A review on machine learning in pharmaceutical applications
Keywords:
Machine Learning, Artificial Intelligence, Drug Discovery, Quality by Design, Deep Learning, Clinical Trials, Regulatory GuidelinesAbstract
Despite these advancements, challenges remain, including data quality, regulatory considerations, ethical concerns, and the need for transparency and accountability. Regulatory bodies are developing frameworks to ensure the safety and efficacy of AI-driven drug development. Future advancements include multi-task learning, personalized medicine, and AI integration with robotics and automation, which promise to further streamline drug development. This review provides a balanced perspective on AI/ML in pharmaceuticals, discussing key concepts, case studies, and emerging trends.
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