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Swami, Hemant
- RP-HPLC Method for Simultaneous Estimation of Simvastatin and Ezetimibe in Bulk Drug and its Combined Dosage Form
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Authors
Affiliations
1 Shri Ravi Shankar College of Pharmacy, Bhanpura Road, Bhopal, (M.P), IN
2 IPS College of Pharmacy, Gwalior, (M.P), IN
3 Truba Institute of Pharmacy, Karond Bypass, Bhopal, (M.P), IN
1 Shri Ravi Shankar College of Pharmacy, Bhanpura Road, Bhopal, (M.P), IN
2 IPS College of Pharmacy, Gwalior, (M.P), IN
3 Truba Institute of Pharmacy, Karond Bypass, Bhopal, (M.P), IN
Source
Asian Journal of Research in Chemistry, Vol 1, No 1 (2008), Pagination: 29-31Abstract
This work is concerned with application of simple, accurate, precise and highly selective reverse phase high performance liquid chromatographic (RP-HPLC) method for simultaneous estimation of simvastatin and ezetimibe in combined dosage form. Chromatographic separation was achieved isocratically at 25°C±0.5°C on Luna C18 column (250×4.6 mm i.d.) with a mobile phase composed of methanol: water: acetonitrile in the ratio of 75: 18.75: 6.25 % v/v/v at flow rate of 1.8 ml/min. Detection is carried out using a UV-PDA detector at 231 nm. The retention time of simvastatin and ezetimibe was found to be 13.5±0.5 min and 4.02±0.3 min. respectively. The method was found to be linear in the range of 1-50 μg/ml with mean recovery of 99.21% for simvastatin and 99.50% for ezetimibe. The correlation coefficients for all components are close to 1. The developed method was validated according to ICH guidelines and values of accuracy, precision and other statistical analysis were found to be in good accordance with the prescribed values. Thus the proposed method was successfully applied for simultaneous determination of simvastatin and ezetimibe in routine analysis.Keywords
Simvastatin, Ezetimibe, RP-HPLC.- Bioefficacy of Different Biopesticides against Major Foliage Feeders on Soybean [Glycine max (L.) Merrill]
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Authors
Affiliations
1 Department of Entomology, Maharana Pratap University of Agriculture and Technology, Udaipur - 313001, Rajasthan, IN
2 Krishi Vigyan Kendra, Badgaon, Udaipur - 313001, Rajasthan, IN
1 Department of Entomology, Maharana Pratap University of Agriculture and Technology, Udaipur - 313001, Rajasthan, IN
2 Krishi Vigyan Kendra, Badgaon, Udaipur - 313001, Rajasthan, IN
Source
Journal of Biological Control, Vol 33, No 4 (2019), Pagination: 378-381Abstract
Field experiments were conducted to evaluate the efficacy of different biopesticides, viz., Nomuraea rileyi @ 1 × 108 conidia/lit, Beauveria bassiana @ 1 × 109 CFU/ml minimum @ 5 ml/lit, Metarhizium anisopliae @ 1 × 109 CFU/ml minimum @ 5 ml/lit, dipel @ 1 kg/ha, spinosad 45 SC @ 0.5 ml/lit, neem seed kernel extract (NSKE) @ 5% and neem oil @ 2% against foliage feeders of soybean namely, semi looper (Chrysodeixis acuta) and tobacco caterpillar (Spodoptera litura) during Kharif, 2016. The result revealed that all treatments were significantly superior over control. The mean larval population of C. acuta and S. litura ranged from 1.29 to 9.37 and 0.92 to 6.98 larvae per meter row length (mrl) at 3, 7 and 10 days respectively after the application of treatments. The treatments comprising Spinosad 45 SC @ 0.5 ml/lit proved highly effective in reducing the population of C. acuta and S. litura with lowest overall mean larval population of 4.71 and 3.02 larvae per mrl, respectively. Against C. acuta NSKE @ 5% was least effective and against S. litura neem oil was observed as least effective with maximum over all mean larval populations of 7.75 and 4.97, respectively.Keywords
Biopesticides, Chrysodeixis acuta, Foliage Feeders, Soybean, Spodoptera lituraReferences
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- The Era of Artificial Intelligence in Pharmaceutical Industries - A Review
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Authors
Affiliations
1 Sagar Institute of Research and Technology - Pharmacy, Bhopal, MP., IN
2 School of Pharmaceutical Science, SAGE University, Indore, M.P., IN
1 Sagar Institute of Research and Technology - Pharmacy, Bhopal, MP., IN
2 School of Pharmaceutical Science, SAGE University, Indore, M.P., IN
Source
Research Journal of Science and Technology, Vol 14, No 3 (2022), Pagination: 183-187Abstract
As a growing sector, the Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry contributes in the drug discovery process, giving emphasis on how new technologies have improved effectiveness. As in the current scenario artificial intelligence including machine learning may be considered the future for a wide range of disciplines and industries specially the pharmaceutical industry. As we know today pharmaceutical industries producing a single approved drug cost the company millions with many years of rigorous testing prior to its approval, reducing costs and time is of high interest. The involvement of Artificial Intelligence will be useful to the pharmaceutical industry and also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics.Keywords
Artificial Intelligence, Pharmaceutical, Machine learning, Research, Chemistry.References
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