The Blue Box
In 2014 I started my bachelor's in biomedical engineering at the University of Barcelona, where I started understanding biology from an engineering point of view: calculus, algebra, electronics… always focussing on the human body.
I believe that great discoveries happen when we humans learn from biology and model it through hardware and software. This thought indeed motivated me towards my bachelor thesis: I once met a dog that smelled patients’ breath and barked if s/he had lung cancer. If biology had a way to do it, we engineers could build a device on this principle too. And so my bachelor thesis started.
In 2017 the hypothesis was proven, which motivated me to further pursue my project, and California seemed to be the right place. At the University of California Irvine I pursued the master of embedded cyber-physical systems and I conducted its master thesis on my project.
Cancer is the second leading cause of death worldwide. Breast cancer diagnoses in the US have been rising from 226,000 in 2010 until now and are expected to hit 294,000 by 2030, remaining the 4th most diagnosed cancer. The most popular current screening solution is the mammogram, but an ongoing strong debate on its performance -mainly because of its low sensitivity- is leaving an open spot at the market to be filled by a pain-free, low-cost, non-irradiating new approach.
Our proposed solution, The Blue Box, enables the patient to get self-tested at home, just by downloading an app and introducing a urine sample in a box. Thanks to an AI-powered embedded algorithm, The Blue Box will not only increase women's survival but also change the way the current medicine is practiced - shifting the focus from reactive into preventive medicine.
The American Cancer Society predicts that breast cancer will represent 30% of all cancers diagnosed in the US in 2020. However, research dedicated to it is not proportional to its incidence. Actually, the NIH recognised women as underrepresented in medical research.
This trend can be observed in the field of oncology, specifically considering current breast cancer screenings. Indeed, a study by the CDC stated that only 65% women attended it in the last 2 years, potentially resulting in 1/3 breast cancers being detected too late, and thus women having a worse prognosis and survival chance. Reasons for women skipping the mammogram-based screening are multiple: pain (41% of interviewees), difficulty of work absence and poor insurance coverage according to the Journal of Women’s Health.
Furthermore, according to the Catalan (Spain) Department of Health, only 6.45% of breast cancers diagnosed via mammogram are actually cancer. In other words, the sensitivity of the mammogram is dramatically low.
Finally, although its dose is not substantial enough to be considered harmful, biennially exposure to the mammogram increases breast cancer risk itself.
In conclusion, there exists a need for a non-invasive, inexpensive, sensitive and in-home breast cancer screening.
After having a Blue Box delivered at home, the user just needs to download an app and follow three simple steps: Collect a urine sample in a container; introduce it in The Blue Box; and wait 30 seconds.
During these 30 seconds, The Blue Box performs a chemical analysis of the sample and sends the results to the cloud, where an AI-powered algorithm is run. This leads to a diagnosis, which is communicated via app.
The Blue Box is a change in the way society fights breast cancer. As opposed to the current painful and inconvenient routinary procedure that oftentimes leads to anxiety, The Blue Box enables women to get self-tested at home.
Also, because our solution is non-invasive and non-irradiating, the frequency of use and the range of targeted population is unlimited - thus leading to (1) more breast cancer diagnosis and (2) earlier stage diagnosis.
The latter can potentially lead, in turn, to higher breast cancer survival rate and radically lower healthcare expenses (considering both screening and treatment costs).
Finally, replying on chemical analysis in lieu of imaging, the diagnosis depends on not only a physician’s expertise but also a numerically quantitative result.
Due to its irradiating nature, mammogram-based screenings only target a narrow population segment (typically women aged 45-65) – for the diagnosis power to outweigh its cancerous radiation dose. Nevertheless, The Blue Box is aimed at all women from all ages.
The proposed scenario is that of every family owning a Blue Box, which can be used by all its female members at their desired frequency and indefinitely. Every single user owns an account at The Blue App, which keeps track of her screening history throughout her whole life.
In turn, the Blue App gathers data from users worldwide, which is then used to release new software versions with enhanced prediction algorithms that get automatically installed to every Blue Box at every home.
