FOOD AND DRUG ADMINISTRATION

CENTER FOR DRUG EVALUATION AND RESEARCH

NINETY-NINTH MEETING OF THE

CARDIOVASCULAR AND RENAL DRUG ADVISORY COMMITTEE

8:08 a.m.

Thursday, May 29, 2003

Holiday Inn - Silver Spring

8777 Georgia Avenue

Silver Spring, Maryland

ATTENDEES

COMMITTEE MEMBERS:

JEFFREY BORER, M.D., Chairman

Director, Division of Pathophysiology

Weill Medical College

Cornell University

525 East 68th Street, Room F467

New York, New York 10021

JAYNE E. PETERSON, R.PH., J.D., Acting Executive Secretary

Advisors and Consultants Staff

Center for Drug Evaluation and Research

Food and Drug Administration

5630 Fishers Lane, Room 1093

Rockville, Maryland 20857

PAUL ARMSTRONG, M.D.

Professor, Department of Medicine

University of Alberta

251 Medical Science Building

Edmonton, Alberta, Canada T6C37

MICHAEL F. ARTMAN, M.D.

Professor of Pediatrics

Pediatric Cardiology

New York University Medical Center

530 First Avenue, FPO Suite 9-V

New York, New York 10016

BLASE A. CARABELLO, M.D.

Professor of Medicine

Houston Veterans Affairs Medical Center

Medical Service (111)

2002 Holcombe Boulevard

Houston, Texas 77030

SUSANNA L. CUNNINGHAM, PH.D.

Consumer Representative

Professor, Department of Biobehavioral Nursing

School of Nursing, Box 357266

Seattle, Washington 98195-7266

ATTENDEES (Continued)

COMMITTEE MEMBERS: (Continued)

THOMAS FLEMING, PH.D.

Professor and Chair

Department of Biostatistics

University of Washington

Box 357232

Seattle, Washington 98195-7232

ALAN T. HIRSCH, M.D.

Associate Professor of Medicine and Radiology

Minnesota Vascular Diseases Center

University of Minnesota Medical School

420 Delaware Street SE, Box 508 FUMC

Minneapolis, Minnesota 55455

JOANN LINDENFELD, M.D.

Professor of Medicine

Division of Cardiology

University of Colorado Health Science Center

4200 East Ninth Avenue, B-130

Denver, Colorado 80262

BEVERLY H. LORELL, M.D.

Professor of Medicine

Cardiovascular Division

Beth Israel Deaconess Medical Center

330 Brookline Avenue

Boston, Massachusetts 02215

STEVEN NISSEN, M.D., F.A.C.C.

Vice Chairman, Department of Cardiology

Professor of Medicine

Ohio State University

The Cleveland Clinic Foundation

9500 Euclid Avenue, F15

Cleveland, Ohio 44195

THOMAS G. PICKERING, M.D., D.PHIL.

Professor of Medicine

Director, Integrative and Behavioral

Cardiology Program

Cardiovascular Institute

Mount Sinai Medical Center

50 East 98th Street

New York, New York, 10029

ATTENDEES (Continued)

SPECIAL GOVERNMENT EMPLOYEE CONSULTANTS: (Voting)

JEAN T. BARBEY, M.D.

Assistant Professor

Medicine and Pharmacology

Acting Director, Division of Clinical Pharmacology

Georgetown University

3900 Reservoir Road

Washington, D.C. 20007

L. GAY BERNITSKY, M.D.

Urology Network of New Mexico, LLC

5501 Jefferson NE, Suite 700

Albuquerque, New Mexico 87109

PHILIP HANNO, M.D.

Division of Urology

Hospital of the University of Pennsylvania

Medical Director

Department of Clinical Effectiveness and Quality

Improvement

University of Pennsylvania Health System

Philadelphia, Pennsylvania

PETER KOWEY, M.D.

Professor of Medicine, Jefferson Medical College

Chief of Cardiology

Lankenau Hospital and Main Line Health System

Lankenau Medical Office Building

100 Lancaster Avenue, Suite 556

Wynnewood, Pennsylvania 19096

EDWARD L.C. PRITCHETT, M.D. (participating by telephone)

Consulting Professor of Medicine

Divisions of Cardiology and Clinical Pharmacology

Duke University Medical Center

P.O. Box 2785

Durham, North Carolina 27715

ATTENDEES (Continued)

SPECIAL GOVERNMENT EMPLOYEE CONSULTANT: (Non-voting)

DAN M. RODEN, M.D.

Professor of Medicine and Pharmacology

Chief, Division of Clinical Pharmacology

Division of Clinical Pharmacology

Vanderbilt University School of Medicine

Nashville, Tennessee

ACTING INDUSTRY REPRESENTATIVE: (Non-voting)

JOHN NEYLAN, M.D.

Vice President, Clinical Research and Development

Wyeth Research

500 Ariola Road

Collegeville, Pennsylvania 19426

FOOD AND DRUG ADMINISTRATION STAFF:

GEORGE BENSON, M.D.

DONNA GRIEBEL, M.D.

VENKAT JARUGULA, PH.D.

LESLIE KENNA, PH.D.

DOUGLAS THROCKMORTON, M.D.

MARCEA WHITAKER, M.D.

REPRESENTATIVES ON BEHALF OF SANOFI-SYNTHELABO:

SYLVAIN DURRELMAN, PH.D.

PIERRE MAISON-BLANCHE, M.D.

JIM OPPERMANN, PH.D.

CLAUS ROEHRBORN, M.D.

JEREMY RUSKIN, M.D.

DOMINIQUE SALLIERE, M.D.

JON VILLAUME, PH.D.

WOJCIECH ZAREBA, M.D., PH.D.

ATTENDEES (Continued)

REPRESENTATIVES ON BEHALF OF BAYER PHARMACEUTICALS:

JOHN CAMM, M.D.

BOB CLARK

GERALD FAICH, M.D.

PAUL MacCARTHY, M.D.

JOEL MORGANROTH, M.D.

DR. P. SUNDARESAN

MARY TAYLOR, M.P.H.

THOMAS SEGERSON, M.D.

UDHO THADANI, M.D.

ALSO PRESENT:

CULLEY CARSON, M.D.

RODNEY FALK, M.D.

KATHERINE McCOMAS, PH.D.

WILLIAM SHELL, M.D.

MICHAEL SWEENEY, M.D.

C O N T E N T S

QT PROLONGATION ISSUES ASSOCIATED WITH TWO NEW DRUG APPLICATIONS: NDA
21-287, ALFUZOSIN HCl, SANOFI-SYNTHELABO INC., FOR THE PROPOSED
INDICATION OF TREATMENT OF THE SIGNS AND SYMPTOMS OF BENIGN PROSTATIC
HYPERPLASIA; AND NDA 21-400, LEVITRA, VARDENAFIL HCl, BAYER
PHARMACEUTICALS CORPORATION, PROPOSED FOR THE INDICATION OF TREATMENT OF
ERECTILE DYSFUNCTION

\* \* \*

AGENDA ITEM PAGE

CONFLICT OF INTEREST STATEMENT

By Ms. Jayne Peterson 12

FDA PRESENTATION

By Dr. Douglas Throckmorton 19

SANOFI-SYNTHELABO PRESENTATION:

Background - by Dr. Jon Villaume 21

Pharmacokinetics - by Dr. Jim Oppermann 27

ECG Studies - by Dr. Wojciech Zareba 39

Conclusions - by Dr. Jeremy Ruskin 98

BAYER PHARMACEUTICALS PRESENTATION:

Introduction - by Ms. Mary Taylor 113

Assessment of the QT/QTc Effect

of Vardenafil - by Dr. Thomas Segerson 116

QT/QTc Study Design, Heart Rate Correction

and Risk of Cardiac Arrhythmia -

by Dr. Joel Morganroth 151

OPEN PUBLIC HEARING

by Dr. Culley Carson 182

by Dr. Michael Sweeney 186

by Dr. Rodney Falk 195

C O N T E N T S (Continued)

FDA PRESENTATION:

Introduction - by Dr. Donna Griebel 199

Effect of Alfuzosin on QT Interval -

by Dr. Venkat Jarugula 200

Effect of Vardenafil on QT Interval -

by Dr. Leslie Kenna 204

Safety Summary and Summary of Review Issues -

by Dr. Donna Griebel 208

COMMITTEE DISCUSSION AND RESPONSE TO FDA QUESTIONS 261

P R O C E E D I N G S

(8:08 p.m.)

DR. BORER: Welcome to the 99th meeting of the Cardiovascular and Renal
Drugs Advisory Committee of the U.S. FDA.

We\'ll begin the meeting which will deal with issues relating to QT
prolongation on the electrocardiogram by drugs that are not
antiarrhythmic drugs.

We have a number of special government employees sitting ad hoc on the
committee today because of the nature of the drugs we\'re going to be
talking about and the problems we\'re going to be discussing. So I\'d
like to begin by having everybody at the table introduce him or herself.
John, why don\'t you begin.

DR. NEYLAN: I\'m John Neylan. I\'m Vice President of Clinical Research
at Wyeth Research. I serve on the committee as the industry
representative.

DR. ARTMAN: My name is Mike Artman. I\'m a pediatric cardiologist at New
York University School of Medicine.

DR. CARABELLO: I\'m Blase Carabello, a cardiologist from the Baylor
College of Medicine and the Houston VA.

DR. BARBEY: I\'m Toby Barbey, clinical pharmacology from Georgetown
University.

DR. HIRSCH: My name is Alan Hirsch. I\'m an associate professor of
medicine and cardiovascular specialist and vascular medicine clinician
at the University of Minnesota Medical School in Minneapolis.

DR. PICKERING: Tom Pickering. I\'m at the Cardiovascular Institute at
Mount Sinai Hospital in New York.

DR. ARMSTRONG: Paul Armstrong, cardiologist, University of Alberta.

