What signals in our bodies indicate disease?

With scientific advancements, researchers have a better understanding of the signals in our bodies that indicate the onset of diseases. Theodoros Zanos, head of the neural decoding and data analytics lab at the Center for Bioelectronic medicine at the Feinstein Institute for Medical Research in New York joins Hari Sreenivasan to discuss the future implications of this groundbreaking technology.

TRANSCRIPT

With scientific advancements, researchers now have a better understanding of the signals in our bodies that indicate the onset of diseases.

Joining us to discuss the future implications of this groundbreaking technology is Theodoros Zanos, head of the Neural Decoding and Data Analytics Lab at the Center for Bioelectronic Medicine at the Feinstein Institute for Medical Research in New York.

What is bioelectronic medicine?

Hari, thank you for having me.

Bioelectronic medicine is a new field in medicine that tries to use technology to treat and diagnose all kinds of different diseases and conditions.

We know for a fact that most of our organs are innervated and connect to our brain and communicate.

Mm-hmm.

And they communicate their function and whether something goes wrong.

So, what bioelectronic medicine is trying to do is develop these devices that will listen in on this communication between our brain and our organs, and try to diagnose diseases early, before symptoms arise, and actually treat them by stimulating the nerves or blocking a specific signal.

So, do we -- Have we figured out the language that the organs are using?

So, that's what we're trying to do.

The language of the nervous system is something that we're trying to figure out.

So, one of the things that we're trying to do is listen in on this back-and-forth.

And we do that by placing electrodes, which are microphones, very close to nerves or inside the brain.

And what that enables us is to listen in on these very tiny electrical signals that are used from the brain and the neurons to actually communicate the function of specific organs and also tell the organs what they should be doing, how they should function.

So, one of the key components of these devices is to take that language and try to decipher it into something that we understand and care about.

And that's what we're trying to do in my lab and in the center in general.

So, what sort of diseases are we talking about?

What are the things that are more likely to be able to be visible?

So, what we're focusing right now are diseases like Crohn's disease or rheumatoid arthritis, which are autoimmune diseases.

And previous work at the Feinstein Institute by our C.E.O., Dr. Kevin Tracey, has been instrumental in identifying the role of the neural system in regulating these diseases and, in general, our inflammatory reflexes.

So we're focusing on diseases that are related with our immune system but also our metabolic system, such as diabetes.

And then we also look at the other chronic diseases, like paralysis, as well.

So, what are you able to see now?

Say, for example, if someone is heading into diabetes, what is their body doing?

Is their pancreas telling their brain things all the time, that you're basically starting to pick up on?

Mm-hmm. So, that's really what we're trying to do.

We're trying to pick up on the signals that the pancreas deliver, are sending to the brain, through their sensors.

So, there are sensors that constantly monitor our state, our homeostasis, as we say.

Mm-hmm.

And that really is the language that we are trying to pick up the signals.

We're trying to eavesdrop on this back and forth.

And if used, for instance, in the case of diabetes, whether someone is getting into hyperglycemic or hypoglycemic state, and then turn around and use the same device and the same electrode that listens in on this activity, to actually start stimulating the nerves.

And by stimulating the nerves, we've seen before that we can alter, in the case, again, of diabetes, blood glucose levels.

So, in essence, a closed-loop device that will listen in, identify the problem, and then intervene and start stimulating without the patient even having to do anything or even experiencing any symptoms.

So, how would this device get into my body to be able to listen to these signals?

So, at this stage, we're mainly working with devices that would require implantation, so a surgery.

The main nerve that we're working on right now, which is called the vagus nerve -- it innervates the majority of our peripheral organs -- is located in the neck, so it's quite easily accessible for neurosurgeons to put a sensor there.

Right now, there are surgeries that are happening that place sensors on the vagus nerve in patients with epilepsy, and that takes around 45 minutes.

So it's not a hugely invasive procedure, but it is invasive.

However, we're looking at noninvasive solutions, as well.

We try to stimulate and record from the nerves without actually having to do the surgery.

Well, could this become the sort of pacemakers of the future, where we would actually have implantable devices that are measuring certain types of organs, certain types of signals, and then change those or modify those, based on the needs?

Mm-hmm, that's exactly the idea.

The idea is to -- The pacemaker, you could say, was the predecessor in all of these.

The idea is to have a device that will listen on this activity.

And it doesn't necessarily have to be tailored for one specific disease.

Right now, we are working, targeting specific diseases.

But in the far future, what we are looking to doing is developing these devices so that they will try to tackle all kinds of different diseases that start from a breakdown or a malfunction in the neural system.

When pacemakers were invented, we didn't have at least the advancements in machine learning and algorithms that we have today.

So, what can you take from all of the information that's out there, all the technologies, and how do you make this new kind of pacemaker smarter?

So, that's exactly what my lab is trying to do.

We are trying to use machine-learning algorithms that are out there right now, and they keep on evolving.

And we're trying to use the same ideas that big companies, like Google or Amazon, use to try to understand what we're saying to their devices, decipher our voices, and translate them into actions that the device will need to make.

Kind of the same idea, we try to apply it to listening in on the nervous system, translating that language into actions, and then having a device that is also adaptable.

So it changes according to the different state of the organism and also other problems that might arise.

So it becomes smarter as it's inside the body.

Learns from the body but also teaches the body how to heal itself, and really converts neural signals into what we call health signals.

How far are we from seeing devices that use these kind of technologies?

So, right now, there are several small clinical studies that are carried out at the Feinstein Institute, as well as in Europe and other places in the world.

But, however, the devices that would enable such things would need several years from now to be deployed in the market.

However, we feel comfortable that the first iterations on specific conditions should work, and they are being test right now in clinical trials.

And as I said before, the goal is to make a device that's not tailored to one specific disease but a device that will understand that something is going wrong anytime of the day for a lot of different diseases and try to intervene.

All right.

Theodoros Zanos, thanks so much for joining us.

Thank you for having me.