Journal of Pharmaceutical Analysis and Drug Research ISSN: 3108-0839 (Online)

Authors : Dr. Richa Sharma, Mr. Aditya K. Mehta

Abstract: Artificial Intelligence (AI) is revolutionizing pharmaceutical analysis by enhancing efficiency, accuracy, and predictive capabilities. AI algorithms, including machine learning, deep learning, and neural networks, enable automated detection, quantification, and prediction of pharmaceutical properties. Applications include spectral analysis, chromatographic data interpretation, impurity profiling, dissolution studies, and predictive stability modeling. Integration of AI with analytical instrumentation improves data handling, reduces human error, and accelerates drug development cycles. This paper reviews current applications, analytical techniques, regulatory considerations, and future perspectives of AI in pharmaceutical analysis. Tables summarize AI applications, analytical tools, and performance parameters. Emphasis is placed on harnessing AI to achieve robust, reproducible, and quality-driven analytical outcomes.

Keywords: Artificial Intelligence, Machine Learning, Pharmaceutical Analysis, Predictive Modeling, Spectroscopy, Chromatography, Drug Quality Assessment