On the Application of Artificial Intelligence and Cloud-Native Computing to Clinical Research Information Systems: A Systematic Literature Review

The pharmaceutical and biotechnology sector is an intricate and rapidly evolving industry encompassing the full lifecycle of drugs, medicines, and clinical devices. Its growth is driven by factors such as the aging population, the rise in chronic diseases, and the increasing focus on personalized medicine. Nevertheless, it also faces significant challenges due to rising costs, increased complexity, and regulatory hurdles. Through a systematic literature review (SLR) as a research method combined with a comprehensive market analysis, this paper explores how several leading early-adopter healthcare companies are increasing their investments in computer-based clinical research information systems (CRISs) to sustain productivity, particularly through the adoption of artificial intelligence (AI) and cloud-native computing. As an extension of this research, a novel 360-degree reference blueprint is proposed for the domain analysis of medical features within AI-powered CRIS applications. This theoretical framework specifically targets clinical trial management systems (CRIS-CTMSs). Additionally, a detailed review is presented of the leading commercial solutions, assessing their portfolios and business maturity, while highlighting major open innovation collaborations with prominent pharmaceutical and biotechnology companies.