FDA Direct: The Power of Real-Time Clinical Trials

He's good.

Bigfoot's good. We're good.

And so we're going to do this.

That's actually his name. Bigfoot.

He doesn't exist.

People don't think he exists.
But you've met him.

Someday we'll get him more on.

I think people have seen his hand, like.

Like the actual Bigfoot.

So I'm here with FDA's chief
AI officer, Jeremy Walsh.

We have a big announcement today,
and we're thrilled to have with us

two doctors that we love, Dr. Emma Meagher

from the University of Pennsylvania.

She's Professor of Medicine
and Pharmacology and also the Vice Dean

for Clinical Research
and Translational Research.

And Dr.Jennifer Litton,

Chief Clinical Research Officer
at MD Anderson Cancer Center.

If you have not heard of the University
of Pennsylvania or MD

Anderson Cancer Center,
let me tell you a little bit about them.

They are small, up and coming institutions
in the health care system.

So great to have you here.
And thanks for joining us.

Exciting day.

Yeah, very exciting day.
It was a great day.

I mean, I, I can't thank you
both enough for, taking the time to come.

Come to the FDA.

Listening to both of your
sort of stories was just had,

left such
an impression on me in terms of the

the work that you do every day, you know,

taking care of patients
and trying to drive, you know,

both from the drug development
side on the, on the,

on the sort of the cancer delivery side,
a cancer, cancer sort of patient side.

So I think I was,

it was really just a profound experience
to sort of listen to that.

Why don't you say
we just came from the announcement?

So maybe you can share a little bit
about what it was.

What's been happening
is that over time,

the FDA receives
more and more information, right?

You've got your phase one trials,
your phase two

trials, your phase three trials.

And so as part of that process,

you enroll as a patient, you go into a
site, you, your data is being collected.

It's being, as you mentioned,
sort of being transformed

into multiple different systems,
which is then sort of cleaned, right,

you know, looked at,
analyzed, cleaned, locked,

and then eventually
sort of sent to the FDA. Right.

This this takes time, right.

And it's costly and it's time consuming.

And also actually kind of a little bit
prone to error in some scenarios as well.

Right.

So, so there's a lot of stuff
that happens within that process.

And so what the FDA sitting here is saying
how can we reimagine that?

You know, and it really
it comes down to to the, the,

the sort of the thought processes,
what data do we need to make a decision?

What information does the FDA truly need
in order to make a regulatory decision,

especially in your early phase
one and phase two trials? Right.

Like where we mostly focus
for on the safety side.

So I think today was an announcement
around that.

You know, we have launched real time
clinical trials.

We are looking at,

you know, we're starting from a standpoint
of the least amount of information

as possible. Signal data. Right.

Any type of signal, the FDA defines
that's part of this trial industry will,

you know,

be will be analyzing and then they'll be
sending that estimate in real time.

And then our reviewer
is going to be looking at that.

And so that's the
that's the beauty of what we're doing.

We're almost kind of resetting the clock
a little bit, restarting

the conversation around.

We know we get we know you can send us
everything.

Let's start with what we need.

So I think that's kind of the was
was was the announcement today right.

So today the FDA announced the first ever
real time clinical trial.

This is not a theoretical
it's not an idea.

It's not a panel to discuss the
the future possibility.

It's not an expression of intent.

It is live.

It is up and running.

Your centers are participating.

And so it's exciting.

Tell us a little bit about it.

If you could start, start, Emma.

Just really excited about the idea

that the FDA
is focusing on process innovation.

I mean, it's long overdue for all of us
to actually focus

on that on a very practical level
in the trenches.

You know, this
the amount of time that you spend entering

information into systems, and there's no
shortage of them, is lost time.

It's mind numbing.

Mind numbing, and it's actually mind
numbing for the people who do it.

So much so that it's really hard
to keep them in their jobs.

You know, they're not terribly
well-paying jobs to begin with.

And it's boring, repetitive work,
and it is prone to error, no question.

And then it gets analyzed
by the docs who are in the fields

doing the trials, and then it gets
transmitted to the company,

who then analyze the information.

And it's kind of redundancy
and repetitiveness that isn't necessary.

So this concept is

has a real potential
of being transformative.

I think that it if we do this
truly as a partnership, and I said

this earlier today, years ago,
the FDA was a regulatory body.

Today, the FDA has a position
that it wants to partner on solutions.

And that in
and of itself is transformative.

So for academia to partner with industry
and the FDA in an innovative approach

to actually accelerate
this incredibly painful process,

it can be a game
changer, really can. Need to do right.

We need to do it in a sustained fashion,
but it can be a game changer.

You know, I started off my career in the
s as a study coordinator,

doing breast cancer trials,

which is how I became
a breast cancer doctor.

And it is really not different than

I would sit there, I got a laptop down.

