Neurotechnology? For Cancer? (Ben Woodington & Elise Jenkins)

1. Introduction

2. Timestamps

3. Transcript

Spotify: https://open.spotify.com/episode/6BLZph2uGGUVphbNQ8NGPd?si=SVBSKJM8RdO4AhYzDa-ZfQ
Apple Podcast: https://apple.co/3OU5Zse
Transcript: https://www.owlposting.com/i/189602943/transcript

Introduction

This is an episode with Ben Woodington and Elise Jenkins, who are the cofounders of Coherence Neuro. The pitch for Coherence is as follows: a brain implant that treats cancer with electricity. When I first learned of the company in mid-2025, it was such an alien thesis that I instinctively wrote it off entirely. This surely isn’t clinically plausible at all, maybe it will be one day, but certainly not today.

Then, while I was in San Francisco, I met up with Nicole, Coherence’s chief of staff. After that, I was far more convinced that there was something real here, especially after she told me that the electricity ←→ cancer thesis already has some merit: Optune, an FDA-approved medical device developed by Novocure. This has been on the market for over a decade, and uses externally delivered alternating electric fields to treat glioblastoma. And it works! If Optune is consistently used, glioblastoma patients can live up to twice as long compared to chemotherapy alone. How does it work? Simple: the alternating electrical fields prevent fast-dividing cells from replicating by interfering with the physical process of cell division (specifically, mitotic spindle formation).

After this, Nicole connected me with Ben and Elise, the cofounders of the company. It was an incredible conversation. During it, I was informed that cancer cells behave eerily similar to neurons: hijacking neural pathways, attracting nerves into their microenvironment, and forming synaptic connections with surrounding tissue. Given this set of evidence, none of which felt particularly controversial, an easy logical leap is to ask the question: why can’t you throw neuromodulation at the tumor? Maybe not even just for treatment, but monitoring as well? Optune was a step in the right direction, yes, but surely it can be pushed even further.

So Coherence was born, the only (neurotechnology x oncology) company in existence. Ben and Elise met during their PhD’s at Cambridge, spinning up the startup with the belief that a modality long assumed to be exclusively for neurological conditions like Parkinson’s, epilepsy, and chronic pain, may have a profound role to play in cancer. And perhaps even conditions outside of it.

And during my last trip to San Francisco for JPM 2026, I had the honor to sit down with Ben and Elise to talk about it all.

This conversation covers how Coherence’s first neurotech device (SOMA) works, the molecular reasons behind why neuromodulation affects cancer at all, what the biomarker readouts look like, the obvious Michael Levin comparison, and a lot more. Coincidentally, Ben helped me out a fair bit for my neurotechnology piece awhile back, and that article may be helpful reading material for this episode.

Enjoy!

Timestamps

(00:00:00) Introduction
(00:01:42) How is SOMA different from Novocure’s Optune?
(00:08:57) Why does neuromodulation affect cancer at all?
(00:13:28) How was cancer-nervous system crosstalk first discovered?
(00:15:42) Anti-epileptics and beta blockers as accidental cancer drugs
(00:17:38) What is molecularly happening when you block cancer-neuron crosstalk?
(00:19:50) What is SOMA actually reading out as a biomarker?
(00:20:44) What does it mean that cancer is “very electric”?
(00:22:02) Can you derive universal biomarkers across patients?
(00:23:09) How is the device placed?
(00:24:45) How does the blocking stimulation regime work?
(00:26:43) Is it fair to say this is closed loop?
(00:29:05) Why not just spam the tumor with constant stimulation?
(00:32:31) Why MRI safety is non-negotiable for oncology devices
(00:33:35) Walk us through the patient journey from diagnosis to implantation
(00:36:13) The Michael Levin question: can you reprogram cancer back to normal?
(00:42:29) Efficacy, hospice settings, and the utility of the neuromodulation literature
(00:45:52) Why start with glioblastoma instead of an easier cancer?
(00:48:57) Regulatory strategy and the reimbursement threat
(00:55:37) How well does mouse-to-human translation work for neuromodulation?
(00:58:09) Why didn’t this exist 10 years ago?
(01:01:48) The founding story
(01:06:38) Why build your own device instead of using off-the-shelf arrays?
(01:08:35) Speaking with glioblastoma patients
(01:12:04) What was it like to raise money for this?
(01:13:56) Beyond cancer: TBI, lung disease, and the pan-disease argument
(01:17:40) Hiring at Coherence + what is the hardest type of talent to find
(01:23:17) What would you do with $100M equity-free?
(01:27:15) Are you a neurotech company or a cancer company?

Transcript

[00:00:00] Introduction

Abhishaike Mahajan: Today I’m going to be talking to Ben Woodington and Elise Jenkins, who are the co-founders of Coherence Neuro, a startup that is building therapeutic neurotechnology that manages cancer from inside the body. I first want to talk about what specific device they are building, because I think it really sets the stage for how interesting the Coherence pitch is.

Ben and Elise, welcome to the podcast. Your first device is called SOMA. What exactly does it do?

Ben Woodington: That’s a brilliant opening question. Thank you so much for having us here. To rewind slightly, you’re right, we build technologies that interface with cancer, surrounding biology of cancer using electrical stimulation and recording. We’re really leveraging the intrinsic electrical properties of cancer, and also the way that they intersect and interact with our nervous system. We have a lot of programs ongoing, and I’m sure we’ll talk about some of them today. But as you correctly identified, our first product and program is SOMA, which we’re using in brain cancers. This is a tiny device, a BCI-like device that sits in the skull, and it can deliver an electrical stimulus to a tumor in the brain. We can also record the electrical activity from the tumor and around the tumor for readouts. And we’re working very hard to investigate what those electrical readouts can mean for diagnosis of the patient, for the prognostication of the patient. And of course, the therapeutic potential of that device as well.

[00:01:42] How is SOMA different from Novocure’s Optune?

Abhishaike Mahajan: The interesting thing when I was first researching Coherence is that this is not the first device that uses some notion of electrical fields to interact with cancer. There’s another one called Optune developed by a company called Novocure. Is SOMA fundamentally different from the technology employed there?

Ben Woodington: Fundamentally different, yes. I think the natural development of — we have often said that Novocure is a 25-year-old technology. Optune is a 25-year-old technology. And if Optune is a Walkman, we’re going to be the iPod. It’s a lot more technically dense. We’re doing readout capabilities, recording capabilities. The thing is much, much smaller. We get much closer and in contact with the tumor and the body itself.

Abhishaike Mahajan: Maybe just to give some context as to what the Novocure device actually is, my understanding is that it is a non-invasive device — you stick it to the side of your skull, meant for glioblastoma patients — that emits a low frequency electrical field, preventing fast dividing cells from dividing. What is the evolution of SOMA? What about SOMA is an evolution from that?

Ben Woodington: I’ll let Elise clarify the Novocure point because that was the background of her PhD.

Elise Jenkins: Yeah. So Novocure, as you said, is a wearable device. It’s actually four patches or arrays of electrodes that are positioned on the scalp, on a shaved head. And it delivers alternating current electric fields. They’re actually more intermediate frequency electric fields. And they are proposed to interfere with mitotic spindle formation, the way that cells divide. That’s what Novocure’s technology does.

Abhishaike Mahajan: And what about SOMA ...what is it an improvement on?

Ben Woodington: Though the Novocure device has powerful overall survival statistics, there’s a very steep usage effect curve. When patients use the device around the median time, which is around 18 hours, the overall survival in those glioblastoma patients is about four months. But when they are super users of that device — when they use it 22 hours, 23 hours, or even more — that overall survival goes through the roof and those patients are getting maybe nine months, maybe more, in median overall survival. Which is almost doubling their life expectancy, which is huge. That’s probably the most impactful thing in glioblastoma in the last 20 or 30 years. Now it is a very natural progression to say, okay, why aren’t patients using that device 22 to 23 hours a day? It’s a large compliance issue.

Go inside and you’re in charge of how much stimulus the patient is getting and for how many hours of the day. You offset a lot of those systemic effects — the skin irritation, just the fact that they have to wear something on the head all the time. Patients tend to not like wearing large things on their head. That’s why there’s been so many EEG device failures. Just being able to justify going inside and treating those patients 24 hours a day is a huge benefit already, before you even start talking about the data elements and recording elements that you can introduce, or the novel stimulation regimes that you can start using once you’re inside.

Abhishaike Mahajan: What other electrical things can you take advantage of when you’re actually physically inside the body?

Elise Jenkins: I think there’s a few things. If you think about the way that an electric field is delivered through Novocure’s platform, they require a very large voltage to overcome the skull. There’s a big loss component there. And because of that, they have to carry this very large backpack with a big battery pack, like a car battery, in order to deliver the electric field threshold that they need to enable that interaction with the cell, whether that be mitotic spindle formation or one of the other mechanisms, which is around the process called dielectrophoresis that happens in the cell during metaphase. There are two interactions that happen when you expose that kind of electric fields to cancer cells. And they do that externally using this field. The advantage of going into the brain is that you no longer have that barrier anymore. You don’t need these extremely large electric fields. You don’t need these car batteries. You can have a very small wearable. The interface is non-obtrusive for patients. There’s a big argument around non-invasive versus non-obtrusive. And that’s one of the natural progressions in terms of using this type of technology continuously, which is shown to have the biggest benefit in patients. They’re going in already, they’re doing surgery already on these patients. Let’s put a device in that can deliver that kind of field or other types of electrical stimulation. Let’s do it locally. Let’s also record what’s happening because we’re right there. We’re interfacing with those cells and tissues. And we can do it without being obtrusive to patients’ lives.

