International Journal of Pharmacy Research & Technology (IJPRT) <p><strong>International Journal of Pharmacy Research &amp; Technology (IJPRT) </strong>an International Journal of Pharmaceutical Research &amp; Technology <strong>(ISSN - 2250–0944) (P-ISSN 2250-1150)</strong> (An official publication of <em>Advanced Scientific Research</em>) is established in the year 2009. </p> <p>The aim of the ​<strong>International Journal of Pharmacy Research &amp; Technology (IJPRT) </strong>is to become an effective medium for inspiring the researchers to bring out their contributions in the form of research papers, articles, case studies, review articles and in the fields of Pharmacy, Medical sciences and Science and technology. The dissemination would thus help the industries, professional organisations to adopt and apply the information for creating new knowledge and enterprise. The publication would also help in enhancing awareness about the need to become research minded.</p> <p>All articles published in the journal will be freely available to scientific researchers to all over the globe. We will be making sincere efforts to promote our journal across the world in various ways. It is hoped that this journal will act as a common platform for researchers to pursue their objectives.</p> en-US (Editor) (Technical Supporter) Tue, 26 Sep 2023 17:55:52 +0300 OJS 60 Fabrication of Porous Microspheres of Azithromycin, Incorporating Different Porogens <p>Several antibiotics loaded nebulized formulations allow high local concentrations and a decreased risk of systemic toxicity but this formulation require time-consuming hygienic procedures for administration several times a day. An innovative way to increase drug product stability, patient comfort, and therapeutic effectiveness is to formulate an easily administered sustained-release, biodegradable, and biocompatible porous microspheres. Here the Ionotropic Gelation method has been opted for the preparation of a porous microsphere loaded with Azithromycin by inclusion of different porogens. The structural morphology of porous microspheres was investigated by Scanning Electron Microscopy. Microspheres were in the range of 600 -900 µm. with the pores in the size of <br>2-15µm.<br>Among the three porogens used, NaHCO3 showed the maximum porosity of almost 10%, whereas it was 4.9 and 6 for Sucrose and NaCl respectively. Micromeritics properties of porous microspheres were found to be satisfactory in accordance with their flow properties. In Drug release profile it was observed that after 8 hours 65%,57% and 53% drug was released from porous microspheres using NaHCO3, NaCl and sucrose as porogens respectively. To ascertain the drug release mechanism and release rate, data of all the formulations were fitted to Zero order, Higuchi Matrix, Korsmeyer Peppas model to explain the kinetics. The dug was released in a controlled way and the pattern indicated that they obeyed Higuchi kinetics. The value of release exponent ‘n’ calculated for all the formulations indicates that the formulations released drug in non Fickian (anomalous) release mechanism (n&gt; 0.5) i.e., erosion followed by diffusion.</p> GOPA ROY BISWAS, NURJAHAN KHATOON, ANURANJITA KUNDU Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Tue, 26 Sep 2023 00:00:00 +0300 Book GPT: An Innovative PDF Querying Tool <p>Access to information that is timely and reliable is becoming increasingly important in today's fast- paced environment. A common format for transmitting information, PDFs frequently contain crucial data that must be retrieved and analyzed. Yet, it can be time-consuming anderror-prone to manually search through PDFs for the necessary data. In this paper, we describe a hybrid strategy that makes use of the capabilities of Natural Language Processing (NLP) methods to read and produce precise responses from PDFs. We employ k-Nearest Neighbor to locate the data points that are most pertinent to a particular query and Universal Sentence Encoder to convert sentences into fixed-length numerical vectors. We also incorporate the cutting-edge language model Open AIGPT-3 top roduce text that is similar to that of a human being for increased accuracy. By creating the interactive user interface, our tool will enable the users to either upload a pdf or to provide an appropriate URL to ask a query. Our method makes it possible to quickly and accurately extract answers from PDFs in real-time applications, such as those seen in the information retrieval, legal ,and health care sectors[1].