The laptop was this big,
and you would open it

and you would take it from the paper
records.

You would put it into this,
and then it went to three other places,

and you were collecting so much data that

because there was this fear of
if I don't get the right

piece of data, I'm not going to get
the answer I need at the end.

So let's collect

every time this person sneezes, let's
how many times a day do they sneeze?

And and I'm not trying to make a joke
about because safety and rigorous

clinical research is important.

But that's the whole point of today.

You’re saying we’re absolutely going to do
rigorous clinical trials.

We are going to see safety signals.

We might even see them sooner
and be able to see trends sooner

than a whole bunch of people
grabbing forms and putting them together

and hoping someone gets to them
and looks and says, oh, there's, you know,

interstitial lung disease, where we could have picked that up, you know, earlier.

I also think we're going to get to a point
in oncology and in clinical research

where we're going to start
seeing the pre-signals.

And we can't do that
unless we have this technology.

But we're saying,
okay, we know this person.

If they have X, Y, and Z,
they're going to have

a hospitalization in days.

That's where we're going.

And this is the very first step.

People
ask what is real time clinical trial.

It's where we as
FDA scientists can see these endpoints

or safety signals in the cloud as
the trial is happening in real time live.

And so this is a new data feed
that has the potential of

making more efficient the massive data

consolidation and analysis

that goes into these giant applications
and just make it more efficient.

It's really a milestone.

If you think about pandemic preparedness.

This is a huge. 
Would have been a game changer.  

Don't you think?
Yeah, %.

I mean, we in our roles,
we were responsible for creating strategy

and clinical research during Covid
and it was a nightmare.

We didn't have data systems.

You know, I remember it at a.m.,

we had, early AM call at p.m.,
we had a PM call.

We looked at all of the clinical data
from all of the emergency

rooms across the health care
system, the ICUs.

And we were.

We had spreadsheets.
I mean, it was primitive.

So even at that level, not
even thinking about trying to collect data

in a trial, not leveraging systems
to look for signals.

And I agree with you.

I think I think we'll get early signals.

So I think it's transformative.

The other place where I think that is,
can be a real game changer

is while we need process, innovation
and how we do the trials, we also need

process innovation and what is necessary
to get a product to approval.

And what we were talking about
a little bit earlier today

is that as you go through this process,
I am pretty certain

you're going to realize
you ask for too much data

and that actually, how the trials will be
done will require

less invasive testing on the patients,
which will actually increase their ability

to participate remotely,
which will completely democratize

the ability of rural and urban
environments to be able to participate.

We require for these resist criteria
and oncology trials

MRIs done every six months.  CAT scans done
every alternative every six months.

So that's bringing your patients
into the health care system.

They don't need to be there.

So I really think that the the utility
of the information

that you collect using this technology

will not only help us execute our trials
and industry design the trials,

but also might help regulators reimagine
what data points they need.

That's a great point.

I mean, that's was one of the the focuses,
like the the way in which this real time

trial worked
was that when we started it, we said, hey,

listen, send us over your protocol. Right.
And then what

what are we going to send back?

We're going to send back what the,
the basically the reporting criteria.

Right.

When you do that at that early phase
in the process, what you're forcing

the FDA, we're forcing the FDA to do
is to make a decision on what's important.

Yeah.

You know,

which actually gets to this point
of like of like, what do you really need

to make a decision?

And so when you have to make

those judgment calls, right, you know, it
does it changes the calculus of what,

what do I actually really need to know
in this at this part of the process,

what what's the onus
we're putting on, you know.

And so so that's that's
one of the objectives of the of

sort of the approach is to, is
to, is to have our is to have the FDA work

in concert with the sponsors to be like,
let's think about what's necessary.

Minimum necessary.

Minimum, minimum necessary
in order to get to a decision.

That's our
that's because when you think about it,

if you're kind of restart the process,
that's where you start.

You know, you're like,
okay, what's the bare minimum I need?

Nothing more. Right.

And then over time we'll, you know,
we'll build up certain

OK, well, I needed that piece.

I really would have like, you know,

the narrative,
a little bit of the narrative information

around this event or something like that
helps me get helps me,

you know, quantify it.

Okay. Great.

You know, or I wanted to have something
additional around, the

like a, an adverse event type or whatever
it might be.

Those are literally the conversations
I had yesterday right when as the

as the team seeing that, seeing the data
roll through, they're going,

well that's great.

You know, I need a couple extra
fields here and here.

And that should be
all I really need for this section. Right.

And the same thing that they're saying is
what data can we use inside the FDA

that we already have, right,
to help inform us on?

Well, what's going on.

So I think this gets to a, an aspect
where,

you know, the FDA has never really used
all of its historical information

and all of its previous data. Yeah.
To help.

Very aware of that.

Yes. So, so, so this is a
this is a part of the process where like

if, you know, give me the
the least amount of information

I need upfront to make a decision.

