Drug Disease Association

Drug-disease association research focuses on computationally predicting which drugs might effectively treat which diseases, accelerating drug development and repurposing existing medications. Current research emphasizes machine learning approaches, including contrastive learning, self-supervised learning, and neural network architectures, to overcome challenges like limited labeled data and the need for robust feature representation of drugs and diseases. These computational methods aim to improve the efficiency and reduce the cost of drug discovery by identifying potential therapeutic uses for existing drugs, ultimately impacting patient care and pharmaceutical innovation.