</p> D.SANTHAKUMAR, L.SASIKALA, A.BALAJEE Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Fri, 10 Nov 2023 00:00:00 +0300 Ephemeral Resilient Signcryption and Piecewise Deep Belief Network forReliable with QoS aware Streaming Social Media Data Transmissionin 5G Network <p>Fifth Generation Mobile Network (5G) is supported by wireless network services to offer extensive data transmission to improve device-to-device transportation quality, as well as minimize working costs. It allows users to seamlessly access a variety of multimedia services in social network platforms such as live streaming applications like Internet live sports networks, youtube, Facebook, etc... There are various security and privacy issues related to the user’s shared multimedia information. With the fast-growing 5G technology, privacy preservation of streaming data transmission in social network platforms plays a vital role for handling the attackers. In order to improve the QoS aware secure streaming data transmission in a 5G network, a novel technique called Ephemeral Resilient SchnorrSigncryptive Piecewise Damped Convolutional Deep Belief Network (ERSSPDCDBN) is introduced with higherreliability. The ERSSPDCDBN technique first collects the social media stream data. After that, secure data transmission is performed by applying an ephemeral resilient schnorrsigncryption. For enhancing security, ephemeral resilient key generation, signcryption, and unsigncryptionis carried out by using signcryption method. Followed by, the user authenticity is verified based on digital signature verification using a simple matching coefficient. If the signature is valid, the authorized user obtains the original data and avoids the attackers. During data transmission, Piecewise regressive Damped Convolutional deep belief network is developed for achieving higher throughput and minimum latency. Experimental of ERSSPDCDBN is conducted by using six metrics.</p> SURESH N, P KANMANI P Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Fri, 10 Nov 2023 00:00:00 +0300 Evolutionary Modeling and Analysis on Investment Consumption Optimization <p>Genetic algorithms are optimization methods that are primarily used in financial analysis to facilitate better hands-on analysis with various software packages. The traders can use the parameters set, which are then applied using genetic algorithms for optimization. The financial applications optimize the parameters to represent the risks to the traders using evolutionary methods. Fixing the parameters is an essential step in the evolutionary process, and the financial parameters should correlate to modifications with market turns. This research focuses on determining the financial rank of supermarkets using clustering and evolutionary algorithms to identifythe risks in various decision-making and multi-disciplinary applications. This research also analyzes the optimal investment and some strategies required for consumption in asset modeling. The decision maker may fail in information processing due to the cost and can make financial portfolio decisions based on the signals observed. Hence this research developed the optimization model using clustering and evolutionary algorithms to determine the strength of observation, consumption strategies, and optimal investment based on the constraint value-at-risk and the cost of information processing. The wealth proportion spent by an investor on consumption lies between 0.01 and 0.09. Under the value-at-risk assumption, the stability of the optimal consumption proportion is inferred over the long-run period and will not exceed 7% of the investor's overall wealth.The experimental results prove that the proposed model works better than the state-of-the-art methods.</p> RAJA MARAPPAN, VENKATESAN R Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Fri, 10 Nov 2023 00:00:00 +0300 Hyperledger Fabric Framework For Blockchain Technology Using Tabu Search And Teaching Learning-Based Optimization Algorithm <p>There has been a steady growth in popularity of the permissioned blockchain platforms recently, among which the Hyperledger Fabric has been identified as one of the most popular distributed ledger platforms. The fabric includes several components like endorsers, committers, and ordering services. Furthermore, it includes different phases of processing in a transaction like the phase of <br>endorsement, commit phase, validation, and ordering phase. Owing to a large number of components or phases, the Fabric will provide different configurable parameters like the block size, channels, state database, and endorsement policies. Therefore, a major challenge while setting up new and effective blockchain networks is identifying the right value set for the parameters. The Tabu Search (TS) with the Teaching Learning Based Optimization (TLBO) is employed for optimizing a block size with an endorsement policy for various channels in this work. The results of the experiment proved that the results of the experiments had better latency and <br>throughput, thus resulting in better and optimum performance.