Abhishaike Mahajan: And the actual device itself is emitting the exact same type of field that the Novocure device is emitting, or something else?

Elise Jenkins: It can do either. We’ve been looking at — a lot of my PhD work was looking at Novocure’s types of stimulation, tumor treating fields. But the advantage of being closer is that you can start to look at different types of stimulation. Neuromodulation is something that we are particularly interested in. We’ve been exploring different ways of optimizing electrical stimulation in these types of cancers. Neuromodulation is a really interesting one. When we started development of the SOMA platform, we were really interested in the data that you could actually record. That was — we knew that there was a therapeutic intervention that you could use. Novocure had already shown that clinically. We were really interested in the data element. When we started looking at what happens longitudinally when you record electrical activity from these tumors, based on a lot of history of neural interactions that happen with these cancer cells, we started to discover that there were these very interesting biomarkers that are really relevant to what people target with neuromodulation. And that was what drove us to consider beyond just what Novocure is doing with electrical stimulation — field-based mitotic spindle, cancer cell focused — to what’s happening in the rest of the environment and how can we actually target or look at the rest of the environment, modulate that behavior, and how would that affect cancer cells. That’s what we’ve been looking at, optimized strategies for stimulation.

Abhishaike Mahajan: Just to have a good mental model for what the SOMA device actually is and where it is placed in relation to the cancer itself — should I imagine it as like you have a little head right here and a bunch of spikes coming out of it that poke directly into the cancer?

Ben Woodington: We wouldn’t use the word spikes. We would use leads or threads. But yes, the brains of the device is that part that you see that’s anchored in the skull. And as Elise said, that’s delivered at the time of surgery through a very small perforation in the skull. Then the front end of the device is modular. We have leads and threads that come off the front of that device and we can position them in and around the resection cavity after a tumor has been removed, or into a tumor maybe without resection. Then in the rest of the body, we can look at targeting specific nerves or tumors there as well. And as Elise alluded to, we’ve seen some pretty promising results looking at neuromodulation — slightly lower frequency regimes rather than super high frequency regimes — in those peripheral cancer indications as well.

[00:08:57] Why does neuromodulation affect cancer at all?

Abhishaike Mahajan: Whenever I’ve brought up Coherence to other people and mentioned neuromodulation in combination with cancer, there’s always this surprise that neuromodulation does anything to cancer. What is the intuition for why you would expect neuromodulation to do anything to cancer? I can buy that monitoring the nervous system nearby the cancer helps you have some notion of biomarker, but why does performing neuromodulation at all affect it?

Elise Jenkins: I think maybe the same surprise that others might have when they first hear this is the same surprise that people who discovered these interactions had. Cancer cells behave and act a lot like neurons. And I think that was a big surprise for the entire field that started to make these discoveries. A lot of cancer cells — and not just in the brain, this happens in other organs as well — mimic a lot of the behavior that neurons have. They hijack neural pathways. They have an ability to attract neurons into their environment. They also have an ability to attract nerves into their environment. If you’re outside of the brain, all of these properties make a really nice opportunity for you to then consider neuromodulation or other targeted strategies that are not just looking at the cancer cell itself. You could consider a similar analogy with the immune system. When people are looking at immunotherapy, they’re not targeting the cancer cell. They’re targeting a completely different subsystem in biology that they can leverage and tune in a way to target cancer cells. And when people have started to unpack this opportunity — that cancer cells are behaving so similarly to neurons — it massively opens up the therapeutic opportunities that you can exploit, things we have used for decades in other indications. I think that similar surprise was also a surprise to the people who discovered it.

Ben Woodington: And that’s recent. These are recent discoveries over the last five to ten years. Not mechanisms that have been uncovered and explained for 50 years, which is the exciting thing.

Abhishaike Mahajan: Is it fair to say that glioblastomas have the most nervous system interaction and maybe prostate cancer has the least, or is it not that clean?

Ben Woodington: I can say one thing and then maybe Elise can say the other. It’s difficult to draw a side-by-side comparison between glioblastoma brain cancers and peripheral cancers in the body simply because of the nature of those tumors. The tumors in the brain are in a sea of neurons. It’s a volume of conductive tissue, neural tissue, whereas tumors in the rest of the body are heavily innervated with nerves but are not existing within this sea of neurons. So it is tricky to draw exactly a side-by-side comparison. It does change how we design the devices and how we introduce them to the body. But yes, they do still have these neural features.

Elise Jenkins: I think if you’re studying gliomas or tumors of the brain, it’s a natural curiosity to imagine that cancer cells might have some type of similar features because they’re an extension of oligodendrocytes or astrocytes or whatever other brain-type glial cell. It’s not so unbelievable to think that cancer cells might behave similar to the environment they’re in in the brain. And I think that’s also why a lot of the research has been more well-established in the brain — in gliomas and diffuse intrinsic pontine glioma [DIPG], which is a pediatric glioma. A lot of the research is very well-established in those regions. But I also think that’s just a consequence of proximity — how close they are to that environment. When you start to look at these interactions happening in other organs, I don’t think it’s a matter of proximity. I think it’s just a consequence of the fact that people have done a lot of research already in glioma. And now that people are starting to observe these interactions happening in other organs, it’s exploding. If you were to do a PubMed search on cancer neuroscience and look at the trajectory of publications coming out in this space, it’s exponential. I think we’re only at the very start of that now. I think we will start to see that these interactions are possibly happening in every cancer in the body, not just ones in the brain.

[00:13:28] How was cancer-nervous system crosstalk first discovered?

Abhishaike Mahajan: You mentioned that a lot of this research is relatively new, past five to ten years. How was it first established that there is any crosstalk between cancer and the nervous system?

Ben Woodington: By one of our idols and collaborators.

Elise Jenkins: It’s possible that this initial discovery really is a byproduct of over 50 or a hundred years of bioelectricity research. If you look at some of the really early research where people are talking about voltage-gated channels and interactions, the idea that cancer is very electric — that’s not a new phenomenon. That’s been something that people have been talking about and studying for a very long time. I think the discovery that Michelle Monje’s group at Stanford made, where they were able to show that there were basically similar behaviors in cancer cells that were very similar to neurons — and then they actually started looking at, well, if you patch neurons and you start to depolarize these neurons, what happens to the cancer cell? They started to see that not only are they mediated by neural interactions explicitly through synaptic interactions, but they’re also mediated by paracrine signaling. When neurons release specific factors into the environment, or even cancer cells releasing those types of factors, there is this network effect. And that network effect is actually really bad . There’s this reciprocal engagement that they discovered, which has now caused a bunch of researchers to say, there’s so much going on here. What are those individual mechanisms? Which ones are happening through neurotransmitters? How many of them are actually synaptically integrating? It creates this opportunity for a whole new host of targets, whether that be new drugs to discover or new ways to therapeutically intervene, but also looking at repurposing. People have been looking at repurposing epilepsy drugs as neural inhibitors. People have been looking at retrospective studies in gliomas — what happens if you were on an anti-epileptic and you also had glioma, and how is their survival different? You do see these types of differences retrospectively. So now people are starting to do those kinds of studies forwards, which is awesome.

[00:15:42] Anti-epileptics and beta blockers as accidental cancer drugs

Abhishaike Mahajan: Does that mean you can imagine at some point it will become standard of care for all people who have glioblastomas to be on an anti-epileptic, or it’s not that open and shut?

Elise Jenkins: They’re running these trials at the moment. I think if there is a significant benefit, I can’t see why they wouldn’t add that as a standard of care. We’re talking about patients who have such poor prognosis, such poor survival. The standard of care has not changed for 25 years. If there is anything that’s beating or contributing to current standard of care, I can’t see why — if the side effects are not completely debilitating, the quality of life is still very important — but if they can do that, then I don’t see why that wouldn’t be a natural progression as well.

Abhishaike Mahajan: That’s cool. I usually don’t hear about free lunches like that. When I think of anti-epileptics, they aren’t super side effect heavy.

Ben Woodington: Another famous example from another one of our collaborators, Erica Sloan at Monash, where they’re looking at beta blockers — another relatively innocuous drug, generic, widely available. Again, looking at retrospective studies on the outcomes of patients that happened to be on beta blockers and showed pretty profound impacts, reducing the chance of metastasis from breast cancers, I believe, in a way that you wouldn’t necessarily expect from something innocuous and that has not typically been used in cancer therapy. It’s exciting. It’s this uncovering of biology that we haven’t thought about before. There’s drug repurposing opportunities, but also forward looking — what does that mean for our understanding of biology and cancer and the system itself and how we can design new therapies as well.

[00:17:38] What is molecularly happening when you block cancer-neuron crosstalk?

