Judith: Welcome to Berry's In the Interim podcast, where we explore the
cutting edge of innovative clinical trial design for the pharmaceutical and
medical industries, and so much more.
Let's dive in.
Scott: All right.
Welcome everybody.
Back to in the interim.
I'm Scott Berry.
I'm your host, and I am a statistician, as, as many of you
know, uh, Bayesian statistician.
And here on, in the interim, we explore things.
Around clinical trial science, medical decision making, uh, data
analytics, uh, this is our space.
We, we have a new studio here.
We're we're, our technology has changed a little bit, and for those
of you who consume this via video, looks like a bit of a different place.
Um, I am, I am recording from a different place here.
Uh, as, as you'll see throughout multiple different places, I was,
I was traveling to this place as I introduced the topic for today.
I was traveling here and I was, I was connecting through an airport and I had,
uh, it was a bit of a long day and I, I was looking to get something to eat.
And I went by a, uh, hamburger place with, with quite a line, and
I'm deciding do I want to go there?
Do I wanna wait in the line?
And I decide, no, I, I don't want that.
Choice.
I I and because I believe at one of the places next door with a really short
line that there's a, a really good, uh, uh, chicken bowl, uh, by the way, a, a
a bit of fan of kava if you have kava.
So I think that's what I'm getting.
And so I say no to the burger place.
I, I, and I go and I to get my chicken bowl.
And so I get this, and it turns out it wasn't at all what I was expecting.
And I got something very different than that.
And it turned out to be almost kind of a chicken salad type thing.
And it was interesting because then I got that and I'm, I'm
walking by the burger place.
You know, I, I, I really wish I would've.
Gotten the burger, uh, in this setting.
Uh, it's the, the, the, the trials and tribulations of travel.
Well, it, it introduces a bit of my topic today, and the, the, the
title of today's discussion is Regulators False Choices and ICHE 20.
And so I'm gonna try to tie this all together in, in what I mean by this.
So I'll start by talking about the ICHE 20, uh, Kurt and
I did a discussion of this.
We, you can go back and, uh, previous EP episode of the ICHE 20, it's
a draft guidance document, uh, that discusses adaptive trials.
Now, most of this is good.
Most of the ICHE 20 is good in the sense that the existence of it, that
adaptive designs are confirmatory trials.
And by the way, backing up ICHE 20 is very much a harmonization.
And so what goes in there is largely.
Harmonized, essentially agreed throughout many, many regulators, global regulators.
And so in some level, this is the floor of things.
Now, different, different, uh, regions are gonna have different behaviors on things,
but to some extent a floor level things.
So from that perspective, adaptive designs are confirmatory.
Sample size.
Adaptations are confirmatory.
Enrichment trials are confirmatory, seamless trials are confirmatory response.
Adaptive allocation is confirmatory and it has a small set on
Bayesian being confirmatory.
All of these things are in there.
Now, as you can go back to that there, part of this is, it's written from a
pretty, um, pretty negative viewpoint.
Uh, uh, I'll say that from the perspective of a lot of it is very cautionary.
It, it's not inviting in that perspective, but yet its existence
is still a positive thing.
I wanna jump into.
What I'll call the paragraph and.
It's because this paragraph has been, uh, used, uh, uh, almost weaponized.
Now I'm gonna go into this.
I'm gonna talk about regulators and I, and I do wanna say this upfront.
I think regulators do an amazing job and their perspective is different.
I've never been a regulator.
I've been proposing designs to regulators for more than 25 years,
and I think they do a tremendous job.
So part of this may border on what you.
You consider criticism, and I'm gonna try to put myself in the mind of a
regulator and think of that perspective of what happens when you're on that
side and, and evaluating designs.
But from that side and perspective, there's a particular paragraph and ICHE
20 that I think has been weaponized and I think the paragraph is wrong.
So I thought that this would make a good podcast, uh, to
be a bit controversial here.
So first in ICH-E20 There's a section that talks about, this is section three
and it talks about the adequacy within the development program, section 3.1,
and it had, this is not the paragraph yet, but it has the
sentence that says A stepwise.
Program with careful analysis and evaluation of completed exploratory
trials helps inform the goals and design choices for subsequent confirmatory
trials, and ultimately generate data necessary for regulatory decision making.
Somewhat of an inno, innocuous sentence, but it lays out this notion
that a stepwise program, to some extent is a bit of the gold standard.
