Cough Detection App
for clinical trials

AI-POWERED APP AS AN REAL-WORLD EVIDENCE TOOL FOR DISEASE EVOLUTION AND DRUG RESPONSE ANALYSIS IN A TRIAL
An average of over 1,700 clinical trials take place in the respiratory space each year 1
Cough is a symptom of asthma, COPD, IPF, cystic fibrosis, heart failure, COVID-19, and many other diseases

In clinical trials, endpoints aimed at disease burden on patient's life, often document information through questionnaires

Daily cough, and especially night cough, could be under-reported in this context
Current issues facing clinical trials
Clinical trials and their generated results are crucial. However, a common problem facing clinical trials is the poor recruitment of eligible participants
26%
of respiratory trials fail to recruit to their target sample size, leading potentially to underpowered study results 2
30%
of participant drop out before the
study ends 3
40%
of long-term trial participants stop taking their medication after one year 4
Real-life digital biomarkers for clinical trials
Powerful solution to extract deeper insights
Automatic cough traction
The significance of cough in assessing the health status of trial participants is crucial. Our platform now makes the cough objective and reliable data for researchers.
Metadata toolset
Insubiq's patient app accurately captures multiple patient-generated vital signs affecting the condition of the trial participant
Data Management
The Platform is customizable with dozens of digital biomarker modules for detailed analysis. API for clinical data management platforms
Connectivity
Platform can integrate and collect data from many wearables devices and provides a continuous stream and early access to meaningful data
Innovations
First and only in-app AI cough detection algorithm. We do not record and analyze your sensitive data on external servers. Your privacy is protected.
Integration with smartwatches to capture extra vital signs relevant to the trial
Algorithm validated with independent healthcare experts.
HIPAA Compliant. Proprietary patent-protected technology
Book a demo
Insubiq Inc.
251 Little Falls Drive, Wilmington, DE, 19808
References
2. Delsing LJA, Brailsford W, Buxtfeldt C . Finding the patients for respiratory clinical trials: successful recruitment by adapting trial design. Journal of Lung Diseases and Treatment 2016;2:1–7.
3. Differential dropout and bias in randomised controlled trials: when it matters and when it may not. Bell, Melanie L., Kenward, Michael G., Fairclough, Diane L., and Horton, Nicholas J. (2013) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4688419/
4. Smart Medication Adherence Monitoring in Clinical Drug Trials: A Prerequisite for Personalised Medicine? NCBI. Zijp, Tanja R., Mol, Peter G.M., Touw, Daan J., and van Boven, Job F.M. (2019) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833361/