AI-Driven Drug Discovery: Accelerating Pharmacological Research with Deep Learning
Abstract
Traditional drug discovery is a time-consuming and costly process. This paper explores how AI, particularly deep learning, accelerates drug discovery by predicting molecular interactions and optimizing candidate selection. We implement a generative adversarial network (GAN)-based model to identify potential drug compounds for cancer treatment. Our findings demonstrate that AI-driven drug discovery reduces research timelines and enhances the efficiency of pharmacological breakthroughs, paving the way for faster clinical trials.
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