Drug discovery
27 articles · search the full text for this term
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Medicinal Properties of Oxytenanthera abyssinica: A Narrative Review
Abstract: Oxytenanthera abyssinica, a plant local to the African landmass, has gotten a parcel of intrigued in later a long time for its conceivable restorative benefits; it has been utilized in conventional medication for decades since of its assumed mending capabilities. In spite of its long history, careful logical examination into its restorative potential is being attempted. This review paper explore into the multidimensional part of O. Abyssinica is in progressed …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 13, Issue 2, 2026 Read article
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The Dual Crisis: Antibiotic Resistance and the Discovery Void – A Review of Novel Therapeutic Strategies and Non-Traditional Approaches
Abstract: The global rise of antimicrobial resistance (AMR) has emerged as one of the most critical public health challenges of the 21st century, threatening to undermine decades of therapeutic success and rendering conventional antibiotic regimens increasingly ineffective. Parallel to the escalating resistance rates is a profound “discovery void,” characterised by a steep decline in the development of new antibiotic classes since the late 20th century. Together, these two interconnected crises create …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 47–65 Read article
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Green Medicines in Drug Discovery
Abstract: The process of finding new leads for medicines using natural products is challenging. It discusses bioactive composites generated from natural resources, including phytochemical analysis, characterization, and pharmacological investigation. The success of these resources in the process of discovering unique and effective pharmacological combinations that may help mortal coffers is the primary focus. Natural goods have long been employed as a source of medicinal compounds, and they have shown promising results. …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 1, 2026 · pp. 32–48 Read article
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Exploring the Intersection of AI Network Pharmacology and Ayurveda: Innovations in Traditional Medicine
Abstract: Integrative frameworks that integrate traditional medicine and modern computer research are increasingly important for advancing evidence-based, individualized healthcare. One interesting strategy is the combination of Ayurveda, network pharmacology, and artificial intelligence (AI). AI expands the capability by allowing for the quick analysis of biomedical big data, the identification of therapeutic trends, and the optimization of treatment plans. Ayurveda, with its long-standing emphasis on individualized care, holistic balance, and natural remedies, …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 92–98 Read article
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Application of Artificial Intelligence in Drug Discovery
Abstract: The application of artificial intelligence (AI) in medicine, especially through machine learning (ML), is revolutionizing new-age drug discovery research. AI is found as an efficient and powerful tool to narrow the gap between disease detection and developing and identifying potential therapeutic agents for a cure. This review provides a summary of the latest developments in AI and its potential application in drug discovery for untreatable diseases. The review also examines …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Accelerating Drug Discovery with AI: Transforming the Pharmaceutical Pipeline
Abstract: The revolutionary potential of artificial intelligence (AI) is examined in this essay the pharmaceutical industry, highlighting its application across the drug development lifecycle. Artificial Intelligence, specifically via deep learning models and machine learning (ML) such as GANs, RNNs, and transformers, enhances drug discovery, formulation, toxicity prediction, and clinical trials. It streamlines processes like identification of targets, virtual screening, modelling of structure-activity relationships, and medication repurposing. AI is also employed in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 77–84 Read article
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AI and ML in the Chemical Industry: A Review of Transformative Applications and Future Prospects
Abstract: The chemical industry, a key growth indicator of the global manufacturing ecosystem, is experiencing a digital transformation driven mainly by advancements in Artificial Intelligence (AI) and Machine Learning (ML) in this sector. These technologies are totally revolutionizing current and traditional methodologies by significantly improving process efficiency, reducing costs of manufacturing, accelerating R&D, and improving safety and sustainability standards. Proper utilization of Artificial intelligence (AI) and machine learning (ML) in chemical …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Pharmacy Teachers' Contribution to Preserving Education's Integrity and Quality in the AI Era
Abstract: Artificial Intelligence through its modern approach supports the development of pharmacy education through customized methods and automatic evaluation systems and computerized training exercises. Students benefit from AI tools which include intelligent tutoring systems together with virtual assistants and simulation platforms because these tools improve their knowledge of pharmacology and drug formulation as well as clinical practice. The transition to AI-controlled education creates new academic integrity issues and ethical problems and …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 20–42 Read article
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Current Updates On Employability Of Artificial Intelligence In Healthcare Science & Research
