When using digital health technology (DHT) in clinical trials, we need to specify an endpoint. However, does your digital endpoint matter to the patients? Is it based in the context of their life? For regulatory purposes this seems to be an imperative. As such “black box” algorithms, despite their many benefits such as high predictive accuracy, could be a barrier to gaining a label claim.
This paper discusses the difference between a digital biomarker and a digital clinical outcomes assessment. We build on the foundations by focussing on the meaningful aspects of health and suggesting a framework for DHT development based on the DiMe Playbook. We will also go one step further in this talk than we did in the paper. Here we will and start blue sky thinking about how to combine the highly predictive algorithms underlying digital biomarkers with the patient relevant aspects of digital clinical outcomes assessments. This discussion will move us closer to deriving patient relevant endpoints which can be enacted on an enhanced timeline.
