Abstract
The application of artificial intelligence (AI) in drug discovery is transforming the pharmaceutical industry, enhancing the efficiency and accuracy of the drug development process. Neural networks, a type of machine learning model, have shown great promise in analyzing complex biological data and identifying potential drug candidates. This article explores the role of neural networks in pharmaceutical research, focusing on their applications in drug discovery, including predicting molecular interactions, optimizing compound screening, and designing novel drugs. Additionally, the article examines the challenges and opportunities of integrating AI-driven approaches into the drug discovery pipeline and their potential to revolutionize the future of medicine.
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