BARDA is collaborating with Aidar Health, Inc. to develop and validate the company’s Aidar COVID-19 decompensation index (AIDI), a new early warning system that uses MouthLab, a U.S. Food and Drug Administration (FDA)-cleared device, to enable timely intervention in COVID-19 patients at risk for severe illness and rapid deterioration.
Integrated devices and artificial intelligence (AI)-enabled technologies like AIDI have the potential to provide early and actionable health status information to empower individuals and health care providers.
Identifying early signs of COVID-19 disease progression or deterioration (such as difficulty breathing, chest pain, fainting and sudden dizziness or weakness) is crucial to ensuring successful patient outcomes. Delays in accurately detecting these warning signs may worsen prognosis and impact the quality of life of patients. While clinicians can evaluate hospitalized patients more closely, intervening early can be difficult when their patients are being clinically surveilled from home. Robust early warning tools such as MouthLab, when combined with data science, can effectively monitor a large number of individual subjects' physiological parameters in real-time and detect early signs of deteriorations. This will enable the managing physicians to provide timely intervention and ultimately, help avoid an Emergency Department visit/hospitalization.
AIDI is designed as a multi-sensor-based machine learning technology for real-time automated detection of decompensation. MouthLab and the AIDI are being evaluated for accurate detection of physiological changes early enough to allow timely intervention for COVID-19 patients at risk of deterioration, thereby reducing the likelihood of hospitalization, severe disease, or death. AIDI is based on multiple physiological trends including combination of temperature, blood pressure, electrocardiogram (EKG) data, heart rate, respiration rate, oxygen saturation (SpO2), and other lung functions, which can be useful for the monitoring of not only infections but also cardiovascular diseases.
BARDA is partnering with Aidar to develop and validate the AIDI using Mouthlab (an FDA 510k cleared and CE marked device that measures over 10 vital health parameters) in a cohort of COVID-19 patients, in collaboration with several health systems across the U.S. in a clinical study. By leveraging a demographically diverse user cohort, the study can also increase the understanding of how COVID-19 infections specifically impact different population groups.
MouthLab has the potential to be a commercially available remote monitoring device for daily health assessment. A single breath, in tandem with other sensors, can convey vital health information in real time to individuals and their care providers, enabling enhanced patient care monitoring and management.
This award is one component of BARDA’s DRIVe Medical Countermeasures portfolio. Please visit BARDA’s DRIVe Portfolio to learn more.
About Aidar Health, Inc.:
The following information is provided by the company and does not indicate endorsement by the federal government of the company or its products.
Aidar Health, Inc., is a fast-growing health technology and digital medicine company with the mission to enhance the quality of life of patients with chronic conditions and enable positive health outcomes. Aidar aims to design, develop, and deliver clinically validated breath- and saliva-based sensors and evidence-based therapeutic interventions for various chronic conditions, including heart failure, chronic obstructive pulmonary disease (COPD), infectious disease (i.e., COVID-19), and chronic kidney disease, among many others. Aidar Health seeks to provide improved health outcomes for users through precision medicine, smarter engagement, and disease management tools for providers and caregivers, drug titration and treatment validation tools for biopharmaceuticals, and cost-effective solutions for payers. Aidar has built a revolutionary medical device, MouthLab, and a cloud-based enterprise platform, which leverages proprietary AI and machine learning algorithms, digital biomarkers, and real-world data, to enable proactive, predictive, and decentralized care and research.