Excerpted from Transcript provided by

**NEAL R. GROSS**

COURT REPORTERS AND TRANSCRIBERS

1323 RHODE ISLAND AVE., N.W.

\(202\) 234-4433 WASHINGTON, D.C. 20005-3701 www.nealrgross.com

"*The difficulty of simulating clinical conditions in pre-clinical
testing*"

# By Thomas Fogarty, MD

DR. FOGARTY: Okay. I\'ll stand here. Not too close, because she may hit
me. No, I don\'t know what this slide is doing here. Actually, Rod White
gave it to me just before I came in here, and said, show this slide and
guess who it is. And I know you all think it\'s Juan Parodi. But
actually it isn\'t. It\'s Dorothy Abel just before she started at the
FDA.

Actually, the reason I show this slide is that \-- The reason I show
this slide, you know, technology testing is a little bit like wine
testing or tasting. If you taste it before it\'s mature, you\'re going
to get a very different perception.

I think the technology that we test also has to reach a certain state of
maturity before we can figure out proper testing. I think we are getting
close or closer to maturity. You never get there with a technology, but
somewhere along the line you have to start thinking about testing that
relate to clinical implications.

I think this meeting is about that. So it does have some significance to
this meeting. I\'m sure, as these devices mature, we are going to better
define the tests relative to predictability of failure modes and what
kind of failure modes. But we are kind of struggling, because we are not
mature.

Now the other thing, in hearing what we\'ve been talking about, really
we are talking about failures and how to test to prevent those failures.
If you look at the evolution of most devices, we do some testing before
they actually reach the clinical state, but after they reach the
clinical state, we identify failures. Then we try to figure out what we
have to do to prevent those failures.

So I want to kind of categorize, you know, what\'s fails? Not only
what\'s fails but from whose perspective is there a failure? We all talk
about the perspective. It could be a company perspective. It could be a
physician\'s perspective. It could be a perspective from the FDA, but we
rarely talk about the perspective of a patient, and I do want to kind of
just remember that that is the ultimate perspective that counts.

The reason I bring that up is a real life experience. Actually, the
second case that we enrolled at Medtronic, Rod and I did. It was in a
clinical protocol, and it failed. It\'s failed from my perspective,
Rod\'s perspective, the hospital\'s perspective, the company\'s
perspective, and the FDA\'s perspective. But from the patient\'s
perspective, it did fail.

What happened was we put the device in, got it properly located. We
couldn\'t deploy it. So we took it out. The patient woke up, and Rod
said, you know, we can do a standard repair or we can delay this and do
what we intended to do. And guess what? The patient said, well, I\'m
going to wait.

So he was our fourth case, and everything went well, and Rod just gave
me the slide five years later, and everything is fine. So from his
perspective, that was not a failure. He ultimately got what he wanted.
The timing perhaps was off, but he got what he wanted, and he did suffer
a little bit. He got two anesthesias instead of one.

So I think when we talk about failures, we also got to think and start
thinking more often in terms of the patient\'s perspective as to what
constitutes a failure, and it may not be consistent with any of us in
this room.

So if you look at what fails, you can have a procedure fail. What I mean
by that, the concept of aneurysm repair is a procedure, whether you do
it by an endovascular technique or whether you do it by it open.

If that doesn\'t work, for whatever reason, that\'s a procedural
failure. So you\'re going to have a procedure failure, and it\'s going
to be for another reason.

It could be related to technique. It could be related to case selection.
It could be related to the inability of a team or the institution to
implement something, and that\'s a much more common reason for failure
than a lot of us would be willing to accept.

There are certain technologies that does require a coordination of
different skill sets. If you don\'t put them together, you are going to
end up with a failure, but the failure is in implementation.

The one that we should be focusing on, I think, in the purview of the
FDA and others is device failure, because that is something that we can
more easily address. A lot of these others are difficult, and we can\'t
regulate a lot of these things, but we can provide direction relative to
device failures, and we can engage in analysis of failures.

The other is that we could have image interpretation failures, and we
talked about that a little bit, but that failure is related to none of
these things other than our inability to interpret an image.

You know, if you think you are placing it right below the renals but you
don\'t get the right angle on the tube, which is kind of minutiae but
critically important, that thing could be two or three centimeters below
where you want it. For some of us, it wasn\'t immediately obvious that
that was a failure in image interpretation.

The other is you can have a failure in case anywhere along the line,
preoperative care, intraprocedural care and post-operative care, and one
that I don\'t hear commonly, somebody forgot to heparinize.

Well, you know, it\'s a global breakdown in the care, and it doesn\'t
relate to anything but care. You know, whose fault is it? You know,
it\'s ultimately the surgeon, but somehow the patient didn\'t get
heparin when they were supposed to.

