Journal of Applied Pharmaceutical Sciences and Research

PHARMACOGNOSTICAL,PHYTOCHEMICAL AND PHARMACOLOGICAL STUDY OF BOERHAAVIA DIFFUSA - AN AYURVEDIC BOON FOR LIVER CARE

2024-10-25T22:36:54+0530

Boerhaavia diffusa Linn. is a plant that holds significant importance in the field of medicine due to its various therapeutic properties. It has been extensively studied and proven to have hepatoprotective, anti-diabetic, and anti-inflammatory effects. These beneficial attributes have been documented in numerous Ayurvedic texts, making it a key ingredient in many pharmaceutical preparations. The information for this review was acquired from a wide range of literature sources, like Google Scholar, Research Gate, Science Direct, and PubMed to comprehensively understand phytochemistry and the pharmacological activity of B. diffusa. A systematic and structured search strategy was employed to ensure diverse perspectives and findings, that describe the plant's botanical description, traditional uses, chemical composition, pharmacological activities specifically its hepatoprotective effects, and safety profiles. This comprehensive review examines the therapeutic potential of B. diffusa, with a focus on its hepatoprotective effects. The aim is to link traditional knowledge and scientific understanding, offering a valuable resource for researchers, healthcare practitioners, and enthusiasts interested in the multifaceted aspects of this plant. By combining information from Ayurvedic texts and modern scientific studies, the review seeks to contribute to evidence-based research, validate traditional remedies, and promote further exploration of B. diffusa's therapeutic applications, especially in the treatment of liver-related disorders.

THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN PHARMACOGNOSY: ADVANCES AND APPLICATIONS

2024-10-25T22:36:54+0530

A new era of natural product research has been brought about by the application of computational intelligence (also known as AI) into pharmacognosy, which has greatly improved the identification, examination, and creation of therapeutic chemicals originating from natural sources. This review comprehensively examines the role of AI in modern pharmacognosy, highlighting recent advances and diverse applications. Key areas of focus include AI-driven methods for natural product identification, compound isolation, bioactivity prediction, and structure elucidation. Machine learning algorithms and neural networks are increasingly utilized to analyze complex biological data, predict pharmacological properties, and streamline the drug discovery process. Furthermore, AI technologies facilitate the optimization of extraction processes and the development of novel formulations, contributing to improved efficacy and safety profiles of natural products. Case studies illustrate successful implementations of AI in pharmacognosy, demonstrating its potential to overcome traditional challenges and accelerate research timelines. This review also highlights some biological activities predicted with the help of AI. It also discusses the ethical considerations, potential limitations, and future directions of AI applications in this field. Overall, AI stands as a transformative tool in modern pharmacognosy, offering unprecedented opportunities for advancing natural product research and development.

AN APPROACH TO UNDERSTAND SIMILARITIES BETWEEN AI AND THE HUMAN BRAIN

2024-10-25T22:36:54+0530

Artificial intelligence (AI) and neuroscience have a long history of working together. The daily social and economic activities are supported by artificial intelligence (AI), which is a significant piece of technology. One of today's most hotly disputed topics is artificial intelligence (AI), and there doesn't seem to be much agreement on how human and artificial intelligence vary and overlap. Discussions on a variety of relevant subjects, including ethics, healthcare, agriculture, education, and trustworthiness, are marked by implicit anthropocentric and anthropomorphic assumptions. It significantly supports Japan's economy's sustainable growth and provides solutions to a number of societal issues. AI has gained attention recently as a means of fostering growth in both industrialized nations like the United States and Europe as well as developing nations like China and India. Deep neural networks (DNNs), which have grown to be potent and common tools to simulate human cognition and frequently generate similar behaviours, can also be described as AI. DNNs appear to categories real-world images in the same way as people do, for instance, thanks to their hierarchical, brain-inspired organization of computations. Deep neural networks (DNNs), a subset of the larger machine learning family, are becoming more and more effective in commonplace real-world applications like automated face recognition and self-driving automobiles. The School of Psychology and Neuroscience at the University of Glasgow has recently published new research in the journal Trends in Cognitive Sciences that takes an approach to understanding whether the human brain and its DNN models recognize things in the same way, using comparable steps of computation.

