SREENIVASA CHARAN ARCHAKAM
@spsp.ac.in
Head-Department of Pharmaceutical Analysis
SRI PADMAVATHI SCHOOL OF PHARMACY
EDUCATION
Ph.D In Pharmaceutical Sciences
RESEARCH, TEACHING, or OTHER INTERESTS
Pharmaceutical Science, Analytical Chemistry, Spectroscopy, Drug Discovery
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Sreenivasa Charan Archakam, Keerthisikha Palur, Rajitha Galla, Sai Sucharitha Padiri, Praveen Kumar Tulasi, and Ranganayakulu Diviti
EManuscript Technologies
KEERTHISIKHA PALUR, SREENIVASA CHARAN ARCHAKAM, PRIYANKA PATAKAM, KAVYA ORUPALLI, PADMAJA YADAVALI, YOGESWAR POTHAPALA, and RANGANAYAKULU DIVITI
Asian Journal of Chemistry
The present work discusses the development and validation of chemometric assisted UV spectroscopic methods for analyzing two drugs amitriptyline hydrochloride and propranolol hydrochloride in their marketed formulation. The developed methods are two prominent chemometric models namely, principal component regression (PCR) and partial least squares regression (PLS) on which several research articles have been published for their immense contribution in the quantification of multi-component formulations. Linearity of the UV spectroscopic method was in the concentration ranges of 3-15 μg/mL of amitriptyline hydrochloride and 5-45 μg/mL of propranolol hydrochloride. The PCR and PLS chemometric models were established by employing fourteen mixtures as a calibration set and five mixtures as a validation set and were executed in the wavelength range of 240-320 nm with data interval of 5 nm. The statistical parameters obtained from both the methods revealed their validity and hence allows their suitability for analysis in regular quality control laboratories.
Keerthisikha Palur, Sreenivasa Charan Archakam, and Bharathi Koganti
EManuscript Technologies
Keerthisikha Palur, Sreenivasa Charan Archakam, and Bharathi Koganti
Elsevier BV
Keerthisikha Palur, Bharathi Koganti and S. C. Archakam
Journal of Applied Pharmaceutical Science
An isocratic reverse phase HPLC method using chemometric model was developed and validated for the simultaneous determination of Ambroxol hydrochloride, Terbutaline sulfate and Guaiphenesin in their combined dosage form. Central composite design which is a subset of Response surface Methodology was used as the chemometric model. The separation of three drugs was carried out by using Phenomenex C18 column and detection at 220 nm using UV detector. Based on initial trials, the three factors selected for the design were Methanol (MN) concentration, Mobile phase pH and flow rate in the range of 55-65% (v/v), 4-5 units and 0.6-1 ml/min respectively. The impact of the selected factors on the responses like retention time of first peak (tR1), resolution of 2nd and 3rd peak (Rs2,3) and theoretical plates of first peak (TP1) were evaluated. Derringers’ desirability function was used to optimize the responses. The conditions which were optimized for the assay of drugs were MN, ACN, 50 mM KH2PO4 (pH 5) in the ratio of 55:10:35 at a flow rate of 0.8 ml/min. The developed and optimized method was validated as per the ICH guidelines and can be used for routine analysis in quality control laboratories.
Keerthisikha Palur, BharathiKoganti, and Sreenivasa Charan Archakam
GP Innovations Pvt. Ltd.
To develop two Chemometric-assisted analytical methods like UV spectrophotometry and RP-HPLC methods for the quantification of Atorvastatin calcium (ASC) and Aspirin (APN) in the capsule dosage form. Chemometric models used in UV spectrophotometry were Principal component regression model (PCRM) and Partial least-square regression (PLSR). Both the models were applied for the drugs in the calibration ranges of 4-20 and 30-150 μg/mL for ASC and APN respectively. Total of nineteen laboratory prepared mixtures were used for calibration and prediction set of the models. In addition, RP-HPLC method by using chemometric approach for was developed using C18 column at room temperature with a mobile phase of acetonitrile: methanol: triethylamine (53.1:11.9:35 v/v/v), pH- 3.0, with detection at 275 nm. PCRM and PLSR models were evaluated by statistical parameters and RP-HPLC method was optimized by using Response surface methodology. The developed methods like UV and RP-HPLC by using chemometrics showed almost similar results and both the methods can be used for their analysis.
Keerthisikha Palur, Bharathi Koganti, Sreenivasa Charan Archakam, Sridhar Chenchugari, Bhavana Nagireddy, Mahesh Babu Devabhaktuni, and Meenakshi Sankranthi
EManuscript Technologies
Objective: To develop the UV-spectrophotometric method and to apply the Chemometric designs to the developed method for the simultaneous estimation of Atorvastatin calcium (ATR) and Aspirin (ASP) in intact capsule dosage form without further extraction. Methods: The UV-Spectrophotometric method was developed by using methanol as solvent for both the drugs and the data generated from the absorption spectra was mined by two Chemometric designs which were based on the principles of linear regression analysis method (LRC) and Crammer’s matrix method (CRM). The wavelengths selected for linear regression analysis and crammers’matrix methods were 245 nm (wavelength of maximum absorption; λ max of ATR) and 275 nm (wavelength of maximum absorption; λ max of ASP). Results: Both the methods hold good linearity for ATR from 4-20 μg/ml and for ASP from 20-120 μg/ml with regression coefficient values of 0.9999 and 0.9991 respectively. The intraday and inter-day precision was found to be less than 2% RSD. The percentage recovery was in the range of 100.1-102.65 for Atorvastatin calcium and 99.95-101.15 for Aspirin by both the methods. The percentage assay was found to be 102.52 for ATR and 98.9 for ASP by LRC method and 101.62 for ATR and 98.84 for ASP by CRM method. Conclusion: The developed methods neither require any cumbersome separation procedure nor complex derivatization procedures for the analysis of the two drugs and moreover they are effective in minimizing the errors in analysis, simple and economical. Key words: Chemometrics, Regression analysis, Cramer’s Matrix method, Atorvastatin, Aspirin.