STATISTICALLY OPTIMIZED AND BOX-BEHNKEN DESIGN ASSISTED METHOD DEVELOPMENT AND VALIDATION OF AN ANTIPSYCHOTIC MEDICATION OLANZAPINE AND ITS RELATED IMPURITIES BY REVERSE-PHASE HPLC-UV SPECTROSCOPY

Objective: Statistically designed and Box-Behnken design (BBD) assisted reversed-phase high-performance liquid chromatography-ultraviolet (HPLC-UV) method was developed and validated for the identification of an antipsychotic medication Olanzapine and its organic impurities in pure drug along with forced degradation studies. Methods: The present developed method employed BBD optimized chromatographic conditions comprising of an Inertsil ODS 3V analytical column with dimension 250 mm x 4.6 mm and particle size 5µ. The isocratic mobile phase was used as a mixture of monobasic sodium phosphate buffer (0.01 M, pH 6), methanol and acetonitrile in the proportion of 40/30/30, v/v. The mobile phase flow rate and UV λmax was 1 ml/min and 260 nm, respectively. The method was optimized by Box-Behnken design using design expert software, comprising of three factors for Olanzapine for instance flow rate (A), mobile phase composition (B) and pH (C) while resolution between Olanzapine related compound A and Olanzapine related compound B (Y1) and tailing of Olanzapine (Y2) were taken as a response. Results: Application of BBD yielded statistically designed method with excellent quality parameters achieved in terms of linearity with the coefficient of correlation (R2>0.9999), limit of detection (LOD, 0.0023-0.16 µg/ml), the limit of quantification (LOQ, 0.007-0.39 µg/ml), accuracy (99-100%) and precision ((2%, relative standard deviation (%RSD) were evaluated as per latest available procedures. Conclusion: Forced degradation conditions were carried out, demonstrated that the optimized method was stable and no any interfering peaks eluting at the similar retention time of the studied compounds. The method was found to be stable, easy, rugged and robust, could be applied for the similar types of the pure drug

AN INNOVATIVE METHOD DEVELOPMENT AND FORCED DEGRADATION STUDIES FOR SIMULTANEOUS ESTIMATION OF SOFOSBUVIR AND LEDIPASVIR BY RP HPLC

Objective: To develop an innovative, rapid, simple, cost-effective, stability indicating reverse phase-high performance liquid chromatography (RP-HPLC) method for simultaneous estimation of ledipasvir (LP) and sofosbuvir (SB) in combination pill dosage form. Methods: The method was developed using C8 column, 250 mm x 4.6 mm, 5 mm using mobile section comprising of 0.1% (v/v) orthophosphoric acid buffer at pH 2.2 and acetonitrile in the ratio of 45:55 that was pumped through the column at a flow rate of 0.8 ml/min. Temperature was maintained at 30 °C, the effluents were monitored at 260 nm with the help of usage of PDA detector. Results: The retention time of LP and SB were found to be 2.246 min and 3.502 min. The approach was found to be linear with the variety of 9-36 µg/ml and 40-240 μg/ml for LP and SB respectively, the assay of estimated compounds were found to be 99.65% and 99.73% w/v for LP and SB respectively. Conclusion: The pressured samples changed into analyzed and this proposed a technique turned into determined to be particular and stability indicating as no interfering peaks of decay compound and excipients were observed. Hence, the approach was easy and economical that may be efficiently applied for simultaneous estimation of both LP and SB in bulk and combination tablet system

A REVIEW ON OPTIMIZATION OF DRUG DELIVERY SYSTEM WITH EXPERIMENTAL DESIGNS

The present review article aims at determining the various possible techniques available to enhance the quality, safety and efficacy of pharmaceutical formulations by exploring most suitable and practically applicable experimental designs and optimization techniques. As we know that pharmaceutical industries are constantly in search of novel ideas to improve quality by various optimization techniques, hence in present review article we shall discuss latest optimization techniques and experimental designs to achieve the best combination of product and process characteristics under the given set of conditions. Experimental designs and optimization techniques are the tools that are simultaneously and systematically used to identify various types of problems that may influence research, development and production of pharmaceutical formulations. These are organized an approach to determine the relationship between the factors affecting a process and the output of that process. The screening methods discussed here include factorial design, fractional factorial designs, full factorial design, mixture designs etc. Recently, different software has been used in implementing optimization techniques in pharmaceutical products to enhance product quality by using most suitable available facilities

Condition Monitoring and Maintenance Management with Grid-Connected Renewable Energy Systems

The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of action. But with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow, monitoring and maintenance are a few of the prime concerns. These problems were addressed widely in the literature, but most of the research has drawbacks due to long detection time, and high misclassification error. Hence to overcome these drawbacks, and to develop an accurate monitoring approach, this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic (PV) system and highlighted along with a brief overview on existing fault detection methodology. Based on the drawback a data-driven machine learning approach has been used for the identification of fault and indicating the maintenance unit regarding the operation and maintenance requirement. Further, the system was tested with a 4 kWp grid-connected PV system, and a decision tree-based algorithm was developed for the identification of a fault. The results identified 94.7% training accuracy and 14000 observations/sec prediction speed for the trained classifier and improved the reliability of fault detection nature of the grid-connected PV operation