DR. RODEN: Dan Roden, clinical pharmacology and cardiology at
Vanderbilt.

DR. BERNITSKY: Gay Bernitsky. I\'m a clinical urologist.

DR. LORELL: Beverly Lorell, a cardiologist at Harvard Medical School and
Beth Israel Deaconess Medical Center.

DR. CUNNINGHAM: I\'m Susanna Cunningham. I\'m a professor in the School
of Nursing at the University of Washington in Seattle.

DR. LINDENFELD: I\'m JoAnn Lindenfeld. I\'m a cardiologist at the
University of Colorado.

DR. BORER: Jeff Borer. I\'m at the Weill Medical College of Cornell
University.

MS. PETERSON: I\'m Jayne Peterson. I\'m the acting Executive Secretary
of the advisory committee for today.

DR. FLEMING: Thomas Fleming, University of Washington, Seattle.

DR. HANNO: Phil Hanno, urologist at the University of Pennsylvania.

DR. KOWEY: Peter Kowey. I\'m a cardiologist and electrophysiologist from
Philadelphia.

DR. NISSEN: Steve Nissen, cardiologist, Cleveland Clinic Foundation.

DR. KENNA: Leslie Kenna, clinical pharmacology reviewer, FDA.

DR. JARUGULA: Venkat Jarugula, clinical pharmacology reviewer, FDA.

DR. WHITAKER: Marcea Whitaker, medical officer, FDA.

DR. BENSON: George Benson, urology team leader, FDA.

DR. GRIEBEL: Donna Griebel, Deputy Director of the Division of
Reproductive and Urologic Drug Products.

DR. THROCKMORTON: Doug Throckmorton. I\'m the Director of the Division
of Cardio-Renal Drug Products.

DR. BORER: In addition, we have one voting ad hoc member of the
committee, Edward Pritchett, who is a consulting professor of medicine
in the Divisions of Cardiology and Clinical Pharmacology at Duke, and
Dr. Pritchett is on the telephone and can hear us and participate,
though he\'s not physically present.

Before we move on, I want to remind everybody that what happened just
now is important to happen throughout the meeting. That is, if you\'re
going to say something, press the button on your microphone and speak
into the microphone please. It will help us to know that you have
something to say and it will be possible for the transcriber to hear
you.

Jayne Peterson will now read the conflict of interest statement.

MS. PETERSON: Good morning. It\'s quite a long one today, so bear with
me.

The following announcement addresses the issue of conflict of interest
with regard to this meeting and is made a part of the record to preclude
even the appearance of such at this meeting.

Based on the submitted agenda for the meeting and all financial
interests reported by the committee participants, it has been determined
that all interests in firms regulated by the Center for Drug Evaluation
and Research which have been reported by the participants present no
potential for an appearance of a conflict of interest at this meeting
with the following exceptions.

Dr. L. Gay Bernitsky has been granted a waiver under 21 U.S.C.
355(n)(4), an amendment of section 504 of the Food and Drug
Administration Modernization Act, for ownership of stock in one of
alfuzosin\'s competitors who also makes an alpha adrenergic blocker, and
this is valued at less than \$5,000. Because this stock interest falls
below the de minimis exemption allowed under 5 C.F.R. 2640.202(a)(2), a
waiver under 18 U.S.C. 208 is not required.

Dr. Jeff Borer has been granted a waiver under 18 U.S.C. 208(b)(3) for
his consulting with one of the sponsors of Levitra. The firm also makes
competing products to alfuzosin and Levitra. Dr. Borer consults on
unrelated matters, for which he receives \$10,001 to \$50,000 annually.

Dr. Susanna Cunningham has been granted waivers under 18 U.S.C.
208(b)(3) and under 21 U.S.C. 355(n)(4), an amendment of section of 505
of the Food and Drug Modernization Act, for ownership of stock in one of
alfuzosin\'s competitors which is valued between \$25,000 and \$50,000.
The 21 U.S.C. 355(n)(4) waiver also includes ownership of stock in one
of Levitra\'s competitors valued between \$5,001 and \$25,000. Because
this stock interest falls below the de minimis exemption allowed under 5
C.F.R. 2640.202(a)(2), a waiver under 18 U.S.C., section 208 is not
required.

Dr. Thomas Fleming has been granted a waiver under 18 U.S.C. 208(b)(3)
for membership on three unrelated data monitoring committees supported
by one of the sponsors of Levitra who is also a competitor of both
Levitra and alfuzosin. He receives between \$10,001 and \$50,000 per
year. Dr. Fleming\'s waiver is also for his membership on two additional
unrelated data monitoring committees supported by a competitor to both
Levitra and alfuzosin. He receives less than \$10,001 per year.

Dr. Alan Hirsch has been granted a waiver under 18 U.S.C. 208(b)(3) for
his consulting with the sponsor of alfuzosin. Dr. Hirsch consults on
unrelated matters for which he receives less than \$5,000 annually and
for his membership on a speaker\'s bureau for the sponsor of alfuzosin.
Dr. Hirsch does not receive any personal remuneration from this
interest. However, his employer receives less than \$5,001 annually in
support of the Vascular Medicine Research Fellowship.

Dr. Peter Kowey has been granted a waiver under 18 U.S.C. 208(b)(3) for
the following interests: Consultant to the sponsor of alfuzosin on
unrelated matters for which he receives less than \$10,000 annually.
Consultant to a firm that makes competing products to alfuzosin and
Levitra. He consults on unrelated matters and receives less than
\$10,000 annually. Consultant to one of the sponsors of Levitra on
unrelated matters. The firm also makes competing products to alfuzosin
and Levitra. He receives between \$10,001 and \$50,000 annually.
Lectures for one of the sponsors of Levitra. The firm also makes
competing products to alfuzosin and Levitra. And lectures for a firm
that makes competing products to alfuzosin and Levitra. He receives
between \$5,001 to \$10,000 a year from each.

Dr. Edward Pritchett has been granted a waiver under 21 U.S.C.
355(n)(4), an amendment of section 505 of the Food and Drug
Administration Modernization Act, for ownership of stock in a competitor
to alfuzosin and Levitra. The stock is valued between \$5,001 to
\$25,000. Because the stock interest falls below the de minimis
exemption allowed under 5 C.F.R. 2640.202(a)(2) a waiver under 18 U.S.C.
208 is not required.

Dr. Dan Roden has been granted a limited waiver under 18 U.S.C.
208(b)(3) for the following interests: Stock in a competitor of
alfuzosin. The stock is held in a trust fund and is valued between
\$50,001 to \$100,000. Consulting with one of the sponsors of Levitra on
unrelated matters for which he receives \$10,000 annually. The firm also
makes competing products to Levitra and alfuzosin. He receives less than
\$10,001 per year. Under the terms of the limited waiver, Dr. Roden will
be permitted to participate in the committee\'s discussions concerning
alfuzosin and Levitra, but will not be voting.

A copy of these waiver statements may be obtained by submitting a
written request to the agency\'s Freedom of Information Office, room
12A-30 of the Parklawn Building.

In addition, we would like to disclose that Dr. John Neylan is
participating in the meeting as an acting industry representative,
acting on behalf of regulated industry.

In the event that the discussions involve any other products or firms
not already on the agenda for which an FDA participant has a financial
interest, the participants are aware of the need to exclude themselves
from such involvement and their exclusion will be noted for the record.

With respect to all other participants, we ask in the interest of
fairness that they address any current or previous financial involvement
with any firm whose products they may wish to comment upon.

Thank you.

DR. NISSEN: Are we ready for a coffee break yet?

(Laughter.)

DR. BORER: The meeting is open for public comment, and I think we have
one, Jayne, that you want to introduce.

MS. PETERSON: Yes, if I could introduce Mr. Katherine McComas. This is
really not public comment. Katherine is conducting a survey, a conflict
of interest survey, for the University of Maryland, and she\'d like to
say a few words.

DR. McCOMAS: Good morning. My name is Katherine McComas, and I\'m
working with the FDA on a study of public understanding of the conflict
of interest procedures that the FDA uses to monitor and manage its real
or potential conflicts of interest of its advisory committee members.
This study is being conducted across multiple centers at the FDA and
across multiple meetings.

I also have a separate survey that I\'ll be distributing to the advisory
committee members under separate cover.

I realize you have a very busy day today. The survey takes about 15
minutes to fill out. If you have a chance to complete it today, there\'s
a box on the registration desk where you can drop it. Otherwise,
there\'s a business reply envelope that you can drop it and it will make
its way to me.

We really appreciate your taking the time to fill this out. The more
responses we get, the more valid and reliable our results and the better
we are able to make recommendations to the FDA about ways to improve, if
necessary, the conflict of interest procedures to improve overall
satisfaction and understanding with the process.

I\'ll be around today. If you have any questions, please seek me out.
And thank you again for your time and thank you for letting me address
the group.

DR. BORER: Thank you.

If there is no public comment, we\'ll move on to the agenda. There is an
introductory statement on the agenda. I\'ll summarize it here, read it
in part. QT prolongation issues associated with two new drug
applications: NDA 21-287 for alfuzosin hydrochloride from
Sanofi-Synthelabo for the proposed indication of treatment of the signs
and symptoms of benign prostatic hyperplasia; and NDA 21-400 for
Levitra, or vardenafil hydrochloride, from Bayer for the proposed
indication of treatment of erectile dysfunction.

We\'re asked to focus our discussion on the clinical trial designs which
may be used for the assessment of QT prolongation and the pros and cons.
The approaches to the correction of QT interval for drugs that affect
heart rate. And I\'m sure we\'ll be discussing the positive negative
characteristics of each of the correction algorithms that\'s being used
now. And risks of cardiac arrhythmias associated with different degrees
of QT prolongation, which is really the meat of the discussion.
Pre-marketing clinical safety data from these applications and
post-marketing safety data relevant to cardiac QT prolongation from
drugs in the same two drug classes, that is, alpha adrenergic blockers
and phosphodiesterase type 5 inhibitors, will be considered.