Abhishaike Mahajan: Before we move on to using these signals as a biomarker of cancer itself — let’s say SOMA works, you’re able to prevent the cancer from interacting with the rest of the nervous system, and somehow that improves prognosis, which given the evidence you’ve given so far feels like not too large of a logical leap. What do you suspect is molecularly going on that is actually helping the patient? What about breaking the crosstalk is actually benefiting?

Elise Jenkins: I think there’s a whole host of things going on. There’s not a single molecular interaction that happens between neurons and cancer cells. There are interactions that happen with what they call pacemaker cells, which are specific cancer cells in the network that have synaptic integration with neurons. And then they have this gap junction-mediated network that happens between cancer cells. When we’re looking at neuromodulation as a regime for electrical stimulation, we look at something called a blocking regime, which essentially is a depolarization block. You either try to stop the neuron from being able to propagate action potentials, which in turn could mean things like blocking neurotransmitter release. Glutamate is a primary example — a primary excitatory neurotransmitter that has a really profound impact on cancer cells. There’s a lot of glutamate in the brain. Being able to reduce some of that — when people have used pharmacological blocking of AMPA receptors, they see around a 50% reduction in tumor volume in mice. So we imagine that there is a whole host of things that you’re interacting with when you block that.

Abhishaike Mahajan: Maybe a dumb question, but why does reducing the levels of the neurotransmitters lead to a reduction in tumor volume?

Elise Jenkins: They’re growth factors. Glutamate and neuroligin-3 is another one — another paracrine signal that is picked up by gliomas — they are growth factors.

So you’re blocking growth factors.

[00:19:50] What is SOMA actually reading out as a biomarker?

Abhishaike Mahajan: And with regards to the actual biomarker aspect of SOMA — you implant the device, maybe it’s post-resection or before a resection — what is the actual readout that you’re getting?

Ben Woodington: Fundamentally we’re recording electrophysiological signals as well. For all intents and purposes, you can think of this like a brain-computer interface. We’re recording electrically, we’re stimulating electrically. We’re reading out the same endogenous electrical activity of the brain as a device that’s trying to read out motor intent, for example. We’re looking at spike rates across the brain and more broadly, local field potentials — frequency shifts in the brain. Cancer cells do have this intrinsic electrical property as well. And you can measure that and we have measured that.

[00:20:44] What does it mean that cancer is “very electric”?

Abhishaike Mahajan: Before you move on — you mentioned that cancer is very electric. What does it mean that something is very electric? Why is cancer very electric?

Elise Jenkins: They have a very high expression — or they retain a very high expression — of voltage-gated ion channels. When they say they’re very electric, they hold a particular membrane potential. They depolarize under certain events. Those depolarizing or hyperpolarizing events usually occur during the stage of the cell cycle. That’s what we mean by that — they’re very electric.

Abhishaike Mahajan: Sorry, go ahead.

Ben Woodington: It’s important to clarify. We are looking at this electrical activity of the brain. We use that as a proxy for what is going on in the tumor or near the tumor. Because of these interactions between the tumor and its microenvironment, we can use that electrical proxy to inform ourselves of what’s going on in the tumor. We’re not measuring specific biomarkers or specific proteins in that microenvironment. We’re measuring the electrical activity of the microenvironment and what that means. Trying to correlate that to tumor volume, or drug responsivity, or seizure activity, or maybe the aggressiveness and growth rate of the tumor — trying to do all of that from electrical proxies.

[00:22:02] Can you derive universal biomarkers across patients?

Abhishaike Mahajan: That sounds very custom from patient to patient and tumor to tumor. Are there actually some universal properties that you can derive from the EEG-esque readouts or spiking that you’re getting?

Ben Woodington: We’re going to find out in humans. Yes, in rodents. But of course rodents are very homogeneous between mouse and mouse. We’re going to find out in humans. I will say, using electrical biomarkers as a proxy for something else is not new. People are doing this in other areas of medicine. People are now looking at this in Parkinson’s, in pain, in depression. And in those spaces, there’s still a lot of variability between patients. We expect to be able to demonstrate the same thing in humans between patients by training one model and applying it to multiple patients. That’s the end goal. Of course, proof will be when we run our long-term human studies, because these have never been done before. It’s one of the most exciting things — people have done this intraoperatively. You can take a recording from a patient, from a tumor while they’re under in surgery.

[00:23:09] How is the device placed?

Abhishaike Mahajan: We’ve been talking about when you actually implant the device — it could be pre-removal or post-removal. The pre-removal setting makes some sense to me. You attach the leads into or around the tumor itself. In the scenario where the tumor has been removed, are you just placing it into the cavity where the tumor was found, trying to see if there are any tumor cells left over? What’s the use case there?

Ben Woodington: In the margin. In the brain cancer case, most recurrences — glioblastoma, to paint a picture, is a horrendous disease. Always terminal, unfortunately, and very poor mortality rates. Those patients, even after a resection — somewhere between 70 to 80% of patients are having a resection, are fit enough to have a resection — all of them will get a recurrence again. And of those patients that get a recurrence, most of them, I think 90%, are in the margin of where the resection was made. That’s where your residual cells are. That’s where your tumors start again. That’s where we’re targeting first. Now that’s not to say we can’t go more broad area, and we have internal programs where we’re looking at broad area coverage, maybe from the surface of the brain, maybe deeper in the brain. The goal is to get as much coverage of the brain as possible so you can control distantly as well.

[00:24:45] How does the blocking stimulation regime work?

Abhishaike Mahajan: This is somewhat clear in the case where you’re purely recording and you get this spike readout. For the case of intervention, what does the perturbation you’re applying actually look like? You mentioned something about blocking. Could you talk a little bit more about that?

Elise Jenkins: There is a multitude of stimulation regimes, but one of the ones that we’re really particularly interested is this blocking regime. When we started looking at biomarkers — when we started recording longitudinally — what are the electrical biomarkers that we’re seeing change in the brain? We saw a really interesting peak in hyper-excitability. If we look in the high gamma range, you see this week-to-week increase in high gamma activity in tumor-bearing mice. Frequencies above 70 Hertz. That’s where we tend to see very distinct changes in brain activity during progression of disease.

What led us to thinking about blocking was, well, if we know the general spike rate of these kinds of neurons in a particular region of the brain — it varies throughout — computationally, we started deriving some neuromodulation parameters that looked at modeling the neuron and essentially looked at, can we block, can we stop this activity from happening? If you generate an action potential, how do you stop it from generating again? And what consequence might that have on cancer growth? That’s essentially the types of perturbations that we’re looking at. If you’re not familiar with blocking, you can think about it similarly to how you would evoke a neuron. If you stimulate a neuron, you evoke an action potential. When you block, you essentially stimulate at a faster rate such that when it tries to regenerate or repolarize, it can’t. You leave it in this constantly depolarized state. It can’t reach a threshold. It can’t activate. That’s the kind of perturbations that we’re interested in, in the brain and outside of the brain.

[00:26:43] Is it fair to say this is closed loop?

Abhishaike Mahajan: Is it fair to say that this is closed loop and that it is not actively learning about the electrical state of the cancer?

Ben Woodington: Currently, no. This is an open loop system. Rather than thinking of this as a closed loop therapy, we prefer to think of this as a theranostic platform. We have some electrical stimulation where we’re treating this disease and we have a diagnostic function where we’re reading out and we present the clinician and the patient with what is going on. You can imagine that would be overlaid on an MRI to say what’s going on with the tumor in real time, very fast. That’s great — it’s a new diagnostic weapon. Eventually, of course, you train these models and these systems to be better than clinicians so that you can make these systems closed loop. That’s the holy grail across many aspects of neuromedicine, where you no longer have to have a second diagnostic readout and say, how do we tune the stimulation, where do we position the next device, the next electrode. Instead, the system’s doing that for you, optimizing exactly where it’s treating, where it’s stimulating.

Elise Jenkins: It might be helpful to understand that when we started trialing these types of blocking stimuli in the brain — high frequency blocking is not new, people have been doing this for a while throughout the body — there is a way that you can understand whether or not you’re having an effect in the brain. What we typically do is record a segment of electrical activity, process that data, look at the frequency band. We apply stimulus, we then record again, and we see that there is a transient response when you deliver this type of neuromodulation, where you can see a decrease in the high gamma range that we’re interested in. And that’s also how we threshold. That’s also how we would work out — do we need to increase the stimulus, do we need to change the stimulus, do we need to change which pairs of electrodes we might be using to achieve a certain area of activation or blocked regions of the brain. We can use those kinds of methods of pre and post recordings to tell us whether or not we’re having the effect that we desire.

[00:29:05] Why not just spam the tumor with constant stimulation?

Abhishaike Mahajan: Incredibly naive question on my end, but it sounds like you just want to be constantly stimulating all points of the tumor as much as possible to prevent it from ever being able to fire off an action potential.

Elise Jenkins: Pretty much.

Ben Woodington: In some scenarios, yes. But we are also running studies where we’re looking at dosing, because there are other mechanisms at play as well. Some of those mechanisms — you don’t need to be stimulating and spamming them constantly. You can perhaps dose once a day and elicit some local biological response as well.

