AI in Pharma R&D: Bridging Breakthroughs and Future Frontiers

The review is devoted to the use of artificial intelligence (AI) in scientific research and development to create new or repurpose authorized drug products, as well as to the use of AI-based solutions to discover new biomarkers and shorten the time to diagnosis of various diseases. The following areas of AI application are considered: the search for new pharmacologically active substances, the development of formulations and drug production technology, preclinical trials, and intelligent diagnostics (identification of new biomarkers; development of software products to interpret research results and increase diagnostic accuracy). Examples of AI use by leading pharmaceutical companies and a list of the most popular AI models in drug development are provided. The revolutionary contribution of AI in drug discovery lies in reducing the time to identify new drug candidate molecules by more rapidly identifying potential biotargets, performing virtual screening, optimizing promising candidates based on predictive data on pharmacokinetic and toxicological profiles, and searching for the optimal way to synthesize potential drugs. In addition, another area of AI application is the development of drug-delivery devices and systems that improve patient compliance and usability. This paper presents examples of AI use in intelligent diagnostics that prove their high accuracy and time efficiency compared to conventional methods of diagnostics, risk assessment, and prognosis in oncology, cardiology, and other areas of medicine. The implementation of AI technologies in medicine is intensifying, raising questions of ethics, the quality and adequacy of data, the effectiveness and safety of results for patients, personnel competence and readiness for change, as well as issues related to intellectual property rights.