And but let me be empowered to use

all the information that we sit on that
we have in order to help drive to,

to help understand
what's actually happening here.

Yeah, it would be. Sorry. Go.

No, no, no, I was going to say but
but do you see that?

Then where the whole traditional
if you do a study, you wait for it

to report out,
then you write the phase two,

then you wait for a report out
and then you could see where

it's a single study with stop, go, no go.

And we get quick answers from both,
you know, the sponsor

and academia and the FDA.

And it just triggers it without re
contracting, without redoing it.

And you write that one trial
for the whole development

with just the blanks of the couple places.

So I mean, the dead spaces
that you were talking about,

Commissioner, are long between trials

and they should be,
we should be ready to roll with the next

if we have that early signal
that this one is going to change lives.

The Recovery trial was actually
a great example of that.

Is that the steroid trial.

Yeah. During Covid.
So it had multiple arms.

And so the way it was designed
it was sort of like an adaptive

trial design where you come in
to this study and the first patients

will be randomized to A, B,
and then you would do an interim analysis.

And then based on the safety signal,

you'd say, no, we're going to stop here
or lack of efficacy signal.

But the people who had a response
would continue.

Then you add another arm
and then you keep on adding arms.

Now, while that was a very good design
during a pandemic

where you didn't have companies
sort of competing with,

well you had less of the companies
competing with, with each other,

it still is a model approach to rapid

acquisition of data that drives decisions,
real time decisions.

I would I love to see us
stop having phase one, phase one A,

phase one B, phase two
A, phase two B phase three another.

Phase three. Phase four. Absolutely.

Because not only do
I think it takes way too long,

you don't get a lot of incremental
information over that time.

And you're describing the sort of gaps between. Yes.

So obviously you're not saying
we should not be doing clinical trials.

What you're saying is the gaps between our
our dead time, where we're doing

paperwork right, and stuff that we so
we saw a statistic,

that I just mentioned % of the time
from the initiation of phase one

until the FDA final NDA or BLA
application is dead time.

That is, there's no ongoing clinical trial
that's happening.

So it makes what you're describing,
makes all the sense in the world,

makes so much sense
that sometimes you wonder if

Why are we not doing it?

Well, I think it begs both, right? What?

Why why weren't you doing it
before? Right?

Why weren't we?

It's really a collective responsibility.

And if it's so intuitive

that it should have been done,
are we missing something along the way?

And I think you know

that it's going to be in the
in the pudding of how you actually do it.

And I also think that we don't actually
know what the right answer is.

You know what?

This is going to be very much
a learning process.

You know,
I don't even call it a pilot approach.

I think this is an iterative process
that as we go along,

we won't necessarily stop to say,
was that right or was that wrong?

We'll actually just keep keep
on reinventing as we go through the process.

You know, the irony is some US centers
refused to participate

in the Recovery trial
because it didn't meet their elaborate

study design, preconceived ideas,

but in the end,
maybe the intervention that saved

the most lives in 
was the use of steroids in the ICU early,

so notice I said to avoid the.

I know, I know, I was going 
to challenge your

I had a good idea to challenge
the Commissioner.

So, are we going to add something?

Jennifer.

Oh, I didn't know if I cut you off.

No, no that’s ok.

So, in

James Lind did
what may have been the first

clinical trial for scurvy. Yep.

And so do you want to tell this story?
I do.

I love the story.

She didn't know I was going to say it.

I might even actually challenge the date.

I think that was the date
that it was published.

I think you're right.

But the study was actually done earlier.

This is such a neat study. So,

it was conducted amongst

the British Navy and they, sent out,
they knew that

that seamen were dying,
but had no, no idea why.

So this particular physician decided
he would design the first ever

clinical trial.
He didn't know it was a clinical trial.

And he randomized sailors

to six different interventions.

Oh, I'm not going to remember all of them.

Vinegar.
Vinegar, salt water.

There was something.

Salt water.
I remember that it's disgusting.

And and then one was was citrus
fruits. And,

they demonstrated that, that citrus fruits

dramatically prevented
the onset of scurvy,

which was why the British Navy

then became known as

“limeys.”

Well, they refused.

The Navy refused for many years
to adopt the findings.

Yes they did.

You know, they did.

what you see happens today
in modern medicine.

And that is you have a very

powerful trial.

And people find a way to nitpick it
and ignore the results and write it off,

because they may not have liked
the person who did the trial.

But it was a classic example

of how the dogma that it couldn't
possibly be.

Right. Yeah.

And if you think about, history,

it it really,

there were over a million people
that died of scurvy.

I mean, it was and tragically,
it affected the African slaves

that came across.

They would lose half the crew,
half the individuals and passengers.

And ironically,
the cure was right in front of their eyes

but ignored for a long time.