Abhishaike Mahajan: I’m curious, if you’re actively going to be working with a clinician to tune the actual inner workings of the SOMA, what are the knobs of control that the clinician is actually allowed to tune? If it seems like just overloading the tumor with stimulus is what you’re doing in practice.

Ben Woodington: I would draw a parallel between radiotherapy. Whole brain radiotherapy is really fucking grim. If you’ve ever seen a patient go through whole brain radiotherapy, it is gnarly. It is awful. It affects their whole brain, as the name suggests. And those patients are never quite the same afterwards. Clinicians don’t want to do that. They do it as a last resort and they try to use very focused technologies where they can hit the tumor very hard and spare the rest of the brain. That would be the approach that we would take as well. And it’s the approach that Optune takes — they focus that field, focus the stimulation to as much of a concentrated point as they can, so they can hit that area as hard as possible. That’s what we would want to do as well, rather than targeting the whole brain.

Abhishaike Mahajan: Instinctively, why is there any off-target effects if all of the threads are around the tumor?

Ben Woodington: Because current spreads.

Elise Jenkins: The network in the brain is crazy. You have long-range projection neurons. You might be affecting the body of a neuron in one area that has a projection going very far away. There is definitely a network effect. One of the things that we’ve been looking at is how you can computationally model what the affected area of tissue might be — affected meaning the area that would be blocked. We’ve integrated neuron models into our computational models that essentially tell us, this is the threshold that we need to hit in order to block a neuron X distance away. You build these really nice balloon-type shapes around the electrodes that tell you how far you’re actually going to reach if you want to block neurons. And then of course there are probably some neurons, as an extension, that are connected somewhere else in the brain’s network. At the same time, you’re also imagining that in glioblastoma, when these patients are having resections, they’re having big chunks of tissue just taken out. Trying to preserve function and being aware of which areas of eloquent cortex you want to try to avoid so that you’re not inhibiting movement or inhibiting speech or inhibiting critical functions — trying to design the stimulation parameters or the way that you might activate those electrodes, where should they be in order to avoid those spots. You can do that by taking the MRI into account as well.

[00:32:31] Why MRI safety is non-negotiable for oncology devices

Abhishaike Mahajan: Actually, I’m curious — you do mention that SOMA is MRI-safe. Why is that important or particularly useful?

Ben Woodington: It is absolutely critical for oncology. MRI is not going anywhere. It’s the gold standard imaging technique. It’s used in the brain more than anywhere else. In glioma cases, they ideally want the patient to be having an MRI every three months. If you introduce a device to the body that is non-compliant with MRI, that’s a massive problem. That’s one thing. The second step is not just inducing compliance into the device, but making sure that device doesn’t cast any artifacts. MRI relies on magnetic fields, and if you have a magnet in your device or large chunks of metal, that will affect the MRI image. You start casting shadows, and your clinician’s not going to like that. We’ve spent a lot of time engineering this device and using technologies in this device to overcome this issue.

[00:33:35] Walk us through the patient journey from diagnosis to implantation

Abhishaike Mahajan: External from the actual inner workings of the device with regard to therapeutic interventions and the biomarker readouts, I am curious about the practical use of this device in a clinician’s workflow. What will it look like? You’re diagnosed with glioblastoma — you immediately have this put in, or what?

Ben Woodington: We’re going to work our way up through patients. Our first patients will be the most sick, recurrent patients who are probably coming in for their second surgery at this point, and the device will be left behind. Then we’d be moving towards newly diagnosed patients. Let me walk through what that generally looks like for a patient. A patient would usually present with perhaps a seizure — fit, healthy, 42-year-old man or woman, has a seizure. They go to A&E, the doctor will say, I think you should have an MRI. You have an MRI. They spot the tumor. Pretty quickly you’re brought into surgery — within a few weeks, ideally — for a resection. Our best clinical access point would be right there. Leave that device behind at that first surgery. The patient will then have radiotherapy and chemotherapy, temozolomide usually. Eventually we want to work our way up and be at the top of that pile.

Abhishaike Mahajan: Let’s say you run the clinical trial with SOMA. The thing that I would be instinctively curious about is that the patients who are most willing to have this device put in are also the sickest, and potentially the device might not be able to do anything at all. Is that at all a concern?

Ben Woodington: No. We will have done a lot of work preclinically to validate this technology. We’re adopting some of the lessons from Novocure as well, which is now very clinically validated — it’s been on the market for 20 years. Of course, early feasibility patients are always signing up for a clinical trial. We won’t be signing those patients up saying we guarantee this is going to end your disease and you’re going to live forever. That’s not something we can do, just like any other drug or device trial. We’re going to be working within the bounds of ethics of clinical trials as well. But there’s a hell of a lot of work that leads up to that so that we’re confident we’re going to have a clinical and therapeutic effect.

[00:36:13] The Michael Levin question: can you reprogram cancer back to normal?

Abhishaike Mahajan: One thing I did want to ask — whenever someone outside of the bio field hears about bio, their first thought is Michael Levin. If I put my Michael Levin hat on and look at Coherence Neuro, my thought is: well, if you put SOMA into a glioblastoma, why can’t you just reprogram it back into a normal neuron, because all cancer is membrane depolarization gone awry? That probably isn’t true, but what is your view of the Levin-esque understanding of bioelectricity?

Ben Woodington: I’m going to hold back for a second.

Elise Jenkins: The way I interpret Levin’s interpretation of what’s going on in cancer is essentially that cancer is maybe mostly influenced by external cues, less so by genetic abnormality. I think that aligns a lot with the way that we’ve been building this technology and how we would use it — we’re trying to influence the environment, given that that’s a dominant factor for how these diseases are able to thrive. If you can believe that cancer cells are able to modify themselves to thrive in a particular environment, it shouldn’t be so far-fetched or impossible to believe that the same can be said in reverse. I think the challenge against some of this thinking is that cancers are normally diagnosed at a really late stage. At that point you have a significant number of driver mutations that have happened. Saying that you can essentially nudge these cells back into a healthy state is a bit of an oversimplification. However, I do think that by using something like a bidirectional interface — where we’re no longer just relying on what we see in a cell at a specific point in time, a snapshot at day one or day five, and we miss everything that happens in between — I think there is a lot of information that we can get out of longitudinal data. What happens to that cancer cell or that environment over the course of its evolution? We don’t have that yet, and that’s exactly what we’re trying to build. And I think it’s not infeasible to think that these types of devices will be able to have single-cell resolution at some point. So while I don’t fully buy just yet that you can just nudge these cells back into a healthy state, I don’t think it’s so far-fetched. If we understood what was happening that makes them change through time — which we still don’t know — perhaps if we listen to them and read from them and learn what’s happening, I don’t think it’s that crazy that we can start thinking about what kind of nudges we need to make to put them back into a healthy state. This is not super crazy.

Abhishaike Mahajan: So the argument is that at the very start there is genuinely membrane potential gone wrong, and then driver mutations are acquired, and then it’s irreversible.

Elise Jenkins: I think that in a simplistic view, you could say that, but there is so much going on in a cell. It’s an oversimplification to say that one single voltage channel is driving this entire process. I think there are multiple things going on — multiple different membrane potential-mediated interactions that are happening that drive the change in DNA or whatever else it might be that says, now change this expression, express more of this protein, so that you can leverage the environment. As they’re growing, that growth happens exponentially. You’re having so many more of these mutations happening. And as the environment changes, they change again. They’re really clever at figuring this out. I think that because we catch it after so many things have happened, it’s very hard to work out how you’re going to go back and change 15 or 16 different steps with one single application.

Ben Woodington: In a highly heterogeneous tumor environment that now has 40 different cell types or however many.

Elise Jenkins: And I don’t think you can make the claim that if you stimulate that environment — let’s say you try to target just the cell — that there’s no consequence to the neighboring non-cancerous, healthy participating cells. You’re going to modify them too. How do you design a protocol or a system that essentially only targets those specific channels, for example? If you look back at around 2010, there was a really incredible review article that looked at what happens in cancer cells — what happens to the membrane potential, what happens when they depolarize just before they enter a certain stage of the cell cycle. It’s called cell cycle-mediated membrane fluctuations. There’s so many things involved in that process. I don’t know how you could really specifically target one specific version of the ion channel that can mediate that change. It’s complex.

Ben Woodington: I’m going to go one level higher. Ion channels are important. Membrane potential is important. And our best chance to mess with it and target it is by using electrical biological interfaces like high-density BCIs. That’s exciting. I think there’s a lot of potential there. I don’t think we know yet what the downstream effects can be, because a lot of this has been done in a dish. A lot of this has been done maybe in simplistic rodent models and not a lot of this has been done at the network level and single-cell level in a human brain. So I think it’s exciting, there’s a lot of potential. Jury’s out on whether you can fully reverse cancer back to a healthy state.

[00:42:29] Efficacy, hospice settings, and the utility of the neuromodulation literature

Abhishaike Mahajan: At least for SOMA-like devices that have been tried in mouse models — has there been anything more complicated than mice, or is it just mice?

Ben Woodington: Mice for cancer. All of our safety work is done in larger mammals. The cancer models in larger mammals are less useful, let’s say. Spontaneous models in some companion animals can also be used.

Abhishaike Mahajan: How well does this work in mice? Like neuromodulation for cancer.