Digital Signature and Key Agreement

Diffie Hellman key exchange protocol is the most commonly  used protocol. This protocol is used to exchange keys in a network. But it has bit m to exchange keys over a network but it has some drawbacks.  This is the first proposed algorithm through which parties can exchange information without knowing each other. This algorithm permits exchange even over a insecure networks. Hellman algorithm was introduced  by Martin Hellman and Whitfield Diffie in 1976. It is useful over a large number of authenticated protocols. Moreover,  it works on transport layers too. In this research efforts are being  made to declare new agreement protocol based on key confirmation and  Diffie Hellman algorithm as well. This work also ensures the  digital signature standard (DSS) with the help of Diffie-Hellman key exchange protocol by making use of two integers randomly. This protocol also performs on the elliptic curve cryptography in asymmetric encryption

An IoT-Based Thermoelectric Air Management Framework for Smart Building Applications: A Case Study for Tropical Climate

This study investigates the performance of the thermoelectric air conditioning (TE-AC) system smartly controlled by the Internet of Things (IoT)-based configuration for real tropical climatic application. Air cooling management was done through thermoelectric coolers, and an Arduino microcontroller with various sensors such as a temperature sensor, simple RF modules, and actuators was used to control the indoor climatic conditions based on outdoor conditions. The result shows that when the input power supply to the IoT-based TE-AC system is increased, the cooling capacity of the framework is also enhanced. Significant power and carbon emission reduction was observed for the IoT-based TE-AC system as compared to the TE-AC system without IoT. The IoT-incorporated system also ensures better microclimatic temperature control. Additionally, the system cooling capacity improves by 14.0%, and the coefficient of performance is increased by 46.3%. Thus, this study provides a smart solution to the two major energy harvesting issues of traditional air conditioners—an increase in energy efficiency by employing a TE-AC system and a further improvement in efficiency by using an IoT-based thermal management system

A A VALIDATED REVERSE-PHASE HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY-CHARGED AEROSOL DETECTOR TECHNIQUE FOR THE SIMULTANEOUS ESTIMATION OF SITAGLIPTIN AND ERTUGLIFLOZIN IN PURE AND PHARMACEUTICAL DOSAGE FORMS

Objective: The main objective of the present work is to develop and validate a selective reverse-phase (RP) high-performance liquid (HPLC)-charged aerosol detection technique for the quantitation of the sitagliptin and ertugliflozin in dosage form to attain high degree of sensitivity. Materials and Methods: In present HPLC technique, separation of drugs was achieved on Phenomenex C18 column (250×4.6 mm, 5 μ) with a mobile phase composition of phosphate buffer (pH – 5.8), acetonitrile, and methanol in the proportion of 40:40:20%V/V. 1 ml/min flow rate and 256 nm wavelength detection were maintained for the elution of drugs in the chromatographic system. The retaining time of sitagliptin and ertugliflozin in column was found to be 4.2 and 2.4 min, respectively. Results: The projected technique was successfully applied for the quantitation of sitagliptin and ertugliflozin as a single combined mixture. The linearity statistics for calibration curves shown a good linearity in the concentration range of 0.3125–10 μg/ml for sitagliptin and 0.0625–2.5 μg/ml for ertugliflozin. The average values of regression coefficient, slope, and intercept were 0.9998, 8688.2, and 1977.6 for sitagliptin and 0.9996, 33602, and 1852.6 for ertugliflozin. The technique was validated as per the International Council for Harmonization guidelines. The limit of detection and limit of quantification findings were 0.082 and 0.247 μg/ml for sitagliptin and 0.04 and 0.12 μg/ml for ertugliflozin. Conclusion: The developed and validated RP-HPLC-charged aerosol detector technique of sitagliptin and ertugliflozin in dosage form showed that the method was accurate and selective with high degree of sensitivity

Metasurface-Based Solar Absorption Prediction System Using Artificial Intelligence

Solar energy is a significant, environment-friendly source of renewable energy. The solar absorber transforms solar radiation into heat energy as an effective green energy source. Therefore, increasing its absorbing capacity can improve a solar absorber’s effectiveness. This paper proposes a tungsten tantalum alloy with silicon dioxide (WTa-SiO2) ceramic layer-based solar absorber system with two different metasurfaces to enhance absorptivity and boost the solar absorber efficacy. The absorbance is also improved by adjusting the resonator thickness and material thickness, and the maximum visible light absorption is achieved by the suggested solar filter design. Moreover, Golden Eagle Optimization (GE)-based deep AlexNet algorithm is proposed for predicting the parameter variation and their effect on absorbance. The optimization technique is used to increase the effectiveness of the solar absorber by optimizing the design parameters. The features from the WTa-SiO2 design are extracted by the proposed Principal Component-Autoencoder (PC-AE) method. Experimental results show that the proposed system can effectively predict absorptivity with a reduced computational time. The proposed method demonstrates superior prediction performance with an absorption prediction efficiency of 99.8% compared to the existing methods. Thus, the proposed WTa-SiO2 metasurface-based solar absorber can be used for photovoltaic applications