New AI tools for digital medicine: The PIN, the PATCH and the GATEWAY.
The Pin and Patch detect viral or bacterial infections. They collect medical, motion and contact tracing data to diagnose COVID-19.
Adrián Rica Vicente,
Innovation Manager and Co-founder of VidaApp.
- Recover (Improve health & economic system resilience), such as: Best protective interventions, especially for vulnerable populations, Avoid/mitigate negative second-order consequences, Integrate true costs of pandemic risk into economic systems
With the ongoing coronavirus pandemic, a lot of testing for the virus is taking place globally. PCR testing is becoming the most common method used to identify whether someone is infected with COVID-19 or not. However, large institutions are failing to recognize that PCR testing is not scalable economically, especially for poorer countries, nor is it the more effective method to test for COVID-19.
A study at MIT confirmed that cough detection has a 98.5% sensitivity, is less invasive and easier to scale at larger quantities. Another study published by Stanford suggested that constant monitoring of vital signs and motion is also an accurate method to identify COVID-19, as infected people tend to have altered vital signs and less physical activity. With those two main studies in mind, our devices offer a combination of both suggestions - a constant monitoring of motion and vital signs and a cough detection - to identify COVID-19 at a cheaper and more efficient manner than what is conventionally and currently used. Thus, our solution reduces a logistic problem to the healthcare system.
As medical device manufacturers, the device will have to be CE/FDA marked and registered on the reimbursement list.
Who is the end user?
- Healthcare provider: physician, pharmacist, hospital (...). If end-user is payor, we reach them through hospital or through purchase organizations.
- Patient: full or partial reimbursement (ex. 100% for telehealth covered by social security).
- Company: B2B, direct payment.
Who is the payor?
- Patient, out of pocket, rare.
- Social security and private insurance
- Private hospital: usually direct negotiation
- Public hospital: can go through networks or purchase organizations.
Mainly, we target dependent people, whose care is provided at homecare, long term care and health facilities. Our current objectives align with the challenge of using data to aid in a global pandemic. Bio-Pin is more oriented to healthcare professionals and the patch to patients.
Currently, we are collaborating with strategic partners, where we have a partnership with EIT Digital and Golden Spear – a Silicon Valley AI startup - to provide the early Sars-Cov-2 diagnosis algorithm. Pilots are installed in the US in two schools and one hospital in San Francisco Los Angeles to test out our products and improve them based on the needs that arise.
- Pilot: A project, initiative, venture, or organisation deploying its research, product, service, or business/policy model in at least one context or community
- Artificial Intelligence / Machine Learning
- Imaging and Sensor Technology
- Software and Mobile Applications
Our solution will provide
A unique set of devices and AI tools to tackle pandemics as well as cardiovascular and respiratory chronic patients management.
A valuable data bank regarding:
- AI monitoring of SARS-coV-2, as well as other viral and bacterial infections.
- AI Cardiovascular and Respiratory health monitoring.
Dissemination of Results: The result of the pilots and clinical trials will be available for the public in scientific papers with the help of Los Angeles Children Hospital and Centro de Tecnología Biomédica and Hospital Ramón y Cajal in Madrid.
The project has been designed to impact in five different ways:
Contributing to the public health preparedness and response in the context of the ongoing pandemic of COVID-19 and ensuring the availability of critical technologies and tools.
Contributing to the acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, coverage, and sustainability of diagnosis and clinical management of patients and survivors of COVID-19.
Contributing to proposing recommendations for changes that would allow a fast recovery and better preparedness, including in the health care systems, for future health emergencies.
To accelerate the deployment and market uptake of mature health technologies for the prevention and optimized treatment of the COVID-19 disease, by delivering results within 3-12 months to end-users at scale.
Optimizing health resources by adding AI-aided processes that reduce the need for human intervention in time and resources consuming tasks.
We already have a family of medical devices (pin, patch and gateway) ready for production, after serveral prototypes we do have the definitive hardware for data farming.