As an introduction to this discussion, Doug Throckmorton, Director of
the Division of Cardiovascular and Renal Drug Products, will welcome us
and provide some background.

DR. THROCKMORTON: Dr. Borer, thank you very much. I have two general
things that I\'d like to say. The first is just to sort of provide a
little bit of context for the meeting today.

Detecting proarrhythmic risk for drugs that are not antiarrhythmics has
emerged as a real concern in drug development and has occupied a lot of
attention and a lot of concern both within and without the agency and
the sponsors that we regulate. That concern has emerged in two different
ways.

One, there has been the release of a preliminary concept paper of
thoughts that will potentially lead to a guidance document from the
agency or the international regulatory community about how to think
about looking for this proarrhythmic risk using primarily the biomarker
QT prolongation on the electrocardiogram, although obviously the use of
post-marketing as well and other adverse events. That release of that
document led to a public meeting in early January where public comment
was solicited and received.

Today we have an opportunity to look at two trials that have been
conducted following some of the suggestions that were discussed in both
that paper and at that meeting in January. It will be interesting to
have feedback from the committee with regard to the wisdom of that
suggestion, whether or not they believe this particular trial design
gives them the answers that they feel they need as regards QT interval
prolongation.

The one other thing that I need to mention, Jeff, is I\'d like to take
the opportunity to thank three members of the Cardio-Renal Committee.
This is their last meeting, and I\'d like to use this opportunity to
personally thank them and thank them on behalf of the agency for really
terrific service that they\'ve rendered over the last several years. Dr.
Hirsch, Dr. Lindenfeld, and Dr. Fleming have all really contributed
materially to the discussion and the assistance that the agency has
received from this committee, and I\'d just like to thank them because
it\'s been a real pleasure to work with them and I think they\'ve really
helped us a great deal.

Thank you.

DR. BORER: I think all of us sitting around the table, as well as the
sponsors, would add to your note of thanks to the three people who are
leaving.

With that, we\'ll move on to the formal presentation, first from
Sanofi-Synthelabo. Dr. Jon Villaume will introduce the presentation.

DR. VILLAUME: Good morning. My name is Jon Villaume. I\'m representing
Sanofi-Synthelabo Research, the developer of alfuzosin hydrochloride.
Alfuzosin is before the FDA for the treatment of the signs and symptoms
of benign prostatic hyperplasia, but today we will be presenting
electrocardiographic studies that we have performed to assess the effect
of alfuzosin on cardiac repolarization.

In this presentation, we\'ll provide evidence to demonstrate that the
studies we have performed are adequate to make an assessment of the
effect of alfuzosin on cardiac repolarization; that the effect size that
we see, as measured by the QT interval length, is small, even at
supratherapeutic doses; and that these increases are not clinically
significant.

The reason we have made that conclusion is the following.

First, the increase the we see at the maximum studied dose is likely to
be the maximum that will be achieved because the drug is
pharmacokinetically very well behaved.

Two, we have used a control agent that produces a modest increase in QT
interval length in a reliable manner, and our effect size at
supratherapeutic doses was well below that level.

Further, drugs that have represented a ventricular arrhythmogenic risk
produce effect sizes that are much larger.

And in addition to that, we have something that many sponsors don\'t
have at the time of initial approval, and that is we have a large
post-marketing database, and in our surveillance of the post-marketing
use of alfuzosin, there is absolutely no signal of ventricular
arrhythmogenic risk.

Now, our presentation is divided into four parts.

First, I will present background on alfuzosin and discuss some of the
issues that bring us here today.

After that, Dr. Jim Oppermann of Sanofi-Synthelabo will discuss
pharmacokinetics as they relate to the evaluation of the adequacy of the
design of the studies that we have undertaken and will describe today.

Following that, Dr. Wojciech Zareba, who is associate professor of
cardiology at the University of Rochester, will describe the study
design and present the results of our electrocardiographic studies.

Following that, Dr. Jeremy Ruskin of the Massachusetts General Hospital
will provide his perspective on our data.

We also have a number of consultants to aid us in answering questions
from the panel. They include Dr. Pierre Maison-Blanche from Hopital
Lariboisiere in Paris. Dr. Maison-Blanche was a principal reviewing
cardiologist on the studies that we performed. Dr. Craig Pratt from the
Methodist Hospital in Texas is also available to answer questions. Dr.
Claus Roehrborn of the University of Texas was the principal
investigator on our large U.S. BPH study, and Dr. Roehrborn is an
authority on BPH. And finally, we have Joel Verter of the Statistics
Collaborative to address analytical issues. We also have additional
members of Sanofi-Synthelabo who will also be available to answer
questions.

Alfuzosin was first approved for this indication in 1987. It\'s now
approved in 108 countries, including all of Europe and Canada and
Australia, but it has never been marketed for any indication other than
BPH.

We filed an NDA for a once daily dosage form in December of 2001, and
that NDA demonstrated that there was an improvement in the symptoms of
BPH and it also increased urinary flow. In those studies we identified
10 milligrams once daily as the therapeutic dose and that no dose
titration was necessary. This dose is important because it will become a
benchmark dose in the studies that we\'re discussing today.

Finally, the drug was very well tolerated in these studies.

Now, our NDA also contained a number of additional sources of
information that are very relevant to the assessment of ventricular
arrhythmogenic risk, besides the ECG studies.

First, we provided results of assay in the hERG potassium channel, and
we provide results here, all conducted in the same system, first of a
number of drugs that are associated with ventricular arrhythmogenic
risk, astemizole, cisapride, and terfenadine. And then we have an
assessment of all of the approved alpha blockers.

We present first the IC50 for each of these drugs in this particular
assay and then provide the IC50 relative to the Cmax at the therapeutic
dose of each of these drugs. You can see, at least for alfuzosin, there
is a wide separation between the Cmax at therapeutic dose and the
concentration necessary to provide inhibition in this particular assay,
and this is contrasted to the ratios that are obtained with the drugs
that are known to be associated with ventricular arrhythmogenic risk.

Next we have a number of clinical sources of information. In the NDA, we
provided a high dose ECG study and that was study 4532, with the highest
dose of 40 milligrams per day. We\'ll be presenting that briefly later.
That showed no clinically significant increase in the QT interval length
at supratherapeutic dose.

As I mentioned before, since the drug has been on the market since 1988,
primarily in Europe, we have a large experience base from post-marketing
use, accounting for 3.7 million patient-years of use, and we\'ve
identified no signal of ventricular arrhythmogenic risk. Very
importantly, there has never been reported to us, either in any of the
clinical studies or ever in post-marketing use, a single case of the
signature adverse event for drug-induced ventricular arrhythmia, and
that is a torsade de pointes type of arrhythmia.

Now, in October 2001, we received an approvable letter from the FDA, and
that approvable letter did not identify any issues related to the
efficacy of the drug. The only issue that was raised related to the
assessment of the effect on cardiac repolarization. Based on the
approvable letter that we received and then subsequent discussions with
the FDA, it became apparent that they felt they could not evaluate
whether alfuzosin did or did not have an effect on cardiac
repolarization because the method that we had employed in our ECG
studies was novel and had not been used extensively to evaluate drugs
known to have an effect on cardiac repolarization. Therefore, the study
needed to be validated.

The second issue was that we had not performed an interaction study with
ketoconazole at the maximum allowable dose.

To address those issues, we had several discussions with the FDA and
obtained their recommendations on the studies that we should perform and
developed a plan, and that plan included study 5105 that compared single
doses of 10 and 40 milligrams of alfuzosin to placebo. It was very
similar in design to the previous study, 4532, except that now we have
added to the study a positive control and that control was moxifloxacin,
an approved antiarrhythmic, as I said, that has been known to reliably
produce a modest increase in the QT interval at the therapeutic dose.

We also provided the protocol for a study to assess the interaction with
the maximum allowable dose of ketoconazole.

With that, I will turn the podium over to Dr. Jim Oppermann who is
responsible for clinical pharmacokinetics at Sanofi-Synthelabo, and Dr.
Oppermann will discuss the pharmacokinetics of the drug as it relates to
the design of the studies that we will be showing today.

DR. OPPERMANN: Thanks, Jon, and good morning.

Today I\'d like to talk about the pharmacokinetic properties of
alfuzosin that demonstrate that the QT interval evaluation that we did
after a single dose is appropriate. And secondly, I\'d like to talk
about the intrinsic and extrinsic factors that may alter or increase the
exposure to alfuzosin and compare those factors relative to the exposure
that we had in the 40 milligram ECG study and demonstrate that in fact
at this dose, we basically exceeded those exposures that would be
expected to be achieved in the clinical situation, even at the extremes
of certain exposures.

Now, when considering single-dose versus repeated-dose designs, there
are three major factors to worry about. The first is the time to reach
steady state. The second, what is in fact the exposure after repeated
administration versus single administration, and then thirdly, what\'s
happening to the metabolites?

With respect to time to reach steady state, on this graph I\'ve plotted
the trough levels of alfuzosin, that is, 24-hour samples that were
obtained after the first dose, second dose, third dose, fourth, fifth
dose of a once-a-day regimen. 24 subjects were in this study. As you can
see graphically, basically there was no difference in the mean values
across the 5 sampling days. Statistically they say the same thing.
There\'s no day effect. So based on this analysis, we can conclude that
steady state is essentially reached after the first dose.

Now, let\'s look at a 24-hour plasma profile comparing single and
repeated administration. So this particular slide represents the plasma
concentration time profile in 58 subjects receiving a single dose of an
alfuzosin tablet. As you can see, there\'s a nice prolonged plateau,
basically plateauing from around 6 hours to 14 hours. And if we now
overlay that graph with the plasma concentration time profile that
occurs after 5 days of repeated administration in 42 subjects, you can
see that there are very small differences from a single dose to repeated
dose in these two curves.

