ANNE One: Remote Monitoring with AI-Enabled, ICU-Grade Wearables

Sibel’s ANNE One is an ICU-grade wearable sensor system with predictive analytics, and real-time streaming for advanced remote patient monitoring.

Steve Xu MD is a physician-engineer, academic, and entrepreneur with direct experience building advanced medical technologies to address unmet clinical needs worldwide.

The COVID-19 pandemic has led to an unprecedented strain on healthcare systems worldwide—in the U.S., the available ICU-beds numbered in the single digits for multiple states. In low- and middle-income countries (LMICs), the healthcare system is frailer with inherently lower capacity for both healthcare personnel and essential supplies. When we fail to "flatten the curve", the suffering is disproportionately borne by the most vulnerable—frontline healthcare workers, older adults in long term assisted living facilities, and low income individuals who delay necessary care for other conditions.

A foundational problem is that in the face of unprecedented demand for healthcare services, traditional hospitals are easily overwhelmed. A large influx of patients present with a spectrum of mild infections better managed at home to life-threatening sepsis requiring immediate ICU-level care. Thus, there is a critical need for new technologies powered by predictive data analytics that allows for the rapid scaling of ICU-grade physiological monitoring for care anywhere. The ability to project care beyond the hospital walls allows for tracking early signs of disease in vulnerable populations, monitor those infected safely in a remote setting to protect precious hospital capacity and frontline workers, and to determine adequate recovery for a safe return to work.

1. Frontline Healthcare Workers: we have already monitored more than 200 frontline nurses/doctors at multiple sites during the COVID-19 pandemic. Our sensors were used to surveil for physiological signs of deterioration prior to symptom development.

2. Nursing home residents: with support from the National Institutes of Health and Anthem Inc (2nd largest insurer in the U.S.), we demonstrated the feasibility of virtually deploying our sensors in two separate nursing homes to monitor older adults for a continuous 2-week quarantine period. 

3. LMICs: with support from the Gates Foundation, Save the Children Foundation, Grand Challenges Africa, and the U.S.-India Science and Technology Endowment Fund, we have deployed the ANNE system in 5 LMICs (Ghana, Zambia, Kenya, South Africa, and India) monitoring more than 2,000 subjects in total to date.

4. Mothers / newborns: Sibel has a strong background in monitoring physiological health in newborns (>250) and pregnant women. With pandemics, obstetrical and neonatal care must continue uninterrupted given the already high mortality/morbidity in these populations for LMICs. This work was recognized by Nature Magazine / Merck where Sibel was named the inaugural winner of the 2020 Nature SpinOff Prize for our work in newborns with advanced sensors.

Sibel Health is highly committed that our proposed solution has public goods as a direct output. These outcomes include:

• Open-access, peer reviewed publications of our scientific and technological findings
• Open-source database outputs from our sensors that allow for the broader scientific community
• Open SDKs (software development kits) that enable developers to integrate our sensors into other software applications

Furthermore, Sibel believes that the sensors / systems deployed in LMICs should also be manufactured there. As experts in manufacturing processes for soft/flexible electronics, Sibel is committed to placing key components of the supply chain in LMICs to provide high-paying, technology-oriented economic job opportunities. While our technology is a healthcare system addressing predominately UN Sustainability Goal 3 (Good Health and Well-Being), we believe the scaled production of these sensors will also address UN Sustainability Goal 8 (Decent Work and Economic Growth) and 9 (Industry, Innovation, and Infrastructure).

Frontline healthcare workers (FHWs): when deployed in this population at scale in the LMIC settings, our sensors will monitor for signs/symptoms of disease as well as monitor recovery in case of infection. Our existing work in more than 200 healthcare workers show strong engagement, excellent adherence, and appreciation of the data outputs provided by the system. In doing so, we will identify COVID-19 cases early, support recovery, and prevent spread for precious FHWs in LMICs.

Nursing home residents: when deployed here, we will demonstrate the ability to virtually launch our remote monitoring system in older adults residing in nursing homes. In case of illness, these patients maybe more safely monitored instead of a traditional care setting or detect COVID-19 earlier in the setting of severe staffing shortages to prevent hotspots. We have already demonstrated the feasibility with local nursing homes. The target goal is to avert mortality.

LMICs: remote monitoring offers the ability to rapidly expand access in the settings of a pandemic where demand skyrockets particularly in mothers/newborns where monitoring needs are the greatest. The ability to expand care with our sensors ensures other conditions do not worsen (e.g. neonatal mortality/morbidity) in the setting of a pandemic.

