Bell Labs, Brain-Computer Interfaces & DBS Innovation with Hemant Bokil

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Welcome back to the
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Stein Fireside Podcast series.
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We're here with Bryan Klassen,
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Matt Baker,
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and our visitor, Hemant Bokil
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We'd like to talk with you today about
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sort of his journey from physics to
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academia to industry
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with Boston Scientific.
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And, well, Matt, why don't you start us
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off with the first question?
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Maybe start off what you got started on
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in undergrad and how that led you to
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neuroscience in general.
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Oh, my . So undergrad was math.
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I was interested in physics, but the
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physics department in the school I went
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to was not very cooperative with allowing
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me to do stuff that was extracurricular.
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What school?
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In India.
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Yes.
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And the math department was. They allowed
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me to cut classes and
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just go and read on my own.
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And with extracurriculars?
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I mean, basically just reading stuff
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that's not, you know,
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not in taught in class.
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So I chose to do math and I continue to
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study physics on my own.
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And then for my PhD, I
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started doing physics.
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So initially I was doing sort of very
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mathematical physics, elementary
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particles, that kind of stuff.
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Then I switched to condensed matter
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theory and did my PhD in statmic
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condensed matter theory.
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And what convinced you
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to go into the brain?
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Oh, that's another funny thing.
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So I was a postdoc at the ICTP in
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Trieste, which is International Center
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for Theoretical Physics.
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And that postdoc, the postdocs there get
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their own funding and their own time.
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So it's interesting in Italy.
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And they are not tied to
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any particular person's lab.
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So you can talk to anybody you want.
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And I happened to just meet this guy who
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was doing a PhD in neuroscience.
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And I started talking to him and just got
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more and more interested.
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It seemed like an interesting thing.
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I saw in the library there they had the
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Nichols book, From Neuron to Brain,
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because Nichols was
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actually there for some years.
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So I just thought, oh my
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god, this is really interesting.
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And compared to that, high temperature
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superconductivity and things like that
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are interesting, but
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they're just super difficult.
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So then I just made the switch.
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Initially, I thought I would go into a
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wet lab and try to
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learn through experiments.
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So I applied to a random lab who was
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advertising, asking for physicists.
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I went there, not knowing much about the
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place, but I couldn't do experiments.
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I just could not.
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I saw the first slice experiment.
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I said, no, this is not for me.
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Animal research or tissue culture?
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No, this was a slice experiment.
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Battle Cortex, rat slices.
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Was it just too rote for you?
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I am squeamish.
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In school, I didn't do biology.
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I quit biology the moment I could quit
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biology, because I knew I was going to
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have to do frog
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dissections the next year.
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Fair enough.
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So that was interesting.
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That's sort of how I
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stumbled into neuroscience.
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So what I decided to do was modeling.
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So this guy was a Battle Cortex guy, also
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interested in olfaction.
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He was interested in whether there can be
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a phaptic coupling in
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the olfactory nerve.
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What do you explain
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what a phaptic coupling is?
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A phaptic coupling is this idea that
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cells that are close to each other can
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actually affect each other without
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synapsing onto them,
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just because of the proximity and the
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electric field can sort of jump across
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and cause activations.
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So if you imagine two cables, you can
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have a signal running down one cable.
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And the other one gets axons.
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So you have axons with nodes of rhombia,
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and those triggering depolarizations in
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the nodes of rhombia in one cell can
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cause the actual potential of another
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cell to speed up and
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align, so they run together.
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So he was interested in the olfactory
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nerve, and the olfactory nerve has this
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peculiar property that most of the axons
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are unmyelinated, but
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they are in fascicles.
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So he said, do you think this is
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something you can help with?
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Do you think there's a reason why we
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should expect a phaptic
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coupling in this model?
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So I started thinking about it, and
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coming from a physics background,
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obviously you start thinking in terms of
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how you can simplify the system.
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So I came up with a
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mean field description.
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So did you start with Hodgkin-Huxley kind
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of things, and then discretize them?
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Yeah, well, so no, I
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didn't do simulations.
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So I was trying to just come up with a
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very basic mean field description to see
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whether you could make some
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simplifications that allowed you to,
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let's say you have an axon start going in
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the middle of this fascicle
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surrounded by other axons.
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And you ask yourself, well, can this axon
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activate all the other
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axons in this fascicle?
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What are the limits of that activation?
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And you look at things like the
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cross-sectional area of the extracellular
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and intracellular space, and based on
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that, you have predictions of the
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resistance, either parallel or
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perpendicular, and you know, you
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approximate, you know the resistance is
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very small and focus on
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the resistance is very large.
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And you can write down a kind of a mean
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field model, and based on that, you can
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show that in the olfactory nerve, there
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should be a sort of
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rampant, a phabatic interaction.
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And then that was the mean field, so then
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I did some simulations to see whether the
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predictions matched, and
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it turned out to match.
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This guy whose lab I was in, he tried to
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do some slice experiments. Funny thing
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is, so we sent this to J. Neuroscience,
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and J. Neuroscience, the reviewers said,
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we like the modeling, we
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don't like the experiments.
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Takeout in vivo.
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Which is what we ended up doing,
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basically, because it
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was hard to measure.
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Didn't the experiments
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corroborate the model?
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No, so it was hard to interpret the
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experiments, because the resolution just
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wasn't there, right?
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Which kind of got me frustrated, right,
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with modeling and then trying to check
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things in experiments.
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So I thought, okay, this is not going to
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work, and they're just sitting in the...
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The experiments are too difficult if
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you're asking interesting questions, so
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then what do I do next, right?
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So I saw this job with Partha doing
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basically BCI type
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stuff. This was in 2002.
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Which lab?
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At Bell Labs.
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Oh, at Bell Labs, yeah.
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So the joint position between Bell Labs
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and Richard Anderson's lab, at Contech.
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Sure, yeah.
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That was sort of, I think, the very early
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days of the BCI funding,
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right? This is 2002, there was.
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So I applied, and
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they liked what I'd done.
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So had Kleinfeld already left by then?
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Kleinfeld had left, yeah. There was sort
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of in the dying days, a few
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people were sticking around.
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Was Mike DeWees there then?
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Mike DeWees? I think I overlapped with
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him. No, he was at Cold Spring Harbor.
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Okay, sorry. My mind is good.
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But like a few months after I went,
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people started dispersing.
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People started looking for the jobs, and
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people were listening for saying,
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"There's no more crazy stuff here."
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Or, "I'll cut that."
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Can you tell, do you know the story about
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Bell Labs? There's
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some great books on it.
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Can you tell us a
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little bit about Bell Labs?
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Oh, sure.
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It's like...
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The weird thing I can tell
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you about Bell Labs, right?
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So Bell Labs was basically the laboratory
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of Bell Telephone Company, right?
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Back from the early days, right?
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And it's where the transistor was
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invented, it's where high temperature
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superconductivity was discovered.
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There was this sort of immense number of
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basic science people
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who were at Bell Labs.
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People who went on to
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win Nobel Prizes, right?
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Richard Anderson was there for a while.
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Many, many famous people
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who were at Bell Labs, right?
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And if you walk through the hallways of
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Bell Labs, like the
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patent wall is like crazy.
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It's a long, long
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corridor full of patents, right?
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But they could do it because
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they were a monopoly, right?
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There was no competition. They could just
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fund and then some stuff came out, some
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stuff didn't come out.
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Shockley was there.
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But then I guess what I've heard is that
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in the 80s, when this
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antitrust stuff happened,
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it was broken up into
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small baby bells, right?
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Then they couldn't support that level of
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basic research, right?
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So the first cuts
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came at that time, right?
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And then when I went in 2002, a second
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round of cuts came because Lucent,
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which was at that point the owner of Bell
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Labs, was bought by Alcatel.
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And they said, okay, fine.
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We have to stop this, right?
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Yeah, so it was a weird time.
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It was, you know, really, really
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wonderful science going on
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there, some weird stuff also.
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I don't know if you've read
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the book Plastic Fantastic.
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No.
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Oh, you haven't? So there was this guy,
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Hendrik Schoen, at Bell Labs.
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He, I know him because I
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used to play soccer with him.
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Oh.
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And he was, I think the year I was there,
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00:10:02,368 --> 00:10:03,970
he wrote like eight nature
279
00:10:03,970 --> 00:10:05,204
papers or something, right?
280
00:10:05,605 --> 00:10:07,974
About some crazy new material
281
00:10:08,474 --> 00:10:09,775
that he had discovered, right?
282
00:10:10,242 --> 00:10:11,777
And he was reporting to
283
00:10:11,811 --> 00:10:14,013
the head of R&D at Bell Labs.
284
00:10:14,013 --> 00:10:15,381
I forget the guy's name, but a very
285
00:10:15,381 --> 00:10:17,550
senior, very well-known physicist, right?
