DEVELOPMENT OF HPLC STABILITY DEMONSTRATING METHODOLOGY FOR QUANTIFYING AZELNIDIPINE AND TELMISARTAN IN TABLETS AND BULK TYPES: VALIDATION FOLLOWING ICH DIRECTIVES

Objective: Azelnidipine (AZEL) and Telmisartan (TELM) combination is referred to the sufferers of hypertension. No analytical process has yet been mentioned for the TELM and AZEL combination analysis. We, therefore, have designed for its first time stability demonstrating methodology based on HPLC for analysing TELM and AZEL in the tablets and bulk. Methods: The assay of TELM and AZEL was get done on a 250 mm length C18 column (Supelco, 4.6 mm inner diameter, 5.0 μm particle size), and utilized 0.1M Na2SO4 (pH 3.6) and acetonitrile (55% volume: 45% volume) as the mobile solvents phase, at a stream rate 1.0 ml/min. HPLC recognition of TELM and AZEL was taken by a photodiode array sensor set at 258 nm. For validation of the stability demonstrating methodology proposed in terms of sensitivity, precision, specificity, linearity, device adequacy, robustness and accuracy, ICH directives were followed. Results: Calibration curves of TELM and AZEL were generated in the array of 20-60 µg/ml and 4-12 µg/ml with recovery percentage ranges of 99.62%-101.05% and 97.76%-100.17%, and detection limits of 0.020 µg/ml and 0.009 µg/ml, respectively. TELM and AZEL stability was inspected in the existence of acid, base, light, heat, and oxidation and it was realised to be more stable under oxidation degradation testing conditions employed when compared to acid, alkaline, photo, and heat degradation testing conditions applied. Conclusion: The observations demonstrated that the described HPLC stability demonstrating methodology was suitable for quantitating TELM and AZEL combination in tablets and bulk.

Reliability Analysis Based on a Gamma-Gaussian Deconvolution Degradation Modeling with Measurement Error

In most degradation tests, the measuring processes is affected by several conditions that may cause variation in the observed measures. As the measuring process is inherent to the degradation testing, it is important to establish schemes that define a certain level of permissible measurement error such that a robust reliability estimation can be obtained. In this article, an approach to deal with measurement error in degradation processes is proposed, the method focuses on studying the effect of such error in the reliability assessment. This approach considers that the true degradation is a function of the observed degradation and the measurement error. As the true degradation is not directly observed it is proposed to obtain an estimate based on a deconvolution operation, which considers the subtraction of random variables such as the observed degradation and the measurement error. Given that the true degradation is free of measurement error, the first-passage time distribution will be different from the observed degradation. For the establishment of a control mechanism, these two distributions are compared using different indices, which account to describe the differences between the observed and true degradation. By defining critical levels of these indices, the reliability assessment may be obtained under a known level of measurement error. An illustrative example based on a fatigue-crack growth dataset is presented to illustrate the applicability of the proposed scheme, the reliability assessment is developed, and some important insights are provided.