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Development and Method Validation of Baclofen by RP-HPLC in Bulk Drug and Pharmaceutical Formulation.

Kamaldeep Singh, Gurvinder Pal Singh, and Sandeep Kumar Sharma

In the present work simple and sensitive RP-HPLC method has been developed for the quantitative estimation of Baclofen in bulk drug and pharmaceutical formulations. A rapid and sensitive RP-HPLC Method with UV detection (253 nm) for routine analysis of Baclofen in Bulk drug and Pharmaceutical formulation was developed. Chromatography was performed with mobile phase containing a mixture of Methanol: Water: Acetic Acid (100:100:0.5) with flow rate 1.0 ml/min The linearity was found to be in the range of 10-50 μg/ml with (r2=0.999) A known amount of the drug solution (80, 100 and 120 %) was added to the powder sample of the tablet formulation and subjected to the estimation of the drug for the recovery studies. There was a high recovery of Baclofen (100.03%, 100.18%, and 100.05%) Robustness of the proposed method was determined by analysis of sample by changes in different parameter like flow rate, detection and Column temperature using similar operational and environmental conditions, the tailing factor was found to be less than 2. The precision of the assay was determined in terms of intra and inter-day variation in the peak area for a set of drug solution (30 μg/ml) assayed three times on the same day and on three different days The intra and inter day variation in the peak ratio of the drug solution was calculated in terms of co-efficient of variation (CV) and obtained by multiplying the ratio of standard deviation to the mean with 100(CV=SD/MEAN X 100)All the parameters are compared with standard raw material of baclofen. The proposed method was validated in accordance with ICH parameters and applied for analysis of the same in marketed formulations. The proposed method was validated by determining sensitivity, accuracy, precision, robustness stability.

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化学文摘社 (CAS)
谷歌学术
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学术钥匙
研究圣经
全球影响因子 (GIF)
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宇宙IF
电子期刊图书馆
参考搜索
哈姆达大学
国际组织研究所 (I2OR)
宇宙
日内瓦医学教育与研究基金会
秘密搜索引擎实验室

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