Applying advanced technologies to improve clinical trials: a systematic mapping study
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Applying advanced technologies to improve clinical trials: a systematic mapping study Esther Nanzayi Ngayua1 · Jianjia He1 · Kwabena Agyei‑Boahene2 Received: 22 April 2020 © The Author(s) 2020
Abstract The increasing demand for new therapies and other clinical interventions has made researchers conduct many clinical trials. The high level of evidence generated by clinical trials makes them the main approach to evaluating new clinical interventions. The increasing amounts of data to be considered in the planning and conducting of clinical trials has led to higher costs and increased timelines of clinical trials, with low productivity. Advanced technologies including artificial intelligence, machine learning, deep learning, and the internet of things offer an opportunity to improve the efficiency and productivity of clinical trials at various stages. Although researchers have done some tangible work regarding the application of advanced technologies in clinical trials, the studies are yet to be mapped to give a general picture of the current state of research. This systematic mapping study was conducted to identify and analyze studies published on the role of advanced technologies in clinical trials. A search restricted to the period between 2010 and 2020 yielded a total of 443 articles. The analysis revealed a trend of increasing research interests in the area over the years. Recruitment and eligibility aspects were the main focus of the studies. The main research types were validation and evaluation studies. Most studies contributed methods and theories, hence there exists a gap for architecture, process, and metric contributions. In the future, more empirical studies are expected given the increasing interest to implement the AI, ML, DL, and IoT in clinical trials. Keywords Artificial intelligence · Machine learning · Deep learning · Internet of things · Clinical trials
Introduction The pharmaceutical landscape is rapidly evolving in a manner that is causing an increase in costs and timelines for conducting clinical trials. Randomized clinical trials (RCTs) are the epitome of providing the highest level of evidence for the causal relationship between a clinical intervention and the target outcomes, hence they are commonly applied in the * Jianjia He [email protected] 1
School of Business, University of Shanghai for Science and Technology, Shanghai 200093, China
2
School of Medicine, Tongji University, Shanghai 200092, China
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Vol.:(0123456789)
Scientometrics
innovation of medical solutions (Mayo et al. 2017; Sen et al. 2017). The increasing costs of clinical trials happening amidst a declining global output of medical innovations is a cause for alarm. The last decade is characterized by several failures in drug launches happening at a rate that could be the highest ever encountered (Lodha 2016). About one in every five clinical trials do not complete enrollment of participants due to reasons such as complexities of applying the stringent eligibility criteria and rigid inclusion criteria (Be
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