Abstract
Artificial intelligence (AI) is revolutionizing the field of drug discovery by streamlining processes, enhancing predictive models, and improving efficiency. Machine learning (ML) algorithms, particularly deep learning, have shown great promise in identifying potential drug candidates and optimizing clinical trial designs. AI applications range from molecular simulation and drug repurposing to the development of personalized medicine strategies. Despite its potential, challenges such as data quality, model interpretability, and regulatory concerns need to be addressed. This article discusses the current advancements in AI-driven drug discovery and the hurdles faced, highlighting its future potential in transforming the pharmaceutical industry.
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