The Role of Artificial Intelligence in the Formulation, Characterization, and In-Vitro Prediction of Liposomal Nanomedicines for Nutraceutical Applications
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Abstract
The integration of artificial intelligence (AI) into nutraceutical sciences is revolutionizing the development of nanomedicines, offering significant advantages in streamlining processes and enhancing precision. This review article emphasizes the application of AI in three key areas of liposomal formulation development. Firstly, in formulation design, AI-driven platforms and machine learning (ML) algorithms predict optimal compositions and process parameters, reducing the need for traditional,. Secondly, AI enhances characterization and quality control by automating data analysis from methods such as transmission electron microscopy (TEM) and dynamic light scattering (DLS), providing high-throughput and reproducible results while minimizing human error. AI algorithms can also integrate data from various sources to ensure real-time batch consistency. Lastly, AI models are crucial for in-vitro prediction, simulating molecule release kinetics, cellular uptake, and safety profiles to de-risk lead formulations before costly clinical trials. The article underscores that for manufacturers like West Bengal Chemical Industries Ltd., Kolkata, India (WBCIL), leveraging these AI applications can enhance product quality, improve formulation efficiency, and increase industrial scalability.
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