Trends in the industry of clinical trials - S. S. Milovanov; V. V. Popov; N. V. Teplova (Фармакоэкономика)
Background. The clinical trial (CT) industry is subject to changes, some of which are rapidly developing and their directions can be predicted, while others develop gradually, forming stable tendencies, which requires analysis to confirm and predict them. According to the generally accepted time gradation, there are an operational (up to 1 month), short-term (up to 1 year), medium-term (up to 5 years), long-term (up to 20 years), and long-term (over 20 years) prognoses. A short-term forecast is common in CT industry.Objective: to identify trends in the development of CT industry until the end of 2024.Material and methods. We searched publications in Russian and English segments of the Internet in open access sources in ClinicalTrials.gov, PubMed/MEDLINE, Google Scholar, Academia, ResearchGate, CyberLeninka, eLibrary databases by key query “trends in clinical trials” for the period from January to March 2023. The query “history of clinical trials” was also used in Russian part of the Internet through Google search. The analysis included publications on the history of CT development over 1936–2023. The total number of sources analyzed was 59 (9 Russian and 50 English).Results. The tendencies in CT development can be divided into two groups. The first one is related to CT organization and conducting, while another is associated with development of innovative drugs. In the first group, the trends have persisted since 2022 and are expressed in the ongoing digitalization of operational activities, a shift from centralized research to decentralization, while the protocol design has changed towards patient-centricity. In the second group, the number of expected drugs has decreased and a shift towards biological drugs, gene and cell therapy has become more pronounced.Conclusion. Trends in CI are characterized by a number of innovations, primarily related to digitalization, the development of telemedicine technologies, mathematical modeling, artificial intelligence, virtual CI, decentralization and patient-centricity.