nQ is a computational biotechnology company with experience in digital phenotyping through AI-aided analysis of personal device interactions. We have developed digital biomarkers for Parkinson's disease in early and newly diagnosed/untreated stages of disease. In addition to PD, we are currently conducting a number of separate clinical trials to develop digital biomarkers individually relevant to Multiple Sclerosis, ALS, Alzheimer's disease, and mTBI with industry partners and academic centers including Cleveland Clinic and Massachusetts General Hospital. OUr AD trial has advanced to yield early and promising results measuring cognitive decline and delineating PD and AD symptomatology.
In prodromal stages of neurodegenerative diseases such as PD, digital biomarkers offer possibility of detecting actual subclinical symptoms known to predict phenoconversion better than biochemical markers which often predict disease risk but not timing.
Some key advantages of our digital biomarkers include:
-Continuous, longitudinal, remote, real world quantification of psychomotor symptoms;
-Patients are not burdened with completing structured tasks or clinic visits for data collection. Patients use their personal devices as they normally would and data is collected passively and transparently, often 24/7;
-Patient privacy and security is ensured at each step of algorithm. Biomarkers perform even though content of what patients type on their personal devices kept confidential and secure.
Specific to Parkinson's Disease:
-Five peer reviewed publications reflecting 4 clinical trials demonstrating technical validation and clinical validation in PD patients;
-Performance in correlating to UPDRS-III and differentiating healthy controls from from Parkinson's disease with AUC>0.90 in early PD patients thus far published. Follow-up work from our group and academic research by others have demonstrated continued increase in accuracy with increased data and refinement;
-Performance in longitudinal symptom monitoring, distinguishing medication responders from non-responders.
Use cases in multiple phases of clinical trial and in the clinic post-approval:
-Cohort enrichment - pre-screening of patients to undergo more expensive or detailed diagnostic testing;
-Symptom Fluctuation/Disease Progression Monitoring - characterize subpopulations of patient cohorts: responders, early progressors etc;
-Outcome measure - Smartphone interaction is inherently relevant to daily function. Precise quantification can detect treatment responses missed by cruder metrics.
-Disease screening for diagnostic referral;
-Symptom monitoring as an independent or companion software to aid treatment titration, monitor compliance;
-Generate real world data and evidence (RWE);
-Supporting telehealth visits, access to patients in under-served/remote areas, via telemetry.