So when we look at failures, we ought to try to break it down more
discretely. Now the complex thing about this, these can be interrelated.
So you know, one can lead to another, and it gets real complex. But
usually you are able to identify what fails, at least relative to the
device, and you may also identify failures in other areas.

The one I didn\'t mention is a failure in manufacturing, but as we all
know, companies never have that failure. But what we do know, I think,
we should reflect on.

You know, we do know that stents fracture. We know that sutures break
and create bigger holes. We know that fabric does wear, and we also know
that any or all of the above can cause device failure, and sometimes
lead to procedure failure.

So those are kind of the basic things we know, and I\'m sure we know
some other things, but these are, I think, the critical elements of what
we currently know at the present time.

Now what we don\'t know \-- There\'s a whole bunch of things we don\'t
know. It\'s very important to know what you don\'t know, but
unfortunately, you don\'t know what you don\'t know, because you don\'t
know it. But if we always knew what we didn\'t know, somehow we would
gain that knowledge.

You know, you can plan and plan and plan, but it\'s always the thing
that you didn\'t anticipate that usually gets you. So that means we
didn\'t know something, and we didn\'t realize we didn\'t know it, but
that is the way it goes.

There are a lot of things that we do not know, and I think we know some
of it, but we don\'t know all of it. I think it serves us well to
acknowledge that we know some components but not all.

You know, we don\'t certainly know all the physical parameters that we
should know. There\'s probably one area we know a fair amount about. The
biologic interface, we know very little about, and I think that\'s an
important element that we have to learn more about. But I don\'t know
quite how to do it.

I mean, I\'m sure there are techniques of identifying this, but what we
are trying to do is relatively complex, particularly because, if you
consider the biologic interface on Day One is going to be very different
than the biologic interface at three to five years, and is that
important or not important? It probably is, but I don\'t know.

Electrical mechanical issues we know a little bit about, but we probably
know more about that relative to bench testing than anything else.

The healing response, which is critical in the performance of these
devices \-- we do know that all people don\'t heal the same. Therefore,
some people are going to heal better, some less well. That will probably
influence performance parameters, particularly longitudinally.

Reconfiguration: We\'re trying to know something about it. We got a lot
to learn. The fact is not all aneurysms reconfigure. Some do, to a
certain extent in adverse ways. Some do in positive ways. And which ones
are going to do what, I think we got a lot to learn about.

Now the kind of testing that one does \-- I just want to reflect a
little bit, because I think we sometimes get confused what we can really
test.

Toxicity testing is probably one of the easiest and the one that has a
format that everybody is familiar with. Guess what? Because it\'s been
around forever. So that\'s something that, you know, probably is mostly
a nonissue except perhaps when it comes to new materials.

Some of the tests that could apply, particularly, to antigenicity are
relatively new. So we are using new tests in the environment of a new
material, and that sometimes leads to a lot of misinformation. But
toxicity testing is pretty well figured out.

Fatigue testing: I think the content of the meeting indicates we don\'t
know as much as we should about fatigue testing in the environment that
we are using these materials, and we got to learn more about that.

We talked a little bit about computer 3-D modeling by various
techniques. Certainly, I think, at least as I reflect on my own
experience, that\'s something I know so little about that I\'m not sure
I as an individual could contribute. But I\'m certain there are people
around that can, and probably we haven\'t taken optimal advantage of it.

You know, modeling without bench testing is another, and you can do that
with computer modeling. You can do actually physical modeling. Both will
teach you a lot. There\'s not \-- They should be used in parallel, not
to the exclusion of one another.

Bench testing, I think everybody acknowledges, is something that should
be done, but what we should do, we\'re struggling with.

Animals: They certainly are important. I think the preferred animal is
an attorney. But they do teach us something. If they don\'t teach us
anything about the device, they teach us about technique. So we learn
technique which prepares us for the first clinical implant, which I
think I really very, very important and should not be ignored.

Cadaver testing: Unfortunately \-- and I didn\'t realize this, but \-- I
did realize it, but I didn\'t realize the significance of it. You know,
actually, cadavers and autopsies in the United States are at an all-time
low. The reason: Nobody pays for it.

So if you get an autopsy, unless it\'s dictated by a coroner, cadavers
are extremely difficult to get hold of. We have a stand-in-line at
Stanford to get hold of cadavers. Actually, they have to import them.
They are extremely difficult. Actually, you can learn an awful lot.

Some of the extraction tests that we did originally with stent grafts
were all done in cadavers. In other words, what forces do you need to
dislocate something? It\'s a number that we were trying to get hold of,
and it actually ended up being much more complex, but at least it gave
us a rough parameter of what we had to deal with in the design.