286
00:10:18,517 --> 00:10:20,119
And people started trying to replicate
287
00:10:20,119 --> 00:10:21,587
those experiments elsewhere, right?
288
00:10:22,154 --> 00:10:24,490
And they couldn't, right?
289
00:10:24,490 --> 00:10:26,258
And then it turned out that the guy had,
290
00:10:26,359 --> 00:10:28,527
you know, had fudged a lot
291
00:10:28,527 --> 00:10:29,929
of stuff, made up things.
292
00:10:29,929 --> 00:10:30,730
He was getting, I mean, he
293
00:10:30,730 --> 00:10:33,933
was, he was like 26 or 28.
294
00:10:34,500 --> 00:10:36,736
He was 26 or 28, and he had offers from
295
00:10:36,769 --> 00:10:38,704
Princeton, Harvard, Stanford, like they
296
00:10:38,704 --> 00:10:39,939
were all trying to hire him, right?
297
00:10:40,272 --> 00:10:41,941
And then the story broke, but, you know,
298
00:10:41,974 --> 00:10:42,808
there was nothing there.
299
00:10:43,476 --> 00:10:44,777
And I remember thinking to myself, oh my
300
00:10:44,777 --> 00:10:46,245
God, but he never cheated in soccer.
301
00:10:47,480 --> 00:10:49,215
He's such an honest guy.
302
00:10:50,816 --> 00:10:51,484
That's hot.
303
00:10:52,885 --> 00:10:54,620
So, yeah, but then, you know,
304
00:10:54,620 --> 00:10:56,455
so people started dispersing.
305
00:10:56,455 --> 00:10:58,090
Partha dispersed, went to Cold Spring,
306
00:10:58,224 --> 00:10:59,692
followed him there to Cold Spring.
307
00:11:01,227 --> 00:11:01,927
Partha Mitra.
308
00:11:01,994 --> 00:11:03,295
Partha Mitra, yeah, yeah, of course.
309
00:11:03,396 --> 00:11:07,099
Yeah, so that project was sort of
310
00:11:07,633 --> 00:11:12,438
initially to decode, basically build a
311
00:11:12,505 --> 00:11:14,173
BCI for a monkey, right?
312
00:11:14,840 --> 00:11:18,010
But unlike what Donohue was doing, they
313
00:11:18,010 --> 00:11:19,678
were doing spikes and
314
00:11:19,812 --> 00:11:21,347
rate models, basically,
315
00:11:21,414 --> 00:11:22,481
regression on rates.
316
00:11:23,816 --> 00:11:26,252
What Richard's lab
317
00:11:26,252 --> 00:11:28,287
was focused on was LFPs.
318
00:11:28,354 --> 00:11:28,654
Yeah.
319
00:11:28,921 --> 00:11:31,157
So trying to decode from LFPs, right?
320
00:11:32,024 --> 00:11:33,893
So I worked a little bit on that, right?
321
00:11:33,893 --> 00:11:40,299
We wrote a paper on sort of decoding, but
322
00:11:40,299 --> 00:11:43,602
decoding where you don't just, the monkey
323
00:11:43,602 --> 00:11:45,504
is making these reach tasks
324
00:11:45,504 --> 00:11:46,238
or saccadic movement tasks.
325
00:11:46,238 --> 00:11:47,773
I saw the parietal reach region.
326
00:11:47,840 --> 00:11:49,508
Yeah, parietal reach region and also
327
00:11:49,542 --> 00:11:50,509
parietal eye movement.
328
00:11:50,743 --> 00:11:52,178
Parietal eye movement.
329
00:11:52,611 --> 00:11:54,613
This is all EKAG and...
330
00:11:54,613 --> 00:11:56,248
This is, no, this is electrodes.
331
00:11:56,382 --> 00:11:57,616
It's electrodes, right?
332
00:11:57,650 --> 00:11:59,885
But the tasks are basically either
333
00:11:59,885 --> 00:12:01,754
central reaches or a saccadic eye
334
00:12:01,754 --> 00:12:02,721
movement center, right?
335
00:12:03,222 --> 00:12:05,725
So we did some work on decoding that, but
336
00:12:05,725 --> 00:12:07,059
not just decoding in the sense of
337
00:12:07,059 --> 00:12:09,095
classification of the directions,
338
00:12:09,462 --> 00:12:11,297
but actually decoding in the sense of
339
00:12:11,630 --> 00:12:12,832
detecting the events.
340
00:12:12,965 --> 00:12:14,967
And is this a Georgióbula-style decoding
341
00:12:15,034 --> 00:12:17,403
of, you know, you should center out in
342
00:12:17,403 --> 00:12:19,071
different directions, relooking it to me?
343
00:12:19,438 --> 00:12:21,207
So that is a relatively
344
00:12:21,207 --> 00:12:22,241
straightforward problem.
345
00:12:22,241 --> 00:12:23,709
If you're just trying to sort of do
346
00:12:23,709 --> 00:12:25,344
center out tuning, tuning curve and
347
00:12:25,344 --> 00:12:26,412
predicting what direction
348
00:12:26,412 --> 00:12:27,213
the monkey is going to move,
349
00:12:27,613 --> 00:12:29,181
it becomes a much more difficult problem
350
00:12:29,181 --> 00:12:30,883
if you're not only predicting where the
351
00:12:30,883 --> 00:12:31,750
monkey is going to move,
352
00:12:32,118 --> 00:12:33,552
but when the monkey is going to move
353
00:12:33,819 --> 00:12:35,654
without using any cues, right?
354
00:12:35,654 --> 00:12:36,355
Because that becomes a
355
00:12:36,355 --> 00:12:38,124
whole different ballgame.
356
00:12:38,124 --> 00:12:39,191
So we wrote a paper on that.
357
00:12:40,159 --> 00:12:43,729
And around that time, the
358
00:12:43,729 --> 00:12:45,865
MBL course was starting, right?
359
00:12:46,599 --> 00:12:50,069
So one thing that, you know, kind of
360
00:12:50,102 --> 00:12:52,438
brought me into sort of doing something
361
00:12:52,438 --> 00:12:53,806
that was more related to
362
00:12:53,839 --> 00:12:55,608
time series and stuff like that,
363
00:12:55,608 --> 00:12:57,743
and I think Pratya would do it as well,
364
00:12:58,444 --> 00:13:00,813
was I kind of wanted to
365
00:13:00,846 --> 00:13:02,148
do something useful, right?
366
00:13:02,181 --> 00:13:03,783
And I'd left physics because I, you know,
367
00:13:03,783 --> 00:13:05,317
it was too abstract and, you know, I
368
00:13:05,317 --> 00:13:06,852
wanted to sort of become more practical.
369
00:13:06,852 --> 00:13:12,124
So, right? And then, you know, then the
370
00:13:12,124 --> 00:13:13,793
same reason I left
371
00:13:14,226 --> 00:13:16,529
computational modeling of neurons,
372
00:13:16,595 --> 00:13:18,330
you know, that one little thing I did
373
00:13:18,330 --> 00:13:20,099
with olfactory nerve
374
00:13:20,099 --> 00:13:21,133
and a flap tick, right?
375
00:13:21,133 --> 00:13:22,535
But then I said, OK, this is not working
376
00:13:22,535 --> 00:13:23,469
either. So let's move to
377
00:13:23,469 --> 00:13:24,403
something more concrete.
378
00:13:24,403 --> 00:13:26,272
So, you know, data science and data
379
00:13:26,772 --> 00:13:28,374
analysis seemed like something that was
380
00:13:28,374 --> 00:13:29,508
more concrete, like at least you're
381
00:13:29,508 --> 00:13:30,943
characterizing what you see, right?
382
00:13:31,443 --> 00:13:32,144
Not trying to build
383
00:13:32,144 --> 00:13:32,978
theories on top of it.
384
00:13:34,046 --> 00:13:37,316
And one of the thoughts we had was that,
385
00:13:37,850 --> 00:13:39,752
you know, people in neuroscience don't
386
00:13:39,752 --> 00:13:41,120
have the skills to
387
00:13:41,120 --> 00:13:42,621
analyze this data, right?
388
00:13:42,621 --> 00:13:43,856
They just don't at that
389
00:13:43,856 --> 00:13:45,891
point in 2002, 2003, they didn't.
390
00:13:46,025 --> 00:13:48,661
I think Bijan's paper was the first one
391
00:13:48,661 --> 00:13:50,896
that even talked about spectra in, you
392
00:13:50,896 --> 00:13:52,198
know, LFPs, more or
393
00:13:52,198 --> 00:13:53,632
less, one of the early ones.
394
00:13:54,633 --> 00:13:57,803
So, and that had just come out. So we
395
00:13:57,803 --> 00:14:00,372
thought, OK, let's build some software
396
00:14:00,840 --> 00:14:02,274
that makes it easy to do this.