And if you then look at the pharmacokinetic parameters, single dose
versus repeated dose, for Cmax, a very small increase. For AUC,
approximately a 15 percent increase was observed, single versus repeated
dose, and essentially no difference for Cmax. This base value basically
agrees with the exposure increase you would expect for a drug that\'s
got a half-life of 9 hours, which alfuzosin does.

Now, what\'s happening to the metabolites? This is a radiochromatogram
of a plasma sample taken from a subject who received C14-alfuzosin. The
first thing to note is that alfuzosin is in fact the major radioactive
component in this sample. The metabolites that occur are in the
background. They\'re very low level. There are two major peaks here
which represent the glucuronides of alfuzosin itself and the
glucuronides of its two O‑desmethyl metabolites.

Now, what is the time course for this appearance and disappearance of
these metabolites in plasma? Again, this is a graph from a radioactive
study conducted in 3 human subjects given 10 milligrams of the
C14-alfuzosin. The top curve represents total radioactivity, which then
would be the sum of alfuzosin and its metabolites, and the bottom curve
represents alfuzosin itself.

First of all, you can see from this curve that the metabolites, which
are the differences here, are rapidly produced. So, therefore, they
would be expected to be present at the time you\'re doing a single dose
evaluation of the QT interval. And secondly, the metabolite
disappearance mirrors the disappearance rate of alfuzosin. So they\'re
formed and rapidly eliminated. They\'re probably formation rate-limited
because they\'re glucuronides and they are rapidly excreted. So under
these conditions, there would be no expected accumulation of metabolites
after repeated administration.

Therefore, based on the steady state, the results after repeated
administration, and the fact that metabolites don\'t accumulate, we feel
that the single dose design to evaluate QT effects is in fact
appropriate.

Now, what other factors might increase exposure to alfuzosin, factors
that might impact on the choice of the top dose or the design of the QT
interval study?

First of all, metabolism is the primary elimination pathway of
alfuzosin, and in that regard, CYP3A4, cytochrome P450 3A4, is the
primary isozyme responsible for metabolism of alfuzosin. In vitro, in
human hepatocytes, ketoconazole inhibits 90 percent of alfuzosin\'s
metabolism.

We had done a study with 200 milligrams, the recommended dose of
ketoconazole, and the agency asked us to go back and do a study with
400, the maximum allowable dose, and we did that. This study was
conducted in 12 healthy male volunteers, and the study design was
alfuzosin alone, then treatment with ketoconazole for 8 days, and on the
7th day of that 8-day treatment, alfuzosin was given again.

These profiles represent the results from that study. The bottom curve
is alfuzosin when given alone. The top curve is alfuzosin when given in
the presence of ketoconazole at steady state, and the parameter changes,
as a function of the high dose of ketoconazole, were for Cmax, 2.3 times
increase, and for AUC, 3 times increase.

Now, the 40 milligram dose was the dose chosen for the ECG study based
on those results, but we also looked at the exposure that we got with
the 40 milligram dose relative to other factors that might increase
exposure. So we had conducted a study in hepatic impairment and
basically in moderate and severe hepatic impairment. The clearance
changes are roughly 3- to 3.5-fold difference. Age has a slight effect
in subjects that are greater than 75 years old. There\'s a slight
increase in AUC and Cmax in the order of 1.3-fold. Renal impairment has
about a 1.5-fold effect on the plasma concentrations. This is as
expected because renal clearance is only a minor pathway. Less than 10
percent of the dose is excreted in urine, as alfuzosin itself. Here\'s
the ketoconazole results, which I showed you. Diltiazem, which is a
moderate 3A4 inhibitor, as expected, gave lesser effect than
ketoconazole, about 1.5-fold, and then basically this is the small
increase in AUC that we saw with a repeated dose versus a single dose.

So the bottom line is that 40 milligrams covers all these situations,
and it should be noted at the 40 milligram dose in both of the ECG
studies, that there was a significant percentage of postural hypotension
that was achieved. 20 percent of the subjects had an issue with postural
hypotension indicating that we\'re getting close to the top tolerated
dose.

We also compared the exposure that we got in the 40 milligram QT study
with data that we had generated during our phase III trials. In this
particular slide, we have plotted the actual peak concentrations. These
were determined in this 10- to 14-hour window after alfuzosin dosing in
our phase III trials, and basically you can see at the sampling times of
days 28, 56, and 84, there\'s very little change. There was no
accumulation in these subjects, with the n\'s listed here. Basically if
you go back to one of my initial slides where I showed the peak levels
that were achieved in the two pharmacokinetic studies, they\'re in the
same range there too. So there\'s no accumulation from day 5 to day 28.

So under these conditions ‑‑ and these are, again, real-time situations.
People here are on 3A4 inhibitors. The subjects are old. Some of them
have renal impairment. You can see we greatly exceeded that exposure.

We actually did a little simulation where we said, okay, what would
happen if you had renal impairment than then you, on top of that, took
ketoconazole, or what about age and, on top of that, ketoconazole?

This is what this graph shows. So here are the estimated Cmaxs,
simulated Cmaxs, and AUCs that you would predict would occur in
subjects, for example, who are greater than 75 years old and who had
taken ketoconazole or subjects who had moderate or severe renal
impairment and had taken ketoconazole, and then I compared this to the
exposure that we got. For example, here\'s the Cmax in the 40 milligram
ECG study. So you can see that even in the simulated conditions, the
dose that we used seems to cover the exposure.

So what I tried to show today, first of all, is that evaluation of the
QT interval after a single dose is in fact appropriate for alfuzosin
because the steady state is reached very rapidly, exposure after
repeated administration is very similar to single dose, and that the
metabolites which are formed are rapidly formed and eliminated with
similar half-lives as alfuzosin itself. Secondly, the exposure that we
got on the 40 milligram dose covers the clinical situation even in the
real-world, worst-case scenarios.

Thank you.

DR. BORER: Dr. Oppermann, before we continue, I want to take some time
for any questions that have to do with clarification of what you\'ve
presented. I\'d like to begin with two, and then we\'ll see if there are
any others.

First, a minor one. The postural hypotension you mentioned, my
recollection is ‑‑ and I just want a confirmation of this ‑‑ that to
account for this, when you did your studies, you had people reclining
for, I think it was, 12 hours before you did the measurements. Is that
correct?

DR. OPPERMANN: Yes.

DR. BORER: More importantly, you showed us time to peak plasma level and
justified the 1-day dosing on the basis of that. That seems reasonable
except that in theory it\'s conceivable that the time to peak QT effect
is not the same as the time of peak plasma concentration. Do you have
any information that would allow us to be confident that the time to
peak QT effect, whatever that may be, is reasonably captured by the time
to peak plasma concentration that you gave us?

DR. OPPERMANN: Can I go to my backup slides, or do you want to hold
that? I have a backup slide that might address it.

First of all, we are not aware of any situation actually where the QT
changes were at a time point significantly different than at Cmax, or
saying it in other words, that there were QT changes that occurred at
later times than Tmax. We\'re not aware of any situation like that.

Slide 21 please. Obviously, we don\'t have tissue concentration data in
humans, although actually we have prostate values in humans. But we
don\'t have heart concentrations.

So in trying to evaluate what\'s happening in other tissues,
specifically the heart, this is a graph showing heart concentrations of
total radioactivity and plasma concentrations of total radioactivity
after administration of the radioactive alfuzosin to rats, 8 rats in the
study. So this curve again represents alfuzosin itself, and alfuzosin
and its metabolites, the combination of that.

I have a similar curve, if you just wanted to measure alfuzosin here,
but this represents both metabolites and alfuzosin.

So, first of all, you can see, as I mentioned before, in plasma the
radioactivity levels are rapidly reached in the heart, but then they
decline at approximately the same levels as plasma. So if we can
extrapolate rat to human ‑‑ and we can because the metabolic profile is
very similar ‑‑ measuring it at times of Cmax is probably appropriate.

DR. BORER: Okay. I don\'t want to take any more time with this. Now, I
appreciate those data. We may want to come back to this topic later, but
that\'s fine for now.

I\'d like to ask if anyone else has any issues of clarification here,
and I\'d like to specifically ask Dr. Pritchett, since I can\'t see when
you press your red button here, if you have any questions you want to
ask Dr. Oppermann right now.

DR. PRITCHETT: I do not, Jeff. Can you hear me?

DR. BORER: Yes, fine. Thank you.

DR. PRITCHETT: Jeff, the only mikes that I can hear are the mikes at the
committee members\' desks. I cannot hear the speakers from the podium or
from the audience. So if you can get someone working on the audio there,
it would help me here.

DR. BORER: Okay. We will try and do that right away.

DR. PRITCHETT: Thank you.

DR. BORER: So that would account for you have no questions or comments.

(Laughter.)

DR. BORER: Steve Nissen has to leave at about 10:30. So, Steve, do you
have any questions you need to raise at this time?

DR. NISSEN: No.

DR. BORER: Anybody else? Dan?

DR. RODEN: I\'d like a little clarification about the metabolites. You
haven\'t shown us where the C14 was inserted on the molecule, so I\'m
not 100 percent confident that measuring C14 activity is a measure of
actual metabolite accumulation. And since you know the pathway is 3A4
and yet you show us glucuronides as the major product at 1 hour, I
wonder if you know the identity of these major metabolites, and do you
have any information on their cardioactivity?

DR. OPPERMANN: No, we don\'t have any information on the cardioactivity
of the metabolites.