QUALITY BY DESIGN STRATEGY FOR DEVELOPMENT AND VALIDATION OF AN RP- HPLC METHOD FOR MARKER-BASED STANDARDIZATION OF FISETIN IN MARKETED HERBAL PREPARATIONS

2024-10-25T22:36:54+0530

Introduction: This study underscores the importance of QbD in developing pharmaceutical processes, with a strong emphasis on risk assessment. It demonstrates how QbD principles were applied to create a reliable and cost-effective HPLC method for fisetin capsules, ensuring consistent quality within defined criteria. Method: The method, developed through a rigorous Design of Experiment approach, employs an isocratic elution method using a Chemsil ODS-C18 column with a mobile phase composition of 70:30 methanol to 0.1% OPA. Detection of peaks was achieved with a UV detector set at 362 nm, and an optimal flow rate of 1.0 mL/min was determined. The column oven was maintained at an ambient temperature, and the injection volume was set at 10 μL. Result: Thorough validation following ICH Q2 (R1) guidelines verifies the method’s reliability. Key parameters evaluated during this process include linearity, which was established over a range of 10 to 50 μg/mL with an r² value of 0.997; LoD and LoQ, determined to be 2.903 and 8.797 μg/mL, respectively; and precision and robustness, with %RSD values found to be below 2%. Furthermore, accuracy and assay tests were performed, and the results were within the acceptable range as specified by ICH guidelines. Discussion and Conclusion: The method is particularly suitable for analyzing fisetin capsules in the pharmaceutical industry due to its remarkable sensitivity, selectivity, precision and accuracy. Designed for routine pharmaceutical quality control, this method effectively distinguishes between marketed drugs and the innovator product.

PHYSICO-CHEMICAL STANDARDIZATION AND PHYTOCHEMICAL SCREENING OF POTENTIAL MEDICINAL HERB: RUBIA CORDIFOLIA (ROOTS)

2024-10-25T22:36:54+0530

Rubiacordifolia L., (Rubiaceae) frequently diagnosed as Indian Madder is a crucial medicinal plant used in Indian normal treatment for curing pretty a variety disease. The present research about used to be as soon as carried out to analyze the biologically vigorous compounds current in Rubiacordifolia root, stem and leaf of a vary of solvent extracts i.e., Methanol, acetone, chloroform, petroleum ether and aqueous. The phytochemical screening posted that they have been fantastic for anthraquinones, glycosides, flavonoids, steroids, phenols and saponins and had been bad for alkaloids, tannins and quinones of all solvent extractions. The crude dried plant fabric was once subjected to the physico-chemical evaluation. A fluctuate of parameters such as extractive value, moisture content, ash cost at the equal time with acid insoluble and water-soluble ash and so forth have been evaluated with the truly encouraged motivated honestly beneficial recommended beneficial useful resource of way of the utilization of contemporary day procedures. The Loss on Drying (L.O.D.), Ash Values (total ash, acid insoluble ash, water soluble ash). Water soluble extractive, alcohol soluble extractive of dried root powder. The presence of these biologically full of existence compounds in R. cordifolia, a treasured medicinal plant precipitated except a doubt absolutely endorsed advocated actually beneficial really helpful beneficial aid that this plant is being used as medicinal drug for curing fairly an extent health hassle in every and each and every and each day medicinal constructions and can in addition be employed in the remedy of a fluctuate of ailments in producer new day remedy too.

IN-SILICO EVALUATION OF ROSIGLITAZONE PRODRUG AGAINST NEURODEGENERATIVE DISEASE

2024-10-25T22:36:54+0530

Introduction: This study explores the molecular interactions and pharmacokinetic properties of a prodrug, rosiglitazone their potential as therapeutic agents. Material and Methods: Molecular docking was conducted using AutoDock Vina, with the prodrug showing the strongest binding affinity (-10.5 kcal/mol) compared to rosiglitazone (-10.2 kcal/mol) and the co-crystallized ligand (-9.4 kcal/mol). Result and Discussion: Detailed interaction analysis revealed that the prodrug forms multiple hydrogen bonds and π-π interactions, particularly with Trp286 and His447, highlighting its strong binding capacity. Rosiglitazone demonstrated similar interactions, though with fewer bonding sites. Absorption, distribution, metabolism, and excretion (ADME) profiling was performed to assess pharmacokinetic properties using Swiss ADME. The prodrug and rosiglitazone exhibited high gastrointestinal absorption but were not permeant to the blood-brain barrier (BBB). In contrast, reticuline was found to cross the BBB, making it a strong candidate for central nervous system (CNS) applications. Reticuline, however, is a P-glycoprotein (Pgp) substrate, which may affect its bioavailability due to efflux transport mechanisms. All compounds showed no violations of Lipinski’s rules, indicating favorable drug-like properties, with a bioavailability score of 0.55. Conclusion: The study concludes that the prodrug, with its superior binding affinity and favorable ADME properties, holds significant promise for systemic therapies, while reticuline’s BBB permeability makes it a potential candidate for CNS-targeted treatments. Further research is warranted to optimize their clinical applications.