And I, it, it, that sentence has is isn't a problem, but it, it, it
sort of sets it out that almost what we're doing now is kind of right.
And things that are different than that are, are pushing against that.
But that moves into in the same section.
And this is line 1 0 1 in this draft guidance.
So this is the paragraph now, and the start of this says
the number and complexity of adaptations at the confirmatory
stage should generally be limited.
So that's the first sentence, and I'm gonna push back on that.
And then it continues increasing either of them.
So the number and complexity.
Increasing either of them as a replacement for a sequence of multiple
trials can impair the ability to answer important clinical questions
and limit the opportunity to carefully reflect on prior results to design a
development program most effectively.
So that's, that's the paragraph.
It does continue on.
I think those two sentences are, are what we'll spend a good bit of, of
this, this episode, talking about, it says, before planning a confirmatory
trial with multiple adaptation sponsors, sponsors should discuss whether
additional exploratory trials are necessary to investigate the questions
addressed by the proposed adaptations.
So this paragraph has, has been somewhat weaponized in a way, and I know that
sounds pejorative, but you, that this idea that the number of adaptations, the number
of interims and the complexity is bad.
And it's a replacement for a sequence of multiple trials.
Now, remember, going back to some extent that's the right answer here.
So a couple things about this, and so by the way, this has been presented where
designs have been presented to regulators.
They've come back and they've pushed back on the design some form of
no, and they've cited this draft.
Paragraph for the reason for that.
It's too complex.
Do a separate trial and then a simple phase three confirmatory trial.
So within the guidance document on adaptive trials that says
all of this is confirmatory, there's a paragraph that really.
Limits much of it to something that I'm gonna push back on,
and I think it's largely wrong.
So first, there's this, this general thought that more adaptations is
somehow bad or somehow not good.
I think this is largely a myth.
I don't believe it creates more bias.
Yeah.
It's operationally more complex by the way.
Marginally.
It's to do, you know, seven interims compared to six is
marginally very little to do.
Two compared to one is marginally very little.
That first one in setting up the process of how this is
done is an operational lift.
It's it's minor relative to the general operational burden of
running a clinical trial, but.
I, I think this is largely somewhat of a myth that multiple adaptations
in some way increases potential bias.
And to some extent, I think it almost decreases it when you do a single
adaptation in a trial, a single futility or a single success analysis.
And much of these, what I'll call myths, come from the traditional
thing of the only adaptations or stopping for success, yes or no.
And now trials have moved on greatly as many of those that I
read that are in this guidance.
Uh, the possibility of those.
So when you do one of these analyses and you continue on, or you don't stop or you
jump futility, there's something learned about what's going on in the trial.
It's, you know, depending on when it, it, the relatively minor, but people
can perceive there to be potential biases of that when you do one.
That's the biggest potential there.
If you did a hundred in a trial, each one of these, I, I mean,
it's just, it's like daily.
These are being done essentially ignored, and we've done trials.
I SPY two used to do interims daily.
It, it eventually went to weekly.
And I think by the way, trials are more likely to go that way.
It essentially removes these, these types of concerns.
So I, I wanna push back on that, but that's not even necessarily
the, the, the large extent of it.
It's that overall this sets up, and this is where I'm gonna get into
this idea of sort of false choices.
This somewhat sets up the notion that adaptations are shortcuts.
That when the alternative is doing multiple exploratory trials, that
somehow adaptations are always shortcuts.
And by the way, when you read this ICHE 20, that's an overriding
thought about this guidance document.
It's, it's the part that when you read it, much of it is set up in that way.
And I think it's a false choice, and I think false choices set that up.
And so I wanna walk through this a little bit.
I'll walk through it with examples and try to explain what
I, what I mean by that from it.
So I, I, I'll start with an example trial.
And this trial, uh, was conducted several years ago.
The trial's over the name of the trial is Sepsis Act, and it was a
trial run by faring pharmaceuticals.
It was the treatment for sepsis and they had a treatment, uh, a
form of a long-acting vasopressor, and they had three doses.
And to explore.
And they were, they wanted to explore the, the effective dose and they wanted
to explore the effective dose on clinical outcomes, not necessarily biomarkers.
So the role is a long-acting vasopressor going to be beneficial on clinical
outcomes for patients with sepsis.
So they have three doses in placebo, and the question is,
what kind of trial do they run?