As a conclusion, the presented breast cancer screening solution can be performed at home, with no need of medical knowledge. Additionally, because it is highly software-based, it is considerably inexpensive to manufacture, which translates into being accessible for an extremely wide population segment, regardless of its economical status and health insurance conditions. Examplewise, a Blue Box is worth $60 and can be reused indefinitely, whilst a mammogram and MRI cost $175 and $700 respectively per single use.
- Elevating opportunities for all people, especially those who are traditionally left behind
Ultimately, this project seeks to:
Catalyze change towards a world in which women’s needs are fully represented in healthcare systems worldwide.
Elevate and create an opportunity for all women to have access to the breast cancer screening that they need.
The latter is achieved by targeting the P4 medicine concept. According to the WHO, the future of medical technology is that of "P4 medicine": predictive, preventative, personalised, and participatory. Coinciding with this trend, The Blue Box seeks to empower the patient and encourage her to inquire and decide on her own health (participatory) whilst prioritising prevention before cure.
During my bachelor studies on biomedical engineering at the University of Barcelona, I took a course on what we used to call "hospital critics". Students were encouraged to enter the hospital, observe and engineer solutions that might impact patient care. This is when I realised how poorly effective the current mammogram-based breast cancer screening was.
Thanks to the interaction with these doctors, I was presented with the case of Blat, a dog that could detect cancer by smelling their owner’s breath. The goal of my career became then clear: I wanted to use my engineering to reproduce the dog’s physiology into an Arduino board and a couple of sensors; and to translate the brain’s olfactory cortex into a Python piece of code. Moved by this passion, I asked many doctors about the requirements of a hypothetical new gold standard for breast cancer screening. Since 2017, these have been re-shaped and modified pursuing an ultimate goal: CHANGE the way we -as a society- fight breast cancer.
Thanks to the facilities of the Institute of Biomedical Engineering of Barcelona (IBEC) and 90 urine samples from patients from a Catalan Hospital, I could test my eNose to find out a sensitivity of 75%.
In April 2015 my high school teacher explained how the human body turns a piece of bread into 265 kcal with slightly no energy loss. In fact, the 2.5μm-sized mitochondrion is able to do so by working at an efficiency that has never nor is it ever likely to be reached by any other human-designed machine.
This thought from back in my high school years awakened some kind of fascination in me that still continues to amaze me. It did also give place to a slight touch of frustration though – so much yet to be known, the unpredictable nature of biology. In my head -I have always been more of a maths nerd than a biology enthusiast- the only solution to such unpredictability was maths. There had to be a way to explain human biology with maths.
I will never aim at reaching the degree of perfection and design of biology, but biology is what I will observe and learn from every time I want to engineer a solution.
And hence my core passion for this project. I want to diagnose cancer mimicking the olfactory cortex of the dog – learning from biology to create better answers.
It is said that what defines a person is the experiences she has lived and everything she learnt out of them. I strongly agree with that. And if I am to choose what defines me, I think of myself as a person who gets excited about projects, who knows how to transmit that motivation into the people around her and who believes that, with the right partners and a lot of willingness, any challenge is assumable.
From a book by Xesco Espar, former Barcelona football coach, I learned that "a goal cannot get the most out of you if when thinking about it, it doesn’t make you tremble". And this is how the world of research and development makes me feel. I think I'm a creative person who searches until she finds and learns along the way. I also know how to lose, coping with my frustration by taking two steps back, gaining some perspective and resuming.
I dedicated the first part of my career to studying biomedical engineering, which led me to encounter my passion – this project. I then dedicated the second part of my career to learning everything I could about embedded cyber-physical systems, what I considered to be the knowledge I needed to improve my project.
But the perhaps more defining part of my career was this last year, when I have learnt to acknowledge my limitations, and subsequently build a network that has the combined skills to turn my project into a marketed product.
Oftentimes, the sport you're good at is the sport you love. But that wasn't my case, and this is how I learnt about resilience.
The Axel is a jump required to pass the highest exam in artistic roller skating. Years ago I would daily spend hours planning my evening training. I would film myself and then study the videos at home to correct my movements.
