Login / Signup

Towards an Architecture to Guarantee Both Data Privacy and Utility in the First Phases of Digital Clinical Trials.

Fabio AngelettiIoannis ChatzigiannakisAndrea Vitaletti
Published in: Sensors (Basel, Switzerland) (2018)
In the era of the Internet of Things (IoT), drug developers can potentially access a wealth of real-world, participant-generated data that enable better insights and streamlined clinical trial processes. Protection of confidential data is of primary interest when it comes to health data, as medical condition influences daily, professional, and social life. Current approaches in digital trials entail that private user data are provisioned to the trial investigator that is considered a trusted party. The aim of this paper is to present the technical requirements and the research challenges to secure the flow and control of personal data and to protect the interests of all the involved parties during the first phases of a clinical trial, namely the characterization of the potential patients and their possible recruitment. The proposed architecture will let the individuals keep their data private during these phases while providing a useful sketch of their data to the investigator. Proof-of-concept implementations are evaluated in terms of performances achieved in real-world environments.
Keyphrases
  • clinical trial
  • electronic health record
  • big data
  • healthcare
  • public health
  • randomized controlled trial
  • machine learning
  • phase ii
  • climate change
  • ejection fraction
  • deep learning
  • human health