Can I have slide 14 please? This is the metabolic profile of alfuzosin.
The metabolites that I showed you in plasma were the glucuronide
conjugate of this, which is the O-desmethyl and its corresponding
O-desmethyl compound there. So these were the two metabolites, together
with conjugation of alfuzosin itself, which are the major metabolites
appearing in plasma. They\'re also major metabolites in urine.

Another metabolite which appears in the feces is this one, but it
doesn\'t appear to any great extent in urine.

I have a slide where we measured the urinary rate of elimination of this
metabolite as its glucuronide, and this one as its glucuronide, which
basically shows that the half-lives are in the 4- to 6-hour range or
less.

DR. RODEN: It seems to me that the most straightforward way of
addressing what you want to address is to get some concentration data at
steady states or after somebody has been on it for a week or 2 or
something that nobody is going to argue about and tell us what the
metabolite concentrations in plasma are. And do you have those data?

DR. OPPERMANN: No, we don\'t. We actually elected not to measure
metabolites because they were glucuronide conjugates and it would be
very unlikely that they would be pharmacologically active. So at that
point there was a decision not to measure metabolites.

But I think the urinary data do demonstrate that these have relatively
fast half-lives and would not be expected to accumulate.

DR. BORER: Are there any other issues that require clarification before
we move on?

(No response.)

DR. BORER: You can hear now, Dr. Pritchett.

DR. PRITCHETT: I can. Thank you very much.

DR. BORER: Way to go.

Why don\'t we move ahead then?

DR. OPPERMANN: Then I\'d like to introduce Dr. Zareba who will talk
about the methodology and the results of the ECG trials that we did.

DR. ZAREBA: Ladies and gentlemen, it is my pleasure to present for you
data in regards to methodological aspects and findings of the study
focus on the effect of alfuzosin on ventricular repolarization.

This presentation will emphasize how increased heart rate may influence
QT interval and eventually how we can adjust for heart rate and correct
for heart rate in such conditions. We will demonstrate relatively new
so-called Holter based RR bin method which tries to control for heart
rate but not correcting for heart rate. We will speak about design and
results of two studies which were specifically conducted by the company
to evaluate effect of alfuzosin on QT interval.

Alfuzosin is an alpha-1 blocker, and as such, may increase heart rate.
This slide shows data from the study that was mentioned by Dr. Villaume,
study 5105, during which we had subjects administered 10 milligrams and
40 milligrams of alfuzosin, in addition to a positive control of
moxifloxacin 400 milligrams.

As you may notice, on average, there is an increase in heart rate in
therapeutic dose, moderate, about 1.5 beats per minute, which increases
to 3.7 beats per minute with the higher, supratherapeutic dose of 40
milligrams of alfuzosin. It is worth emphasizing that 33 percent of
patients at the supratherapeutic dose showed a heart rate increase which
exceeded 15 beats per minute, and as we know, 15 beats per minute is a
very usual observation we have on an everyday basis in any subject.

This particular change in heart rate, of course, prompts us to determine
methods to adjust the analysis of QT for heart rate, especially since QT
is associated with heart rate, a very strong relationship.

Over decades, we had several methods developed to adjust for heart rate,
and of course, there are traditional QT correction formulae, including
Bazett and Fridericia, which try to compare QT to the standard heart
rate of 60 beats per minute or RR interval 1,000 milliseconds, and they
are broadly used clinically.

Recently there is evidence that those two traditional formulae create
some under- or over-estimation in some subjects whose exponent is not
exactly matching .5 or .33, as it is shown in Bazett and Fridericia.
There are two methods of correction which recently have been exercised.
One is population-based correction with regression modeling, helping us
derive a coefficient which is pertinent for a specific population, and
another is subject-specific. Each individual, having a substantial
number of QT and RR points, has the ability to demonstrate specific
QT/RR correction with a specific exponent which will be pertinent for
the subject.

Let\'s take a look at an example of another subject from study 5105 who
had a 60 beats per minute heart rate which increased to a 75 beats per
minute heart rate, and accordingly, the QT shortened, as physiologic
response should be.

If we look at the Bazett formula, you all of a sudden see that there is
a 24-millisecond over-correction of QT interval with this mathematical
correction. Fridericia performed somewhat better, but if we compare
these two subject-specific based formulae, which is derived based by the
behavior of QT and RR in this particular subject, we can appreciate that
this correction practically follows exactly the pattern of 60 beats per
minute. This approach should be exercised more and more, but this
approach again is based on modeling, modeling which tries to fit the
linear or curvilinear line.

There are other methods which could be exercised, and one of the methods
which I would like to present to you today is the so-called Holter-based
RR bin method.

What is the Holter RR bin method? The ECG required for this methodology
should consist of at least several minutes, but usually it is a 24-hour
Holter recording. And if we have such a recording, we first try to
identify QRS complexes and sinus beats, measure RR intervals between
beats. Subsequently specific beats with a specific range of RR interval
every 10 milliseconds are clustered to create so-called RR bins. Like in
this example, you have a cluster of beats creating a bin of 1,000
milliseconds and 1,010 milliseconds, and subsequently there is signal
averaging implemented to create the final beat which represents this
particular beat. This beat serves for further analysis using manual
measurement of QT, and this measurement is performed blindly and also as
fiducial points which we will see on this slide are kept in digital
format.

This method has the following advantages. First of all, it controls
rather than corrects for heart rate. There is no need for correction
which may eventually incorporate some bias.

On top of it, it provides the ability to explore a wide range of RR
interval for each subject and, therefore, we can exercise direct
comparison of absolute QT at various heart rates. This could be done on
placebo and this could be done on drug.

Another advantage is that we get multiple points to develop even better
fitting of a QT/RR regression model. And the next slide is showing this
kind of example of individual QT/RR relationship. So if we have a wide
spectrum of RR interval and we have behavior of QT through this wide
spectrum of interval on placebo, one could imagine that if the drug had
not any QT effect, we would have superimposed lines. Whereas, where we
have drug, which potentially contributes to some QT prolongation, we
will see an upward shift of this regression line.

This method also allows us to look at specific RR interval. Whether 800,
1,000, or 1,200, we can just simply look at absolute QT on placebo and
on drug and compare it. This has the advantage of avoiding any QT
correction formula.

This method has been applied in two studies which I will be presenting.
The first study is a study Dr. Villaume already mentioned, study 4532,
which was included in the original NDA. And the study, which is the
primary topic of my presentation, is study 5105, was specifically
designed based on the recommendations of FDA, and this study compared
single doses of 10 and 40 milligrams of alfuzosin with a positive
control in the form of 400 milligrams of moxifloxacin, an antibiotic
known to increase QT prolongation, and of course, placebo.

Speaking about the first of these two studies, study 4532 was a
single-center, randomized, double-blind, four-way crossover study
involving 24 healthy male subjects who were administered 10, 20, and 40
milligrams of alfuzosin and placebo. This study included Holter
recordings done at screening, at four periods of single-dose
administration.

As was already reported in the original NDA, this study showed that
there was a 2-millisecond increase in QT1000 which reflects QT measured
at 60 beats per minute with an upper confidence interval of just 3
milliseconds. There was no evidence for dose dependency in this
particular study.

Because this method of the Holter bin approach was relatively novel, FDA
requested that we provide additional evidence that this method is useful
and is sensitive enough to identify any signal on ECG. Therefore, the
study 5105 was designed with the following objectives: to validate the
Holter bin method by using both a positive control and QT corrections
from 12-lead ECG recordings. Again, a positive control using
moxifloxacin at therapeutic approved dose of 400 milligrams. And to
reassess the effect of alfuzosin given at two different doses, a
therapeutic dose of 10 milligrams and a supratherapeutic dose of 40
milligrams, on QT interval using the Holter bin method.

Again, this study was a single-center, randomized, double-dummy,
four-way crossover study involving 45 subjects who are given alfuzosin
10 and 40 milligrams as well as placebo and moxifloxacin 400 milligrams
as a positive control. Each period consisted of a run-in placebo,
followed by a single-dose administration, and there was a washout of 5
days between successive periods.

The primary endpoint was QT measured using this novel Holter bin method.
Change in QT1000 was of primary interest because it is similar to other
formulae which try to correct for heart rate exactly at 60 beats per
minute. On top of it, the other primary endpoints included change in QT
at RR bin with the largest number of complexes, as well as change in QT
averaged over all RR bins.

On top of this primary endpoint, we wanted to exercise other
measurements of QT utilizing standard 12-lead ECGs. They included
individual-based corrected QTcNi. We used also population-based
correction based on the population of interest, as well as traditional
formulae I mentioned before, Fridericia and Bazett.

On top of it, we also explored some measurement of QT interval at other
heart rates spanning throughout quite a wide range of RR intervals.

It\'s important to emphasize that we tried to

make sure that those measurements are performed in the time window which
matches the highest concentration of the drug. In light blue, we can see
concentration of the drug given at 10 milligrams; in dark blue, given at
40 milligrams; and in red, the concentration of the moxifloxacin which
was used as a positive control.

As you may notice, the administration of moxifloxacin was on purpose
shifted 6 hours later after the administration of alfuzosin to
accomplish matched peaks of plasma concentration. The period between 7
and 11 hours was of particular focus to make sure that we will be able
to evaluate QT at maximal action of these drugs.

The study was powered to detect a 5-millisecond change caused by
moxifloxacin in Bazett corrected QTc. This 80 percent of power required
45 subjects and simultaneously, these 45 subjects were sufficient to
provide more than 80 percent of power to detect just a 3-millisecond
difference using the Holter bin QT1000 method for any treatment group.

Moving to the results, I will first show you moxifloxacin data. The
Holter bin method with QT1000 demonstrated a 7-millisecond increase in
repolarization duration after therapeutic and approved dose of 400
milligrams of moxifloxacin. This was confirmed by individual correction,
population correction, and traditional formulae. This particular
exercise led us to believe that in fact the Holter bin method is
successfully able to identify a potential signal if it exists.

