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Abstract
The integration of artificial intelligence into microfluidic platforms is transforming drug delivery systems.
- Microfluidics allows for precise control of small fluid volumes, facilitating the production of uniform drug carriers.
- Traditional manual optimization methods are often insufficient for navigating the complex parameter space of microfluidic reactors.
- Artificial intelligence techniques, including machine learning and deep learning, can enhance the design and optimization of drug delivery systems.
- AI integration supports the development of self-driving laboratory workflows that may streamline drug formulation processes.
- The regulatory environment surrounding AI-assisted pharmaceutical development is evolving as these technologies advance.
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