And they want to explore dose, and then they want to run a phase three trial.
Well, when we started looking at this, initially, they thought of,
okay, maybe we do a phase two trial, separate sequential trials, and
explore three doses in placebo.
Well, to get some idea of the effect.
Of dose on clinical outcomes like length of, of organ support and
mortality, that the endpoint in this trial ends up being a composite of
mortality and length of organ support.
For those that survive an ordinal endpoint, that 200 patients, or a
hundred patients, or 200 patients was, was insufficient to select dose.
It's, it's too small.
As you start to get into 400, 500, 600 patient trials, you're almost starting
to get into phase three territory.
So to run a realistic phase two trial to understand clinical outcomes
starts to get to 5, 6, 700 patients.
Well, you now you're getting into mini phase three trials.
So they explored this and they ended up with, here's, uh, I'll
describe the Sepsis ACT trial.
Where, when a hundred patients are enrolled equal randomization
to three doses and, and placebo response, adaptive randomization
starts only on the active doses.
The, the randomization to control is fixed.
And by the way, it's fixed at, uh, a third, so 33% and then
the remaining 67 are set up.
So it wasn't equally to all of them, but the doses are equal and placebo's 33%.
The response adaptive over these three doses, it also had the possibility
of adding a fourth dose if the dose response looked increasing.
Within that.
So a neat little design that at a hundred, these RAR updates start.
Once 200 patients are enrolled, and by the way, those happen monthly.
So every month RAR is reset.
So now we're starting to do a good number of interims In this stage.
One of the trial, once 200 patients are enrolled, the trial could go to stage two.
That would be selecting a single dose and moving to one-to-one randomization.
And the final sample size would be 1800 patients, including stage one,
and that would form a phase three trial and interims keep happening
monthly, and it could go from 200, anywhere up to 800 could be the
dose ranging portion of this trial.
At 800, there's a forced decision.
Now you have to go to stage two or you have to stop, and it's a
large phase two trial, but largely you'd be stopping for no go.
I, I won't call it futility, but it's a no Go to phase three, and
it becomes a large phase two trial.
If things are going very well and you've identified a dose, it could go
earlier and it's eight 1800 is the, is the max, is the final sample size, and
so there's no adaptive sample size.
If this goes to phase three, the trial ended up running, uh, more than 20
interim analysis during the course of it.
And this, this is considered a complex design, multiple interims and.
So now I, I'll, I'll claim that if this, this design would be submitted
in the presence of that paragraph, it would be very easy for a regulator to
look at that design and say, that's too complex, too many interims.
Go run a separate phase two sequential trials are better as set up.
Go run an 1800 patient phase two trial.
Then when you've selected dose, made your decisions go run an
1800 patient phase three trial.
So as a regulator, maybe that's what you're evaluating.
So when presented this seamless two three trial with a, with
a good number of interims.
In the trial, a fair amount of complexity.
And again, I'll back up and think that these, these interims
aren't causing more bias.
They're not somehow risking this.
It's not a bad thing that these are done.
I think in some ways they de-risk all of it, but
the the when, when saying, oh no, you can't do that trial.
They think the alternative.
Is an 800 patient phase two, followed by an 1800 patient, phase three.
The problem is, that's not the alternative, that's a false choice
as this extreme sort of value is, oh no, I don't want that.
I, I'm gonna get this other thing, but you're not getting that.
So you say no to design a and now you've got a paragraph that somewhat weaponizes.
A reason to say no to that.
Hoping you're going to get design B 800 plus 1800, but you
don't get B, you get design C.
What do you get in that circumstance?
Well, you either get that they don't explore dose and they go to phase three
or a small 200 patient trial that actually does a really poor job at dose finding.
Go no go.
Followed by 1800 in that.
So the design you want, which is 2,600 patients in the
separate, is never gonna be run.
It's a false choice.
And the reason for that, now coming back to this idea within this trial
is, is this adaptive design a shortcut?
And it is a shortcut.
When evaluated compared to 800 and then 1800, it's a shortcut.
Uh, in that setting.
It's combining the 800 with the 1800.
Now we can control type 1 error.
We can understand all of the characteristics of this.
We can make it a confirmatory trial, but it is using 1800
patients rather than 2,600.
It's efficient within that perspective.
So, but compared to 800 and 1800, you could claim it's a shortcut, but that's
a design that's never going to be run.