Sibel believes that medical monitoring should be democratized, low-cost, and available to all. Our vision statement is Better Health Data for All. Thus, we believe low-cost, clinical grade sensors compatible with ubiquitous mobile phones will allow clinicians and healthcare administrators to better care for patients in any care setting.

Our sensors will monitor 10,000 lives by the end of 2021 with existing engagements alone. With funding from this proposal, we hope to reach 50,000 in 2021 and expand from 5 LMICs to 10. We have existing partnerships with large contract manufacturers that enables us to produce 100,000 sensor units per month (currently 5,000 kits per month) at lower production costs. We have built a strong and experienced regulatory/compliance team focused on global approvals for the ANNE One system in all nations we operate. In the next 3 years, our projections for scale include launching at least 250,00 ANNE sensor kits globally across all care settings and monitoring at least 1.5 million individuals—from hospitals to the home. Our target is to reach 30 countries with at least half of them in the LMIC setting. Ultimately, we want the ANNE system to be the default choice for monitoring solutions worldwide.

Sibel is an outcome oriented company focused on measure indicators of success. Our impact goals are as follows:

• Number of ANNE One sensor kits deployed (currently more than 2000)
• Number of patients monitored (currently more than 4000)
• Number of patients monitored who represent vulnerable populations (currently ~50%)
• Number of monitoring hours captured (currently more than 1 million)
• Deaths averted
• Serious medical illnesses averted
• Number of countries deployed in (currently 18)
• Number of LMICs deployed in (currently 5)
• Data quality per monitored hours (currently exceeds 85%)
• Adherence to wear (currently >95% for 4 days of wear per week in our large scale clinical trials)

Supply chain: currently, the world is facing a shortage of semiconductors. As we scale in our production, we will have to mitigate and manage this challenge. We currently have a strong engagement with a major semiconductor manufacturer and strong contract manufacturing partners to help us mitigate these challenges. 

Cultural: wireless sensors may not be immediately accepted by all users. We will have to demonstrate clinical efficacy and performance to win over skeptics through high quality studies and peer-reviewed publications. 

Market: although remote monitoring is an area of tremendous growth, these tailwinds may shift with the changing pandemic. While demand currently is exceptionally strong, it may not fully remain that way. We will need to continue to forecast accurately to ensure we are addressing the market needs.

Data Scalability and Management: while we do currently have a highly scalable, server-less architecture, the data generated by these sensors will only grow exponentially with more users. We further have developed novel on-sensor compression software to reduce data file sizes. However, the ability to manage the ever increasing data payload, cost effectively store it, and make it useful is a major challenge. We will work with large technology partners to develop innovative technical solutions.

Non-profits: Gates Foundation, Save the Children Foundation, Merck for Mothers. For-Profits: J&J, Draeger, Verizon, KT Corporation, Anthem. Academic Institutions: Northwestern, Red Cross Hospital (SA), Aga Khan University, UNC-Chapel Hill, and UTH Lusaka. Government: U.S.-India Science and Technology Endowment Fund, NIH, NSF, and Department of Defense.

Sibel is a unique company. We're not investor-driven. We're mission driven to deliver Better Health Data for All through advanced sensors, predictive analytics, and a compatible / scalable software backends.. Our technology and innovations are underpinned by decades of the most advanced engineering research conducted by the leading voice in the field of advanced wearables. Thus, we're driven towards delivering impact enabled by breakthrough technology.

The Trinity Challenge inspired us to apply because it is bold - and it is focused on delivering transformative impact worldwide. We believe the Trinity Challenge is willing to make big bold bets on promising teams to drive meaningful change. The focus is not on pilots, but real progress. Outcomes, not outputs. At Sibel, we believe we're ready - our whirlwind last 2 years have prepared our team of 46 strong to accelerate from our current deployments to the next level where everyday we can deliver Better Health Data for All. COVID-19 - and all of the suffering it has caused worldwide - has only inspired our team to push our technology forward.

Microsoft: the sensor solutions we offer generate a large amount of physiological data. We further envision these datasets to be paired with outside datasets for deep learning. The ability to work directly with Microsoft Azure on scaling our cloud solution at low costs in low bandwidth settings will yield important technical solutions as we scale.

Gates Foundation: while we have existing engagements and active programs with the Gates Foundation, we foresee additional opportunities to expand our work with them beyond maternal / fetal / neonatal monitoring into global pandemic monitoring.

University of Cambridge/Imperial College London/JKU Med/NUS/Nanyan Technological University/Tsinghua University: we have a long standing interest in collaborating with some of the leading academic institutions worldwide around new technology development as well as clinical deployments.