Health Security & Pandemics Challenge
Sibel's ANNE One
ICU-grade wearable sensor system for advanced remote patient monitoring
One-line solution summary:
ANNE One is an ICU-grade wearable sensor system with predictive analytics, and real-time streaming for advanced remote patient monitoring.
Pitch your solution.
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.
Therefore, we have developed an ICU-grade wearable sensor system that allows medical personnel to continuously monitor vital signs and to identify predictive analysis, and remote care with smartphones or tablets without expensive monitoring equipment in areas where medical facilities are scarce.
The ANNE One system is the most comprehensive monitoring platform with embedded machine-learning enabled alerts that can identify early COVID-19 infection prior to symptom onset, monitor deterioration, and track recovery. These systems enable healthcare providers to remotely monitor patients to preserve hospital capacity and reduce unnecessary exposure.
What specific problem are you solving?
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 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, monitoring 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.
What is your solution?
The ANNE One system has developed as soft and flexible sensors that can continuously monitor clinical-grade vital signs from premature infants to adults. Advanced processing algorithm further provides unique measurements that include cough count, fall count, peripheral arterial tone. It is designed to be scalable, low-cost, comprehensive, and predictive for early infection with algorithms trained on more than 100,000 hours of data collected from COVID-19 patients. This data can be stored continuously or streamed in real-time to a wide range of ubiquitous mobile devices for both point-of-care diagnosis or store-forward analysis. Data storage and processing in Sibel's cloud server further expands the use cases into remote patient monitoring. These systems can obtain ICU-grade data without expensive medical equipment in a low-resource setting.
Who does your solution serve, and in what ways will the solution impact their lives?
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 survey for physiological signs of deterioration prior to symptom development. Furthermore, 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.
2. 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 may be more safely monitored instead of a traditional care setting or detect COVID-19 earlier in the setting of severe staffing shortages to prevent hotspots. The target goal is to avert mortality. For some cases, we have already demonstrated the feasibility of virtually deploying our sensors in local nursing homes to monitor older adults for a continuous 2-week quarantine period with support from the National Institutes of Health and Anthem Inc (2nd largest insurer in the U.S.).
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. 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.
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.
Which dimension of the Challenge does your solution most closely address?
Strengthen disease surveillance, early warning predictive systems, and other data systems to detect, slow, or halt future disease outbreaks.Explain how the problem you are addressing, the solution you have designed, and the population you are serving align with the Challenge.
We envision the ANNE One system to be always ready for rapid scaling and deployment during pandemics with use cases that include detecting early infections in high-risk populations using predictive analytics, supporting a safe transfer of care from hospitals to homes to preserve capacity and reduce unnecessary exposure to frontline healthcare workers, and tracking recovery of the sick to ensure safe return to work. Generally, these systems can be used to not only remotely monitor patients anywhere with ICU-grade comprehensiveness, but to also alert users and healthcare providers of signs that may be suggestive of infection in an automated fashion.
In what city, town, or region is your solution team headquartered?
Chicago, IL, USAWhat is your solution’s stage of development?
Growth: An organization with an established product, service, or business model rolled out in one or, ideally, several communities, which is poised for further growth.Explain why you selected this stage of development for your solution.
While Sibel was founded in 2018, it has rapidly scaled from 4 founding engineers to 46 in only 2 years. ANNE One has already been submitted to the FDA with expected clearance by June 2021 with demonstrated accuracy and performance.
The impact to date includes the launch of ANNE One in 5 continents, and 18 countries including 5 LMICs in partnerships with major philanthropies, NGOs, large companies, payers, and government organizations. Overall, we have touched more than 40,00 patients with over 1 million monitoring hours for patients ranging from 26 weeks pre-term to 94 years of age.
Specific to COVID-19, Sibel was one of only 7 companies awarded funding from the 2020 CARES Act and the U.S. Department of Defense to develop algorithms to predict for early COVID-19 infection. We recently completed a clinical trial allowing us to develop a machine-learning algorithm in identifying early COVID-19 patients using our sensors and submitted it in April 2021 for FDA Emergency Use Authorization.
Who is the Team Lead for your solution?
Steve Xu
If you have additional video content that explains your solution, provide a YouTube or Vimeo link here:
Which of the following categories best describes your solution?
A new application of an existing technologyWhat makes your solution innovative?
1. Technology: the ANNE One system represents a major technology advancement. We believe this system represents the most comprehensive suite of advanced sensors offering ICU-grade monitoring compatible with mobile devices. Beyond capabilities for traditional vital signs (heart rate, respiratory rate, SpO2, and temperature), the unique mounting location of the sensor on the suprasternal notch allows the capture of important, clinically-relevant respiratory biomarkers impossible for wrist-mounted sensors. Here, we continuously determine respiratory sounds, cough count (a sign of infectiousness), wheezing, and sleep quality.