I trained so hard... only to be later told by my trainer that I was not prepared for the exam. This fired many emotions, which I later very carefully analysed.
I used sadness to give myself space to grief my loss.
I used the anger to empower myself and speak up.
I used my endless passion for skating to fuel my next step: I couldn't attend the exam, but I did some research and found a contact in the mayor's office who gave me the keys of the skating rink in my town. I started training there every weekend by myself and started chasing a new goal: I didn't need to prove myself to the examiners – i just needed to prove it to myself.
And so I learnt how to actually enjoy skating.
As a student, I attended the European Meeting of Healthcare students as my country's human rights (HHRR) and peace delegate. It was hosted in a beautiful hotel in the heart of Greece, with views over a refugee camp a couple bus stops away.
The absurdity was overwhelming: I would spend a whole week discussing HHRR but sleeping in a warm comfortable bed at night instead of in a tent – just because I had been born in Spain instead of Syria.
That turning point made me reconsider my whole action plan as a HHRR delegate. I then promised myself to "talk less and move more". I campaigned on that idea and got elected as the next national office of HHRR and peace of that student association.
I then started my new project, #moving. We would fly back to the Greek refugee squats to observe, ask and learn... and provide what we can.
Coordinating it taught me a lot, but the golden lesson was:
No great change can be predicted.
When I felt most useful is when I stopped planning and listened to my team. What's our goal? What do refugees need TODAY? Forget the plan and adapt as a team.
- For-profit, including B-Corp or similar models
As early as Roman times, medicine has paid special attention to human physiological metabolites, e.g. uncontrolled diabetes was historically diagnosed by a sweet taste in urine, liver failure produced a fish-like smell... However, human metabolic studies did not meet the oncology field until April 1989 when Dr. Hywel Williams and Dr. Andres Pembroke from King’s College Hospital, London reported a case in the journal The Lancet about a Collie-Doberman owner who attended their practice.
She claimed her dog was showing increasing interest in licking a mole in her leg. The mole was then shown to be cancerous and removed, saving the patient’s life. This turning point made it clear that cancer produces metabolic changes in human physiology, thus altering the body's taste, texture, odour, shape...
This event, which serves as a solid proof of concept, has not yet reached the market. In fact, even if breast cancer is one of the top 4 most diagnosed cancers worldwide, research on its most effective prevention strategy is still non conclusive.
We, however, present a different approach. By relying on AI, we are able to perform a series of chemical analysis on the sample and combine its results, leading to one integrated diagnosis. The last version of the algorithm that we built was able to properly classify 100% of the human samples (n=90).
ORGANISATION ACTIVITIES
In-home pain and anxiety-free breast cancer screening device aimed at the general public
OUTPUT
Delivery of a Blue Box and a Blue App to the end-user to get self-tested at home.
SHORT-TERM OUTCOME
Female patients get engaged in a novel breast cancer screening system that is available and affordable to everyone - regardless of her economical and social status.
- Women above 40-45 decide to skip/complement the mammogram-based screening with The Blue Box
- Younger women (not included in the healthcare system screening yet) decide to actively prevent a breast cancer late diagnosis by getting self-tested at home
MEDIUM-TERM OUTCOME
The patient undergoes self-screenings at its chosen frequency and timing. She refers the technology to other women in her household. Hence, the test is frequently taken by a large population segment.
The above helps shape the patient of the future - one that is empowered to own and decide on its own health.
By participating in the screening program, the user provides her metabolic data and medical condition, which is used by The Blue Box developers to enhance the AI-based classification algorithm.
LONG-TERM OUTCOME
Breast cancer mortality decreases thanks to early prediction.
THE MISSION OF The Blue Box
As a conclusion, the proposed solution is designed to help women, a social group typically underrepresented in medical technology and research, live a full life without the fear and anxiety caused by the currently offered breast cancer screening programs.
- Women & Girls
- Low-Income
- Minorities & Previously Excluded Populations
- 3. Good Health and Well-Being
- 5. Gender Equality
- 9. Industry, Innovation, and Infrastructure
- 10. Reduced Inequalities
The current readiness stage of the project is prototyping. The solution has not reached the market -nor the user- yet.