Elise Jenkins: In pharmacological settings, what people have shown is around 50% reduction in DIPG, so pediatric glioma. That’s essentially our target. We’ve been looking at how different types of stimulation parameters work in glioblastoma versions of those models. We’re still working on that right now.

Abhishaike Mahajan: Is that for monotherapy or is that combined with something else?

Elise Jenkins: We do both. We’re looking at combination treatment with the standard of care, which is temozolomide, and we also do standalone treatment with a host of different neuromodulation parameters.

Abhishaike Mahajan: Actually, this is something we completely did not discuss. Is SOMA useful even if a patient is going to live only two more months — just for reducing symptoms? Is there a good argument that could be made there, or is it iffier?

Ben Woodington: There has been work that has shown that neuromodulation can be used to reduce seizure activity. And electrical stimulation can be used to reduce seizure activity. There’s a hell of a lot of work that’s been shown that you can reduce pain. You’re talking to some of the same nerve bundles that the sensory neurons are traveling down. I think it’s very likely that we will end up reducing seizure burden, pain burden, et cetera. But again, we can’t speak to our rodents. We’ll have to find out when we do our intraoperative and safety work in humans.

Abhishaike Mahajan: My impression is — are you able to just automatically take advantage of all the neuromodulation literature that’s out there when using SOMA, or do you need to build up your own corpus of knowledge because it’s a brand new device being used for cancer at the site of where cancer just was?

Ben Woodington: Both, right? We massively leverage elements of Optune and Novocure and elements of the neuromodulation world. This isn’t coming out of thin air. There is a body of work that’s been around in the neuromodulation world for 60 or 70 years. We leverage a lot of that, looking at how electrical stimulation routines affect biology and neural firing. We are adopting some of that and applying it to new diseases.

Elise Jenkins: The only thing I would add is that especially on the device product development for the human device for SOMA, there are so many neuromodulation and electrical neuromodulation devices that exist that we can absolutely learn from — to the extent of how do you characterize the electrodes. This is really important to make sure that they’re safe. All of that literature is directly relevant and useful, and we use it all the time.

[00:45:52] Why start with glioblastoma instead of an easier cancer?

Abhishaike Mahajan: This is more of a broader question, but if it turns out that cancer broadly interacts with the nervous system, why go after glioblastoma specifically? Pan cancer would be too ambitious of a goal to start with, but alternatively, why not go after a cancer that’s perhaps less fatal and a bit easier to work with?

Ben Woodington: I think pan cancer is the right amount of ambition. We do want to go pan cancer with this. I think what we’ve seen historically in cancer treatments — the ones that really move the needle are the pan cancer approaches that tackle some fundamental mechanism. Cut the thing out — one of the most effective approaches for cancer treatment. Burn it with radiation — one of the most effective treatments. Chemo. Immunotherapies. Things that affect lots of tumors. We’re going for the same thing. We want to build devices — one for the brain, one for the torso — and we want to go after as many solid tumors as we possibly can. Any of them that we see an effect in, we’ll be pushing forward. Why start with the brain then is the next question. Because it’s hard. There are a number of reasons for this — economic, technical, and cultural. Number one, Novocure has set the stage for the use of electrical devices in brain cancer. The FDA regulators and payers are comfortable with the use of electrical stimulation devices now in glioblastoma. That’s a big cultural moment for these kinds of devices. Clinicians are comfortable with the use of these devices and with physical modalities of treating the disease as well.

Elise Jenkins: 70 to 80% of patients are having surgery.

Ben Woodington: Number two is the surgical elements. For our first devices — and this may not be the case forever — we’re implanting, we’re going inside. So we want to be looking at diseases where surgical intervention is not uncommon. Bring the barrier right down. The risk floor is established. Leaving something behind is marginal risk there, versus trying to justify with many of these neurotechnology companies trying to justify new surgery for a patient — the risk-reward starts to get complicated. For us, we don’t have that issue. And then the final large reason — there are many, but the final large one — is how many therapy options are out there, and what are the macros looking like for new interventions coming to these diseases. Glioblastoma, unfortunately, is not a pretty picture when it comes to what’s on the horizon. The standard of care has not changed for 25 years. Optune is probably the most transformational thing that’s happened in those 25 years. Outside of that, there isn’t a lot of hope. There aren’t many clinicians singing the praises of other technologies coming online over the next 10 years. We want to be at the top of that pile. We want it to be resection, radiation, radiotherapy, chemo, and us. That’s not as easy of an equation for, say, breast cancer.

[00:48:57] Regulatory strategy and the reimbursement threat

Abhishaike Mahajan: You mentioned that Optune has paved the way for medical devices to be used. I’m assuming that by virtue of this being invasive, there will be some new territory that you have to navigate. What is that new territory? What are the logistical and regulatory challenges ahead?

Ben Woodington: Regulatory — we’re not scared of regulatory. We will get this device approved. It’s very likely that we’ll get breakthrough designation for this device. I’m not concerned about that. Reimbursement is your biggest threat and challenge in devices, always. We need to be designing trials, designing the device, designing how the patient interfaces with these devices, and how that also makes payers happy. Novocure has laid some of that groundwork, but there will be different costs. There will be different costs involved in the surgery with the patient, how the surgeons are interacting with the device, how the external components are being supplied to the patient. We need to design trials and a go-to-market strategy that lends itself to that.

Abhishaike Mahajan: This is maybe related to the actual implantation process itself, but do you need a Coherence employee alongside the surgeon, helping guide how exactly the device is put in?

Ben Woodington: It’s a good question, but no. We’ve been designing these technologies alongside clinicians, neurosurgeons, and neurologists to make sure that we are compatible with what they already do. How they plan surgeries, how they implant devices — so that we’re not having to build a hundred-million-dollar robot.

Abhishaike Mahajan: The Neuralink way.

Ben Woodington: There’s obviously some incredible engineering that’s gone into that, but right now we want to get into patients as quickly as possible. They don’t have much time and we want to get there fast. The best way to do that is by giving a device to a clinician that requires minimal surgical training to start

implanting in patients.

Abhishaike Mahajan: That makes sense. Well into a question I’ve had for 30 minutes now. What are the axes of improvement that are on the table for SOMA to be improved upon?

Ben Woodington: Size is critical. The smaller you can go, the wider your patient population and the safer these technologies are. Everyone’s trying to move to more and more minimally invasive approaches where eventually, as Elise said, you’re going through some very small, single-digit millimeter access point into the body.

Abhishaike Mahajan: If it’s at a certain size, are you limited to the most severe, largest tumors?

Ben Woodington: We’re already very small. Our device is about half the width of a Neuralink device, which is compatible with standard burr perforations into the skull — the kind they’ll do for a biopsy, for example.

Abhishaike Mahajan: Is there a good visual indication?

Ben Woodington: A thumbnail. About the size of a thumbnail.

Yeah. Now there are other improvements, of course — power efficiency, electric coverage, all these kinds of elements. Eventually maybe you want high-density electrical coverage to get more and more precision in your stimulus and recording. There’s of course always improvements to be made.

Elise Jenkins: Big one for me is access. Right now, one of the limitations that you might see across a lot of neurotech platforms going out today is how much access of the brain can they get. Neuralink has a really high-density multi-thread device, but they’re all going into a specific region of the brain. One thing that we’ve been really focused on is how do you get multiple access points? How do you create a device or a platform that can access the front of the brain, versus the side of the head, versus somewhere at the back of the head — so you can access multiple areas, but your surgery is still very minimally invasive. By shrinking everything down really small, you can imagine not just having one of them — maybe you can have multiple of them. Now you’re not only accessing this specific region of the brain, but also this region and this region, or across hemispheres, to see if it’s migrating across. That’s something that is pretty hard but quite interesting on our end.

Abhishaike Mahajan: Actually, if a tumor is on one side, why would you care about what’s going on on the other side? The tumor is at the occipital cortex — why would you care about what’s going on in the frontal cortex?

Elise Jenkins: Because of these network effects in the brain. You have a crossover point in the corpus callosum where you have neurons — motor activity that might be happening on one side is actually projecting over.

Abhishaike Mahajan: Okay, they’re projecting on over.

Elise Jenkins: So you can imagine that if you have a very diffuse tumor that is making its way across the brain and actually going to project into the other hemisphere — if, long down the line, you had a device on the primary side of the resection with some electrodes or probes in that region, but you know that they are going to at some point migrate across, you can also put an electrode there and pick up the signals before they start moving across, and maybe start stimulating earlier on that side of the brain.

Abhishaike Mahajan: Wait, what do you mean by migrate across?

Elise Jenkins: It’s not uncommon for very diffuse tumors to move from one hemisphere across to the other hemisphere.

Abhishaike Mahajan: I did not know that. It’s terrifying.

Elise Jenkins: It’s really terrifying. And you can’t see this on MRI for diffuse tumors because they don’t pick up the contrast. You can’t see them, which is a problem. But you can record them. And we know that we can record them. So if you were able to implant in multiple regions of the brain across hemispheres, you can start to actually record when that is happening. You can pick them up from long-range projection neurons as well. We could start recording that information and also start intervening at a much earlier time point.