Over the next one year we will continue developing the software in special the data analytics, training the diagnosis algorithm with the data obtained in the pilots in the US and Spain.
In three years time, we will absorb more medical knowledge and consolidate a team specialized in AI powered patient monitoring, expand our solution for viral and bacterial infections, new tools for cardiovascular and respiratory monitoring and enter in other health fields such as diabetes, obesity, geriatrics and mental health.
Our mission is to save lives and money to the health system offering devices, software and services for a new digital medicine.
In order to measure our progress with the COVID-19 early diagnosis, we will manage the Sensitivity and Specificity of the algorithm.
Sensitivity and specificity are statistical measures of the performance of a binary classification test that are widely used in medicine:
- Sensitivity (True Positive rate) measures the proportion of positives that are correctly identified (i.e. the proportion of those who have some condition (affected) who are correctly identified as having the condition).
- Specificity (True Negative rate) measures the proportion of negatives that are correctly identified (i.e. the proportion of those who do not have the condition (unaffected) who are correctly identified as not having the condition).
We will also measure the impact in terms of patient's quality of life, hospital admissions, bed occupancy, the decline of health professionals exposure to infected patients, the automation of the vital signs data gathering, satisfaction of the payers and end users with the solution, and how the solutions impacts in the healthcare expenditure.
In the case of health authorities fighting the virus we will help them to reduce:
- Deaths
- Hospital Admissions
- Use of Intensive Care Units
- Transmission of the Virus (infected people)
- Costs and resources dedicated to SARS-coV-2
- Italy
- Spain
- United States
- Chile
- Costa Rica
- France
- Germany
- Saudi Arabia
- United Kingdom
There are technical, legal and financial barriers.
Technical barriers have been solved in the data farming but need further work in the data science. We have already compared the values obtained by the devices (temperature, oxygen level in blood, heart rate...) with those provided by gold standard with positive result.
We now train the remote auscultation software to detect patterns in the audios from heart and lungs, cough and sneeze obtained by the digital microphone. All this needs further efforts as well as the diagnosis algorithm.
Legal barriers are also important, we do have as medical partners the Children Hospital in LA, US and Hospital Ramón y Cajal in Madrid, Spain. The Centre for Biomedical Technology is an academic institution that belongs to Universidad Politécnica de Madrid, they will help us also in the Regulatory Pathway in Europe.
General Standards:
- ISO13485 Quality Management System for Medical Device Manufacturers
- ISO14971 Risk Management System
- General Data Protection Regulation in EU (GDPR) and HIPAA in US
Specific Standards:
- IEC60601-1 Medical Electrical Equipment
- IEC62304 Software as a Medical Device
- IEC62366 Human Factors
Regarding funding we have partnership with GoldenSpear AI-startup based in Silicon Valley and Barcelona, bringing 33 engineers and investors.
- For-profit, including B-Corp or similar models
- https://www.medibiosense.com/ UK cardiovascular software company.
- https://www.goldenspear.com/ Silicon Valley, US Artificial Intelligence company has collaboration with LA Children Hospital.
- https://www.mohmo.eu/ EIT Digital COVID contact tracing initiative.
- http://www.ctb.upm.es/ Centro de Tecnología Biomédica (Universidad Politécnica de Madrid). They will help us in clinical trials.
- https://www.comunidad.madrid/h... Top reference Hospital Ramón y Cajal in Madrid.
We were really active in the Nordic chips before the pandemic already have pulse oximetry, temperature monitoring and a 12-lead ECG with a full cardio screening so we thought it was a good idea to add symptoms and contact tracing to cope with SARS-coV-2.
We started analysing the symptoms like fever, persistent cough, fatigue, shortness of breath... and we ended up with these family of devices and 2 patents filling applications.
Then we were scouted and invited to the Trinity Challenge by mail and we found it was a wonderful opportunity for the project success.
Medical organizations involved in SARS-coV-2, cardiovascular and respiratory specialties, geriatrics...
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Co-founder and Innovation Manager at VidaApp.com