The fourth episode focuses on data quality in clinical research, and how it relates to medication adherence. It features Antoine Pironet - a data scientist with a background in biomedical engineering, experienced in analyzing data collected in national registries and data in electronic medical adherence systems. Let's listen to some of his experience with the analysis of medical adherence data. Let's learn about patients' behavior and how they may influence the final results in clinical trials in terms of computed efficacy. Let's get inspired by measuring medication adherence instead of harassing patients. 

The third episode focuses on machine learning and artificial intelligence applied on medical data. It features Dr. Alexander Krannich - a biostatistician whose professional carreer includes data-related positions in a clinical trial office at a large university hospital, CROs, pharma corporations, and recently also in a private company focusing on telemedicine. Let's listen to some of his experience with good data managers, who are able to think out of the box, and who care not only about the data, but also about patient's dynamics. Let's get inspired by carefully prepared digital ecosystems which may help in avoiding mistakes. And regarding the quality of data? The same as always: garbage in = garbage out!

The second episode focuses on the people side of data management. Dr. Alexander Schacht, who is also an influencing podcaster within the data science community, describes several extreme cases of bad data management, including unstructured data and poorly designed studies. There are also some promising news about validated R-software for pharma! 

Insights into data management applied in medical research from a top scientist. Professor Ivo Provazník is a biomedical engineer, working for Brno University of Technology, running also his own technological startup. Will he convince you that "the data is capital"?