Abhishaike Mahajan: Is it obvious how many SOMA-like devices you would want in a glioblastoma patient’s brain? Is there a max — like seven of them is enough to cover all the important spots?

Elise Jenkins: It would be entirely based on their MRI. In the pre-operative setting, you would take their MRI. The surgeon will know the extent of resection that they will likely be able to perform, and you’d pre-plan with software that essentially tells you: position the electrodes in this position to get this coverage. That would be how we would do that.

[00:55:37] How well does mouse-to-human translation work for neuromodulation?

Abhishaike Mahajan: Returning back to an earlier thread about all the mouse discussions we’ve been having — how big of a concern is translatability from a mouse platform to pig, to human? Is membrane depolarization a pretty well-conserved phenomenon across all life, or is it case by case?

Elise Jenkins: Particularly in neurons, it’s very well conserved from mice to pigs to humans. We started almost all the way in computation — in silico — then we went into in vivo models. In vivo models for cancer are mouse models.

Abhishaike Mahajan: What do in silico models look like for neuromodulation?

Elise Jenkins: You model the neuron using a Hodgkin-Huxley model. You can computationally, mathematically build that model. You can get that model to generate a specific spike rate. Those are quite well characterized depending on the region of the brain you’re in. Then you can start applying stimulus in silico — computationally — that helps you with selection of what kind of stimulation parameters you think might work best for the region of the brain that you’re in. Then you go into mouse models. These are the most relevant models we can use for oncology. We use orthotopic models, xenografted models. We take human cells, put them in the brain. It’s quite a hard model to do. Then we take a device that is already very difficult to make small for humans and we make it 10 times smaller and put it in a mouse brain. We do a number of tests over short durations to work out the optimal stimulation parameters and the effect of those. Then we go to large animals. We’ve done large animal studies. We’ve been able to show the same suppression effect in large animals in healthy brain. And the natural progression from that is to go into humans. We just got approval to do our first-in-human study to try the stimulation parameters in humans. So far the trajectory seems as good as we can possibly expect.

Abhishaike Mahajan: That’s exciting. Does that translate to a Phase 1 trial?

Ben Woodington: It’s our first-in-human safety work. It’s not a Phase 1, but we’ll be doing recording, mapping, and stimulation safety across the brains of patients.

Abhishaike Mahajan: And this is for glioblastoma patients?

Ben Woodington: It’s for glioblastoma. And that will lead into our next phase.

[00:58:09] Why didn’t this exist 10 years ago?

Abhishaike Mahajan: Exciting. Why does this not exist today? Why doesn’t every glioblastoma patient have this?

Ben Woodington: There has been a lot of innovation in neural implants over the last 20 to 25 years. Miniaturization of electronics, better powering methods, new electrode materials and lead materials. There has been a hell of a lot of innovation — things that didn’t exist in the early 2000s, frankly. On top of that, with Neuralink coming to the table in BCI, there’s obviously been a lot more focus on the use of these kinds of technologies across diseases. Many diseases. And a lot more cultural acceptance from clinical centers to adopt them. I think that’s one of the reasons.

Elise Jenkins: I also think that for us, the scientific underpinnings of these interactions are still very new. The discovery of bioelectricity is not new, as we said before, but the neural interactions that are happening and observed in cancers are really new. I think that in combination with the ability to miniaturize technology and get it implanted chronically and record and stimulate these environments for patients who have literally nothing else — those have been the limitations before now.

Ben Woodington: And to underline how new that is — we sometimes present to academic cancer groups or cancer neuroscience groups. We show our mouse setups that we’ve developed. And it’s a bit mind-blowing for them that you can do high-density neural recordings across the brain of a mouse over months — four, six months. These are technologies that haven’t quite existed in that way. They didn’t exist in that way 30 years ago. We are really at the early stages of that.

Abhishaike Mahajan: When you go to something like the AACR and present your results, it seems like such an interdisciplinary field. There probably can’t exist that many people in the world who really understand the intersection of cancer and neuromodulation, and whatever other fields you’re intersecting with. Do most people seem convinced today that there is something here, or are there still skeptics?

Ben Woodington: I think if there are not skeptics, you’re not working on the bleeding edge. You want people to not agree with everything you’re saying. Our interactions with clinicians and cancer biologists, I would say, usually go like this: “I’m not sure.” And then we show them data. We talk through it. We show them devices, we show them work. And then there’s a big buy-in — people are very excited. I think they see the same things that we see. By the way, I had the same interaction. I come from a neurotech background, a neuroengineering background. I was working in spinal cord and spinal cord injury for years. I had the same response when Elise showed me this about four years ago. It took me a while to digest the papers and read the research and then go, “Oh man, why is no one looking at this? There’s so much opportunity here. I would do this device and this device and this device.” And now we are having the same effect with clinicians who start saying, “Well, hang on — this is how I would design the device to do this.” There suddenly becomes quite a lot of buy-in. I think we’re just at that takeoff point right now. I think we’re going to see a lot more attention clinically, and probably some companies as well, take off. And we’re excited about that.

[01:01:48] The founding story

Abhishaike Mahajan: Similarly, when Elise showed you this — these results from three years ago?

Ben Woodington: Four years ago.

Abhishaike Mahajan: Do you think that was the only moment a company like Coherence could have been founded, or was it just right place, right time to discover this information and put all the pieces together and think there is an unmet need here that’s filled very cleanly by this device?

Elise Jenkins: I felt like I was very lucky because I was really interested in — actually, I was bought into the PhD to look at a drug delivery implant. I knew nothing about glioblastoma. I knew nothing about cancer in general. I’m an electrical engineer. I really wanted to understand the problem. When I started looking at this problem, it’s horrific. I started looking at the potential of a drug delivery platform — an implantable drug delivery device — what is it going to offer here? These cancers don’t respond to these drugs. Maybe you can repurpose drugs that can’t cross the blood-brain barrier — that’s one advantage — but they still just manage to evade these drugs and kill patients. Then I heard about Novocure’s work. I was like, absolute bullshit. No way this works. This doesn’t make sense. I built a platform to try and replicate the work. There’s a whole history to that. I was like, I’m going to figure out what’s going on here. I’m very curious. And I could not disprove it. I tried, and I kept seeing what they were showing in their data. These cells would halt when you would deliver this type of electrical stimulus. My PI, George Malliaras, at the time — we were talking about, well, what happens? There’s an infinite parameter sweep that you can do here that looks at uncovering how cancer cells behave when you put them under certain electrical stimulation parameters. And at the time was when the work from Michelle Monje’s lab came out. I think it was 2019. One of my other advisors had pointed me to this work. I was quite into the membrane potential. I was like, maybe that’s what tumor treating fields are doing — they’re modulating calcium ions or calcium modulators in the cell.

Ben Woodington: Levin is right. Novocure just don’t know it.

Elise Jenkins: I was convinced that that was what was going on with Novocure. At that time —

Abhishaike Mahajan: The mitotic spindle theory was not proven out?

Elise Jenkins: It’s definitely been hypothesized.

Abhishaike Mahajan: Even today, it’s not known for sure?

Elise Jenkins: There’s been a lot of evidence that suggests that’s what’s going on. Yes. But from an engineering perspective, it was not making a lot of sense to me. You’ve got a very weak force acting on a very strong force happening inside this protected barrier in a cell. I was struggling to fully comprehend it, but it worked. And under certain directionality — actually, it was a piece of work that we worked on together — it does work. If you can control the direction of an electric field, you have a really profound effect on tumor treating fields. That was what we found. But Michelle’s work came out and that was my holy shit moment. I was working in a lab full of amazing people doing neurotechnology — making wearables, making implants, making spinal cord stimulators, everything you can think of that interacts with the body. Our lab was building it. And I was this weird person doing cancer in the group. This paper came out from Michelle’s group. I invited her to give a talk to our group — totally fangirling. I love her work. I was like, there is such an opportunity here. Initially it was actually more on the recording side. I was like, these neurons are interacting with these cells. You can read this. We’ve always struggled to get single-cell resolution, to reconstruct that, because it’s very noisy in the brain. You’re getting all of the neurons telling us most of the information that’s going on. The cancer cell signals maybe are a lot weaker or at a much lower frequency. If we can listen to the neurons, that’s amazing. That was when I went to Ben and said, let’s use your device, let’s put it in here, let’s listen to what’s going on. And Novocure works, so we’ll stimulate using that. And now it’s like, well, there’s way more opportunities that we can do now, because look at all of these interactions that are happening, and all of them are a function of neuromodulation or something that we can modulate with neuromodulation.

Abhishaike Mahajan: At the time, you were working on novel devices for measuring and stimulating?

Ben Woodington: For spinal cord injury — brain interfaces and spinal cord interfaces.

[01:06:38] Why build your own device instead of using off-the-shelf arrays?

Abhishaike Mahajan: Super cool story. This leads well into a question I had that we chatted about previously — why build your own device for this? Why isn’t there some standard like Utah arrays that you can hijack and use? You don’t have to build your own thing. It doesn’t seem like anyone does that — everyone hand-rolls their own thing for their own purposes. Why is that a practice in this field?

