Artificial Intelligence in Pharmaceuticals and Medicine: Regulation, Practice, And Use Cases
In recent years, artificial intelligence (AI) has evolved from an experimental technology into one of the key drivers of transformation in the pharmaceutical industry and the healthcare system as a whole. Machine learning and big data analysis algorithms are used at all stages of the drug life cycle—from molecular target discovery and molecule design to clinical trials, pharmacovigilance, and personalized therapy. At the same time, AI is increasingly being used directly in medical practice: in diagnosis, disease progression prediction, clinical decision support, and robotic surgery.
Such widespread implementation of AI is accompanied by significant legal, ethical, and regulatory challenges. These include the opacity of algorithms ("black box"), the risk of systematic errors and data bias, issues of liability allocation between the physician, the medical organization, and the developer, as well as the protection of patients' personal medical data. This review combines an analysis of AI regulation in pharmaceuticals and medicine in Russia, the European Union, and the United States with practical cases of AI use and court practice, forming a comprehensive picture of the current state and trends in development.