The HIBAD Experience: Using Digital Health Technologies in the GDPR Era

Conducting clinical research presents multiple challenges in data privacy, safeguarding patients’ rights and freedom, and data and sample management. These challenges intensify when the research involves genetic information, biobanks or big health database and, more recently, digital technologies, such as machine learning (ML) and artificial intelligence (AI). This article discusses how some of these issues will be addressed in “HUB Regionale Integrato Biobanca Analisi Dati e Utilizzo Sperimentale” (HIBAD), a project that aims to create an infrastructure to support different clinical research projects through digital health tools. The core of the HIBAD project will be a Regional Biological Resource Center (CRRB), consisting of a biobank and an integrated database of shared clinical records, to combine information from multiple sources, such as electronic clinical records, images, genomics, wearable devices, biological samples. This massive collection of data and samples will be used as a basis for real-world evidence studies, in-silico clinical trials, new clinical trials, and further classification of data through AI and ML techniques. The project also foresees a dedicated digital infrastructure consisting of standardized protocols, procedures, global informed consent and ethics support to ensure respect for ethics, and privacy and regulatory requirements, which would potentially help the creation of high-quality data for valuable research studies. Public Interest Summary Clinical research is extremely important for discovering new treatments for diseases but can be rather complex, especially considering the existence of multiple rules to follow. The project “HUB Regionale Integrato Biobanca Analisi Dati e Utilizzo Sperimentale” (HIBAD) aims to simplify some of the challenges of modern clinical research and to help researchers conducting clinical trials. First of all, we aim to create a big database where data coming from different sources (e.g. patient's health records, analysis of biological samples, genetic results) will be available to physicians for further analysis, even through the newest digital technology tools, such as artificial intelligence and machine learning. Moreover, we will create an infrastructure that supports researchers in respecting clinical research rules, ensuring that the clinical trials are properly conducted, and participants' rights and well-being are respected. The results of the research are sound and reliable.