So there was that publication in

Famous trial showing the polio

vaccine, helped eradicate polio.

And then today at the FDA,
the first real time clinical trial.

Thanks to all of you.

So it's a historic day.

In clinical trial history.
Happy to be a part of it.

What did you think
when you learned about this opportunity?

You know,

I think that one of

the worst things as, as an oncologist is
when, you know, you have a drug

that's showing promise,
you've given it to patients in their,

you know, phase one, and you have patients
who have no other options.

And, you know, this drug,
but it's in the dead time.

And it really matters.

And, and these patients are holding on.

They're waiting for us to right
the trials.

They're waiting for us
to activate the trials.

So every day
that we hold on, on activating a trial

or have it on hold to patient,
it matters to real people.

Yeah.

You think about some of these,
new drugs

that are getting approved every day
matters?

You know, we. Oh, yeah.

You've you've seen that both in that.

Yeah.
What's your clinical area, by the way?

Cardiology. 
Cardiology.

What's that, heart stuff?

Kinda. Okay. Yeah.

I think you're good.

Doesn't matter.

Doesn't matter.
Probably sits in the middle.

That's my kind of cardiologist
right there.

But, you know,
you think about people who are

when you break bad news

and you see people clamoring
for any kind of hope.

And sadly, I think we've all done this way
too many times.

And there's no textbook
that prepares you for it.

And it's always hard.
It never gets easier.

And you think about people
who are just asking the question, is there

anything humanly possible on earth
that can be done to live longer?

And you start asking these questions right
as somebody proximate to that

and you realize delays in this system?

Yeah. Have risks.

They have risks.

The risk is

it may prevent somebody or delay
somebody from getting a promising therapy.

Yeah, I think that's that's really real.

I'll give you two concrete examples.

First is baby KJ. Right.

Gene editing.

I worked very closely with that team
on getting that, submission

to to the FDA, and had the opportunity
to meet the family.

And they were holding on to threads.
That wasn't a clinical trial.

It was a single patient treatment use.

But that
desperation, you see all the time,

the second is,

that the way we write

clinical trials is overly cautious.

And I think this is in part
because what are the reporting criteria?

And so more often than not,
we have patients who don't meet

the eligibility criteria for trials,
but we can't write the next trial

until the data
from the first trial is in there.

And that is exceptionally common
that you have patients in clinic

and you really can't do anything for them

because we're just too inefficient.

in what we're doing,
and it's incredibly frustrating.

Yeah.

I think this is one of the

you know, I was having a conversation
and someone asked me like, what's the

what are you?

I would help summarize, right,
what you're trying to accomplish here.

And I said it's very simple. It's like

aggressive vision.

And we're going to iterate
the implementation.

Right. We're going to do fast
turns on this.

We've already actually done this,
you know, with the data with the initial

we we sent over our clinical trial
reporting scheme

that went out over to the sponsor.

Pass the pass to the pass to the vendor.

They were looking at it.

They came back with some additional things
that they wanted to add into.

It came back to us,
made the updates back to them.

We've done that like three times
in just a couple of weeks.

And so this idea of, of, you know,
and then and then they're saying,

hey, we think we want a new way
of analyzing this specific criteria.

And then the sponsor saying,
hey, maybe we can do this.

And the FDA is like, maybe we can do this.

So this is the pace and the sort of change
it gets everybody in the boat.

Yeah.

You know, not to be not to make a pun

on our previous conversation,
but it gets everybody in the boat, right.

You know, that you're all working for
the same objective is to get to an answer

as quickly as possible,
you know, and as safe.

Safe.

Safe and effective as possible, you know,
and that's what we're seeing is

we're seeing are we're seeing all the
all the different parties coming together.

Because it's can't be,

I think, to accelerate this to, to move it
at the pace that we needed to move it

for patients.

We can't all just sit back and just say,
well, it's not my

I'll wait for the other person
to come in and do their part.

I’ll wait for that other person to come in
and do their part, or we had to,

we had to mail it over
and, and, we're waiting on a response.

Right. Like that's a horrible thing
to say to patients. Right.

And so the
so I think everyone has sort of a

if you're in this space,
you have a moral obligation

to sort of come in and everyone work
together, try to get there as fast as possible.

It has to happen that way.

I call it poking the balloon.

Yeah.

That if you don't look back

and you're just I'm going to fix this
one spot at a time.

You've stuck your finger in the balloon,
but nothing changed.

Yeah, right.

And that happens all too often.

And this is why the FDA, academia,
our sponsors,

taking that ft view,
it's the only way it's going to work.

It is, it is.

And that's what

I've seen in the recently in this process
was that everybody came coming together.

You know, is
what's really sort of driving it like

like, and different people are coming up
with different ideas now.

And I think the goal now is there's

two parts I'd love to sort of see,
right from industry, from academia,

from all these sponsors to say, okay,
the FDA said we can move, right?