397
00:14:02,274 --> 00:14:06,078
So I spent like the next couple of years
398
00:14:06,111 --> 00:14:08,314
trying to build that Kronax toolbox,
399
00:14:08,314 --> 00:14:09,281
which I have heard of.
400
00:14:10,482 --> 00:14:12,184
That became quite popular, you know,
401
00:14:12,451 --> 00:14:13,686
initially, of course, for the bugs.
402
00:14:15,154 --> 00:14:16,422
So it will be tested on
403
00:14:16,422 --> 00:14:18,457
this in the several programs.
404
00:14:19,558 --> 00:14:21,994
And then so I stayed
405
00:14:21,994 --> 00:14:23,662
with Partha for a few years.
406
00:14:23,662 --> 00:14:26,432
And then at some point we
407
00:14:26,432 --> 00:14:28,601
wanted to make Kronax commercial.
408
00:14:28,767 --> 00:14:30,469
So we had this idea that, OK, we should,
409
00:14:32,004 --> 00:14:33,472
you know, we should do big data for
410
00:14:33,472 --> 00:14:34,773
neuroscience, right?
411
00:14:35,040 --> 00:14:40,379
Yeah. So the company basically, there
412
00:14:40,379 --> 00:14:41,880
were four of us in it, right?
413
00:14:42,014 --> 00:14:44,583
Partha and this guy, business guy, and
414
00:14:44,583 --> 00:14:46,018
then myself and another guy.
415
00:14:46,352 --> 00:14:47,820
We were the two people who were actually
416
00:14:47,820 --> 00:14:48,821
working in it and the
417
00:14:48,888 --> 00:14:50,522
other guys were shareholders.
418
00:14:51,423 --> 00:14:54,894
And so what we did was basically we were
419
00:14:54,894 --> 00:14:56,629
trying to write an SBIR
420
00:14:57,062 --> 00:14:58,831
for a phase two, right?
421
00:14:59,198 --> 00:15:01,133
We had an SBIR phase one, which had sort
422
00:15:01,133 --> 00:15:02,601
of taken Kronax and
423
00:15:02,835 --> 00:15:03,969
done a little bit with it.
424
00:15:04,970 --> 00:15:06,805
We were trying to do an SBIR phase two.
425
00:15:07,773 --> 00:15:11,010
And simultaneously I was consulting for
426
00:15:11,010 --> 00:15:13,979
Intellect Medical, which is the company
427
00:15:13,979 --> 00:15:16,248
that Cameron was associated with,
428
00:15:16,282 --> 00:15:17,283
that was a spinoff
429
00:15:17,283 --> 00:15:18,183
from the Cleveland Clinic.
430
00:15:18,617 --> 00:15:21,253
So I was consulting for them on sort of
431
00:15:21,320 --> 00:15:23,222
algorithm development and some of the
432
00:15:23,222 --> 00:15:25,624
sweet spot stuff that
433
00:15:25,624 --> 00:15:26,759
was popular at that time.
434
00:15:27,359 --> 00:15:28,494
That was paying my salary.
435
00:15:29,328 --> 00:15:31,864
And in the night I was writing SBIR
436
00:15:31,864 --> 00:15:34,400
grants to do this big data stuff.
437
00:15:36,135 --> 00:15:39,571
But then when Boston bought Intellect,
438
00:15:40,139 --> 00:15:41,106
they wanted me to join.
439
00:15:41,140 --> 00:15:44,910
And the offer they gave me seemed like
440
00:15:44,910 --> 00:15:48,914
incredible at the time, especially coming
441
00:15:48,914 --> 00:15:49,982
from academia and then
442
00:15:49,982 --> 00:15:52,284
trying to get funding.
443
00:15:53,352 --> 00:15:55,454
Yeah, exactly. 2008-2009 was the
444
00:15:55,454 --> 00:15:57,156
financial collapse, right? And we were
445
00:15:57,156 --> 00:15:58,457
writing grants in 2010.
446
00:15:59,525 --> 00:16:01,260
Well, before you get to that though, so
447
00:16:01,260 --> 00:16:02,361
if you're talking about leaving...
448
00:16:03,729 --> 00:16:06,732
So Kronax was one attempt to try to
449
00:16:06,799 --> 00:16:08,834
basically make ourselves irrelevant.
450
00:16:08,901 --> 00:16:10,369
That's how Bhartana used to talk about
451
00:16:10,369 --> 00:16:12,004
it. Let's build this package, give it to
452
00:16:12,004 --> 00:16:15,374
people, they can run with it, and we
453
00:16:15,374 --> 00:16:16,342
don't need to work anymore.
454
00:16:18,077 --> 00:16:20,646
This was sort of the other aspect of
455
00:16:20,646 --> 00:16:22,414
that, is writing this book.
456
00:16:22,715 --> 00:16:24,350
So this is a book, it's
457
00:16:24,350 --> 00:16:25,851
called "Observed Brain Dynamics".
458
00:16:26,685 --> 00:16:30,422
Folks in the lab use this as a reference
459
00:16:30,422 --> 00:16:32,858
tool. I've certainly used it in the past.
460
00:16:33,258 --> 00:16:36,729
It's rich not just in terms of trying to
461
00:16:36,729 --> 00:16:38,764
understand biological concepts and how
462
00:16:38,764 --> 00:16:43,235
they can be modeled with explicit
463
00:16:43,469 --> 00:16:45,404
mathematical formulations, but it also
464
00:16:45,404 --> 00:16:46,872
has historical anecdotes.
465
00:16:46,872 --> 00:16:49,308
It talks about, so there's two key here,
466
00:16:49,308 --> 00:16:51,377
and I think you have some stuff with
467
00:16:51,377 --> 00:16:52,478
Shockley as well, right?
468
00:16:53,212 --> 00:16:57,182
Yeah, and it's just a very sort of rich
469
00:16:57,182 --> 00:16:59,918
manual to learn about the types of things
470
00:16:59,918 --> 00:17:00,819
we're interested in.
471
00:17:00,819 --> 00:17:02,721
It would be the first for the Stein
472
00:17:02,721 --> 00:17:03,722
Podcast series, but
473
00:17:03,722 --> 00:17:05,858
will you sign it for us?
474
00:17:06,325 --> 00:17:07,459
It's a little bit cheesy. This is
475
00:17:07,459 --> 00:17:09,728
actually my wife's copy because someone
476
00:17:09,728 --> 00:17:10,796
from the lab stole mine.
477
00:17:13,232 --> 00:17:15,034
We're interviewing somebody whose book is
478
00:17:15,467 --> 00:17:16,301
on the bookshelf here,
479
00:17:16,301 --> 00:17:19,104
so this is very wonderful.
480
00:17:23,876 --> 00:17:26,678
Lovely. Thank you.
481
00:17:26,945 --> 00:17:28,514
What was the rationale behind the cover?
482
00:17:29,114 --> 00:17:33,619
Oh, that. So I guess the idea was that,
483
00:17:34,086 --> 00:17:36,188
this part of the idea, the idea was that
484
00:17:36,321 --> 00:17:39,591
Monalisa's smile is enigmatic, right?
485
00:17:40,092 --> 00:17:41,693
And you see the smile and you try to
486
00:17:41,693 --> 00:17:43,462
figure out what she's thinking or what
487
00:17:43,495 --> 00:17:46,231
she's feeling, and the brain is similar,
488
00:17:46,265 --> 00:17:47,599
that you're sort of getting these little
489
00:17:47,599 --> 00:17:50,436
signals from outside, and you're trying
490
00:17:50,436 --> 00:17:51,603
to figure out what's inside.
491
00:17:52,070 --> 00:17:55,074
I think there's also a mention of the
492
00:17:55,074 --> 00:17:57,543
famous Blind Men and the Elephant story,
493
00:17:57,843 --> 00:17:59,478
where they pick up different parts and
494
00:17:59,478 --> 00:18:00,746
you try to reconstruct the whole.
495
00:18:01,113 --> 00:18:04,149
So yeah, that was sort of the, yeah, and
496
00:18:04,149 --> 00:18:05,284
we had to license that.
497
00:18:06,385 --> 00:18:09,154
Oh, interesting. From Leonardo?
498
00:18:09,388 --> 00:18:10,088
From the Louvre?
499
00:18:11,023 --> 00:18:11,223
Yeah.
500
00:18:12,491 --> 00:18:14,193
How much did you put on the company?
501
00:18:15,194 --> 00:18:16,261
That's kind of interesting.
502
00:18:17,596 --> 00:18:18,197
Yeah, I remember that.
503
00:18:18,197 --> 00:18:20,933
Yeah, so yeah, but that was again, the
504
00:18:20,933 --> 00:18:23,502
idea was to sort of, we kind of thought
505
00:18:23,502 --> 00:18:25,737
that, okay, writing papers is probably
506
00:18:25,737 --> 00:18:28,173
not as useful as writing a book that can
507
00:18:28,173 --> 00:18:30,409
become something that
508
00:18:30,409 --> 00:18:31,343
people can refer to.
