Drug Discovery

Drug discovery, the process of identifying and developing new therapeutic agents, is being revolutionized by artificial intelligence. Current research focuses on improving the accuracy and efficiency of computational models for predicting molecular properties, drug-target interactions, and pharmacokinetics, employing techniques like graph neural networks, transformers, and diffusion models, often enhanced by self-supervised learning and multi-task learning strategies. These advancements aim to accelerate the lengthy and expensive drug development pipeline, ultimately leading to faster identification of effective and safer drugs. The integration of large language models and quantum computing further expands the possibilities for innovative drug design and discovery.