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Digital Technology in Clinical Trials

This event is now offered in a new entirely virtual format.


Session 7 Track 3: Collecting Useful, High Quality Data From Digital Sensor Technologies

Session Chair(s)

Jennifer  Goldsack, MA, MBA, MS

Jennifer Goldsack, MA, MBA, MS

  • Executive Director
  • Digital Medicine Society (DiMe), United States
High-quality data support useful endpoints and their interpretations. For data to have integrity, the data cannot be modified or corrupted in an undetectable and/or unauthorized way during the generation and flow of the data. This session will explore how to collect, transfer, and store high quality digital data generated by connected sensor technologies. The Endpoint Strategy for optimizing these processes will be explained and demonstrated.
Learning Objective :
  • Define the characteristics of high-quality data with integrity collected from connected sensor technologies
  • Describe strategies for ensuring that data captured by connected sensor technologies is high-quality and useful
  • Determine who is responsible for protecting the integrity of data generated by connected sensor technologies at each step of its lifecycle and describe the role of audit trails in ensuring the integrity of digital data

Speaker(s)

Barry  Peterson, PhD

Applying an Endpoint Strategy to Guide Data Collection

Barry Peterson, PhD

  • Wearable Devices
  • Independent Consultant, United States
Jonathan Solomon Helfgott, MS

Ensuring Data Integrity by Design

Jonathan Solomon Helfgott, MS

  • Executive Director, Global Regulatory/Clinical Affairs
  • Stage 2 Innovations, United States
Luca  Foschini, PhD

Data Quality: A RWE Perspective

Luca Foschini, PhD

  • Co-founder and Chief Data Scientist
  • Evidation Health, United States