Then we have human testing. By the time you get through this, you hope
that at the time you are doing your human investigational studies that
you\'ve figured much of it so that adverse events are reduced to a
minimum.

I think that really is the way testing goes. Now would we prefer to
eliminate all potential inappropriate outcomes by testing? The answer is
yes. But it\'s sometimes not achievable.

So when I look at pre-clinical tests, the fact is, no matter how hard we
try, they don\'t always simulate clinical reality. Then you ask, you
know, are we testing the tests, and does it mean anything? I think that
subject has been kind of brought up.

In this environment, it used to be \-- and when you went to the FDA,
that you didn\'t suggest alternative tests. The reason is they would
have you test the test, and to test the test could take an inordinate
amount of time. So that you really ended up wasting time on testing
multiple tests.

You know, that was the environment about ten years ago or 15 years ago.
That\'s changed. So they are beginning to understand that we don\'t
really know how to test, but we at least got to discuss it an come to
some conclusion. Whether you agree or not, you come to some conclusion.

So I think whatever we figure out relative to tests, we ought to say is
this going to really mean anything relative to clinical outcomes. It\'s
critically important. It\'s one thing to have a bunch of interesting
scientific pursuits, but when we are testing relative to safety and
efficacy, we ought to be thinking is this going to have clinical
utility, you know, not in terms of science.

We may use a scientific method to get to document clinical utility, and
we do, but it\'s really not science in its pure form. It\'s essentially
trying to document clinical utility by using appropriate scientific
approaches when they are appropriate.

Now preclinical tests do not always simulate clinical reality. I\'m not
going to spend any time with this, other than to say it is impossible to
recreate or anticipate every anatomy or pathology. You can probably get
to a spectrum of it, but you are not going to anticipate every one of
them.

Now pre-clinical tests, particularly in animal models, and for a lot of
reasons, don\'t always simulate the human. There\'s all kinds of
differences, postural differences, size differences, arterial wall
differences, and we\'ve all discussed those. But they still have utility
in giving you some basic information, particularly relative to
technique.

The other considerations, you know, once again we\'ve gone through, but
the one I do want to talk about at the bottom is individual parameter
testing.

If you have a device that meets a certain performance parameter, you got
to test for it, and nobody may know exactly how to do that, but at least
you have to make an effort to test for that parameter and document its
performance within that parameter.

So I think that is important. That\'s why at this stage it may be
difficult to come up with many, many standardized tests, because the
characteristics of the implant are not going to be the same relative to
performance parameters.

Now this is my engineering side. For me, it\'s easy to hold to this
premise. But when I\'m surrounded by a bunch of bright people, you know,
I sit back and I say, you know, do I or my clinical colleagues
understand this? And when they don\'t because it doesn\'t relate to
clinical utility, I always come up, let\'s keep it simple.

It is important, I think, when we are testing to try to simplify it. If
it gets too complex, and Hugh made this statement \-- if it\'s too
simple and too complex, you know, then it has no utility for anybody.
But keeping it simple is a better way to go.

Now Megan Moynahan will understand this. But I think it is true. You\'ve
got to start with a device that has rationale, and you\'ve got to start
with a device that can be tested in some rational way.

You know, if you start with something that really doesn\'t make sense,
either from a testing standpoint or from a device standpoint, really you
are not going to go anywhere.

The question is how do you do that? Well, essentially you look at
performance parameters in a clinical perspective. So you know, it\'s the
difference between research \-- They all talk about bench-to-bedside.
Most clinicians I know don\'t go bench-to-bedside. They go
bedside-to-bench.

They identify things that can be done better in their clinical practice
or they identify things that they do in their clinical practice that are
not optimal. Then they go to the bench and try to optimize them through
a scientific approach that leads to clinical utility.

So if you start with an inappropriate premise that has no clinical
applications, you really aren\'t going to end up with something that has
clinical utility, which is what this is all about, at least in this
environment.

There are certain facts of life, and this is kind the conclusion. One
is: The human body fails. Technology and devices fail. No amount of
money will change either one of those, and we ought to spend reasonable
efforts to alter what is alterable.

So with that, I guess we\'ll sit down and shut up.

(Applause.)

MS. ABEL: Thank you. I haven\'t had to do any counter \-- what do you
call it when you are in a debate? Point, counterpoint. Okay.

First of all, everyone knows that the picture in the slide was actually
Tom in preparation for an FDA meeting. Second, I knew that we used the
Europeans for initial clinical studies. I didn\'t know we imported them
for our cadaver studies.

Then the other thing: You forgot the quote, you can\'t make a baby in a
month by getting nine women pregnant. I think that that applies to your
talk also.

Those are the three things I just had to get out of my system. Very
inspirational.

DR. FOGARTY: Particularly the nine babies.