What would be run is 200 plus 1800, and the 1800 with the seamless
up to 800 is a better design.
It's better design for regulators.
It's a better design for patients.
It's a better design for sponsors.
Everything about it is better.
And that's the value of adaptive designs here.
And efficiency isn't shortcut efficiency is the ability to answer questions that
aren't going to be done separately.
Now.
Go back to episode 17, by the way, where we, we, I, I talk about a paper, uh, with
Lindsey Berry, Joe Mary, and Kurt Veley.
If you have 1800 patients to use as a sponsor and you have three doses to
explore, a seamless two three trial is going to dominate in terms of getting
the right dose in terms of power.
Any other sequential use of those 1800 patients, you could break
it up into 500 and 1300, uh, compared to a seamless trial.
And that paper shows, uh, uh, Barry et all shows that that's the optimal
way, improves power, dose selection, everything about it is better.
Better than separate trials.
So that's the part of this that I think's a false choice is.
No, I don't want A, I want B.
But you don't get B, you get C.
It happened to me traveling yesterday.
I said no to a thinking I was gonna get, you know, I said no to the hamburger
thinking I was getting something else.
What I got was not that.
Uh, I would've gotten the hamburger had I had the choice.
The same thing from the regulator perspective here now.
What does this mean?
Interestingly, by the way that trial design was, was run, it was given a spa,
a special protocol assessment by the FDA.
Was approved, they said yes.
Uh, there were, there were various interactions and I think the interactions
really were in what, what would be done.
And it was presented, and by the way, this did go to multiple regulators as.
Why don't you do a 200 patient phase two trial and then a phase three trial and
it, we were able to present the different operating characteristics of this, and I
think it was with the ability to see the range of potential possibilities here.
This is actually a pretty good design for all parties involved,
and it's not a shortcut.
Adaptive designs are not shortcuts.
Efficiency is not shortcuts.
Depending on what you think the possibility of those designs are.
Okay.
Interestingly, in that trial where these interims were run, I was actually
unblinded during the course of this trial.
Had this trial been a 200 patient, phase two, they would've run phase three.
They would've run an 1800 patient phase, uh, phase three trial.
The data at that time were quite positive.
Now, by the time 800 rolled around.
It wasn't positive and it stopped for no-go.
And you can go, you can look up the various characteristics of, uh, uh,
the results have been reported on this, and the trial was a no-go.
It didn't go to phase three.
It ended up using approximately 800 patients, uh, with, and I think the,
the result of it was quite good.
200 patients.
It would've conducted a very large, expensive phase three trial with
CMC and the expansion to it, which I think would've been the wrong choice
now, uh, that, that's, that's one particular outcome of the trial, but
we simulated all the possibilities and we know the probability
that of these things happening.
From a 200 patient trial is quite different from the 800 and that was
part of how this trial was built.
So this, this idea is a lot of times a design is presented to regulators and
they're evaluating that single design.
And so when you're evaluating that, it's always well compared to what,
and that's the, that's what as, as somebody who for 25 plus years have been
submitting design to regulators, a lot of times we submit that single design.
And yes, there's a line I use quite frequently, I'm sure I've used it on
another podcast, is when somebody asks me as a statistician, Hey, how's your wife?
Uh, the answer's well compared to what?
Now my wife, by the way, listens to all these podcasts, uh, and
she's a saint, as you can imagine, uh, putting up with, with this.
Uh, but that's the same sort of thing.
It's what compared to what and if you're.
In the mindset of, okay, I've been presented this design a boy.
I'd rather have them do separate trials, big trials sort of thing.
If, if, if I'm thinking that's my comparison, oh, I, I, I might say no to
A, because I think I'm getting B, but B is not possible and it's not gonna be run.
And you get c.
So a recent example of this.
So part of this is how do we, how do we help this process?
And if, if I were a regulator, I might very well do the same thing.
So I don't want this to be a criticism of regulators.
They sit in a different chair and they're evaluating a
single design, a single thing.
How, how is that?
Well, I mean, compared to what, and I might think, oh, you should do, you should
do this adaptive design sort of thing.
So I, I push back on a.
But I don't get a better adaptive design.
Maybe I get a design I think is worse than that one.
So that's a challenge in this interaction.
You usually throw a single design and say, Hey, how about this design?
A recent example of this was another seamless two three trial.