In one year, it is expected for the project to be in the final prototype stage - the one intended to pass human studies and clinical trials.
According to the proposed planning, in 5 years the proposed technology will have reached the US market at least and be accessible for the user:
The female population of the US is of 165.92 million women, estimated to be placed in 119,730,128 households. There is an average of approximately 1 woman in each household that is currently eligible to undergo the routine breast cancer screening program. According to the CDC, only 63% of these women do actually attend it.
According to interviews that we have conducted to 40 women, over 80% of women with previous knowledge of The Blue Box declare themselves interested in acquiring the product.
To estimate the size of a potential market, it has been considered the hypothesis that about half of the women currently concerned about breast cancer (half of the 63%) would know of and be interested in the device. This can be approximated to 31.5% of American households.
This translates into 37,714,999 households that might be interested in the device. Hence, this is a potential future market size for The Blue Box.
In the future, by means of social media, more households might become interested in the product.
Goal ONE
To develop a new (third) fully working prototype:
Software-wise:
Optimisation of the artificial intelligence algorithm. To do so, a hospital has already agreed to supply urine samples so as to gather patient data.
Hardware-wise:
Printing of the electronics in a motherboard and assembly into a 3D-printed container for increased end-customer usability.
*To be achieved during the upcoming year #1 and #2.
Goal TWO
To complete the application for a provisional patent in the US. This patent will secure the technological improvements included in the third (currently existing) prototype.
*This goal is currently being carried out
Goal THREE
To apply for more funding for the following future purposes:
Non-provisional US patent
Intellectual protection outside the US: Europe, Asia
Involving a third party to handle human studies application
Continue research on human metabolites related to breast cancer
The funds needed to complete these steps are expected to come from to main sources. On the one hand, an application to an SBIR award, from the NIH or NFS will be conducted during years 2020 - 2021. Secondly, private investors will be pitched to tackle patenting feed specifically.
*To be achieved during the upcoming years #2 to #5.
Sociocultural barriers
When conducting market discovery interviews, it was noted that some potential end-users were initially reluctant to trust The Blue Box due to two main reasons. Firstly, the average patient over 60 years of age tends to feel anxious when medical diagnoses are communicated via app - with absence of a medical doctor. This trend was remarkably more acute in Asian nationalities than European and US cultures.
Secondly, elderly women that have integrated the mammogram-based screening as the irrefutable standard for breast cancer screening state that they would only trust The Blue Box if formal proof was published that demonstrated that its classification rate is equal or better than that of the mammogram.
Legal barriers
The potential future possibility of a global market implies the need to patent the technology globally. It is therefore a short-term need to protect the intellectual property in the US. Once accomplished, a later challenge will be to pitch investors so as to be able to file European and Asian patent applications.
Financial barriers
The current state of the project as far as funding is concerned is pursuing seed funding. Having completed the proof of concept and developed a working prototype, years 2020-2021 will be devoted to funding applications (as well as conducting further research and improving the current prototype).
Sociocultural barriers
By means of utilising various social media platforms, it is feasible to create a virtual community that is engaged and motivated to make a good and responsible use of The Blue Box. This would make it possible to educate the population: In the case of a positive result (evidence of breast cancer), further medical advice is encouraged, but a result should not be regarded as a diagnosis until confirmed by a doctor.
Additionally, we have contemplated a possible market strategy to mitigate the impact of a diagnosis on a patient: In the event of suspect of a positive diagnosis, instead of receiving a message via app, the patient would receive a video call from a medical doctor. This would have reviewed the case and would not only deliver the potentially stressful news but also a set of next steps to follow.
Legal barriers
We are currently collaborating with two patenting officers to help deal with legal procedures. To date, we have started the process of patenting the artificial intelligence algorithm that powers The Blue Box. During the next year, we will be pitching advisors so as to fund the patent.
Financial barriers
Finally, we are aware of numerous financial opportunities that would provide the necessary funding to translate the current prototype into a marketed product. The MIT Elevate prize is an example of them.