2. Practicality: unlike nearly every other wearable patch system which operate as single-use disposables, the ANNE sensors are fully rechargeable with our wireless charger. All ANNE sensors are waterproof with extended battery life (up to 7 days) allowing for ruggedized use. The reusable nature of the system (£21.8 per sensor at scale) and low cost consumables (<£0.07 per consumable at scale) make this system orders of magnitude less expensive compared to traditional systems.
3. Differentiation: while there are other groups developing wearable sensors and patches-they do not offer the same level of comprehensive monitoring as the ANNE system. Furthermore, these systems lack significant clinical validation in vulnerable populations such as neonates and pregnant women, and in LMIC settings.
4. Algorithms: our machine learning algorithm (submitted to the FDA for EUA) has the ability to detect early COVID-19 infection prior to symptom onset validated in a clinical trial of n=325 subjects funded by the U.S. Department of Defense.
Please select the technologies currently used in your solution:
Select the key characteristics of your target population.
Which of the UN Sustainable Development Goals does your solution address?
In which countries do you currently operate?
In which countries will you be operating within the next year?
How many people does your solution currently serve? How many will it serve in one year? In five years?
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 enable 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 5 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.
How are you measuring your progress toward your impact goals?
Sibel is an outcome-oriented company focused on measuring 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)
What type of organization is your solution team?
For-profit, including B-Corp or similar models
How many people work on your solution team?
Full Time: Sibel has 46 full time team members with 90% representing engineering talent. We have full scale engineering teams for hardware design, mechanics, user interface design, data analytics, software development, cloud development, operations, clinical affairs, and regulatory affairs. We have 3 offices (Chicago-HQ,San Diego,and South Korea) and expect to open a 4th(Spain) by the end of 2021.
Advisors: Lou Simpson, World-Renowned Investor, Northwestern Trustee; Kimberly Querrey, Philanthropist/Investor, Northwestern Trustee; Steffen Prostch, President of Monitoring, Draeger; John Rogers PhD, Professor, Northwestern. Jeffrey Stringer MD, Professor, UNC Chapel Hill.
How long have you been working on your solution?
While Sibel Health was only founded in 2018, it has rapidly scaled from 4 founding engineers to 46 in 3 years. The underlying science and technology is based on more than a decade of advanced engineering research.
How are you and your team well-positioned to deliver this solution?
Our leadership team brings world-class expertise in engineering, global health, and finance. Steve Xu MD MSc (team lead) is a physician-engineer, academic, and entrepreneur. As Sibel's CEO, he grew the team from 4 to 46 engineers in 2 years, launched the product in 5 continents, and executed major partnerships with numerous Fortune 500 companies. John Rogers PhD (technical lead) is one of 25 people ever named to the National Academy of Medicine, National Academy of Engineering, and the National Academy of Science. He is the Executive Director of the Querrey Simpson Institute for Bioelectronics at Northwestern University. Lou Simpson, board member of Sibel, is the former chief investment officer of GEICO and serves/previously served on the boards of AT&T, Comcast, ResMed, and Verisign. Sibel has its own IP including issued and granted patents worldwide as well as worldwide/exclusive licenses from Northwestern/University of Illinois on the core technology. Sibel is diverse with >50% of the team representing individuals of color and 40% women hailing from 6 different countries.
What is your approach to building a diverse, equitable, and inclusive leadership team?
We are highly diverse with a balance of women, under-represented minorities, and immigrants representing more than 60% of our team. We advocate and develop technologies for vulnerable populations including children, pregnant women, and those living in low- and middle-income countries.
Do you primarily provide products or services directly to individuals, to other organizations, or to the government?
Organizations (B2B)Why are you applying to Solve?
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 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 Global Challenges inspired us to apply because it is bold - and it is focused on delivering transformative impact worldwide. We believe the Global Challenges are 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.
In which of the following areas do you most need partners or support?
What organizations would you like to partner with, and how would you like to partner with them?
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.
Do you qualify for and would you like to be considered for the Robert Wood Johnson Foundation Prize? If you select Yes, explain how you are qualified for the prize in the additional question that appears.
Yes, I wish to apply for this prize
Do you qualify for and would you like to be considered for The Andan Prize for Innovation in Refugee Inclusion? If you select Yes, explain how you are qualified for the prize in the additional question that appears.
Yes, I wish to apply for this prize
Do you qualify for and would you like to be considered for the Innovation for Women Prize? If you select Yes, explain how you are qualified for the prize in the additional question that appears.
Yes, I wish to apply for this prize
Do you qualify for and would you like to be considered for The AI for Humanity Prize? If you select Yes, explain how you are qualified for the prize in the additional question that appears.
Yes, I wish to apply for this prize
Do you qualify for and would you like to be considered for The Global Fund Prize? If you select Yes, explain how you are qualified for the prize in the additional question that appears.
Yes
Solution Team
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Solution Name:
Sibel's ANNE One