Quantification of Cilostazol and Telmisartan in Combination Using Risk Profile and Uncertainty Contour: A Contemporary Validation Approach
Dharmendra D, Karan M, Bhoomi P and Rajshree CM*
Quality Assurance Laboratory, Centre of Relevance and Excellence in Novel Drug Delivery system, Department of Pharmacy, Shree G.H.Patel Pharmacy building, Donor's Plaza, The Maharaja Sayajirao University of Baroda, Fatehgunj, Vadodara-390002, Gujarat, India
- *Corresponding Author:
- Rajshree C Mashru
Quality Assurance Laboratory
Centre of Relevance and Excellence in Novel Drug Delivery system
Pharmacy Department, Shree G.H.Patel Pharmacy building
Donor's Plaza, The Maharaja Sayajirao University of Baroda
Fatehgunj, Vadodara-390002, Gujarat, India
E-mail: [email protected] ; [email protected]
Received date: May 22, 2014; Accepted date: June 15, 2015; Published date: June 25, 2015
Citation: Dharmendra D, Karan M, Bhoomi P, Rajshree CM (2015) Quantification of Cilostazol and Telmisartan in Combination Using Risk Profile and Uncertainty Contour: A Contemporary Validation Approach. J Chromatogr Sep Tech 6:278. doi:10.4172/2157-7064.1000278
Copyright: © 2015 Dharmendra D, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Risk profile and uncertainty estimation are the two major and important parameter that need to be carried out during the development of pharmaceutical process, to obtain reliable results. The conventional method validation schedule needs to be improvised so as to certify extraordinary method reliability to measure quality feature of a drug product. Risk profile assessment, expanded uncertainty and combined standard uncertainty in the analysis of cilostazol and telmisartan in combined tablet dosage form were studied in this research work. RP-HPLC method was validated in our laboratory as per ICH guideline and risk profile assessment has been outlined including uncertainty estimation using the cause-effect approach. In the course of validation, the calibration model found to be impregnable when encountered with lack of fit test and Levene’s test. In uncertainty major contribution is due to sample concentration and mass. The proposed research work clearly demonstrate the application of theoretical concept of calibration model tests, relative bias, risk profile and uncertainty in the methods used for analysis in drug discovery process.