509
00:18:32,544 --> 00:18:34,246
So we wrote some papers, but then this
510
00:18:34,246 --> 00:18:36,348
seemed like a better use of our time, is
511
00:18:36,348 --> 00:18:38,150
to actually put it all in one place. So
512
00:18:38,150 --> 00:18:39,818
it's also very practical in some ways,
513
00:18:39,818 --> 00:18:41,620
like some sections are very practical.
514
00:18:41,687 --> 00:18:43,355
Published in 2005?
515
00:18:44,656 --> 00:18:47,459
2008, I think. And right after that was
516
00:18:47,459 --> 00:18:49,161
the company that was mentioning that we
517
00:18:49,161 --> 00:18:50,462
were trying to raise money for it.
518
00:18:51,029 --> 00:18:52,431
I remember first meeting with you, we
519
00:18:52,431 --> 00:18:54,666
were talking about research, and you
520
00:18:54,666 --> 00:18:55,100
said, "Hey,
521
00:18:55,167 --> 00:18:56,835
Montbockel," and I pulled that off.
522
00:18:57,503 --> 00:19:00,439
I pulled my copy off of my bookshelf next
523
00:19:00,439 --> 00:19:02,875
to my desk, and I was like, "Are you the
524
00:19:02,875 --> 00:19:04,276
same guy? What's going on?"
525
00:19:04,276 --> 00:19:06,912
Yeah, I remember that. Partha was my
526
00:19:06,912 --> 00:19:10,549
mentor, right? So Oxford had reached out
527
00:19:10,549 --> 00:19:11,683
to him even when we were at
528
00:19:11,683 --> 00:19:14,419
Bell, but then we said yes.
529
00:19:14,653 --> 00:19:16,622
He asked me, and I said, "Yeah, sure,
530
00:19:16,622 --> 00:19:18,824
let's do it." And we said yes, but then
531
00:19:18,824 --> 00:19:19,758
it took us many years to
532
00:19:19,758 --> 00:19:20,893
actually get around to doing it.
533
00:19:21,126 --> 00:19:22,494
And in the end, when we did it, I think,
534
00:19:22,928 --> 00:19:25,397
I remember it was like three months of
535
00:19:25,397 --> 00:19:27,566
intense writing, like morning to evening,
536
00:19:27,566 --> 00:19:28,734
just writing, writing, writing.
537
00:19:29,067 --> 00:19:30,435
This is before Chad GPT. It
538
00:19:30,435 --> 00:19:31,103
would have been much easier.
539
00:19:33,705 --> 00:19:35,274
So when you were working with Partha
540
00:19:35,274 --> 00:19:36,708
Mitra, did he make you
541
00:19:36,742 --> 00:19:37,910
carry a yoga mat around?
542
00:19:38,710 --> 00:19:42,014
I see him. I remember sitting down with
543
00:19:42,014 --> 00:19:43,182
him at nice dinners, and
544
00:19:43,182 --> 00:19:44,483
he's got a yoga mat with him.
545
00:19:44,783 --> 00:19:46,919
But I've seen him do headstands in MBL.
546
00:19:47,252 --> 00:19:50,422
He is a brilliant guy. I mean, I've loved
547
00:19:50,889 --> 00:19:53,926
conversations with him. I've loved asking
548
00:19:53,926 --> 00:19:56,461
about some technical nuance, and
549
00:19:56,862 --> 00:19:57,896
incredibly insightful guy.
550
00:19:58,497 --> 00:19:59,331
He is a very wonderful guy.
551
00:19:59,531 --> 00:20:03,201
He is definitely a very deep thinker.
552
00:20:03,235 --> 00:20:06,939
Do you know what he's up to now?
553
00:20:07,739 --> 00:20:09,875
So he got a lot into
554
00:20:10,943 --> 00:20:13,445
this anatomy, basically.
555
00:20:14,780 --> 00:20:18,684
In 2007, 2008, he had a bunch of
556
00:20:18,684 --> 00:20:20,786
neuroanatomists. Suzanne Haber, who is
557
00:20:20,786 --> 00:20:22,454
the one I remember at Gold Spring Harbor,
558
00:20:22,454 --> 00:20:25,457
he had a symposium where he got a bunch
559
00:20:25,457 --> 00:20:27,259
of anatomists together to basically map
560
00:20:27,259 --> 00:20:29,394
out what should be done in anatomy to try
561
00:20:29,394 --> 00:20:31,330
to improve our understanding of circuits.
562
00:20:32,397 --> 00:20:35,634
So he basically shifted the whole focus
563
00:20:35,634 --> 00:20:37,202
of his work towards that, you know,
564
00:20:37,302 --> 00:20:40,138
reconstruction, EM reconstructions, and
565
00:20:40,772 --> 00:20:42,107
algorithms for doing that.
566
00:20:42,307 --> 00:20:44,343
That was sort of a big part of what he's
567
00:20:44,343 --> 00:20:45,210
been doing since then.
568
00:20:46,411 --> 00:20:47,312
Yeah. Okay.
569
00:20:47,479 --> 00:20:50,382
So when you say EM, the electron
570
00:20:50,382 --> 00:20:54,519
microscope, reproducing cellular-level
571
00:20:54,519 --> 00:20:56,221
resolution and different things. I think
572
00:20:56,221 --> 00:20:56,822
he was involved a
573
00:20:56,822 --> 00:20:57,656
little bit in the brain.
574
00:20:57,689 --> 00:20:59,124
Was he doing that with Terry Sinosky? I
575
00:20:59,124 --> 00:20:59,958
remember Terry talking
576
00:20:59,958 --> 00:21:01,293
about modeling a cubic moon.
577
00:21:01,660 --> 00:21:03,261
No, so he's not doing modeling. He's just
578
00:21:03,261 --> 00:21:04,663
trying to reconstruct. Just doing the
579
00:21:04,663 --> 00:21:05,964
analysis. Just the connections.
580
00:21:05,998 --> 00:21:07,799
Terry's things with having algorithms
581
00:21:07,799 --> 00:21:08,667
that we get layer by
582
00:21:08,667 --> 00:21:09,668
layer by layer to align.
583
00:21:09,668 --> 00:21:11,169
Yeah, so stuff like that. Stuff like that
584
00:21:11,169 --> 00:21:12,638
is what he's been doing. And then I think
585
00:21:12,638 --> 00:21:15,073
also he has, he founded a company, I
586
00:21:15,073 --> 00:21:17,376
think, if I'm not mistaken, to do some
587
00:21:18,277 --> 00:21:20,479
automatic radiology stuff, you
588
00:21:20,479 --> 00:21:21,513
know, like that kind of thing.
589
00:21:21,513 --> 00:21:21,813
Sure.
590
00:21:24,316 --> 00:21:25,784
That's interesting. Yeah.
591
00:21:25,784 --> 00:21:26,551
It's useful for us.
592
00:21:27,819 --> 00:21:30,622
So then can you tell us in our audience
593
00:21:30,622 --> 00:21:32,057
what you do at Boston Scientific?
594
00:21:32,524 --> 00:21:35,327
So at Boston, so I told you I joined as
595
00:21:35,327 --> 00:21:36,495
part of the acquisition, right?
596
00:21:37,296 --> 00:21:39,364
And over the years I've done, I've been
597
00:21:39,364 --> 00:21:41,566
there since, right? So I guess I must be
598
00:21:41,566 --> 00:21:43,368
enjoying my job, right?
599
00:21:43,869 --> 00:21:45,337
Initially it was sort of the integration,
600
00:21:45,337 --> 00:21:46,738
right? I mean, integration of a small
601
00:21:46,738 --> 00:21:48,940
company and a big company is a big deal.
602
00:21:49,007 --> 00:21:49,641
It's not something
603
00:21:49,641 --> 00:21:50,842
that just happens, right?
604
00:21:50,842 --> 00:21:53,879
So it took longer than it may have been
605
00:21:53,879 --> 00:21:55,380
expected to take or one
606
00:21:55,380 --> 00:21:56,415
would expect from the outside.
607
00:21:56,982 --> 00:21:58,850
But a large amount of it was integration
608
00:21:58,850 --> 00:22:00,052
of the software into the Boston
609
00:22:00,052 --> 00:22:02,187
Scientific Quality System. So it was a
610
00:22:02,187 --> 00:22:03,221
bunch of things like that.
611
00:22:03,689 --> 00:22:06,992
Writing technical reports that are sort
612
00:22:06,992 --> 00:22:08,160
of compliant with the
613
00:22:08,160 --> 00:22:09,561
Boston Scientific requirements.
614
00:22:09,561 --> 00:22:10,796
You know, I'd run some algorithm
615
00:22:10,796 --> 00:22:12,531
development, but I'd not since we did it
616
00:22:12,564 --> 00:22:13,598
all out in a manner
617
00:22:13,598 --> 00:22:15,133
that BSC would require.