Ben Woodington: It’s a good question. There are white-label device manufacturers where you can take a device and stick it into a neuromodulation indication, stimulate some nerves, and do your thing. But there are indications where it really does make sense to create your own device. You need a certain density of electrodes. You need to be compatible with the clinical workflow — for our case, MRI. We can’t just take any of those off-the-shelf devices. You can’t just stick a Neuralink device in a cancer patient because they’re going to have to have an MRI, and the magnet in that device is going to affect the MRI.

Abhishaike Mahajan: And there’s no off-the-shelf device that’s also MRI transparent?

Elise Jenkins: Definitely not transparent.

It’s really hard to build.

Ben Woodington: So it makes sense for us to design purpose-built devices for the treatment of these diseases rather than taking off-the-shelf devices. That’s not an easy lift. It takes a lot of engineering effort. And we have a very excited but exhausted engineering team who are doing this. But it’s necessary for us.

Abhishaike Mahajan: Returning back to the original story of Coherence — you showed Ben your work, you decided to form Coherence four years ago. What were the initial set of milestones you had set up to prove whether this is a real thing that could be scaled up into a company?

[01:08:35] Speaking with glioblastoma patients

Ben Woodington: For us it’s — do clinicians and patients want this? It’s very easy for engineers and scientists to start creating things that they like, that are passion projects, without actually speaking to the end users. We see this all the time. We went straight out and started speaking to clinicians, and the pull is huge. I don’t think we’ve spoken to a single clinician that has said they wouldn’t use that. Every single one is like, tell me when I can run a trial with this. I want to run a trial with this sort of technology. Then we went out and started speaking to patients. I’ve become friends with a number of glioblastoma patients. I just hang out with them and drink coffee with them and watch them interact with the technologies that they’re using. And I would say it’s pretty universal — this disease sucks and my options suck. I’m using this piece of technology and it’s horrible and I don’t like it. And if you tell me right now that there’s something better, I will go back and get another surgery. That’s a big barrier. People do not like going in for surgery. So getting that clinical and patient pull was huge. Now how do we transform that into tangible milestones? We build the technology that they need. We’ve been doing that now for almost three years, running safety animal studies. As Elise mentioned, we’re then doing a first-in-human safety study. The next piece is — what does our early feasibility look like? Get it in patients. First 10, then a hundred, then maybe 500. And show that there is a meaningful clinical, therapeutic, and diagnostic benefit to these patients.

Abhishaike Mahajan: I’m curious — these glioblastoma patients that you’re friends with — one device they interact with is probably Optune, and I’ve heard it kind of sucks because you have this constantly heated device near your head 24/7, above 18 hours a day. What other technology do they have that they potentially use to help their disease?

Ben Woodington: Not a lot. There are some things on the horizon that people have started experimenting with, that people have been on in trials — looking at ultrasound-type devices, blood-brain barrier disruption-type devices, convection-enhanced delivery devices. They’re not great.

Abhishaike Mahajan: No silver bullet.

Ben Woodington: It’s also just the quality of life and the patient impact. I don’t want to sit here and talk negatively about Novocure. I’m really happy that company exists. I’m happy that technology was created for those patients who are in desperate, dire need. The engineers, the scientists, the people that run Novocure — kudos to them for bringing a novel technology to those patients who desperately need it. And of course those patients are using it because it is extending their lives. But there’s so much more you can do to enhance the quality of life for those patients who don’t want to spend the rest of their lives traveling with companions to align stickers on their head and being affected by skin rashes and the pain associated with all of that. There is much more we can do for those patients.

[01:12:04] What was it like to raise money for this?

Abhishaike Mahajan: Back to the creation of Coherence — you talk to the providers, you see there’s demand. You talk to the patients, you see there’s demand. Now it’s time to raise money. Coherence feels like it’s in this weird place where the thesis is so strange that there’s not really many investors I can imagine off the top of my head who instinctively... did their PhD in this area and understand what you’re talking about. How difficult was it to raise money for a thesis like this?

Ben Woodington: They’ll come around. They’ll see what we all see and they’ll realize how large the pan cancer opportunity is. How hard was it? Both hard and easy.

Abhishaike Mahajan: What was your seed?

Ben Woodington: We did a pre-seed in the end of 2022, early 2023, which was about $2.5 million. And then we’ve just very recently closed our seed round, which was another $10 million. The investors that we’ve brought in follow the same trend that scientists, patients, and doctors all have with us. They’re cautiously skeptical at the beginning — hang on a second, does this work? — and then go in a very big way, get very interested, obsessed, both on the therapeutic opportunities but also on these data creation opportunities. We’re living in a world now where there are a lot of AI bio companies out there, and they desperately need data — novel datasets that are showing progression of disease and novel insights from human biology. That’s exciting to a lot of our investors as well. A lot of people are excited by BCI, but they’re all looking for what’s going to be the killer application. When people get that impression of us, they go all in.

[01:13:56] Beyond cancer: TBI, lung disease, and the pan-disease argument

Abhishaike Mahajan: Speaking of TAM expansion, one market is pan cancer. But I imagine there is a very reasonable logical leap you can make that membrane potential is probably important for a lot of diseases. Is that true? Could you make a reasonable argument that you don’t really need to do these five-year-long Alzheimer’s disease progression readouts — you can get a decent proxy from electrical readouts? Is that at all an argument people are trying to make?

Ben Woodington: It’s an argument that people are trying to make. It’s not something that we’ve done inside the company. But people are exploring electrical and other physical stimulation modalities in Alzheimer’s. People are looking at recording readouts for Alzheimer’s, Parkinson’s, other neurodegenerative diseases. And then of course there’s a whole host of neurological disorders that people are looking at — both electrical readouts and electrical stimulation — and other systemic diseases like diseases of the immune system and other things as well.

Elise Jenkins: The nervous system is involved in everything. I feel like it would not be a surprise to me that these types of interactions — you can pick up a whole host of things going wrong just by looking at nerves or neurons.

Abhishaike Mahajan: Is there any convincing evidence that, outside of cancer, if someone gave you a few million dollars to throw at another indication on top of what you guys are already doing, what would be the next thing?

Ben Woodington: There’s a company that just launched thats looking at targeting the nervous system for treatment of asthma and COPD. Before I did my PhD, I was actually working in lung diseases, drug delivery for lung diseases. I actually think that’s a pretty big opportunity. Chronic diseases — many patients are not managed particularly well. A lot of hospitalizations. There is evidence that you can stimulate certain nerves to relax the lungs, to bronchodilate. And closed-loop opportunities as well, predicting when someone is about to exacerbate. I think there’s a big opportunity there.

Elise Jenkins: Chronic stress or TBI. TBI is interesting.

Abhishaike Mahajan: Why TBI? Actually... I could fabricate an intuition for myself. I’d prefer you guys give one to me.

Elise Jenkins: I think traumatic brain injury is really interesting and has similar attributes to what you can leverage from glioblastoma. A lot of the time when someone has a traumatic brain injury, they’re already going in to put something into the brain — usually a shunt or something. There’s an obvious access point, which I always think is the biggest barrier to entry right now. Until this becomes more mainstream, that’s the biggest barrier. So that’s an obvious one — they’re going in and doing something already. And biomarkers.

And you can do similar types of strategies to suppress activity there. I’m also really interested in the data side of all of this — how diseases, degeneration, whatever else evolves. I think what would be really interesting with TBI is looking at how you can watch a brain go back to its normal, healthy state — what type of biomarkers give us that indication that something is going right, and how do you steer that. That’s really interesting in TBI. Chronic stress is because it’s regulated by adrenergic signaling. You can just target the vagus nerve or something else. I think that’d be quite cool.

[01:17:40] Hiring at Coherence + what is the hardest type of talent to find

Abhishaike Mahajan: That makes sense. One thing I’ve been curious about — I think I interviewed Hunter Davis a few months ago, the Until Labs cryopreservation guy. His company shares some similarity with yours in the sense of being wildly interdisciplinary in a way that very few other companies in the world are. He had some interesting thoughts about how hiring works in companies like that. I’d like to get both of your philosophies on what makes for people you want to join Coherence.

Elise Jenkins: I think probably curiosity and taking lessons from other industries. Some of our engineers come from the robotics industry. Some come from the med device industry. Some are scientists from completely outside of cancer neuroscience. And then we also have cancer biologists who really know cancer, but also know immunology and also know neuroscience. We look for people who are experts in their domain but also have demonstrated interdisciplinary overlap with multiple things. Robotics is a really nice example of that — you have mechanics, electronics, spatial interactions, and those types of things you have to consider in your design. The scientists are some of the most fun to find, because a lot of them are coming from the neuro background — that’s the kind of talent we seem to attract. But when you introduce them to this concept of these interactions that happen in cancer, people’s minds massively expand. Watching that process — when you start going through that in the hiring, or when you bring them on board, and how quickly they go from never hearing about it ever before to being so bought in, building and designing these crazy experiments to try and uncover some new neural biomarker — that’s been really cool to watch. Especially when you have this crazy idea many years ago that no one’s ever heard of, and you’ve got all these people that are super pumped about that discovery and want to build something that interfaces with that discovery. That’s been really cool. Mostly I’m looking for interdisciplinary. Yes.

