Artificial intelligence for optimizing recruitment and retention in clinical trials: a scoping review

Abstract

Abstract Objective The objective of our research is to conduct a comprehensive review that aims to systematically map, describe, and summarize the current utilization of artificial intelligence (AI) in the recruitment and retention of participants in clinical trials. Materials and Methods A comprehensive electronic search was conducted using the search strategy developed by the authors. The search encompassed research published in English, without any time limitations, which utilizes AI in the recruitment process of clinical trials. Data extraction was performed using a data charting table, which included publication details, study design, and specific outcomes/results. Results The search yielded 5731 articles, of which 51 were included. All the studies were designed specifically for optimizing recruitment in clinical trials and were published between 2004 and 2023. Oncology was the most covered clinical area. Applying AI to recruitment in clinical trials has demonstrated several positive outcomes, such as increasing efficiency, cost savings, improving recruitment, accuracy, patient satisfaction, and creating user-friendly interfaces. It also raises various technical and ethical issues, such as limited quantity and quality of sample size, privacy, data security, transparency, discrimination, and selection bias. Discussion and Conclusion While AI holds promise for optimizing recruitment in clinical trials, its effectiveness requires further validation. Future research should focus on using valid and standardized outcome measures, methodologically improving the rigor of the research carried out.