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*Corresponding Author E-mail: patelmehul7295@gmail.com
The integration of artificial intelligence (AI) into QbD frameworks has further revolutionized this process, enabling enhanced efficiency, precision, and innovation in formulation development. This review explores the role of AI in advancing QbD for pharmaceutical formulations, highlighting its applications, benefits, challenges, and future potential. By analyzing recent advancements, Our goal is to present a thorough grasp of how AI-driven QbD is influencing medication development going forward. Quality by Design (QbD) frameworks that incorporate artificial intelligence (AI) offer a revolutionary method for developing pharmaceutical formulations..This review explores how AI-driven tools enhance the QbD process by optimizing formulation design, predicting critical quality attributes (CQAs), and streamlining risk assessment. By utilizing machine learning models, AI enables accurate determination of essential material characteristics (EMCs) and vital process parameters (VPPs), reducing experimental trial-and-error. The abstract highlights case studies where AI has improved formulation stability, bioavailability, and manufacturing efficiency. Furthermore, it discusses the potential of AI to integrate real-time data analytics for continuous process verification, ensuring robust quality control. The authors emphasize that AI-augmented QbD accelerates development timelines.
Artificial Intelligence (AI), Rheumatoid Arthritis(RA), Essential Quality Characteristics (EQCS), Essential Process Metrics (EPMS), Process Evaluation Technology (PET)