Ben Woodington: Code-switching across disciplines is super important. It’s the same as a lot of deeply technical companies — it’s about your ramp of being able to learn. How steep is that? Because we have electrical engineers that need to come in and learn biology really fast. We have computational neuroscientists that come in and need to learn how to run what would be adjacent to clinical studies really fast. BCI and neurotech is a field that covers so many touch points — electrical engineering, neurobiology, to the sort of stuff that you do. It’s hard to find people that are willing to spread themselves across that many fields.

Abhishaike Mahajan: What do you think is the rarest skillset to find and/or to teach?

Ben Woodington: We know this because it’s the person we’re always trying to hire. Very good electrical engineers and embedded systems engineers. They’re hard to find.

Abhishaike Mahajan: Is it that there aren’t many hardware people?

Ben Woodington: I think a lot of the electrical engineers that have come out of Stanford or wherever get attracted by the tech industry. They’re often good programmers. So they go to Google or Meta or wherever. We need them when they’re at least a few years into their career, with a few projects behind them, a few product cycles, if we’re lucky. And most of them have gone into tech. Bringing them back into hardware is tricky. I think we’re seeing a shift now. Hardware is kind of hot again. Maybe in a year or two, there’ll be a bit of lag and then we’ll see more hardware people that we can bring into the fold. But it’s always the positions that we’re fighting most for.

Abhishaike Mahajan: I think some of the most talented people who have joined the companies I’ve been a part of have been ex-engineers at places like Cerebras, Uber, or the big SaaS companies. What is the big company in your field that you wish you could just pull all the engineers from to come work for you? Is there one, like Neuralink?

Elise Jenkins: I think Neuralink could be a good one, given that they’ve just taken strides in being the first ones to take both a high-density BCI and a robot into trial in a really short period of time. There’s a lot of things that those people would have learned along the way that could definitely be leveraged at a company like ours. I think there’s a challenge when you’re trying to do something really new, but it’s also a regulated technology. There’s this balance of being able to bring in people who really know how to build medical devices that are not scared of things that are new. That’s a really hard balance to find. There’s no company, maybe apart from Neuralink where that exists.

[01:23:17] What would you do with $100M equity-free?

Abhishaike Mahajan: The last question I have — if you were given a hundred million dollars, equity-free, to push this work forward as fast as possible, but you had to spend it within the next year, what would you spend it on?

Ben Woodington: Can I give one and a half answers?

Abhishaike Mahajan: You can have as many answers as you want.

Ben Woodington: This technology exists. The technology that we’re building fundamentally — there are no more science challenges. This is an engineering optimization piece now. Being able to get those technologies into as many human beings, as many cancers as possible — we could build such insane datasets. We could build such incredible real-time, real-world datasets that would blow a lot of people’s minds for what you can access from that data. You just can’t run that many trials all at once if you don’t have a hundred million equity-free cash. If you’re offering, I will take it. The other super exciting thing would be — fab floor, engineering integration floor, clinical scientists, clinic — all in one building. Everything in house.

Abhishaike Mahajan: Including a clinic?

Ben Woodington: A neuro-oncology clinic. That would be insane. I think you could do that for just about a hundred million if you did it maybe not in America. That would be incredible. Being able to highly iterate — build devices, build them in your own clean room, validate them, get them in patients really fast and start running studies, collecting data, and becoming that hub of those studies.

Abhishaike Mahajan: Why does it matter? Why do you care about having a clinical oncology suite inside the building?

Ben Woodington: So you have some control over the functions, the implants of the device, the same surgeons, quick readouts connected to your teams. When our preclinical and engineering teams are working in unison, it’s humming. You’re getting data out that the engineers and the computational scientists are analyzing overnight, feeding back into the next day’s experiments. That’s not really possible in clinical studies. There’s this barrier between you and the hospital, where you’re waiting for data, then you have to wait, then you have to submit new ethics to run a new study. Being able to turn that wheel super fast would be pretty exciting.

Abhishaike Mahajan: This is leading into a lot more questions, but I am just now realizing I never actually asked — is there an experimental loop that goes on? In rodents, at Coherence — where you design one version of the device, implant it, see how well it works?

Ben Woodington: Constant iteration. Both on our preclinical devices — where we’re recording data from these animals, running new stimulation regimes — and on the primary product development pathway as well. Both of those have tight iterative loops.

Abhishaike Mahajan: You exist amongst many other neurotech companies, and you’re probably the most alien amongst them. Do you pay attention to most of the neurotech research that’s going on outside of your immediate field, or is it not super applicable to what you are doing?

Ben Woodington: Firstly, I take it as a great compliment to be called the most alien neurotechnology company. That’s good. Secondly, both of us are having conversations almost every day about what’s going on in the field. It’s entirely relevant, both from a technology landscaping exercise and from a cultural landscaping exercise — which indications are getting more heat in the use of neurotechnology, where are people most excited, what are the innovations convincing more clinicians and patients to adopt these technologies. We need to be abreast of all of this, because there are some similarities with the technology stack and how it’s introduced to the patient as well.

[01:27:15] Are you a neurotech company or a cancer company?

Abhishaike Mahajan: Do you think you’re a neurotech company with ambitions to attack cancer, or a cancer company with ambitions to use neurotech?

Ben Woodington: I personally am a neurotechnologist that wants to develop technologies that can help a lot of people. And oncology seemed like the fastest and highest-impact route to get there. If I can speak on behalf of Elise — and maybe she’ll say I’m wrong — I think Elise comes more from an “oncology matters, and I’m going to use whatever tool I can to help these patients, and this makes sense” perspective. Is that an accurate read?

Elise Jenkins: I think so. I don’t know why the two have to be separate. There are so many debilitating conditions and diseases that need attention. There are two major diseases in the world that are causing death or suffering for a lot of people — cardiovascular disease and cancer. I feel like we can have a really big impact here by leveraging technology that is well-established in other indications that could have huge potential in cancer. I fit in either camp. I want to develop technology that will benefit people.

Ben Woodington: That’s fair. I’m more neurotechnology-pilled. Neurotechnology is crazy. Why are we not using it in all these indications? It’s amazing. It’s going to change everything — from the extreme cases that some of the neurotechnology and BCI companies are making to just day-to-day medicine. I just think that cancer is an extremely promising way to get there and to scale these technologies into a lot of people.

Abhishaike Mahajan: Do you suspect that the full landscape of possible perturbations is pretty limited and you’ve discovered most of them, or you may actually expand that over time?

Elise Jenkins: Initially it’s looking at well-established regimes. If you were to take what Setpoint or Galvani were doing in vagus nerve stimulation for rheumatoid arthritis — they’re targeting immune response there, with well-established parameter sets that are published in literature and have been done in humans. Those are the safer bets that you’d want to try in a novel indication. We are starting with those types of things, with some variations that depend on the nerve that you’re targeting, whether you want to increase immune function or immune activity or decrease stress. They’re very different types of stimuli that you’d apply, but they are well-established.

Ben Woodington: It’s actually a real problem in clinical programming generally — not in our field, but in other fields, for example, pain. The clinical programming profession hasn’t caught up with the engineers. You’ve got more and more complex devices. You’ve now got hundreds, in some cases, of electrodes with thousands of different potential waveform characteristics that you could apply to each electrode. Which gives you this multi-billion parameter operational space. And then you’ve got a clinical programming nurse sitting there saying, where do I even start on this? There’s this massive space now that I have to operate in to try and treat the pain of this person. It’s a job that probably will end up being done by some AI model down the road, using some sort of Bayesian optimization — not a nurse going, “does it feel better or worse by doing this?”

Abhishaike Mahajan: Is that currently how it’s done?

Ben Woodington: It’s currently how it’s done. You would be quite surprised how much human-in-the-loop there is in electrophysiological medicine, where you’ve got people watching a screen saying, “I think they’re going to have a seizure soon.” And someone else going, “well, better stimulate their brain to stop that happening.” And there’s no model, no computer really in the loop giving early indication.

Abhishaike Mahajan: You mentioned a bit about what gives you anxiety, Ben. I’m curious what gives you anxiety, Elise, or if you’d like to add to your answer.

Elise Jenkins: I think for me it’s maybe a combination of anxiety and frustration. You want to move as quickly as humanly possible. The impact that we need has to happen in humans. You need to get to humans as quickly as possible, but you don’t have all the answers in that design process. That is frustrating and can be anxiety-inducing. You’re having to make some assumptions about what might happen in certain scenarios, or how to design this implant, and it has to be safe, of course. That iteration — you just want to get to humans as quickly as possible, but you have all of these things that you need to consider. That’s frustrating, drives me a little insane.

Ben Woodington: I totally agree with that. You work in the cancer field yourself, correct? We’re not in the ads business. We’re not interested in pumping out a few extra targeted ads to people. We’re in the game of actual human beings who are dying quickly. And we’re trying to get technologies that can help those patients as quick as possible. That is frustrating. That is anxiety-inducing, especially when you maintain a close connection with those patients and you see those patients dying. And then you’re screaming at people in the office to move quicker because you’re very connected to that.

Abhishaike Mahajan: I don’t think I have any other questions. This has been an amazing conversation. Thank you so much, Elise and Ben, for coming on.

Ben Woodington: Thank you so much. It’s been a pleasure. Had fun.