618
00:22:15,133 --> 00:22:17,035
So some of the initial period was just
619
00:22:17,035 --> 00:22:17,903
that, like getting us
620
00:22:17,903 --> 00:22:19,771
all on board, so to speak.
621
00:22:20,305 --> 00:22:25,744
And then after that, I've done things
622
00:22:25,744 --> 00:22:28,880
like thinking about which kind of brain
623
00:22:28,880 --> 00:22:31,283
atlas we would need at Boston because
624
00:22:31,350 --> 00:22:33,952
what came from intellect was something
625
00:22:33,952 --> 00:22:35,120
called the Morrell Atlas.
626
00:22:35,420 --> 00:22:38,223
So that's what the intellect people had,
627
00:22:38,256 --> 00:22:41,126
right? So we spent some years after we
628
00:22:41,126 --> 00:22:45,130
joined looking at what
629
00:22:45,130 --> 00:22:46,131
other options were there.
630
00:22:46,164 --> 00:22:49,401
So we thought, okay, should we do sort of
631
00:22:49,434 --> 00:22:51,236
this free surfer type of thing like
632
00:22:51,236 --> 00:22:53,572
Bayesian segmentation?
633
00:22:53,572 --> 00:22:54,773
Should we do something else?
634
00:22:55,374 --> 00:22:58,009
So that was some of it. And then over the
635
00:22:58,009 --> 00:23:01,313
past few years, most of my work has
636
00:23:01,313 --> 00:23:05,217
focused on sort of creating a framework
637
00:23:05,217 --> 00:23:06,585
for doing research and novel
638
00:23:06,585 --> 00:23:08,754
stimulation patterns in DBS.
639
00:23:10,322 --> 00:23:13,792
And then more recently, looking at things
640
00:23:13,792 --> 00:23:17,062
like strategic questions about what one
641
00:23:17,062 --> 00:23:18,563
should do, what one should not do in
642
00:23:19,097 --> 00:23:20,932
terms of how to bring this forward.
643
00:23:22,167 --> 00:23:24,336
The company as a whole is focused on a
644
00:23:25,370 --> 00:23:27,005
large amount of our focus has been on
645
00:23:27,005 --> 00:23:28,673
imaging and improving
646
00:23:28,673 --> 00:23:30,075
the... basically making...
647
00:23:30,575 --> 00:23:34,246
The way we see it is we want to make the
648
00:23:34,246 --> 00:23:36,948
job of the programmers easier, to make it
649
00:23:36,948 --> 00:23:39,317
faster, quicker, and more accurate.
650
00:23:39,317 --> 00:23:40,685
And the space-type programmers, you mean?
651
00:23:41,119 --> 00:23:44,923
By neurologists, nurse practitioners, the
652
00:23:44,923 --> 00:23:46,158
folks who are programming DBS.
653
00:23:46,158 --> 00:23:47,392
We're writing the DBS devices.
654
00:23:48,059 --> 00:23:51,029
So we try to make that faster by getting
655
00:23:51,062 --> 00:23:53,532
advanced imaging into the workflow and
656
00:23:53,532 --> 00:23:55,467
making that workflow go smoothly.
657
00:23:56,334 --> 00:23:58,203
Most recently, there has been sort of...
658
00:23:59,104 --> 00:24:00,472
you may have heard of this Illumina.
659
00:24:00,739 --> 00:24:01,373
Yeah, we have.
660
00:24:01,940 --> 00:24:04,276
So that's sort of one of the latest
661
00:24:04,276 --> 00:24:05,644
things in that line of thinking.
662
00:24:06,278 --> 00:24:08,980
And then on the research end, we have
663
00:24:08,980 --> 00:24:13,385
thought for many years that, you know,
664
00:24:13,385 --> 00:24:14,953
130 hertz, 60 microseconds
665
00:24:14,953 --> 00:24:15,954
cannot be the whole story.
666
00:24:16,955 --> 00:24:18,023
So it just cannot be.
667
00:24:18,757 --> 00:24:23,261
So we started off working with Peter
668
00:24:23,261 --> 00:24:25,630
Tauss many years ago on coordinate reset.
669
00:24:27,232 --> 00:24:29,401
But a lot of the work we did initially,
670
00:24:29,701 --> 00:24:32,404
for three or four years, was sort of
671
00:24:34,039 --> 00:24:35,874
one-off solutions for one-off things.
672
00:24:35,874 --> 00:24:37,476
So if we wanted to work with Peter to do
673
00:24:37,476 --> 00:24:38,977
coordinate reset, we'd build a little
674
00:24:38,977 --> 00:24:40,011
tool that just does
675
00:24:40,011 --> 00:24:41,413
coordinate reset and nothing else.
676
00:24:42,380 --> 00:24:44,516
We were interested in what happens if we
677
00:24:44,516 --> 00:24:45,684
change the pulse shapes.
678
00:24:45,951 --> 00:24:48,320
Our stimulators are very capable. A lot
679
00:24:48,320 --> 00:24:49,988
of that capability is hidden from the
680
00:24:49,988 --> 00:24:52,023
users for regulatory reasons.
681
00:24:52,991 --> 00:24:54,459
So we did some experiments on pulse
682
00:24:54,459 --> 00:24:55,760
shaping. We built a tool for
683
00:24:56,027 --> 00:24:57,262
manipulating the pulse shape.
684
00:24:58,063 --> 00:24:59,164
Is that the WaveRider tool?
685
00:24:59,531 --> 00:25:00,866
That's not the WaveRider tool. That's
686
00:25:01,233 --> 00:25:04,603
something that... basically, the group we
687
00:25:04,603 --> 00:25:06,838
work with on that project is a group in
688
00:25:06,838 --> 00:25:09,674
Leuven, Miles McLaughlin and his team.
689
00:25:10,141 --> 00:25:11,009
So we built a little
690
00:25:11,042 --> 00:25:12,911
Python-based tool for doing that.
691
00:25:12,911 --> 00:25:14,546
Another Python-based tool
692
00:25:14,613 --> 00:25:15,647
for doing coordinate reset.
693
00:25:16,882 --> 00:25:18,149
Then a few years ago, we thought, "Okay,
694
00:25:18,149 --> 00:25:19,951
this is not scaling very well. We really
695
00:25:19,951 --> 00:25:21,319
need to ask more questions
696
00:25:21,319 --> 00:25:22,654
and have more flexibility."
697
00:25:23,221 --> 00:25:25,023
So we built this thing called Chronos.
698
00:25:26,291 --> 00:25:28,960
And now we are sort of having a bunch of
699
00:25:28,960 --> 00:25:30,195
studies starting in
700
00:25:30,195 --> 00:25:30,996
various parts of the world.
701
00:25:30,996 --> 00:25:31,663
Which brings you here.
702
00:25:32,130 --> 00:25:32,330
Wonderful.
703
00:25:34,432 --> 00:25:37,402
Could you explain what was the original
704
00:25:37,636 --> 00:25:39,437
kind of rationale for the 130
705
00:25:39,538 --> 00:25:41,072
Hz and deep brain stimulation?
706
00:25:42,274 --> 00:25:44,809
That came over through a cell
707
00:25:44,809 --> 00:25:45,977
independence discovery.
708
00:25:48,747 --> 00:25:49,614
Ben Abid was
709
00:25:49,614 --> 00:25:53,218
stimulating and saw tremor stop.
710
00:25:54,085 --> 00:25:56,588
And then what happens often in medical
711
00:25:56,621 --> 00:26:00,258
devices is companies do
712
00:26:00,258 --> 00:26:01,293
what has worked before.
713
00:26:02,060 --> 00:26:03,495
Metronic commercialized a
714
00:26:03,495 --> 00:26:05,063
particular set of parameters.
715
00:26:06,064 --> 00:26:10,302
When we approached the FDA, we also asked
716
00:26:10,302 --> 00:26:12,737
for permission to play in that space.
717
00:26:13,338 --> 00:26:14,339
Our stimulators were
718
00:26:14,339 --> 00:26:15,574
much more capable even then.
719
00:26:16,608 --> 00:26:19,711
But we blocked all that capability behind
720
00:26:19,711 --> 00:26:22,914
software so that the average clinician
721
00:26:22,914 --> 00:26:25,350
user basically can do the same things as
722
00:26:25,350 --> 00:26:26,851
the metronic stimulators did, except that
723
00:26:26,851 --> 00:26:27,752
ours was current control.
724
00:26:28,653 --> 00:26:29,788
And we had MICC.
725
00:26:30,055 --> 00:26:33,592
But we didn't open up all the
726
00:26:33,592 --> 00:26:34,426
capabilities that were
727
00:26:34,426 --> 00:26:36,227
there, and we still don't.
728
00:26:37,228 --> 00:26:39,331
And largely the reason for that is
729
00:26:39,431 --> 00:26:41,099
regulatory pressure concerns.
