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Soon You'll Be Able to Detect Cancer Using Your Smartphone

A new start-up named Miroculus has created a device that hopes to detect cancerous cells and various other diseases using your phone and a few drops of blood.
October 23, 2014, 2:00pm

Left to right: Jorge Soto, Chief Technology Officer at Miroculus, Foteini Christodoulou, Chief Science Officer, and Alejandro Tocigl, CEO

The thing about cancer is that you need to catch it early. Once it spreads, it becomes harder and harder to treat. But part of the problem is making yourself go to the doctor in the first place; a lot of people would rather avoid finding out really depressing news, in some cases via invasive poking.

But what if you could detect cancerous cells and various other diseases in 60 minutes using your phone? A new start-up named Miroculus has made a device, "Miriam," that hopes to allow you to do just that. In hugely simplified terms, cancer happens when a cell mutates and begins to multiply. MicroRNAs are the things that regulate how many cells your body creates, so by identifying MicroRNA patterns in your blood, Miriam can work out if anything abnormal is happening, and therefore whether you’re likely to have a disease.

You should, obviously, definitely, 100 percent still suck it up and go to the doctor if you think anything is wrong, but it can't hurt to have something easily accessible that can give you a head start if you have a feeling that something's up. I got in touch with Jorge Soto—Chief Technology Officer of Miroculus—to talk about Miriam and the new era of cancer diagnosis that the machine is looking to usher in.

The Miriam machine

VICE: Hi, Jorge. Tell me how this device came about.
**Jorge Soto: **Our chief scientist and co-founder, Foteini Christodoulou, has been studying the relationship between microRNAs and cancer for the last eight years. She explained the potential of microRNAs and how promising they are as biomarkers. But she also illustrated the challenges about how they are detected these days. So we thought that if we could come up with a device with a low cost solution to detect microRNA and correlate them with specific diseases, we could accelerate the clinical uses of microRNAs as biomarkers to detect disease. Specifically, cancer and metabolic diseases, but also psychiatric diseases.

What were the technological advances that made this possible?
MicroRNA was discovered 20 years ago. But we discovered they are secreted freely in the blood stream five years ago. We used to believe that microRNA was found only in the tissue and organs, but if we find a specific microRNA in the blood we can link it to various parts of the body, as each microRNA tells a story.

For example, if we find microRNA 21 in the blood, it means that something is wrong with your liver. So then we can start asking questions about that. The relationship between microRNAs secreted in the blood and the presence of specific diseases was discovered recently, which allows us to link certain patterns to metabolic diseases such as diabetes and cancer, and psychiatric diseases such as Alzheimer’s. Think of it as a biological fingerprint.

So it’s as simple as placing your blood in the machine and allowing your iPhone to detect the patterns?
Yes. Today, that is how we're doing it. We use 96 well plates [little indents to put blood in], and each well plate looks for a specific microRNA. For example, well A1 is looking for microRNA 21. If you have that microRNA present in your blood when you put your sample in the well, the well will shine green. By measuring which wells are shining and how much they are shining, these parameters allow us to locate the presence of specific diseases. Not only this, but we're able to tell which stage the disease is at. We do it with an iOS app, but by the end of this year we'll have a new version of the device that won't use a smartphone app any more and instead we'll integrate that function into the machine.

What kind of cancers can the machine detect?
There are a lot of scientific publications that detail specific patterns to look for in diagnosing certain cancers with the use of microRNA. At this stage, we're focusing on breast cancer, lung cancer, pancreatic cancer, and eventually ovarian cancer. We wish to start exploring the presence of metabolic diseases such as gestational diabetes, which affects women during pregnancy. It’s treatable and important to detect as early as possible.

How do you see people using it?
Our main objective in the long-term future is for people to include our machine in addition to their annual check up, so you can look for specific diseases at the molecular level. But at this stage we're working with people in clinical trials, as the process we use allows for us to ascertain whether medications used to combat various diseases work. We can see if patients respond to the medication they are on. So, in this sense, it's also a companion tool, which allows you to see if your medication is working.

The wells for the microRNA are patented, but the design for the machine itself has been made open source so people will be able to 3D print it themselves. What's the thinking behind that?
Well, we know that there are people out there smarter than us, and in the past we've seen the benefits of making software open source. We want the best and the brightest to help us—critique us—which, in turn, will allow us to be scalable. We want the device to eventually be cheap for everyone—free, essentially, minus the bimolecular component. We're looking to democratize it. Our strategy is to accelerate the innovation process.

What are your plans for the near future?
The plan is to carry out more clinical trials and evaluations. We're doing some in Germany and starting in Mexico and many other parts of the world. By the end of this year, we're looking to introduce a crowdsourcing element, but this will be announced at a later date. We're confident with the accuracy of the machine, but we're doing work to ensure that we can detect even more microRNAs, which in turn will allow us to correlate and diagnose more diseases with the machine.

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