It explored two doses and, uh, a relatively rare disease, by the way,
exploring two doses and picking a dose, moving to one-to-one randomization,
and going to a section that is then, uh, uh, adaptive sample size.
So three interims to select sample size once it moves to one-to-one,
and that that's the trial design and submitted to regulators.
Now there's some pushback on that.
And again, that paragraph could be used to say, aha, you're doing dose
selection, you're doing several interims.
That's too complex to be confirmatory.
Go run a separate phase two and then run phase three.
And this was actually the advice given by regulars given by the FDA within that.
When this comes back and you're working with the sponsor and you
say, okay, how about the possibility?
Oh, and, and by the way, part of the reason was the pushback is
the endpoint in this trial is a relatively long-term endpoint.
And so we're making dose selection based on early predictive markers.
Now, those markers are not the confirmatory marker endpoint at the
end, which is the longer term agreed.
Uh uh, fields function survives endpoint.
But we have to, because of enrollment and 'cause of the scenario base it, there will
be a little bit of long-term endpoint, but largely it's an earlier endpoint and the
FDA was concerned about the predictability of that and they would rather have a
separate phase two that goes all the way out, long-term clinical outcome,
make your decision and run phase three.
And that was the advice given.
So now the regulator gets this design A and thinks, oh,
that would be a better design.
And you can always create a superset design to an adaptive design that is
better, but that would then be this larger, longer phase 2 larger phase 3
And when going back to the sponsor and saying, okay, is that a possibility?
It's impossible.
They said the company would fold.
That trial can't be run.
So that, I mean, that's where this falls into it is any adaptive design.
You can create a design that's a superset of it and say, oh, you should do that.
It's not a possible choice.
You, you, that you can't do that.
So saying no to A, because I want B, it's a false choice.
So what the, what, what's if somebody, if regulator says, no,
you can't do design a what gets run.
Is a phase 3 trial without dose selection, and that's what the sponsor said.
If we can't run that trial that selects a dose based on earlier interval, we're
just gonna pick a dose and run phase 3 What you get back is not why you said
no to a, so all of a sudden, suppose the regulators understood that the
choice was that design A, that at least selects dose based on an earlier marker.
And then moves into the seamless phase 2/3 part of it into the confirmatory
part, or you just get a phase 3 and they pick the dose with no data.
I think they'd pick design A, and they'd live with picking it on that endpoint, but
when evaluating it, in their mind they're thinking, oh, I, I think you should
do design B, but that's not a choice.
Now, this is a bit of a challenge for us is.
How do, how do we work with that?
How do we present this in a way that's consumable and all of that?
And I'll, I'll come back to that a little bit.
What, what happened here, by the way, is a great story is in the
in-person meeting, the sponsor shared that we can't run that design.
We can't run separate troughs.
I mean, it would not be run.
The agency became a partner in this.
Sort of development as where do we go?
What can we do under this setting?
And largely, uh, a form of a slightly a, a adapted in a good way.
It was what came out of that.
So it was a beautiful interaction.
And again, I think the FDA did a tremendous job in being partners, in
creating better care for patients.
And it was, it was great, but it's this hard aspect of, of evaluating
a single design in isolation.
Another example of this, and I'll, I'll do this relatively quickly, was an
enrichment trial where it started off one-to-one randomization phase three
trial, but there's a concern about what's the right patient population
and there's some risk that we might be enrolling patients who who don't benefit
the, you know, there's always this.
Enrolling people on the healthy side or the less healthy side maybe, that you
can't really mod, uh, you, you can't modify the effect in those patients
sealing and, and, and floor effects.
So.
Starts off enrolling a rather larger set, but could restrict
enrollment, do enrichment in the trial, and to do enrichment.
Well, by the way, when you simulate these trials, you
have to do it relatively early.
If you wait too long to do enrichment, you know your trial's largely
enrolled and it has little benefit.
In it, but it, so you need to do it relatively early.
So the trial had three interims for potential enrichment, and then
had three interims for sample size.
So all of a sudden, this is a six interim phase three trial.
This literally referenced the paragraph that I gave you
as, this is too complicated.
Doomed it by saying, this is this trial.
It makes because of the complexity and the adaptations, it makes that trial
exploratory, and that's, that's death.
It means it's not a confirmatory trial.
By the way, A different regulator region said, yes, the design's good.