730
00:26:41,366 --> 00:26:42,133
And of course patient
731
00:26:42,133 --> 00:26:43,001
safety is the other thing.
732
00:26:44,603 --> 00:26:45,904
So instead what we decide
733
00:26:45,904 --> 00:26:48,073
to do is, that still remains.
734
00:26:48,139 --> 00:26:49,074
We can't just open up the
735
00:26:49,074 --> 00:26:51,409
whole system for clinical use.
736
00:26:51,943 --> 00:26:53,612
But we are hoping that through these sort
737
00:26:53,612 --> 00:26:55,447
of research studies, we will be able to
738
00:26:55,447 --> 00:26:57,949
figure out which portions should be
739
00:26:57,949 --> 00:26:58,717
opened up and which
740
00:26:58,717 --> 00:26:59,050
portions should be opened up.
741
00:26:59,084 --> 00:26:59,551
And hopefully patients are actually
742
00:26:59,551 --> 00:27:00,752
useful from the
743
00:27:00,752 --> 00:27:02,087
standpoint of patient care.
744
00:27:02,988 --> 00:27:06,124
Hopefully discover something interesting.
745
00:27:06,157 --> 00:27:07,125
Yeah, I think it's really exciting.
746
00:27:08,093 --> 00:27:09,561
Hopefully it will be
747
00:27:09,561 --> 00:27:10,795
helpful for patients overall.
748
00:27:11,296 --> 00:27:13,231
I don't think there is a
749
00:27:13,231 --> 00:27:14,466
lot of rationale between 130.
750
00:27:14,933 --> 00:27:16,768
I think it's sort of somewhere between
751
00:27:16,768 --> 00:27:19,571
100, which is about as low as you can be
752
00:27:19,571 --> 00:27:20,905
and have it still work, and then lower
753
00:27:20,905 --> 00:27:22,107
than 180, which is as
754
00:27:22,107 --> 00:27:22,874
high as people want to go.
755
00:27:22,907 --> 00:27:26,378
There is some intro of data suggesting
756
00:27:26,378 --> 00:27:33,284
that when you stimulate the STN, it sort
757
00:27:33,284 --> 00:27:36,454
of shuts down beyond a certain frequency.
758
00:27:37,422 --> 00:27:38,423
And at SNR it shuts
759
00:27:38,423 --> 00:27:40,091
down at lower frequency.
760
00:27:41,993 --> 00:27:43,194
But beyond that, I don't think anybody
761
00:27:43,194 --> 00:27:44,996
really understands why that is the case.
762
00:27:45,764 --> 00:27:47,632
So you said 2010 is
763
00:27:47,665 --> 00:27:48,600
when you joined Boston.
764
00:27:48,733 --> 00:27:49,000
2011.
765
00:27:50,368 --> 00:27:52,704
So their device wasn't out in 2011.
766
00:27:52,904 --> 00:27:53,104
No.
767
00:27:53,571 --> 00:27:54,572
So what was that like?
768
00:27:55,273 --> 00:27:57,542
It was frustrating.
769
00:27:58,543 --> 00:28:02,747
I was working on algorithms like lead
770
00:28:02,747 --> 00:28:04,649
detection, orientation detection, those
771
00:28:04,649 --> 00:28:05,350
kinds of algorithms.
772
00:28:06,351 --> 00:28:08,753
But the actual device, it took a while
773
00:28:08,753 --> 00:28:11,056
because the FDA wanted
774
00:28:11,056 --> 00:28:12,290
us to do a clinical study.
775
00:28:12,323 --> 00:28:14,459
And so you were brain from the start. You
776
00:28:14,459 --> 00:28:15,994
weren't in their spinal cord stay on?
777
00:28:16,027 --> 00:28:18,863
I dabbled in spinal cord a little bit, a
778
00:28:18,863 --> 00:28:20,065
few things here and there,
779
00:28:20,065 --> 00:28:22,934
but not sort of seriously.
780
00:28:24,202 --> 00:28:26,037
I just dabbled. But
781
00:28:26,037 --> 00:28:27,038
mostly I've been brain.
782
00:28:28,073 --> 00:28:29,908
Can you tell us some about the
783
00:28:31,076 --> 00:28:33,812
differences between, because you've seen
784
00:28:33,812 --> 00:28:36,014
it in both places, bringing something out
785
00:28:36,014 --> 00:28:37,048
in Europe and bringing the
786
00:28:37,048 --> 00:28:38,616
same device out in the US.
787
00:28:38,850 --> 00:28:42,420
Same device I know is 25 years. It's
788
00:28:42,420 --> 00:28:44,422
rated 25 years with the CE mark.
789
00:28:44,856 --> 00:28:46,124
And it's 15 years in the
790
00:28:46,124 --> 00:28:47,625
US, but it's the same device.
791
00:28:48,226 --> 00:28:50,428
For my patients, I just tell them that. I
792
00:28:50,462 --> 00:28:52,730
assume it will be the FDA rated to 15,
793
00:28:52,797 --> 00:28:54,933
but I assume it's going to be 25 years
794
00:28:54,933 --> 00:28:56,034
before we need to replace this.
795
00:28:56,034 --> 00:28:58,369
And probably we'll replace it when better
796
00:28:58,369 --> 00:29:00,472
technology that can do things that
797
00:29:00,972 --> 00:29:03,475
current tech can't do comes out rather
798
00:29:03,475 --> 00:29:05,710
than when the pulse generator, the
799
00:29:05,710 --> 00:29:07,545
battery, that is no longer functional.
800
00:29:09,781 --> 00:29:11,549
It's different regulatory structures
801
00:29:11,549 --> 00:29:12,851
there compared to there
802
00:29:12,851 --> 00:29:14,285
and here, and they change.
803
00:29:14,819 --> 00:29:16,855
So for example, now with the new
804
00:29:16,888 --> 00:29:18,690
regulations, and it used to be like when
805
00:29:18,690 --> 00:29:21,092
I joined Boston, one would always say
806
00:29:21,092 --> 00:29:22,627
that it's much easier to get into Europe
807
00:29:22,627 --> 00:29:23,962
than it is to get into the US.
808
00:29:24,796 --> 00:29:28,133
But with the new MDR regulations in
809
00:29:28,333 --> 00:29:29,868
Europe, it's much
810
00:29:29,868 --> 00:29:30,869
harder to get into Europe.
811
00:29:31,870 --> 00:29:36,007
For example, Chronos. That's an example
812
00:29:36,007 --> 00:29:36,808
I'm very familiar with.
813
00:29:37,642 --> 00:29:40,912
Here, we can have a master file with the
814
00:29:40,912 --> 00:29:43,181
FDA. We can submit all our regulatory
815
00:29:43,615 --> 00:29:46,284
stuff to the FDA, and investigators can
816
00:29:46,284 --> 00:29:49,087
approach the FDA saying, "Hey, we want to
817
00:29:49,087 --> 00:29:50,121
do a study with this thing."
818
00:29:52,257 --> 00:29:53,424
Europe doesn't have that.
819
00:29:54,425 --> 00:29:58,196
So every study with a non-CE mark device,
820
00:29:58,563 --> 00:30:00,532
the investigator has to write essentially
821
00:30:00,532 --> 00:30:03,001
an IDE, which is a big burden.
822
00:30:03,968 --> 00:30:05,470
And the reason why we don't get a CE
823
00:30:05,570 --> 00:30:07,972
mark, in part, not the only reason, but
824
00:30:07,972 --> 00:30:09,974
one reason is that we
825
00:30:09,974 --> 00:30:11,176
have to translate everything.
826
00:30:12,377 --> 00:30:14,979
And that's a big burden. That's not a
827
00:30:14,979 --> 00:30:16,781
burden that adds to the capability of the
828
00:30:16,781 --> 00:30:18,116
software. That's just something that
829
00:30:18,216 --> 00:30:19,784
Europe requires because they have so many
830
00:30:19,784 --> 00:30:20,585
different languages.
831
00:30:21,286 --> 00:30:22,987
So they don't have an investigational
832
00:30:22,987 --> 00:30:26,057
device exemption kind of framework.
833
00:30:26,057 --> 00:30:28,826
So it varies a lot. I wouldn't say that
834
00:30:28,826 --> 00:30:29,694
one geography is
835
00:30:29,694 --> 00:30:31,095
necessarily better than the other.
836
00:30:32,197 --> 00:30:35,867
What about the culture of DBS? I mean, of
837
00:30:35,867 --> 00:30:38,636
course, we've interacted with some of the
838
00:30:38,670 --> 00:30:41,840
surgeons from Freiburg, for example.
839
00:30:42,173 --> 00:30:45,577
We have colleagues there who use Boston
840
00:30:45,577 --> 00:30:48,713
Scientific regularly, and we even talked
841
00:30:48,713 --> 00:30:51,983
with them about new features because
842
00:30:52,016 --> 00:30:53,251
things were rolled out there.
