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AI-Powered Excipient Innovation: Transforming Drug Design, ADMET Profiling, and Formulation Developmen
Shikha Baghel Chauhan1, Indu Singh1, Manya Singh1
1Amity Institute of Pharmacy, Amity University, Noida, UP, 201313, India.
Artificial Intelligence (AI) revolutionizes pharmaceutical excipient engineering by enabling rational drug formulation development. AI optimizes medication delivery, enhances therapeutic effectiveness, and personalizes treatments for improved patient outcomes.
Area of Science:
- Pharmaceutical Sciences
- Computational Chemistry
- Drug Delivery Systems
Background:
- Excipients are evolving from inert carriers to active components influencing drug properties.
- Artificial Intelligence (AI) and Machine Learning (ML) are transforming traditional pharmaceutical formulation approaches.
- Industry 4.0 technologies are integrating with excipient engineering for advanced drug development.
Purpose of the Study:
- To examine the role of AI, ML, and computational modeling in rational excipient engineering.
- To explore AI's application in predicting excipient-API compatibility and optimizing ADMET profiles.
- To discuss the integration of Industry 4.0 technologies in AI-driven formulation design.
Main Methods:
- Utilizing Machine Learning (ML), deep learning, and computational modeling for formulation development.
- Employing Artificial Intelligence (AI) techniques like QSAR models, neural networks, and predictive simulations.
- Leveraging Industry 4.0 tools such as digital twins and high-throughput in silico screening.
Main Results:
- AI accelerates formulation development, enhances safety profiles, and enables virtual screening of novel excipients.
- AI-aided design optimizes leads, identifies synergistic excipients, and addresses challenges in toxicity, stability, and scalability.
- Digital twins and real-time analytics are revolutionizing excipient-based systems.
Conclusions:
- AI in excipient engineering offers a paradigm shift for rational, customized medication development.
- Interdisciplinary collaboration is crucial for addressing ethical, validation, and regulatory aspects of AI adoption.
- This study provides a unified platform for advancing AI-excipient technologies in pharmaceutical research.
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