</p> SANJITH NARAYANAN, M. NITHYA, SREEJU SREEDHARAN Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Thu, 16 Nov 2023 00:00:00 +0300 An Efficacy Analysis of Data Encryption Architecture For Cloud Platform <p>With the rise of cloud computing, many data owners are opting to outsource their complex data management systems to commercial public clouds for greater flexibility and cost savings. However, to ensure data privacy, sensitive data must be encrypted before outsourcing, which renders traditional plaintext keyword search obsolete. Therefore, it is crucial to enable an encrypted cloud <br>data search service that allows for multi-keyword queries and provides result similarity ranking to meet the needs of effective data retrieval. While previous works on searchable encryption have focused on single keyword search or Boolean keyword search, they have rarely differentiated the search results. In this paper, we address the challenging problem of privacy-preserving multi-keyword <br>ranked ontology keyword mapping and search over encrypted cloud data (EARM) for the first time. We establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality, given the large number of data users and documents in the cloud.</p> P.DINESHKUMAR, K.GEETHA, V. JEEVA, P.J.ARUN, C.NITHIESH Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Sat, 16 Dec 2023 00:00:00 +0300 Navigating Sentiment Analysis Horizons: A Comprehensive Survey on Machine Learning Approaches for Unstructured Data in Medical Sciences and Science and Technology <p>The increasing field of sentiment analysis on unstructured data has become a focal point of research, witnessing a proliferation of machine learning techniques. This extensive survey investigates into the methodologies embraced by researchers across diverse domains, spotlighting the pivotal role played by automatic feature learning and word embedding models in the booming success of sentiment analysis approaches. The exploration of sentiment analysis techniques, the survey unravels the workings of Support Vector Machine (SVM), Naive Bayes (NB), Artificial Neural Networks (ANN), Decision Trees (DT), K Nearest Neighbour (k-NN), Random Forest (RF), and metaheuristic optimization algorithms, elucidating their time complexities, advantages, and limitations. By synthesizing the challenges faced by researchers, the survey not only offers prominent insights but also depicts the course for future investigations, presenting an open issue in the sentiment analysis. The discourse extends beyond theoretical considerations to practical <br>applications, evaluating the performance of sentiment analysis techniques across a spectrum of real-world datasets. As a comprehensive resource, this survey provides researchers and practitioners with a understanding of the evolving paradigm, fostering informed decision-making and inspiring future innovations in sentiment analysis on unstructured data within the paradigm of machine learning.</p> P.SUGANYA, G.VIJAIPRABHU, G. SIVAKUMAR, K. SATHISHKUMAR Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Tue, 12 Dec 2023 00:00:00 +0300 Keap1-Nrf2/ARE signaling pathway- A promising therapeutic pathway for diseases: A Review <p>Oxidative stress is the major causes of development and progression of many diseases. Nrf2 is a transcriptional factor that regulates the stress response by binding with ARE in nucleus and causes induction of antioxidant genes and phase 2 detoxifying enzymes. In normal conditions Nrf2 inhibited by Keap 1 and during redox imbalance or oxidative stress, Nrf2 gets activated. During such <br>condition Nrf2 activity eventually gets increased and causes the expression of antioxidant genes like HO-1 (Heme oxygenase-1), NQO-1 (NADPH quinone oxidoreductase 1), glutathione peroxidase. Thus, Nrf2-ARE pathway plays important role in diseases like liver disorders, respiratory diseases, inflammatory diseases, neurodegenerative diseases etc.</p> SHIBLANASRIN, VIVEK D., SHAHIN MUHAMMED T K, MRIDULA K, NAYANTHARA K.B. Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Tue, 26 Sep 2023 00:00:00 +0300 Strategies for improving lipid production from various renewable residues using modern computational approaches – A review <p>Over the last decade, there is increasing emphasis over “go-green” mantra for eco-friendly production especially over the fuel industry. The environmental hazard and vulnerability of fossil fuels due to prolonged usage has paved way for bio based fuel production. Lipids are the current trend of research significantly because of their capability to produce biodiesel. This review focuses on exploring the viable production process from various low cost substrates giving high yield. The researchers now target a wide range of microorganisms to synthesize lipids and thus biodiesel. However the volume of fuel generated by microbes is not sound enough to be marketed. This demands extensive research with various microbes and substrates. This work of literature discusses the merits and demerits of various microbial strains and alternative feedstock. This also throws light over the advances in process parameters, lipid extraction methods and conversion of lipids to biodiesel. The final sections of this review give an overview of the cost analysis and the future perspectives of biolipid production.</p> J. IYYAPPAN, BABURAO GADDALA, G. BASKAR, M. GOPINATH, R. HANISHA, A. MUTHULAKSHMI Copyright (c) 2023 International Journal of Pharmacy Research & Technology (IJPRT) Sun, 03 Dec 2023 00:00:00 +0300