We have, it’s carte blanche.

Let's go.

Right. Like and not just
you talk about process improvement.

Not just on this the trial part. Right.

We touched on other areas of the process
as well. Right.

Where else can it.

Can you can you work with sponsors

and using different engaging mechanisms
to say this is taking too long.

How much time do you have?

Lots of ideas on that one.

Not only not only sponsors. 
Yes.

You mentioned earlier
the IND submission process.

Yes. Right.
Yes. There's and you know, I would make,

a point here

that I think you will always find academia
to be a willing partner, in part

because there's very much
a mutual benefit.

We are on the frontline
treating the patients.

And so there's this kind of added
incentive for us to do right by

the patient.

And that's not to say
that pharma isn't also motivated by good.

But if you're not actually
in the trenches.

So one thing that will drive
the ultimate success of this innovation

is that pharma really buys into it, right?

So when we submit INDs to the FDA, pharma
either submits them.

It's a classic industry
funded, industry sponsored trial,

which is big business,
really complicated, really difficult.

And then you have these really innovative
discoveries

that are done under Research INDs.

They still result in products.

Penn has of them. 
Yep.

And when we go through that process
our ability to partner with the FDA.

Life changing. 
Yes.

CAR T cell.  We couldn't have done that
if the FDA wasn't a partner.

CRISPR.

We couldn't have done it
if the FDA wasn't a partner.

So really making sure
that industry holds up its bet.

Academia holds up, but it really has to be
a sustained partnership to make it work.

Yeah.

What's interesting about the IND process,

because we've been deep in the IND phase
one world,

for the last year
and hopefully we'll have pretty soon

some pretty powerful announcements
to make about reforming that process,

because we're losing our competitive edge,
internationally.

And we've got to modernize and streamline
that process to focus on safety.

And we can focus on safety

and reduce a lot
of the onerous requirements or defer them.

And so we have a massive endeavor.

One thing that we've learned
is that sponsors will submit

a lot of information
that we don't need for the IND.

That is the stuff that they perceive

we want, but we don't want it,
or at least we don't want it

at that point.

We can look at it later
or we don't need it.

Along the lines of the million page,

application FDA had received.

But there's this arms race
where they perceive, hey,

let's just send everything,
every print out of every side

test and study. And,

sometimes we don't set clear

guidance on what we require
and don't require

or we say what we do require,

and then it's a gray area
and they're sort of doing guesswork.

Do we want this additional information?

So we have talked about making it
very clear on the FDA website

what you do not need to submit
for different stages for an IND

you do not need to submit X, Y, and Z.

And so maybe that explicit
it will help it.

It will absolutely help.

If you look at the difference
between an IND submitted by an academic

institution versus an IND submitted
by industry, they're night and day.

They’re night and day.

They go through
the same review process.

And it's like half of the INDs

are academic.

I would say. Something like that. 
Yes, yes.

Yeah.

So, you know,
if the FDA is willing to approve it

based on that volume of data,
there's definitely room for improvement there.

And look forward to that.

That's wonderful.
We've got to do it.

Absolutely. Yeah.

I think it gets to the point
where you mentioned like,

as opposed to poking a part of the balloon
is, you know,

there's been a big focus here
around the whole thing, right.

You know, when you think about it
from the pre IND to IND.

To now, what we announced
today was the real time trials. Yeah.

To the filing review. Right.

Which will get down to a day until it's almost there.
Instead of two months

instead of two months. Right.

It's like I mean, it made sense
when you had to bring in all the paper,

it all out, and.

Yeah, crates of paper before

have someone walk around with a checklist,
make sure you got everything

before you actually say
you're good to go on the review.

And then you actually look at that,
and then you think about the review

which is now done
in, you know, that demonstrated

through the Commissioner's, you know,
priority voucher program down to

days, days, less than days.

So you look at that. Right.

And it was I think the point is you
couldn't just focus on one thing, right.

And you had to look at the whole thing
right.

And it gets down to the process
improvement side.

It's like what what's been done?

And so we've been doing this
I think, and we've been

hitting each part of the process,
each part of this.

You know, I like it's like
for laying siege to it is the right term.

But it's been like something where you're
working on each part at the same time.

Right.

And I think what people are starting
to realize is that that was done

with purpose, with focus, with energy
to actually get to these outcomes,

which we're at today.

Right.

Jeremy, what's next for real time
clinical trials?

Sure, I think, you know, what's what's next
is, we're going to go from the what

we built was a proof of concept,

and we demonstrated that
this is entirely possible working life.

So now we want to scale that. Right.

So that goes from a proof of concept into
sort of what we'll call a pilot program.

You know, we had the RFI announced today.

So that's so we're looking forward to sort
of industries feedback around, around,

you know, everything that's going
to be involved and what they want to.