Data for the therapeutic dose of alfuzosin at 10 milligrams did not show
any significant difference in QT duration. If we look at QT1000, the
upper limit is 2.6 milliseconds. The other correction formulae show
similar effect. There is a slight trend toward significance for Bazett
correction, but let\'s remember what I showed you at the beginning. The
Bazett correction has this huge tendency of over-correcting for
increased heart rate.

When we look at 4 times the therapeutic dose, which means 40 milligrams,
which was tested on purpose, as was discussed a moment ago, we observed
a change in QT1000 in the range of 2.9 milliseconds with the upper limit
around 5.5 milliseconds. This was further confirmed by both individual
and population-based formulae. And of course, as expected, traditional
formulae, whether Fridericia or Bazett, showed higher prolongation,
which is not surprising since one-third of the patients in this cohort
showed a substantial increase of heart rate.

We also analyzed two other secondary endpoints on top of QT1000. We
looked at QT change at the largest sample size RR bin, as well as QT
change over all RR bins. As you may appreciate on this slide, the
results were identical, that alfuzosin at 10 milligrams didn\'t show an
effect. At 40 milligrams there is less than a 3 millisecond change in QT
which is less than half of what is seen for moxifloxacin.

We also were interested whether there is any evidence for rate
dependency. Rate dependency shows that for alfuzosin 10 milligrams in
white, we do not see again any significant signal. If we go to 40
milligrams of alfuzosin, at heart rates faster than 60 beats per minute,
again there is no signal. At lower heart rates, below 60 beats per
minute, there is some increase, as I mentioned, and on average we had
this 2.9 in 1000, but as you may appreciate, this does not exceed 4
milliseconds and importantly doesn\'t grow with increased bradycardia.
To compare, we show you the data for moxifloxacin which shows, of
course, some modest QT prolongation along all heart rates we exercised.

The average QT is one important piece of the story, but we also have to
look at outliers. We found that no subject had outliers defined as above
450 milliseconds in absolute terms or change over 60 milliseconds when
we used Fridericia, normalized by population-based or subject-specific
formulae. We found a couple of subjects who had outliers using Bazett,
and further investigation of those subjects revealed that in fact those
subjects had those outlier values because they have increased heart rate
which contributed to over-correction by the Bazett formula.

We tried to further explore the outliers by investigating the subjects
who had higher plasma concentration of the drug. This was above 70
nanograms per milliliter. There were few such subjects analyzed. As you
may appreciate in this table, QTcNi, which is the subject-specific
method, showed that none of those cases demonstrated QT prolongation
exceeding 30 milliseconds when compared to placebo.

Let me, therefore, summarize. Study 5105 using the Holter bin approach
had the required assay sensitivity. With a therapeutic dose of 400
moxifloxacin, the Holter bin method documented a 7-millisecond increase
in QT1000 which was compared with QTc measured using classical
correction methods in the order of a 9- to 12-millisecond increase.

We also demonstrated that at a therapeutic dose of 10 milligrams,
alfuzosin did not produce significant changes in QT1000. At four times
the therapeutic dose, alfuzosin produced a mean QT1000 change of 2.9
milliseconds, less than half of what is observed with moxifloxacin
administered at the therapeutic dose which is approved for clinical use.
We believe that whatever the dose we exercise, there is no clinically
relevant change in QT/QTc which should be of major concern.

Thank you very much, and I will ask Dr. Jeremy Ruskin to continue with
additional summary and conclusions.

DR. BORER: Thank you, Dr. Zareba. Before we go on to Jeremy, or while
you\'re both up there, again I want to make sure there are no issues
that require clarification. Blase?

DR. CARABELLO: Yes. Could you go back to your slide number 35?

DR. ZAREBA: Yes.

DR. CARABELLO: I presume that patient was taking placebo?

DR. ZAREBA: Yes. It\'s just taken from the placebo arm. Correct.

DR. CARABELLO: Okay, thank you.

DR. BORER: Paul and then Steve.

DR. ARMSTRONG: I have two questions. The first relates to providing a
better understanding of the heart rate changes at the different doses,
and the time course of the increase in heart rate relative to the plasma
concentrations you demonstrated, and to what extent those heart rate
changes tracked a blood pressure lowering as opposed to another effect
of the drug of interest. Could you clarify those points for me please?

DR. ZAREBA: There is evidence for heart rate increase by alfuzosin. In
terms of plasma concentration, there is some slight trend. I\'ll be able
to use one of my backup slides.

DR. ARMSTRONG: I\'m especially interested, Mr. Chairman, in knowing
whether the window of Holter interrogation tracked the maximal changes
in heart rate and to what extent those were paralleled by changes in
blood pressure. That\'s what I\'m trying to get at here.

DR. ZAREBA: May I have slide 57 from the backup? We do not have
simultaneous analysis of blood pressure in these patients, so I cannot
comment on this particular aspect of the story.

When we look at heart rate, as you see from this slide, there is some
upward-going regression showing concentration and change in heart rate
in comparison to placebo. So there is confirmed evidence that, apart
from a stepwise effect, which I showed you, with 33 percent of subjects
having a heart rate increase by at least 15 beats per minute at the
higher dose, there is in a continuous fashion some increase with heart
rate.

Unfortunately, as I said, we don\'t have simultaneously acquired Holter
data for blood pressure.

DR. ARMSTRONG: Is there someone within the company that can address now
or later the issue of blood pressure tracking heart rate since I think
that\'s quite germane?

DR. VILLAUME: Can we hold that for later?

DR. ARMSTRONG: Sure.

And my second question, if I may, is in the backup documentation
references, Drs. Malek and Camm comment on an unreliability or a
disconnect between the relationship of the QT interval and the heart
rate changes because of the autonomic modulation of this relationship
and other factors that might mediate it. I don\'t know whether you or
Dr. Ruskin are in the best position to help me understand then the
legitimacy of these measurements through a broad cross section of
circumstances where disconnect between the QT and the heart rate would
be affected.

DR. ZAREBA: There is definitely association of cause between QT and RR
and this is primarily driven by the autonomic nervous system. If we
analyze QT behavior and QT variability and when we analyze separately
heart rate variability, they follow each other in more than 80 percent.
Studies utilizing coherence function, which were done independently of
this study, demonstrated that about 15 to 20 percent of variability of
QT could be eventually coming from a direct effect on the ventricle
without simultaneous influence of sinus node by the autonomic nervous
system. So there is intrinsic ventricular component driving QT. There is
no doubt but this component is relatively small.

DR. BORER: Can I just follow up on that before we get to Steve\'s
question? That there is a relation between RR and QT seems
incontrovertible. But in line with Paul\'s question, I\'d wonder a
little bit about what you did to account for the possibility that the
temporal relationship between the change in heart rate and the change in
QT may not be immediate. I mean, I don\'t know if it is or it isn\'t,
but it may not be. It may take a while ‑‑ I don\'t know how long ‑‑ for
the QT to respond to the heart rate.

And it seems to me that if you\'re looking at bins of RR1000 and people
getting 40 milligrams of a drug that causes some modest degree of
hypotension ‑‑ or some modest fall in blood pressure I would say, not
hypotension ‑‑ some modest fall in blood pressure clearly is associated
with an increase in heart rate. The fact that people had beats at a
heart rate of 60 while that drug was on board is unusual. It\'s
certainly conceivable, but you have to wonder what beats those were.

For example, I could conceive ‑‑ and I\'m certainly not suggesting that
this is what the data showed, but I could conceive of finding a group of
post premature beat beats that had RR intervals greater than or equal to
1000 that might not really be representative of the normal beats or a
few beats interspersed with a lot of others where the RR was 1000 that
might somehow not be representative, and they might have occurred early
in the measurement interval as opposed to later.

So I\'m just wondering what can we say about the temporal relation of
the RR interval change and the QT interval change, and did you do you
something to account for that like, for example, only looking at the
50th beat with an RR interval or after the 50th beat with an RR interval
of 1000 or something like that? I think you understand what I mean. I
just need some reassurance about that.

DR. ZAREBA: There are a couple of points you raised.

Regarding the behavior of QT, of course, this a dynamic phenomenon,
which comes usually from several preceding beats. As it was discussed
with FDA over a year ago, for this particular study there was a
recommendation that we use all beats in the set without eliminating
beats which eventually would be coming from a very long RR or a very
short RR interval. So we accounted for those. If we accounted for the
phenomenon of hysteresis, we tested that we would need to reject 75
percent of beats.

Another approach which could be exercised here, and was exercised by Dr.
Pierre Maison-Blanche several times before, was a selective signal
averaging method, trying to look at QT with preceding heart rate
encompassing 1 minute or even up to 3 minutes prior to measured QT. This
method seemed to be more robust than classical measurement of just one
preceding RR but altogether, generally speaking, results are similar.

Again, based on the recommendation of FDA, we exercised over here all
beats without implementing hysteresis.

DR. BORER: Steve?

DR. NISSEN: Yes. I want to focus on the population in study 5105. I
noticed that these were men with an average age of 27 years of age. Now,
fortunate for me, 27-year-olds don\'t generally have BPH. Even people my
age in their early 30\'s ‑‑

(Laughter.)

DR. NISSEN: ‑‑ rarely have BPH. So the population that\'s likely to get
this drug is going to be an elderly population with a fairly high
incidence of concomitant heart disease. If I look at the people that I
see in my clinic with BPH, they\'re men in their 70s, 80s, and older.

So one of my questions is, why didn\'t you do this study in elderly men,
the population that\'s going to get the drug? Do we know that the fact
that there\'s not so much effect in a young 27-year-old population ‑‑
what does that mean for a group of people that may have concomitant
heart disease? That\'s the first question and I have a follow-on after
that. So reassure me that this population isn\'t any different in their
characteristics of what the drug does to the QT from a population with
heart disease in their 70s and 80s.