Abstract: Over the centuries, tools have been developed to increase refinement to manipulate different tools in many ways to use human digital computers. It can perform the same types of numerical and symbolic operations that can be done by ordinary people, but faster and more reliable. Artificial intelligence algorithms applied to computer applications and software. Include knowledge-based systems. AI is the science that mimics the mental skills of humans in computers. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 72–77 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Revolutionizing Healthcare: AI in Drug Discovery and Pharmacy Practices
Abstract: Artificial intelligence (AI) has emerged as a revolutionary element across numerous sectors, especially in healthcare and pharmacy. AI systems that can execute functions typically necessitating human intelligence, such as learning, problem-solving, and speech recognition, are poised to transform drug discovery, enhance patient care, and reshape pharmacy practices. AI can help discover drugs with predicting interactions with drug destinations, virtual screening, drug reuse, and drugs that accelerate the development of effective …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 94–100 Read article
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A Study on The Impact of Artificial Intelligence in Pharmaceuticals
Abstract: The main goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem-solving, and decision-making. AI is becoming more and more significant in several pharmacy domains, including polypharmacology, hospital pharmacy, drug discovery, and drug delivery formulation development. Various types of artificial neural networks (ANNs), including deep neural networks (DNNs) and recurrent neural networks (RNNs), are utilized in the development of drug delivery formulations and in drug …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 24–32 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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From Clinic Formulation to Development of Acebrophylline
Abstract: Acebrophylline, a commonly utilized bronchodilator with anti-inflammatory properties, has become a key therapeutic option for managing respiratory conditions like asthma, chronic obstructive pulmonary disease (COPD), and chronic bronchitis. This review explores the journey of Acebrophylline from its clinic formulation to its development and commercialization, focusing on the key aspects of formulation strategies, pharmacological properties, and regulatory considerations. The drug’s dual mechanism of action, which involves both bronchodilation and anti-inflammatory effects, …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 35–48 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Computational Biomodeling: Transforming Drug Design with Advanced Simulations
Abstract: Computational biomodeling has emerged as a transformative approach in the field of drug discovery, significantly enhancing the efficiency and precision of identifying and optimizing potential drug candidates. This article explores the various computational techniques utilized in drug design, including molecular docking, molecular dynamics (MD) simulations, free energy calculations, and virtual screening, and examines how these methods collectively contribute to the drug development process. The integration of these advanced simulations allows …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 24–29 Read article
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A Review of Drug Design Techniques Assisted by Computers to Combat Diabetes
Abstract: Diabetes mellitus is a global health concern characterized by chronic hyperglycemia and associated complications. The creation of innovative medicines with enhanced efficacy and safety profiles continues to be a top focus, notwithstanding improvements in treatment. A useful method in drug development, computer-aided drug design (CADD) makes it easier to identify possible therapeutic candidates and optimise lead molecules. An extensive synopsis of CADD tactics used in the fight against diabetes is …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 1–10 Read article
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Review on Computer-Aided Drug Design in RAS Inhibitor Discovery
Abstract: This review explores the utilization of computer-aided drug design (CADD) methodologies in the discovery of inhibitors targeting the RAS pathway, a pivotal signaling cascade implicated in various cancers. Through an extensive examination of computational tools, methodologies, challenges, and recent advancements, this review aims to provide insights into the role of CADD in accelerating RAS inhibitor discovery. The discovery of effective inhibitors targeting the RAS pathway is of paramount importance in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 3, 2024 · pp. 7–14 Read article
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Modern Computer-aided Drug Design Methods: A Review
Abstract: Computer-aided drug design (CADD) has emerged as a crucial tool in the drug discovery process, offering a time-efficient and cost-effective approach to identifying potential drug candidates. This review aims to provide an overview of modern CADD methods, including high-throughput screening (HTS), structure-based drug design (SBDD), ligand-based drug design (LBDD), structure-based virtual screening (SBVS), and ligand-based virtual screening (LBVS). We discuss the basic principles, applicability, and limitations of each method, highlighting …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 2, 2024 · pp. 14–20 Read article
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Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review
Abstract: Quantitative Structure-Activity Relationship stands at the forefront of Computer-Aided Drug Design, providing a systematic framework for understanding the relationship between the chemical structure of molecules and their biological activity. The present review delves into the multifaceted realm of quantitative structure-activity relationship methodologies within the landscape of drug discovery. Through an exploration of diverse quantitative structure-activity relationship models, molecular descriptors, validation techniques, and recent advancements, the present article aims to elucidate …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 55–63 Read article