AI-Enhanced Drug Discovery: Accelerating the Development of Targeted Therapies
Abstract
The process of drug discovery is complex, time-consuming, and expensive. This paper explores how AI and machine learning are being used to accelerate drug discovery by predicting the efficacy of potential drug compounds, identifying new drug targets, and optimizing clinical trial designs. We examine the application of deep learning algorithms, such as neural networks and reinforcement learning, in screening large chemical libraries and predicting drug interactions. The paper also discusses the integration of AI in personalized medicine, where AI can help identify patients who would benefit most from specific therapies, thus reducing trial and error in drug development.
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