Content Comparison

Digital health technologies (DHTs), such as wearable accelerometers, are increasingly being adopted in clinical trials, as they enable objective and continuous evaluations of health parameters, functions and behaviours in the participant’s naturalistic environment. The continuous data stream provided by DHTs combined with artificial intelligence/machine learning (AI/ML) tools can lead to the identification of novel digital endpoints (NDEs) and measuring objective outcomes that are meaningful to patients. These NDEs can support clinicians with early diagnosis, prognosis, and personalised treatments of a wide range of diseases.

To address the need to develop and validate NDEs before their large-scale deployment in clinical trials and gather evidence supporting their regulatory adoption, at Pfizer we have collected in-clinic and at-home data from hundreds of healthy volunteers across age ranges, spanning paediatrics to geriatrics, and device locations. In the first part of this presentation, considerations about the selection of fit-for-purpose DHTs and the validation of AI-driven algorithms for NDEs of gait and physical activity will be discussed as compared to standard measurements. Since understanding individual perception towards using new technologies is crucial for clinical adoption of NDEs, the evaluation of self-reported measures of usability, acceptability, and level of continued usage will also be addressed. Results suggest high reliability and accuracy of DHT-derived gait and physical activity endpoints, for example by effectively tracking walking at different speeds, while ensuring participants’ comfort in wearing DHTs. Finally, the deployment of the validated AI-driven digital biomarkers in clinical studies will be presented, with particular focus on older individuals at risk of frailty and malnutrition.

This Community Forum will take place virtually on 16 18 June at 11:00 (EDT) / 16:00 (BST) / 17:00 (CEST)