Our team is currently partnering with the following organisations at the University of California Irvine (UCI):
University of California Irvine @ Beall Applied Innovation ("The Cove"). The Blue Box is currently a part of their Startup Organic Growth pilot program. They provide advisors, laboratory access, office space and office hours to UCI students who are involved in translational science projects. [More info at their webiste].
The UCI ANTrepreneur centre offers the LaunchPad program, from TechStars LA provides UCI students with an innovation advisor that guides them through the creation of a business plan and in taking the first steps into the market. During the academic year 2020 - 2021 we have been LaunchPad Students. [More info at their webiste].
Both of them are equity and revenue-free.
Starting September 2020, our team will start the following collaborations:
Starting September 2020, I will be a full-time Blue Box developer. I am currently looking for funding to support both the project and my research+development. The University of California Irvine will be a collaborating partner providing advice throughout the development of a new Blue Box prototype.
In 2017, during the development of the first Blue Box prototype, 90 human urine samples were collected from control subjects and from metastatic breast cancer patients from a hospital. The collection protocols and patient consent forms were approved by the ethics committee of the hospital. This same hospital has agreed to initiate a new collaboration by the end of 2020.
The purpose of The Blue Box
To rise the number of breast cancers that are detected in an early stage – when they are potentially more treatable.
Key resources
AI-based classification algorithm (intellectual property)
The Blue Box and The Blue App
Virtual community of end users created in social media
Key partners
Medical community (to recommend and endorse The Blue Box)
Key activities
Data gathering for continuous software enhancement
Real-time customer support
Management of the virtual community – product advertising and scientific divulgation
Value proposition
Comfort: Pain-free and anxiety-free breast cancer screening
Wider population screening: Non-radiating and inexpensive in-home screening that can target a large population segment
Customer relationships
Expected client is challenging to acquire but relatively simple to to receive loyalty from
Channels
Technology has a presence in social media
Primary care medical doctors endorse the utilisation of The Blue Box
Customer segments
Women over 34-45 who are included in national healthcare systems screenings but wish for a better solution
Young women who are not yet included in national healthcare systems screenings
Cost structure
2 (currently) R+D engineers who constantly improve the product
Conferences, events and advertising to attract new customers
Medical professionals who call the end-user to deliver breast cancer diagnoses after running each positive test
Online platform for data storage
Revenue streams
The Blue Box is acquired by a household after a single payment. One Blue Box can provide diagnostic services to more than one user account
Every house pays a quarterly/annually subscription per individual user account.
Fig 4. Value proposition and customer segmentation
Phase 1: Financial dependability on grants and external funding
During the upcoming 5 years of this project, it is expected to rely on grants and awards from external parties as well as friends and family funding. The optimal case would be that of being awarded the MIT Solve award so as to advance research during years 2020 - 2021. This would make possible to do further research on improving the AI algorithm whilst conducting an extensive collection of samples at the aforementioned hospital.
After that, a third working prototype would be ready to undergo a SBIR application to the NIH/NSF. In the optimal case of receiving it, it would support 3 to 5 years of advanced research. After that, the product would be ready to enter the market.
As far as intellectual property protection is concerned, we are currently starting the process of applying for a patent. We are also seeking funding to cover patenting expenses.
Phase 2: Financial undependability.
Once the product is ready, a startup will be registered with The Blue Box as its central product. External venture capital pitching will help support this process. Afterwards, the product will be finally available to the end-customer, thus creating revenue.
Phase 3: Positive revenue
If phases 1 and 2 are successfully accomplished, a third phase might proceed in which the revenue is higher than startup expenses. Having reached this point, it will be possible to invest back in research to further enhance and modify The Blue Box.
The Blue Box team has just started seeking for funding. Whilst several applications are still being revised, one of them was awarded to our team: The project award "People who love what they do", organized by the alimentation brand "Argal" awarded The Blue Box with $2,243. This award will cover all project expenses throughout the summer. It will also cover part of travel expenses required for sample collection and the purchase of new material for better app development.
