Journal of Pharmacreations

Analysis of the Analgesic Effects of Jasminum Multiflorum and Jasminum Sambac Formulations in Experimental Mice

2026-04-11T12:26:04+00:00

The present study was undertaken to evaluate the analgesic potential of JM15 (Jasminummultiflorum) and JS25 (Jasminumsambac) formulations using the hot plate method in mice. Both formulations were prepared using successive solvent extraction and supercritical fluid extraction (SFE) techniques to enrich bioactive phytoconstituents. Analgesic activity was assessed by measuring latency to nociceptive response and percentage inhibition of pain threshold. Both formulations significantly increased pain threshold compared to the control group (p < 0.001), with JS25 demonstrating superior efficacy comparable to the standard formulation. The results suggest that Jasminum-derived phytochemicals, particularly flavonoids and lactones, may exert central analgesic effects through modulation of nociceptive pathways.

Artificial Intelligence in Drug Discovery and Development: Current Status, Challenges and Future Prospects

2026-04-24T09:26:34+00:00

The review article examines the transformative influence of Artificial Intelligence (AI) in redefining the paradigms of drug discovery and pharmaceutical development. It explores how progressive innovations in AI methodologies including Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Reinforcement Learning (RL), Graph Neural Networks (GNN), and Generative AI are being strategically harnessed to address critical bottlenecks in the drug development continuum. Key areas of focus include target identification, lead molecule exploration, rational drug design, optimization strategies, and clinical trial orchestration. The review highlights AI's potential to revolutionize the pharmaceutical landscape by expediting drug discovery trajectories and curtailing the costs associated with introducing novel therapeutic entities.

Artificial Intelligence and Machine Learning in Modern Pharmacy

2026-04-24T09:32:59+00:00

Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in the field of modern pharmacy. They offer new possibilities in drug discovery, precision medicine, patient care, and pharmaceutical research. AI algorithms can process massive datasets, identify hidden patterns, and support decision-making, while ML models continuously improve their performance through experience. This review explores the current applications, benefits, and limitations of AI and ML in pharmacy, with a focus on their impact on drug development, disease prediction, and personalized treatment. The paper also highlights ongoing challenges and future directions in integrating these technologies into clinical and research settings.