And, you know, just in general
what their thoughts are.

Right.

You know, so we look forward
to receiving all those responses.

Then from there will, launch
sort of the pilot program.

Not going to sort of
say that's the final selection.

I think we're we're teetering between,
you know, ten and

sort of trials that we're looking for,

but that'll come out in the final sort
of pilot announcement.

And the goal
there is to look and we're we're focused.

I think our initial thinking
is to focus in on those early phases,

those phase ones, those early,
you know, those early phase twos.

What can we do to sort of
get that information over in real time,

get to our reviewers so that they can make
a regulatory decision,

that they can help say,
we can move this forward, or, you know,

this has got some concerns and we need to
have a, you know, a deeper look at that.

I think that's where we go
next as we go into the, the

and then from from there, it's,

you know, take the successes of that
and to your point iterate.

Just keep iterating it until we get it
refine and good.

And then it becomes
an operational capability.

So one suggestion. Yes.

Include 
or academic INDs in your group of nine.

It's already been suggested.

Yeah.

Surprise, surprise.

Yes I yeah.

And we have a menu for you.

We Yeah

I think we are
we are excited about about this.

You know I the biggest thing of my concern
is can we scale it get like.

Is the can we,
can we move as fast as we want to move?

Right?

I think that the, the desire to move
faster is now

now that you've,
we've shown it's possible. Right.

I think the, the question is, how do we
how do we institutionalize that

and how do we make it part of the process.

Yeah.

So willing industry
partnership is is is essential.

Yeah. You get or on board.

They're quite competitive amongst
each other.

The the onus, what's bring the other.
I have no idea what you're.

Yeah I mean I never heard of it like.
No no.

So if you're out there in the world
listening

right now you're probably saying
what a beautiful campus.

And I would love to come work at the FDA.

And the good news is
we are hiring thousands of scientists.

So, good observation. Number two.

You're probably saying
I can't wait to get to

the RFI
and read it and provide public comment.

Thank you very much.

And number three, you might be saying,

how do I participate in a real time
clinical trial.

And that's coming.
That'll be in the formal pilot. Yep.

After we get through this proof of concept
phase this summer. Yep.

Is that the plan this summer?

Yeah, I think I think end of,

end of spring, early
summer would be kind of our goal after

the public comment period, you know, so

we want input along the entire process
and we want it from everybody.

Yeah. And so, so that's good. So,

it seems like

this is a first step
towards continuous trials, towards

bigger things, towards
reducing what we call the white space.

That is the time between clinical trials

where % of the time

in a drug development is now white space.

But this is not the silver bullet
that the real time trial.

This is a step towards bigger thinking,
but hopefully it is letting people know

and it's sending a signal
that we are willing to be as creative

as we can be while ensuring public safety.

Yeah.

So, that's why your perspectives

are so valuable in this process. Yeah.

I love the concept of partnership.

I mean, I really it feels different,
you know,

feels like we can do
and it's it's not just this piece, right?

It's applying data science tools to real

world evidence, synthetic data,

how we collect data
in trial from wearables.

You know, there's

there's lots of reform that can happen
throughout the entire process.

So it's exciting because you kind of feel
if you have a win in one corner,

you got to move down the pike.

And it's accepting trials.

You know, we can't do the trials of 
anymore over and over and over again.

And we have, you know, for the first time

in my career, really,
I have patients where the

the new drugs are outpacing
their metastatic disease. Wow.

You know, when I think of these patients
with HERpositive or hormone

receptor positive and now even triple
negative breast cancer,

you know, it's happening so fast
and it's happening so fast

that even when you do a phase
three randomized clinical trial,

the comparator arm is out of date
by the time

you even start
putting those patients on the trial.

So we're now thinking, how are we going
to rethink how we do trials?

I have now three drugs
that dropped in the exact same spot,

and I don't know
what's the best for my patient.

We're going to have to rethink
how we do trials, how we get quick,

you know, kill bad drugs quickly
and move on to the next one.

And I think just even just like the trial
you were talking about,

we have to start thinking
outside of the box and get answers faster.

Yeah I agree.
Did you have,

experience with people enrolling
in the real time

clinical trial to be able to say
that this got them energized.

They were all excited.

They were interested?

Or was this something that was,

at a clinical level
where you weren't directly

part of the consent
and didn't have that feedback?

So the trial we did at MD
Anderson was in a different disease.

All right.

So I did not personally do it.

It was in lymphoma.

Michael Wong,

has led it
and he's been doing an amazing job.

Okay.

I can tell you from the experience
for the AstraZeneca, mental

cell lymphoma trial,

there's a learning curve.

It's not naturally intuitive.

And and so taking the time to train

the people in the trenches as to how
you actually make the connection,

the technologies are both excellent,
but you've got to create the APIs between,

clinical pipe and

the EHR,
and then you've got to train the staff on.