We like it, which is, which is a challenge here, but I think the
regulator that said, no, this is exploratory, and use that paragraph.
As a weapon, thought they'd get a different design, run that
trial to understand the patient population and then run phase three.
But that trial's never going to happen.
Uh, it's unaffordable the time the, those large phase twos don't happen in that.
What would happen is they guess at the patient population and they don't
actually explore that and they run a phase three at risk, or they ignore
the region that said no to the trial, which neither one of those is a better
option than trial A of what they got.
And so that's a huge aspect here and, and such a challenge, uh, in these
circumstances of being a regulator because maybe you don't know what
the alternatives are if you reject.
The null.
What's the alternative?
If you reject a design, what, what, what am I gonna get?
Uh, and maybe I would go back and actually really like the one
that, that was already submitted.
And so several parts of this, again, that design this, you know, call it.
A thousand patients in this enrichment phase three trial.
What they'd rather have is a thousand patient exploratory trial to find the
enrichment or the enrichments only can happen up through 400, run a separate
400, and then run a thousand patient phase three, but that's never gonna be run.
That trial is more efficient, sorry, not more efficient, but more powerful than
this seamless thousand patient trial.
But that's not a choice.
And so this now does better than all the alternatives and the adaptations allow
a better trial to be run for everybody.
Another very, very simple example.
It's a very common example.
This isn't a real one, but it's reflective.
The other ones were real examples is reflective of what happens quite a bit.
Is uh, a sponsor's interested in running a phase three trial, one-to-one randomized.
Uh, double blind, all the nice things.
And they say, okay, for, for, uh, an effect that they think their drug has
of Delta, they get an 80, 90, it doesn't matter percent power trials, 180 patients.
And then you show them, well, you know, a smaller effect than Delta,
which is still clinically meaningful.
Might only have 50 or 60% power with your 180.
But they don't wanna run a 300 patient trial because they think
they're better than that and they think that's a waste of resources.
So if given the choice of a single fixed trial, they're
gonna run 180 patient trial.
Now the risk is that there's a clinically meaningful drug that
doesn't hit success with that.
So you show them what if we do several adaptations for sample size?
And suppose we do interims at 150, so if the drug's even more
effective, we get out sooner.
200, 2 50, or 300 with appropriate futility rules.
And success looks and all of a sudden this design performs really, really well
because if their Delta's true, they still get out with something that on average is
180 or, or better than that, they stop at 150, 200 with high probability, and that's
really good if it's clinically meaningful.
But less than that Delta, they still have a good chance of
successor 200, 2 50, or 300.
So a really nice design.
Now, if somebody says, that's too complex, too many interims, they
might think that because they're getting a 300 patient trial.
I say no to that because run the 300 patient trial,
but the 300 doesn't get run.
The 180 patient trial gets run.
So that's the challenge of this.
This is the, the, the challenge of a regulator.
And this is, this is, um, this is not necessarily their fault.
In thinking about what this alternative space, and if I were a regulator, I
might have a different alternative set of designs that I think could be run.
And so I say, oh, you should do the following, but the those are
never gonna be run potentially.
And I get something back as a reaction to this that's worse than the original one.
And these are the challenges of the way these are.
This is particularly done.
So I think we need to communicate that better, which is hard, by the
way, because you can't say, if you don't take a, we're gonna do C in a
way that is almost, uh, blackmail ish.
That, you know, boy, if you don't say yes to our design, you're gonna get this.
Uh, you know, and that, that's really not the way we traditionally
when we submit a design like that.
We work really hard to explain that single design as to what
you're gonna get as a regulator.
Now we don't spend a lot of time comparing to a bunch of other designs.
It's actually can, can be confusing to somebody receiving this.
What, what's the design again?
But I think we need to do a better job of that, to understand the breadth
of the designs that could be run, not in an aggressive way, and showing
that this is a, a better design, a seamless two, three trial designs.
Better design than a lot of the alternatives that could
be run in that scenario.
And so thi this is really our challenge as clinical trialists to be able to
do this in this weird interaction we have with regulators tied to it is.
As this draft guidance on ICHE 20 is going, hoping a bit of that paragraph can
be massaged and less of a sharp weapon for moving forward, uh, in clinical trials.
All right.
I appreciate you joining me today in my, my new digs, and yes, I survive
the travel and in all of that, and so I appreciate you joining us.
Until next time, we'll be here in the interim.