In this lecture, the pivotal role of data quality in clinical research will be explored, covering clinical trials, studies, and patient registries—all within a highly regulated environment.
In this lecture, we shall explore the challenges posed to clinical research (clinical trials, studies, and patient registries) by compromised data quality, and the technical solutions developed to tackle them. The importance of specialized user-friendly, real-time, regulatory-approved Electronic Data Capture (EDC) systems, together with tailored data management processes, will be discussed, emphasizing how software and algorithmic solutions can help ensure data accuracy, reliability, and integrity. We shall showcase CLADE-IS, a unique system for clinical data management ranging from databasing to the use of ensemble learning, developed through in-house R&D at the Institute of Biostatistics and Analyses, a Masaryk University spin-off.
CLADE-IS has been rigorously evaluated and recently approved by an international auditing team, resulting in the awarding of the prestigious ECRIN certification to the spinoff—the only certified data center in Central and Eastern Europe. This certification, coupled with the system's proven usability and scalability, has already positioned the spinoff as a strong partner in co-managing large international clinical trials. Finally, we will delve into how CLADE-IS ensures high data quality through a combination of processes like Data Reviews, Central Statistical Monitoring, Risk-Based Monitoring, and Data Augmentation, supported by a multidisciplinary team including data engineers, data scientists, data managers, and data analysts.
Daniel Schwarz is an Associate Professor at the Faculty of Medicine, Masaryk University, specializing in neuroscience, biomedical engineering, and medical informatics. His research integrates neuroimaging, machine learning, and decision support systems, with a strong focus on virtual patients in medical education. He co-founded the Institute of Biostatistics and Analyses, a Masaryk University spinoff, where he leads a team that develops healthcare software solutions now implemented in major medical institutions across the Czech Republic and internationally. Daniel has extensive experience leading interdisciplinary research projects, collaborating with hospitals and academic institutions, and bridging academic findings with practical applications. His current work focuses on enhancing data quality in clinical research through advanced data integrity practices. He is also an active member of the executive boards of the Czech Society for 3D Printing in Medicine and the Czech Society for Artificial Intelligence and Innovative Digital Technologies in Medicine, both under the Czech Medical Society of Jan Evangelista Purkyně.
Its program consists of a one-hour lecture followed by a discussion. The lecture is based on an (internationally) exceptional or remarkable achievement of the lecturer, presented in a way which is comprehensible and interesting to a broad computer science community. The lectures are in English.
The seminar is organized by the organizational committee consisting of Roman Barták (Charles University, Faculty of Mathematics and Physics), Jaroslav Hlinka (Czech Academy of Sciences, Computer Science Institute), Michal Chytil, Pavel Kordík (CTU in Prague, Faculty of Information Technologies), Michal Koucký (Charles University, Faculty of Mathematics and Physics), Jan Kybic (CTU in Prague, Faculty of Electrical Engineering), Michal Pěchouček (CTU in Prague, Faculty of Electrical Engineering), Jiří Sgall (Charles University, Faculty of Mathematics and Physics), Vojtěch Svátek (University of Economics, Faculty of Informatics and Statistics), Michal Šorel (Czech Academy of Sciences, Institute of Information Theory and Automation), Tomáš Werner (CTU in Prague, Faculty of Electrical Engineering), and Filip Železný (CTU in Prague, Faculty of Electrical Engineering)
The idea to organize this seminar emerged in discussions of the representatives of several research institutes on how to avoid the undesired fragmentation of the Czech computer science community.
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