Introduction to Evidation Health

Alessio Signorini’s presentation addressed how digital data and AI can meaningfully extend clinical insight beyond the traditional boundaries of the clinic. The central clinical problem he highlighted is that most of what we measure in medicine is episodic: visits, labs, imaging, and procedures capture only brief snapshots of a patient’s health. Meanwhile, the majority of relevant physiological and behavioral signals—activity, sleep, heart rate dynamics, voice, daily function, and environment—occur continuously and are largely invisible to clinicians.

Signorini showed how wearable sensors, smartphones, and connected apps now enable the collection of high-frequency, real-world data at scale, which can be transformed into validated digital biomarkers. Examples included monitoring functional decline, detecting influenza-like illness, quantifying treatment effects on activity and sleep, identifying atrial fibrillation risk, tracking migraine burden, and measuring cognitive decline using voice-based signals. These measures often reveal changes earlier and more sensitively than conventional endpoints, and can complement established clinical assessments.

From a physician’s standpoint, the emphasis was on augmentation rather than replacement of clinical judgment. Continuous digital phenotyping provides longitudinal context, helping distinguish true clinical change from random variability and reducing reliance on single data points. Importantly, the work is conducted within HIPAA-compliant, IRB-approved, and peer-reviewed research frameworks, with extensive publication in medical journals and collaboration across hospitals, Pharma, and public health organizations .

The broader takeaway is a shift toward more preventive, personalized, and data-informed care, where clinicians gain visibility into the “other 99%” of patients’ lives and can make better-informed decisions about monitoring, intervention, and outcomes.