
To develop a simple, rapid, accurate and economical UV-visible spectrophotometric method for the determination of hydroquinone (HQ) in its pure form, marketed formulation as well as in the prepared nanostructured lipid carrier (NLC) systems and to validate the developed method.
研究成果
The developed UV spectrophotometric method for the estimation of HQ in pure form, marketed ointment, and prepared NLC-formulation was found to be simple, rapid, accurate, precise, and economical. It is suitable for quality control of pharmaceutical formulations and routine laboratory analysis.
研究不足
The method is limited to the analysis of HQ in specific formulations and may not be applicable to other compounds without modification. The study also highlights the need for further optimization in the preparation of NLC formulations.
1：Experimental Design and Method Selection:
A UV-visible spectrophotometric method was developed for the determination of HQ in its pure form, marketed formulation, and prepared NLC systems. The method was validated following ICH guidelines.
2：Sample Selection and Data Sources:
HQ was used in its pure form, in a marketed cream, and in prepared NLC formulations. The samples were prepared in pH 5.5 phosphate buffer.
3：5 phosphate buffer.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: A double beam Systronics UV-Visible spectrophotometer, model UV-2201 (India) was used. Other materials included HQ, Compritol 888 ATO, TPGS 1000, almond oil, and transcutol.
4：Experimental Procedures and Operational Workflow:
HQ was estimated at UV maxima of 289.6 nm. The method was validated for linearity, precision, accuracy, robustness, ruggedness, limit of detection, and quantification limit.
5：6 nm. The method was validated for linearity, precision, accuracy, robustness, ruggedness, limit of detection, and quantification limit.
Data Analysis Methods:
5. Data Analysis Methods: The calibration curve was plotted between concentrations of HQ and measured absorbances. Linearity was calculated by least square regression method.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