So there's, there's

bits in there
that there will be a learning curve.

Change management.

Yeah. Yeah. For sure.

The one thing I will say is

in our conversations with the team,
the PI was totally on the physician,

totally on board

anything that could keep their CRC
in their row for a month longer.

The the CRC and the project managers
and the regulatory

people are anything that changes
how we currently do it.

We're willing to try. Okay, great.

So I really when I say
the proof is in the pudding,

we just need a little bit more experience.

And there will be

there will be bugs in the process
and trying to to get it executed.

But the, the willingness and

the enthusiasm to do things differently
is there the timing couldn't be better.

Yeah. That's why a strong. Yeah,
yeah, yeah.

I think that the great thing is that
the technology components are all there

now, right?
I don't know if they were there.

You know, like they weren't all there
ten years ago.

Or they they were not there. Yeah.

They weren't there
ten years. There were pieces. Right.

But like now it's
there is no technical limitation.

There's no reason that
this cannot be done, that we cannot scale,

the analysis of data, you know, onsite,
you know, with base with what?

With the, the criteria that the FDA says
we need to hear about.

Right.

There's no way that that can't
there's no reason that this can't be done.

And so and so I think from a from a,

this one, the real time complexity is as
much a process as much a process change.

Right.

You know, but it's, it's we're saying
we're going to move out,

you know, we want to move
at an exceptional speed here.

We want to where we're going to leverage
the latest technologies to do it.

There's no technical limitation.

So let's clean up the process and let's
and let's and let's fix that.

And there's an access issue

whereby you can actually expand access

to clinical trials in this program
as you were mentioning earlier.

Yeah.

I mean explain the rationale.

Well, I think there's a there's so there's
number one, there's the speed issue.

So being able to get more people on
if you can run more of a continuous trial.

Right. So there's access there.

There's you know, the amazing work
that's done at the medical centers

that the, both are part of.

But there's also expanding things out
into the community in rural settings to.

Yeah,
you know, where there's there's a need.

You know, I think the numbers are like %
of most people

live within about two hours of a,
of a, of a medical center.

Right,
so that you can cover a large portion.

But that's that's %
that isn't covered by that.

Right.

So, you know,
looking at technical solutions

that you can still onboard people
into within rural settings,

you know, where they don't have
that immediate access, getting, getting,

you know, industry to be able to sort of
collect the real time data

that's happening in those
in those more rural and rural environments

that that that opens up a huge portion of.

Yeah.

I don't think it's just related
to this technology.

Yeah.

The one thing that Covid showed us
when we had to shut down everything

we continued to do research remotely.

Yeah.

And that and, you know, the regulations
were all modified to allow that to happen.

Now they've

kind of crept back in there a little bit,
but I know they will be changed back.

But the ability to leverage telehealth
for research purposes is enormous.

And we should be doing that
all over the place.

The ability to to ship medication across
state lines, that should be easy.

Yes. Currently isn't, our ability to take
blood pressure recordings off, you know,

your ring or your, your Apple Watch
and to incorporate that data into the EHR.

That's technologically possible. Yes.

We just don't incorporate it.

So there's there's so many technology
solutions that we need

a concentrated commitment
on the part of the regulator

accepting that data,
the pharmaceutical company

agreeing to that change
because that's a big culture.

And then academia making it happen.

You know,
we implement what pharma wants us to do.

I think from,

that blood pressure one is interesting.

One, if you've got someone
in a remote setting

and you can stream their blood pressure
information back to you, right?

You know, under this, under the real time
clinical trial approach,

as long as you're analyzing that data.

Yeah.

You know, you can said send a signal on me

if you're seeing blood pressure, you know,
that's

that's part of the reporting criteria
for that specific, you know, trial.

You could send that signal to me,
but I don't really need to see the data.

Right.

So like the idea that you have to collect
and process and manage

all that data is not necessarily
a requirement

of what we're thinking about
from the real time clinical trial aspect.

So so there's an aspect too of like
normally you'd have to get all that data

to get all that real world evidence data,
and then eventually

trying to try to stream
that or get submit that to the FDA.

But we it then receive that.

Yeah. It's not.
Makes sense.

It's the goal is to sort of
say is to it's to say

if we trust that you're
analyzing the data correctly, right.

You can get a stream as much information.

You just tell us what you're
what you're using as that.

And you can send us
and you send us a signal,

you know,
but it kind of changes the, the focus.

And it like puts the innovation piece
back into your lane, right?

And back into you,
back into your side to say,

I can collect and grab as much information
as, as I want as part of this trial,

and I don't

if I don't have to end up collecting
all that and providing it to the FDA.

You know, what does that mean
to my to my, to how quickly I can.

It reduces the mindless collection of data
for an unknown purpose.

And you're or page.

Pages, million.

