AI applications in drug discovery and personalized medicine

Abstract

The era of artificial intelligence (AI) in drug discovery and personalized medicine is bringing a new twist to the healthcare field, enhancing the ability to identify the target, develop drugs, and design personal treatment regimens when taking into account the profile of a particular patient. They allow for incorporation of complex multi-modes data like genomic, proteomic, and clinical data and predict new biomarkers and therapeutic targets based on AI models like convolutional neural networks (CNN), graph neural networks (GNN), and generative adversarial networks (GAN). These powerful AI models are created by training models in a decentralized manner but with data kept private (federated learning techniques) and may be employed to solve global health challenges. However, such promise is accompanied by issues in the broad clinical deployment of AI like model interpretability, regulatory hurdles, computational bottlenecks, and the need for in-the-field testing. Toward increased alignment of AI research and clinical practice by addressing GBE 2 through implementation of XAI techniques, deployment of models with continuous monitoring across RWD, and adherence to the international regulatory norms. Moreover, the potential of AI to battle global health inequity through democratization of cutting-edge healthcare technologies is necessary to embrace inclusive and diverse personalized medicine. In order to develop a means for facilitating fair AI usage by various demographics, incorporation of transparency and ethics into the data training, as well as data privacy, informed consent, and immunity from algorithmic bias is needed. Future and current projects seek to create this synergy that involves machine learning, biochemistry, and pharmacology and establish new regulatory norms, eventually leading to the creation of scalable, interpretable, generalizable models that will optimize drug development and patient care and healthcare disparities globally. One of these will be near to set AI on a new path of precise treatment and transfigurative health innovation.