843
00:30:53,585 --> 00:30:55,486
The new system came out
844
00:30:56,187 --> 00:30:57,622
there before it came out here.
845
00:31:00,992 --> 00:31:02,994
Is there a cultural difference that you
846
00:31:02,994 --> 00:31:05,296
notice in neurologists and neurosurgeons
847
00:31:05,997 --> 00:31:07,131
in their interactions
848
00:31:07,131 --> 00:31:08,633
with you regarding devices?
849
00:31:09,534 --> 00:31:12,003
In their interactions with me, I mean,
850
00:31:12,003 --> 00:31:15,373
us, on the R&D side, I would say no.
851
00:31:16,741 --> 00:31:19,177
But the practice is definitely different.
852
00:31:19,210 --> 00:31:21,212
I mean, it certainly seems that they have
853
00:31:21,346 --> 00:31:25,583
a lot more time per patient than they
854
00:31:25,583 --> 00:31:28,453
don't have the same pressures as the
855
00:31:28,453 --> 00:31:31,422
American medical professionals face.
856
00:31:31,956 --> 00:31:33,191
The other thing I would say is the
857
00:31:33,191 --> 00:31:34,359
incentives are different.
858
00:31:35,994 --> 00:31:38,096
I've heard, and this is common knowledge,
859
00:31:38,096 --> 00:31:41,733
that you get paid differently
860
00:31:41,733 --> 00:31:42,834
over there compared to here.
861
00:31:43,001 --> 00:31:44,369
There you get paid for the whole DBS
862
00:31:44,369 --> 00:31:47,605
procedure. Here you get paid if you're
863
00:31:47,605 --> 00:31:49,741
doing two different implants on two
864
00:31:49,741 --> 00:31:51,376
different days in some places.
865
00:31:51,409 --> 00:31:53,344
Well, we're fortunate. Nobody, at least
866
00:31:53,344 --> 00:31:55,580
for me, I just do what I think is right,
867
00:31:55,580 --> 00:31:56,781
and I make the same amount.
868
00:31:56,914 --> 00:32:02,153
So people always, yeah, I think that
869
00:32:02,487 --> 00:32:03,755
there's a little bit of a difference in
870
00:32:03,755 --> 00:32:06,658
the way they program.
871
00:32:07,458 --> 00:32:09,027
For example, for our studies, they can
872
00:32:09,027 --> 00:32:12,497
bring patients in and have them stay in
873
00:32:12,497 --> 00:32:14,432
the hospital for these observational
874
00:32:14,432 --> 00:32:15,800
periods. They can stay overnight.
875
00:32:17,235 --> 00:32:18,770
That becomes much more challenging here
876
00:32:18,803 --> 00:32:19,537
than it is over there.
877
00:32:19,804 --> 00:32:22,840
Because they have a different system that
878
00:32:22,840 --> 00:32:25,310
allows them to bring these patients in
879
00:32:25,310 --> 00:32:27,178
for observation for a few days when
880
00:32:27,178 --> 00:32:28,513
they're doing great programmings.
881
00:32:29,414 --> 00:32:30,915
And that's the standard of care in some
882
00:32:30,915 --> 00:32:33,117
of the institutions we work in. It's not
883
00:32:33,117 --> 00:32:34,619
standard of care in any institution in
884
00:32:34,652 --> 00:32:36,020
the US that I'm aware of.
885
00:32:36,554 --> 00:32:39,991
So yeah, I think those
886
00:32:39,991 --> 00:32:41,225
things do differ a little bit.
887
00:32:44,195 --> 00:32:45,263
I'm very excited.
888
00:32:46,297 --> 00:32:47,165
I don't know what kinds of
889
00:32:47,165 --> 00:32:47,999
things you can talk about
890
00:32:47,999 --> 00:32:48,833
and what types of
891
00:32:48,833 --> 00:32:49,934
things you can't talk about.
892
00:32:51,336 --> 00:32:52,203
So if...
893
00:32:52,370 --> 00:32:53,004
I don't know either.
894
00:32:54,238 --> 00:32:56,407
Well, we'll ask Boston Scientific.
895
00:32:56,407 --> 00:32:57,875
They can review it and see what they say.
896
00:32:58,943 --> 00:33:01,245
The dream for me would be to have a
897
00:33:01,446 --> 00:33:04,082
system that has sensing and stimulation.
898
00:33:04,115 --> 00:33:04,649
It was a general
899
00:33:04,649 --> 00:33:06,417
purpose 32-champ platform.
900
00:33:08,753 --> 00:33:10,455
And we heard at this conference, we were
901
00:33:10,455 --> 00:33:11,789
just out about some of the different
902
00:33:11,789 --> 00:33:12,790
things that are out there.
903
00:33:14,992 --> 00:33:16,027
Are you aware of
904
00:33:16,027 --> 00:33:20,598
regulatory challenges in terms of...
905
00:33:21,733 --> 00:33:24,502
or are the companies thinking and talking
906
00:33:24,535 --> 00:33:27,305
about having a general purpose device
907
00:33:27,505 --> 00:33:30,942
and then the software is what's tuned to
908
00:33:30,975 --> 00:33:34,612
each therapy, right?
909
00:33:34,612 --> 00:33:35,213
So if you want to
910
00:33:35,213 --> 00:33:36,547
treat psychiatric illness,
911
00:33:36,681 --> 00:33:38,583
you have to essentially treat it like
912
00:33:38,583 --> 00:33:39,484
it's a new device right
913
00:33:39,484 --> 00:33:40,718
now, is my understanding.
914
00:33:40,718 --> 00:33:41,619
Yeah.
915
00:33:44,122 --> 00:33:45,390
And is that the same in Europe?
916
00:33:46,190 --> 00:33:47,258
It is the same in Europe.
917
00:33:47,658 --> 00:33:49,227
So it goes by... it's a
918
00:33:49,227 --> 00:33:51,028
new study by indication.
919
00:33:51,195 --> 00:33:52,563
So the study burdens
920
00:33:52,563 --> 00:33:54,165
may be different, right?
921
00:33:54,232 --> 00:33:55,133
It's not that you will
922
00:33:55,133 --> 00:33:56,434
always require the study.
923
00:33:56,434 --> 00:33:59,070
Sometimes, you know, we have had C-Mark
924
00:34:00,438 --> 00:34:01,939
for Alzheimer's in
925
00:34:01,939 --> 00:34:03,674
Europe for many years, right?
926
00:34:04,809 --> 00:34:06,611
But... and I think that's
927
00:34:06,611 --> 00:34:07,645
going to expire pretty soon.
928
00:34:09,080 --> 00:34:13,184
But... we can't get an FOG if
929
00:34:13,184 --> 00:34:14,519
raising a gate label, right?
930
00:34:14,952 --> 00:34:16,854
They'll probably require a study, right?
931
00:34:18,222 --> 00:34:21,559
So we don't actually know what is the
932
00:34:21,759 --> 00:34:22,994
precise difference in
933
00:34:22,994 --> 00:34:24,462
terms of the burden, right?
934
00:34:26,330 --> 00:34:28,232
But it would be nice, I think, if you
935
00:34:28,232 --> 00:34:31,102
could get blanket approval for all the
936
00:34:31,102 --> 00:34:32,937
standard targets rather than...
937
00:34:34,072 --> 00:34:35,940
...wherever people have put electrodes
938
00:34:35,940 --> 00:34:37,608
and found them to be safe, but who knows
939
00:34:37,642 --> 00:34:38,810
how to demonstrate that.
940
00:34:39,143 --> 00:34:39,444
Yeah.
941
00:34:39,710 --> 00:34:41,045
I think the burdens are... I mean, from
942
00:34:41,045 --> 00:34:45,149
what I can see, like the FDA has been
943
00:34:45,149 --> 00:34:49,253
more... I guess, risk averse.
944
00:34:49,754 --> 00:34:49,854
Yeah.
945
00:34:49,854 --> 00:34:51,722
And I guess I should also disclose, since
946
00:34:51,722 --> 00:34:52,490
we're on a podcast, that
947
00:34:52,490 --> 00:34:53,724
I'm on the FDA devices panel.
948
00:34:54,492 --> 00:34:54,759
Okay.
949
00:34:54,892 --> 00:34:56,894
So... I should say that.
950
00:34:56,928 --> 00:34:58,463
Yeah. Right.
951
00:34:59,263 --> 00:35:01,966
So yeah, I don't actually know. I don't
952
00:35:01,966 --> 00:35:02,400
know whether it's
953
00:35:02,400 --> 00:35:03,534
possible. It would be nice.
954
00:35:03,568 --> 00:35:05,770
It would make our lives so much easier.
955
00:35:06,437 --> 00:35:09,474
I was asking you earlier today about
956
00:35:09,607 --> 00:35:13,478
whether it could get ANT and CM as a
957
00:35:13,478 --> 00:35:14,979
whole, like, instead
958
00:35:14,979 --> 00:35:16,114
of just going after ANT.