DR. ZAREBA: There are a couple of points which we need to address. I\'m
not sure whether Dr. Ruskin would like to start, or I would be happy to
start.

DR. VILLAUME: Dr. Ruskin will comment on this in his presentation. So if
you\'ll hold that question because it obviously is a pivotal question.

DR. NISSEN: Yes. But you certainly could have found 45 old men to do
this study in. I mean, they\'re out there. So I guess this is for the
FDA more than anybody else. I mean, the question is if we\'re going to
do these sorts of studies, shouldn\'t we do them in the population for
which the drug is intended to be administered?

And the second question, which I think might be similar, is that my
concern about drugs that affect repolarization is what will happen to
patients who may have ischemia. Imagine an older man who is on a drug
like this has an acute myocardial infarction. Will the presence of an
agent that alters the QT have an effect on the likelihood of such a
patient having ventricular fibrillation or torsade or some lethal
arrhythmia? So maybe Jeremy also can comment on that.

But obviously, you can\'t test that very easily, but I\'d like to know
if anybody on the panel or if anyone else can help me understand that
because some of the men that get this drug are going to have acute
ischemic events, and the question is, what does the drug do to the QTc
in the setting of concomitant ischemia compared to not having the drug
on board? I don\'t know that I understand the answer to that question,
not being an electrophysiologist.

DR. ZAREBA: Let me just briefly comment before Dr. Ruskin covers this to
a greater extent. In this particular study, we on purpose exercised a
dose of 40 milligrams which is four times the therapeutic dose. At the
therapeutic dose, we didn\'t have any increase of QT. Therefore, if you
have a patient who has ischemic heart disease and taking the recommended
10 milligrams per day, I do not expect any deleterious effect even in
the presence of an ischemic condition in such patient. The data from 40
milligrams showing just a 2.9-millisecond increase is also reassuring
that we do not expect more.

I\'m not aware of any systematically analyzed data of risk of
ventricular fibrillation and acute MI while on specific drugs. Maybe
somebody else.

DR. KOWEY: Steve, can I just comment?

I\'m not as worried about ischemic disease as I might be theoretically
with, for example, hypertrophic disease where repolarization clearly is
legend. The reassurance that I have ‑‑ and again, Jeremy may address
this ‑‑ is that this class of drug has been used in patients with
hypertension, and although there are some warts in those data, one thing
that I think has not emerged is a clear signal that there has been
proarrhythmia with those drugs using it in a very, very large number of
patients who have hypertrophic disease. I mean, if you\'re going to pick
a target population that\'s going to get this drug that I would worry
about more, it would be hypertrophic disease than ischemic disease. As I
said and in the documents that we received, there\'s a fairly reasonable
amount of reassurance from what we\'ve seen with these drugs that we
haven\'t seen a clear signal of proarrhythmia. So that\'s as best I
think that we might be able to do to help you with that question.

But I think it would also be reasonable ‑‑ this is not a question you
have to answer right away, but it\'s one of my questions. I\'ll preface
this by saying that I realize that there is a strong limitation on
preclinical information, but it would also be reassuring if you could
show us some information preclinically in relevant models that in fact
there are no signals that animals with ischemia or hypertrophic disease
are at higher risk of developing changes, for example, in transmural
dispersion. Those data certainly could be garnered from a basic model.

DR. NISSEN: Peter, just to follow up, that was exactly where I was going
with that, and I was sort of saying it would have been reassuring to
know that in, say, a dog in whom you produce ischemia that you can give
this drug and not lower the threshold for ventricular fibrillation or
torsade.

DR. ZAREBA: What Dr. Kowey said is, in fact, 15 years of experience in
Europe, Australia, and Canada. As you said, these are patients who are
usually probably 70 years old having several ischemic, hypertensive, and
other comorbidities. Therefore, we do not have any post-marketing
evidence for any increased risk in these patients, as well as other
alpha blockers.

DR. BORER: Jeremy, are you going to be discussing this whole area to
some extent?

DR. RUSKIN: I\'ll make a comment ‑‑

DR. BORER: Okay. Maybe we can wait until you do that because I see there
are some other questions here, rather than getting bogged down in this
one issue, which is an important one, but if you\'re going to come back
to it.

John?

DR. NEYLAN: Thanks. I had a question about the Holter methodology. It\'s
certainly very clear why such a relatively novel strategy to evaluate QT
interval effect might be used in drugs that have a chronotropic effect.
And you listed some of the advantages of this methodology over a
traditional surface EKG. I wonder if you could also give us a few
comments about the potential disadvantages. And I\'m speaking of two at
least major areas ‑‑ but my colleagues on the committee may also raise
other points ‑‑ that speak to some of the challenges of validating this
method in the future study of QT.

One is the potential for motion artifact, and I\'m wondering if these
subjects were, in fact, at bed rest or largely confined to bed rest when
you did the period of Holter evaluation because motion artifact
obviously can have an effect on the wave form.

And the second is the wave form itself. Given the limitation of leads
used, are you, in fact, optimizing the best capture of wave form to
optimize the measurement? And is there reliability within the subject as
to the lead placements over several periods of study?

So those are two general thought areas or questions.

DR. ZAREBA: Good questions. Regarding your last point about the design
of the study, the patients were, in fact, in the supine position during
the study, so we eliminated motion artifact in these particular
conditions.

Secondly, the electrodes were positioned in the same identical position
based on simply markers put on the skin, and this allowed us to repeat
this successfully.

Regarding the quality of the recordings and also acquisition of the
data, as well as processing of the data, I didn\'t have time to
elaborate more, but each class there, each bin, for every 10
milliseconds, should consist of at least 50 beats. And this was certain
quality assurance which we implemented, and these clusters in fact
ranged between 50 up to 800 beats depending on the variability of
specific RR intervals. The clusters which were extremely noisy were
excluded either automatically or manually. This, of course, adds to the
labor intensity of this method.

But we believe that this particular method, allowing us to evaluate QT,
at heart rate, whichever you like, it\'s not just correcting with the
risk with one or the other formula we under- or over-correct at high or
low heart rate. Here we have the ability to look at every heart rate and
look at the absolute QT, and this allows us to really answer the
question whether there is any rate dependency as I showed. The QT1000
was chosen because of comparative data for Bazett correction and
Fridericia, but as you may appreciate, there is vast opportunity to look
at other rates and therefore conduct a thorough evaluation of QT.

DR. NEYLAN: Mr. Chairman, could I have one follow- up question?

DR. BORER: Yes, sure.

DR. NEYLAN: And that is given that these subjects were supine, I\'m
curious as to your opinion as to whether this methodology might be
useful in the ambulatory setting for this purpose.

DR. ZAREBA: I think yes. It is exercised in Dr. Maison-Blanche\'s lab
and a few other labs, and it is exercised in conditions of, of course,
everyday clinical conditions which are not associated with a supine
position. This brings, of course, a number of beats which need to be
rejected due to changes either in position or motion artifact, but the
method could be still analyzed. In fact, the recorder which we have been
using, so-called ELA Medical recorder, is a recorder which we are using
in a clinical setting and every day in my class at the University of
Rochester, and we have this RR bin method implemented and it works. We
can do it again with a number of beats requiring rejection higher than
when you have it done in the supine position, but it could be done.

DR. BORER: JoAnn?

DR. LINDENFELD: Just a clarification. The leads in the Holter monitor
and the different position than usual 12-lead ECG. Can you reassure me
that the QT changes that you see in the Holter monitor exactly those we
see on the 12-lead EKG which is sort of our point of reference in the
past? In other words, is a 2-millisecond difference in the 12-lead ‑‑ do
we see a 2-millisecond difference in the Holter?

DR. ZAREBA: May I have slide 83 please?

The position used in this particular setting were mimicking lead II.
This is based on the international standard for Holter monitoring.
We\'re using CMV5 as the primary lead which reflects exactly lead II.
This particular methodology has been used not only in these studies but
several other studies which are used for drug evaluation. This was our
primary measure.

DR. BORER: Mike and then Toby and then Peter.

DR. ARTMAN: Yes. I had some similar questions about the Holter technique
that Dr. Neylan had.

But to expand on that a little bit, again trying to translate to
clinical practice in the real world ‑‑ and one of the things we\'ve been
struggling with are these heart rate changes in response to the drug. So
I think the fact that the subjects were supine help explain perhaps why,
with a decrease in blood pressure, their heart rates were not more
elevated.

So I\'m wondering if you have data on ambulatory patients, patients who
are up and about and may have even greater heart rate changes than this
third of patients who had a heart rate increase above 15. Do you have
data on those subjects and do you have data in other patients who are
ambulatory? That\'s one question.

Then another question to the technical aspects. Were the Holter tracings
screened in any way prior to being sent to the blinded cardiologists for
review?

DR. ZAREBA: Regarding ambulatory data, for this study we didn\'t have
ambulatory data in particular. As I mentioned before, unrelated to this
project, we clinically and research-wise are using the Holter bin method
in our laboratory facility and it works. But again, I don\'t have data
for ambulatory specifically for alfuzosin data.

In terms of question ‑‑ sorry. What was the second one?

DR. ARTMAN: So those patients that did have a significant increase in
heart rate. There was a third of patients on the higher dose and a few
patients on the lower dose.

DR. ZAREBA: We all together had a quite surprising range of heart rates.
We had RR intervals in these subjects ranging from 700 milliseconds to
1400 milliseconds despite the fact that they were supine. So there was
natural variation plus probably some other factors contributing to it,
and because of this relatively wide range, which ranges from 45 beats
per minute up to almost 90 beats per minute, we had the ability to
evaluate a wide range. I focused mostly on 800 to 1200 milliseconds
because this was the main representation of our data, but we have a
limited number of beats also recorded below 800 milliseconds and above
1200.

