Pharma - AI: Decoding Drug with AI

M. Vishnu Vardhana Rao; S. Srinidhi; G. Shivani; B. Deekshitha; A. Kalyani

doi:10.62127/aijmr.2026.v04i02.1283

Pharma - AI: Decoding Drug with AI

Author(s)	M. Vishnu Vardhana Rao, S. Srinidhi, G. Shivani, B. Deekshitha, A. Kalyani
Country	India
Abstract	The pharmaceutical industry generates massive amounts of complex data related to drug composition, interactions, side effects, clinical trials, and therapeutic outcomes. Traditional methods of analysing such data are often slow, error-prone, and require extensive manual effort, which limits the speed of drug discovery and decision-making. To address these challenges, PHARMA-AI: Decoding Drugs with AI presents an intelligent, automated framework designed to enhance drug analysis and accelerate pharmaceutical research through advanced artificial intelligence techniques. The proposed system integrates machine learning, natural language processing (NLP), and predictive analytics to extract meaningful patterns from structured and unstructured drug-related datasets. By leveraging these AI models, the system can predict drug interactions, classify drug categories, identify potential adverse effects, and analyse chemical similarities with improved precision. The platform also incorporates an interactive user interface that allows researchers, students, and healthcare professionals to seamlessly explore drug information, visualize relationships, and generate insights for informed decision-making. The system architecture includes modules for data preprocessing, feature extraction, model training, and real-time prediction. Machine learning algorithms such as classification and clustering models are employed to categorize drugs and detect hidden patterns, while NLP techniques help in understanding descriptive medical data. The implementation demonstrates significant improvements in accuracy, efficiency, and processing speed when compared to traditional manual drug analysis approaches. Experimental results highlight the ability of the tool to reduce analysis time and support early-stage drug discovery by offering reliable predictions and comprehensive data insights. Overall, PHARMA-AI demonstrates how artificial intelligence can transform drug research by providing a scalable, automated, and intelligent solution. The system contributes to bridging the gap between pharmaceutical research and modern computational techniques, paving the way for faster innovation, enhanced medical safety, and improved healthcare outcomes.
Keywords	Artificial Intelligence (AI); Drug Discovery; Machine Learning; Natural Language Processing (NLP); Predictive Analytics; Pharmaceutical Data Analysis; Drug Interaction Prediction; Healthcare Decision Support; Data Preprocessing; Feature Extraction.
Discipline	Engineering
Published In	Volume 4, Issue 2, March-April 2026
Published On	2026-04-12
DOI	https://doi.org/10.62127/aijmr.2026.v04i02.1283

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Pharma - AI: Decoding Drug with AI

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