Financial sustainability of The Blue Box project is predicted to present two phases:
Two main seed funding sources are being targeted at the moment: In a first approach the present MIT Solve will be intended for funding during the academic year 2020-2021. By means of this precise funding, the product will be enhanced and tested with a larger collection of human samples. After this pre-clinical study is completed, if successful, our team will then stand greater eligibility when applying for the SBIR award at the NSF and the NIH.
The main immediate goal to-date is to obtain the first round of seed funding (by submitting the present application). This one is a critical step for The Blue Box project since it will determine the success of future applications.
The current funding round is intended to raise $60,000 for the second half of year 2020 in addition to $1,000,000 for year 2021. Year 2020 will be dedicated to the definitive proof of concept - please find a more detailed budget in the next question. Year 2021 expenses will be invested in patenting the technology in various countries outside the US so as to secure a future global market.
Expenses for July - December 2020
I) Phase 1: Software (July - mid Aug)
No variable costs. $0
Fixed costs: Salary for 2 R+D engineers. $9,000
II) Phase 2: Hardware (mid Aug - mid Sept)
Variable costs: general electronic components. $100
Fixed costs: Salary for 2 R+D engineers. $6,000
III) Phase 3: Testing (mid Sept - Nov)
Variable costs: Materials & Facilities.
Lab bench at ULP. $1,950 x 2.5mo x 2pax = $ 9,750
Office space at WeWork. $560 x 2.5mo x 2pax = $ 2,80
TOTAL: $ 12,550
Variable costs: Travel expenses: $1,000
Fixed costs: 0
*This phase overlaps phase 4. Marketing. For this reason it does not have an associated fixed cost for the salary.
IV) Phase 4: Marketing (Oct - Dec)
Variable costs: Materials & Facilities.
Office space at WeWork. $748 x 3.5mo x 3pax= $ 7,850
Marketing materials (approximately). $1,000
TOTAL: $8,850
Variable costs: Travel expenses: $1,500
Fixed costs. Salary for 2 R+D engineers and one legal advisor: $21,000
MIT Solve would be a great help in overcoming the three previously-stated main barriers:
Sociocultural barriers
A medical device that can provide a life-altering diagnosis might face a sensitive entrance into the market. It is therefore important that we focus not only on providing a high-quality and sensitivity technology but also on how to present it. It is for this reason that we hope that by being part of the MIT Elevate prize community we can connect to fellow entrepreneurs in the healthcare industry with insightful advice on this matter.
Patenting barriers
Patent application is one of the main challenges for 2020. As first-time entrepreneurs, we are highly open to receiving any piece of advice from more experienced fellows. In particular, given the wide history of involvement of MIT in translational science, we would highly value it if we were to be chosen and hence have the contacts and the financial means to have access to patenting officers.
Financial barriers
Finally, another notable challenge to face in the present time is scarcity of funding opportunities. Especially now that universities and non-profit organisations are thriving due to the current world pandemic, it is especially challenging to obtain funding not COVID-related. For this reason, being awarded this prize would propel our research and allow us to start a second round of the studies with human samples, this time with more subjects.
If successful, they would result in higher credibility to the project, which is a determinant factor when pitching for future investors.
- Funding and revenue model
- Talent recruitment
- Legal or regulatory matters
- Monitoring and evaluation
- Marketing, media, and exposure
The Blue Box is a response to the current mammogram-based screening being remarkably inefficient. Hence, our team aims at empowering women to demand better healthcare solutions for themselves.
This project is founded in the belief that women have been placed in a second plane in medical research since historical times, which has led to some of their needs being systematically disregarded.
Additionally, according to our research, about 80% of interviewed women agree on the need for a non-invasive and non-irradiating in-home test such as the blue box. Consequently, by applying to MIT Elevate prize, we aim at obtaining the guidance and the financial resources so that
(i) the need for a better breast cancer screening technology is fully and globally understood
(ii) we are able to perform further patient studies to prove that the presented solution is feasible
We are currently establishing a collaboration at a University Hospital that treats women diagnosed of breast cancer. They are willing to provide input and feedback on the specification that our solution should meet.
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Biomedical engineer
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Computer Scientist