959
00:35:16,581 --> 00:35:17,548
Because ANT is approved,
960
00:35:17,582 --> 00:35:19,350
right? Why is CM not approved?
961
00:35:19,750 --> 00:35:21,452
What is the big additional thing that's
962
00:35:21,486 --> 00:35:28,025
needed for CM to be approved?
963
00:35:28,059 --> 00:35:29,961
More than antinucleus. Antinucleus, I
964
00:35:29,961 --> 00:35:31,295
think, well, if we have a good indication
965
00:35:31,295 --> 00:35:32,096
that we think it's
966
00:35:32,430 --> 00:35:34,966
limbic circuitry or frontal...
967
00:35:36,501 --> 00:35:37,935
...anatomical abnormality,
968
00:35:38,202 --> 00:35:39,270
ANT might be our first...
969
00:35:39,537 --> 00:35:42,473
But I think it'll actually be... CM will
970
00:35:42,473 --> 00:35:45,143
be the most common target for generalized
971
00:35:45,143 --> 00:35:46,444
or perioralandic epilepsy.
972
00:35:46,444 --> 00:35:48,112
So, things involving sensory motor.
973
00:35:48,412 --> 00:35:50,047
But also, different substructures of the
974
00:35:50,081 --> 00:35:55,887
pulvin are now very clear targets that we
975
00:35:55,887 --> 00:35:56,854
should be able to optimize
976
00:35:56,854 --> 00:35:57,989
with one device or another.
977
00:35:58,422 --> 00:35:59,891
I mean, I think that there will be some
978
00:35:59,891 --> 00:36:02,326
other targets that we identified, but I
979
00:36:02,326 --> 00:36:04,762
do wonder whether in cases of
980
00:36:04,762 --> 00:36:07,164
non-legional extratemporal epilepsy...
981
00:36:07,164 --> 00:36:10,835
...or patients with epilepsy where you
982
00:36:10,835 --> 00:36:12,236
don't see any abnormal
983
00:36:12,870 --> 00:36:16,774
structural changes in the brain.
984
00:36:17,108 --> 00:36:18,342
And EEG is telling you
985
00:36:18,342 --> 00:36:19,277
that it's not temporal.
986
00:36:19,644 --> 00:36:21,245
I do wonder if there's going to be more
987
00:36:21,245 --> 00:36:23,514
and more people who go directly to DBS,
988
00:36:24,148 --> 00:36:25,816
with the DBS being determined by a
989
00:36:25,816 --> 00:36:26,517
combination of their
990
00:36:26,517 --> 00:36:27,752
symptoms of symbiology.
991
00:36:28,986 --> 00:36:31,022
Imaging that, I mean, in this case would
992
00:36:31,022 --> 00:36:32,423
be non-legional, but in the
993
00:36:32,423 --> 00:36:35,326
electrophysiology, where we then go
994
00:36:35,326 --> 00:36:36,427
directly to something
995
00:36:36,427 --> 00:36:37,695
like a four-league construct.
996
00:36:38,162 --> 00:36:42,400
So, we do... I mean, I do use the Boston
997
00:36:42,400 --> 00:36:46,270
Scientific Device off-label for targeting
998
00:36:46,737 --> 00:36:49,106
dual structures bilaterally...
999
00:36:49,140 --> 00:36:51,509
...and also for targeting the thalamus at
1000
00:36:51,509 --> 00:36:53,344
the same time as targeting the periphery
1001
00:36:53,477 --> 00:36:54,078
where we think the
1002
00:36:54,078 --> 00:36:54,946
seizures are starting from.
1003
00:36:55,513 --> 00:36:57,648
And I think that's an excellent use of
1004
00:36:57,648 --> 00:36:59,083
that device, but of course this isn't
1005
00:36:59,083 --> 00:37:00,685
something that it's been evaluated for.
1006
00:37:01,052 --> 00:37:02,987
It's just that we know what
1007
00:37:02,987 --> 00:37:04,422
safe levels of stimulation are.
1008
00:37:04,422 --> 00:37:06,490
We work with neurologists who program
1009
00:37:06,490 --> 00:37:07,191
both for movement
1010
00:37:07,191 --> 00:37:08,526
disorders and for epilepsy.
1011
00:37:10,027 --> 00:37:12,263
And so it would be neat if
1012
00:37:12,330 --> 00:37:13,698
companies moved towards...
1013
00:37:14,966 --> 00:37:16,634
...or it's not even companies.
1014
00:37:16,701 --> 00:37:18,035
It would be great if there were a way to
1015
00:37:18,035 --> 00:37:22,106
have hardware with specific governors
1016
00:37:22,106 --> 00:37:24,242
built in regarding the amount
1017
00:37:24,242 --> 00:37:25,242
of current you could inject.
1018
00:37:25,576 --> 00:37:29,013
And then basically individual indications
1019
00:37:29,614 --> 00:37:33,484
were associated with specific parameters
1020
00:37:33,584 --> 00:37:35,086
that your device had to
1021
00:37:35,119 --> 00:37:36,420
have locked into the software.
1022
00:37:36,520 --> 00:37:37,822
I mean, it would seem like that would be
1023
00:37:38,155 --> 00:37:39,056
the thing to go for. It would be an
1024
00:37:39,056 --> 00:37:39,924
efficient use of
1025
00:37:39,924 --> 00:37:41,993
everybody's time and money.
1026
00:37:42,293 --> 00:37:45,930
Yeah, but I guess my one question I would
1027
00:37:45,930 --> 00:37:48,866
have is, you know, like oftentimes I
1028
00:37:48,866 --> 00:37:51,269
think the burden that's put on device
1029
00:37:51,269 --> 00:37:53,004
manufacturers is much
1030
00:37:53,004 --> 00:37:54,105
higher than the burden on you.
1031
00:37:54,405 --> 00:37:55,940
I mean, you guys can do
1032
00:37:55,973 --> 00:37:57,575
whatever you want off-label.
1033
00:37:58,042 --> 00:38:00,211
Exactly, right. And that is not
1034
00:38:00,211 --> 00:38:01,379
questioned by the FDA, right?
1035
00:38:01,612 --> 00:38:05,316
But when we try to sell and market, then
1036
00:38:05,583 --> 00:38:08,653
they would probably should ask us to
1037
00:38:08,653 --> 00:38:10,021
provide evidence that it's safe.
1038
00:38:10,821 --> 00:38:12,523
So I don't know whether the community as
1039
00:38:12,523 --> 00:38:16,794
a whole can build up evidence that these
1040
00:38:16,794 --> 00:38:18,462
different targets are at least safe.
1041
00:38:18,863 --> 00:38:21,699
Forget the efficacy for a minute. But if
1042
00:38:21,699 --> 00:38:23,334
you can maybe build up some kind of
1043
00:38:23,934 --> 00:38:25,336
evidence base that these targets are
1044
00:38:25,336 --> 00:38:27,238
safe, maybe that changes how
1045
00:38:27,238 --> 00:38:28,873
the agencies look at it, right?
1046
00:38:29,040 --> 00:38:30,307
I mean, it seems that a study, a lot of
1047
00:38:30,307 --> 00:38:32,510
people are doing the telomexteria EEG
1048
00:38:32,543 --> 00:38:34,311
just for standard clinical protocols.
1049
00:38:34,311 --> 00:38:35,513
We do at Mayo, a lot of other
1050
00:38:35,513 --> 00:38:36,714
centers do around the country.
1051
00:38:37,315 --> 00:38:38,949
But we could test a variety. And because
1052
00:38:38,949 --> 00:38:40,117
we're sampling so many places in the
1053
00:38:40,117 --> 00:38:41,552
brain, we could test a variety of the
1054
00:38:41,552 --> 00:38:42,586
stimulation parameters
1055
00:38:42,586 --> 00:38:43,621
for each of these targets.
1056
00:38:44,689 --> 00:38:46,824
And maybe that's something that we should
1057
00:38:46,824 --> 00:38:48,392
do or something else out there should be.
1058
00:38:48,392 --> 00:38:48,826
We should think about
1059
00:38:49,927 --> 00:38:52,163
doing it together. Definitely.
1060
00:38:52,797 --> 00:38:53,064
Great.
1061
00:38:54,031 --> 00:38:56,333
Okay. Do you have any questions for us?
1062
00:38:56,333 --> 00:38:56,600
No.
1063
00:38:57,068 --> 00:38:58,803
No? All right. Well,
1064
00:38:58,836 --> 00:38:59,837
thank you so much for joining.
1065
00:38:59,837 --> 00:39:00,338
Thank you.
1066
00:39:00,938 --> 00:39:01,672
Yeah, thanks for coming to
1067
00:39:01,672 --> 00:39:02,807
town and we appreciate that.
1068
00:39:03,074 --> 00:39:03,374
Thank you.