There, you know, million.

I just can't imagine even read.

I mean. Most here, like no Crazy.

Time of a patient to,
you know, there's, you know,

why do we need this many EKGs
in this time?

That's it.

That's a huge.

I've never seen anyone make a major change
based on

these, you know, eight time points
within the same day,

and the patient's
running up and down, and,

and I think that, you know,
your guidance on decentralized trials

have been really helpful
as we really think through hard

IRB questions of who really needs
to be on the too.

No, you can see your regular doctor
near your home who does a history

and physical
as part of their routine scope of care.

And we can ask these questions
and have not made people come out of work,

you know, three
times a week when they don't need to.

And I think even that and if we it
the proof will be in the pudding again

is that getting drugs to the endpoint
by using those trial structures?

I think once we get our first one there,
it will be a floodgate

and it'll be the best thing
for patients, right?

There they go.

Making sense again,

way too logical.

Okay, final question.

How is the food at your hospitals?

You serving ultra processed food
or real food?

Yeah. Real food.

Yeah. Interestingly enough.

So so, you know,
Penn is one of those campuses

that that just keeps on building, right?
They have buildings.

So as long as you go to the newest
building, you get the healthy choices.

If you go to the old building,
bangers and mash here we

but the, the newer buildings.

Yeah, it's, it's it's good.

And I think it's, a strategic investment
in healthy living

that the food is, is

I, I'm going to say
by reputation is really good.

I've never eaten at work,
so I can't really tell you.

Are you. NPO all day. Or.

Pretty much. Yeah. Yeah.

How about an MD Anderson?

Not NPO. Okay.

You know,
I think that there's been a very active

move to move into,
you know, healthier eating.

They've changed
many of our cafeteria choices.

We now have healthy options in vending
machines that are in every building.

So, you know, so at any point of the day,
you can go and get a healthy salad or,

and not have to go and say, what,
you okay?

Not just,
ding dongs without. Not ding. Ding.

Hard. Yes.

That's important.

It's a big initiative.

In this, you know, it is a big
it is a big initiative.

And I would say it's actually a big area
of scientific study at Penn.

Is is the whole thing around healthy food
choices and advertising, advertising

and how we,
we actually play an incredibly important

role in
how we portray the foods that we eat.

And so yeah, no, it's.

Yeah, we've seen the work of, Kevin Volpp.

Yeah. Yeah.

So we're eager to see some of that,
trial data readout.

Yeah. There's, there's
there's more coming. Coming. Right.

It's a it's a really neat study,
which is a perfect example

of what you're trying to use.

So he uses
this platform called Way to Health,

that they built at Penn
and that they use it to collect

food inventories of patients
living throughout the

the urban areas, which cover
very large sociodemographic groups and,

cardiovascular

outcomes, obesity
outcomes and diabetes outcomes.

A real time food trial, real. Time.

So trial. Right. Yeah. Great. Yeah.

But prospective I'm not sure
I call it a trial because no intervention.

Single arm. Single arm, observational.

So real real time real time real time.

Yeah.

But it's real because we are seeing
you know, we are definitely seeing younger

onsets of cancer.

And we think that's related to a lot
of these issues and the processed foods.

But we are really spending a lot
we’re spending...

So we're spending a lot of time digging

into where we shouldn't
because we're deep into the microbiome.

And, that is, you know,
we are just finding out so much there

and how it affects your immune system
and fighting cancer, how different drugs

work differently based on
what's in your GI system.

And it all comes back to the same thing.

So you are what you eat.

Something you wrote a lot of a lot of.

I thought we
were wrapping it up.

This is good stuff.

And this microbiome is, in my opinion,
the great frontier organ system

in the body that we know the least about,
that we should know more about.

And when you look at, increasing rates

of GI malignancies in people under age 
and that plus liver cancer,

which, you know, you could argue liver
as part of the GI tract.

Those are the cancers increasing
as the other cancers are decreasing.

Generally speaking,

how could it not have something
to do with the interface

of what's directly
proximate to the GI tract?

And when you look at some of these
intriguing studies that are observational

and you know,
you cannot derive sweeping conclusions,

but in, in JAMA Surgery,

a study looking at the association

between colon cancer
in young people and C-section delivery.

What do we know about C-section delivery?

You have a different microbiome
by C-section delivery.

Now, C-sections save lives, and sometimes
you need to have a C-section.

But these these are
these are sort of big questions

where now the door is opening
and we're starting to realize

there's a lot there
that we don't know that we should know.

Yeah. It's good.

Yeah. Or work for the scientists.

More work for your researchers
and more grants. So,

yeah.

Thank you for being here.
Pleasure.

Historic day at the FDA.

And it's an honor
to share it with both of you. So.

So as well.
Thank you. Thank you, thank you.

All right, guys, good to be with you.
We'll do it again. Thanks.