Smart Lung Monitoring
for pharmaceutical clinical trials
Leveraging AI to provide a comprehensive, long-term picture of respiratory health
Ultra-Low Power Sensor
Clairways' ultra-low power wearable acoustic sensor allows for long-term, continuous monitoring of the lungs and airways.
Analytics & Reporting
Summary and trends of various metrics are collated and reported for each patient in an easily digestible format that highlights relevant insights and patterns.
AI Symptom Detection
The core of Clairways technology is on-device machine learning that detects and characterizes respiratory metrics:
coughing, wheezing, lung sounds, respiratory patterns, heart rate variability, inhaler use
Value for Clinical Trials
heart rate variability
Capture Reliable Metrics
Reduce your reliance on effort dependent monitoring and participant journals, which hurt both adherence and data quality.
Reduce Your Trial Duration
Enroll participants faster and determine dosing protocol faster, thereby reducing trial duration.
Enable Your Virtual Trial
Recruit for rare disease studies without geographic restriction and eliminate the high costs of participant trial site visits.
Improve Your Commercialization
Demonstrate your treatment’s impact for payors and prescribers with long-term, continuous, objective participant metrics.
The Clairways sensor is adhered to a participant's chest either by a clinician or by the participant
Participants go about their normal lives, while the sensor continuously captures metrics
Easily digestible analytics and summary metrics are transmitted back to the trial
Jeff is experienced in product management, market research, and customer discovery for novel biomedical devices. He previously worked in product management for Endotronix, a Series C funded medical device company. MBA, Tuck School of Business at Dartmouth.
Justice is a pioneer in embedded systems for stochastic modelling of physiological signals. His focus is on deep neural network models for detecting the onset of symptoms in respiratory diseases. PhD, Thayer School of Engineering at Dartmouth.
Kofi is an expert in circuits and systems for wearable devices. He is an Associate Professor of Engineering and the Director of the Analog Lab at Dartmouth College. PhD in Electrical and Computer Engineering, Georgia Institute of Technology.