I only wanted to say that in this particular setting we still did not
have the ability to see any signal whether at lower heart rate or higher
heart rate, and the same in terms of looking at the patients who
presented specifically increased heart rate. Those patients showed
outliers using the Bazett method, but when we look at them using the
Holter bin or the subject-specific normalized method, we did not see any
increase of QT.

DR. ARTMAN: And then the other question was were the Holter tracings
data for individual patients screened before being sent to the
cardiologists?

DR. ZAREBA: Routinely these patients were screened for usual
arrhythmias, as it is done, to make sure that ‑‑ as I mentioned in the
introductory slide for the Holter bin method, we were concerned of
having only sinus beats. So, therefore, annotation had to be performed
to eliminate all artifacts, eventually non-sinus beats, but this was the
only type of prescreening which was done. Otherwise, all beats were
qualified.

DR. BORER: Toby.

DR. BARBEY: Just a very simple question. Your cartoon suggests that the
averaged beats were derived from one single lead?

DR. ZAREBA: From one single lead.

DR. BARBEY: So, not better or worse, but as opposed to the 12-lead
approach where increasingly there\'s a tendency to measure all 12 leads
simultaneously, this technique focuses on the quill of lead II and does
a single lead.

DR. ZAREBA: These techniques allows us to look at other leads, but in
this particular study, we focused on one lead II, which seems to be ‑‑
let\'s say, a modified lead II which seems to be representative usually
in ECG.

DR. BORER: Peter, then Alan, and then JoAnn.

DR. KOWEY: Actually, if you could put of slide 54. This is just a
comment, Jeff, and then I have just a very brief question. But we all
get very hung up on correction formulae and trying to understand exactly
what is happening with repolarization, whereas in real life, it seems to
me that we should be more worried about what\'s happening to the QT
interval.

I want to just tell you that I really like this information. I think
this is not only scientifically sound, but it\'s also clinically
reasonable because if you anticipate any change in heart rate in an
older individual taking this drug, the heart rate would go up, and as
the heart rate goes up, this slide clearly shows that the liability of
the agent is going away.

The other thing that\'s very interesting about these data ‑‑ and I
don\'t think you\'re going to be able to tell us the explanation for
this, but we\'ve seen it in other data sets ‑‑ is that there\'s seems to
be ‑‑ as you get up into even slower heart rates, the QT change actually
gets less. It does a little bit for moxi, but it certainly does it for
your drug. That may be due to other effects the drug is having on
repolarization not measurable by just its effect on IKr.

The question I had was related back to Steve\'s question about target
populations. How well do old men tolerate large doses of this drug? I
would think that the limitation of doing these studies in old men would
be that it would be very difficult to get up to a 40 milligram dose. Is
that true or are we just making that assumption? Is it true that this
study would be very difficult to do in older men? Do you have any
information on what happens if you give a 65- or a 70-year-old man, who
is twice the age of Steve, to see what would happen?

(Laughter.)

DR. ZAREBA: Let me comment further on your comment. I was extremely
attracted to these data too, but I was also intrigued and, to tell you
the truth, happy to see that if you have an older patient who has a
tendency to bradycardia, which also happens quite frequently, and as we
know, bradycardia is a condition which has the ability to prompt torsade
in such situations, that we do not have further increase of QT. This I
think was reassuring clinically for me that we have safety also over
here, especially at night when you have the patient asleep and you may
have, let\'s say, 50 or 45 beats per minute, and we do not have further
prolongation which eventually could prompt torsade. So this was
definitely reassuring.

In terms of age, again, I\'m not sure whether I should really step in
Jeremy Raskin\'s comments which will be coming very soon. So my
proposition is that let\'s go over the issue of age and adequacy of the
patient population after his presentation.

DR. BORER: Let\'s see. Who was next? Alan, JoAnn, and then Tom.

DR. HIRSCH: Well, let me continue the discussion regarding methodology
from my naive age of 20.

Did torsade and sudden death and dysarrhythmias occur suddenly,
spontaneously, occasionally without great predictability? So I want to
methodologically talk about things beyond heart rate change and QT
prolongation in steady state. I\'m going to ignore the safety database
and just talk about methods and say that I\'m concerned, naively
perhaps, whether or not we miss signals of QT change, again in the
supine position, without looking at adrenergic and vagal stimuli that
occur in real life. I don\'t know if the previous EP database has
evaluated this, but again, although the heart rate may increase with a
drug like this, what goes up, must come down. There are going to be
changes in both directions that are transient.

Again, for both of these drug classes where there\'s going to be
occasionally Valsalva maneuvers, straining to urinate, sleep ‑‑ you get
the idea ‑‑ post-exercise responses, in real life, whether it\'s a
25-year-old or a 40-year-old, has the bin method with the Holter been
applied in a more ambulatory setting or in these transients whereby a
bin after these perturbations, these normal physiologic perturbations,
might find a signal of danger that would be completely missed in a
supine steady state condition?

DR. ZAREBA: Yes. First, regarding this concern about various heart
rates, as it was already stated. As I mentioned, the RR interval in
observed healthy subjects ranged between 700 and 1400, which is already,
to a certain extent, a high range. If you speak about 700, we are close
to 90 beats per minute. So, therefore, despite the fact that these
subjects were lying down, they were probably stressed because 12 hours
in bed is kind of a difficult situation to handle. So I think that they
had some range of heart rates which were of interest.

Regarding potential stimulation of the adrenergic system, of course, we
could be concerned, but as was mentioned a moment ago, if you look at
these data which show shorter values of RR interval which potentially
may reflect eventually a higher heart rate with or without adrenergic
stimulation, we do not see any signal. We even see the white bars going
down. So I think there is not a big concern regarding this.

You mentioned also the vagal tone which speaks about low heart rate.
Again, we do not see at the therapeutic dose any signal, and even in the
supratherapeutic dose, it goes down, whether we speak about the Valsalva
maneuver or night. This is why I think we have not that much concern
about this part.

DR. HIRSCH: But to follow up, I\'m going to ignore those particular
safety data, which I agree are somewhat reassuring. It\'s more of a
methodologic question as we look at future drugs. When a drug is being
administered for a certain indication where certain physiologic
parameters may be known to change, straining at stool, coitus, straining
for urination, I was wondering if this method should be actually
evaluated in the clinical condition in which we know the drug is going
to be used. I just raise that for future regulatory questions.

DR. ZAREBA: Let me tell you that there are data ‑‑ and I\'m just trying
to pull out the appropriate slide ‑‑ showing the use of this method in
other conditions. May I have, please, slide number 43?

This particular slide shows the data for exactly the same approach, with
QT1000 using something like adrenergic stress produced by tilt test,
using nocturnal recordings, and using dofetilide, which is another drug
which may eventually not cause adrenergic problems but simply cause QT
prolongation. So in these studies, this method was also shown to be
useful in identifying a potential signal.

May I also have slide number 49 for a moment?

Just recently in December of 2002, Dr. Pentti Rautaharju analyzed almost
12,000 healthy subjects trying to look at this phenomenon, looking at
heart rate and looking at QT in absolute value and trying to identify
normal confidence intervals. So we already have substantial data to
learn what we should consider as the upper limit of normal without any
correction.

So the evidence is growing for this new method. I fully agree with you
that we do not have yet sufficient data in the literature, but I truly
believe that this method will be slowly, slowly more often presented at
these meetings because of their particular advantages.

DR. BORER: JoAnn and Tom.

DR. LINDENFELD: Drugs like this sometimes change the T wave, and I\'m
interested in just understanding your technique. If you know by the
Holter bin method how many beats are counted, how many actually are able
to be counted. And then if you know that, I wonder if that changes
between placebo and drug, and if it changes based on the RR interval. So
I\'m wondering if the drug were to change the T wave, if you would
measure less beats that might be altered with drug or at different RR
intervals. Just so I understand the technique better.

DR. ZAREBA: It\'s a very good question. Let me start with slide number
45 from the backup set.

On this slide, you see the number of complexes at each RR bin during the
four run-in placebo periods for all subjects. As you may see over here,
despite the fact that we are repeating this four times in the same
subjects, there is pretty much overlap, confirming that we have evidence
for a wide range of RR intervals.

Simultaneously, when we look at slide number 46, we look right now at
treatment periods, and of course, as you see in this blue line, for 40
milligrams of alfuzosin, there is some shift in number of complexes
which are eligible for analysis, naturally because the drug increases
heart rate, so we have shorter RR intervals dominating this. However,
the overlap throughout the entire recording is so substantial that we
can easily correct.

You also mentioned T waves, so I will ask you to show me slide number
30. We, in fact, were concerned that a drug like alfuzosin could
eventually change the morphology of T waves. As we know, some drugs
which affect the HR channel may lower amplitude of the T wave, and we
tried to look whether in this setting we have any evidence for flat,
notched, T wave or unusual U waves, which may eventually be of concern
regarding safety.

As you see on this table, we have no cases of flat T wave. We have just
very infrequent cases, single cases, of notched T wave, but there was
absolutely no difference between four arms of the study, and in terms of
unusual U waves, it\'s also very infrequent. So all together the
findings were very infrequent and it was not in any way associated with
drug.

Secondly, of course, a very flat T wave will compromise analysis of QT.
Therefore, in the rejection system, some of those T waves had to be
rejected because of the inability of measuring QT.

DR. LINDENFELD: Can we just go then back to the last slide just so I
understand this? I apologize. The one you just showed. Yes.

So that at higher heart rates, there are far fewer beats that can be
counted. Is that what this demonstrates?

DR. ZAREBA: I would not say far fewer because we speak about 300 beats,
300 beats over here, 150, 150 here.

DR. LINDENFELD: Well, but there are far more beats at higher heart
rates.

DR. ZAREBA: So 150 beats to analyze QT I think is sufficient.

DR. LINDENFELD: But at higher heart rates, that means you\'re throwing
out a lot more beats.

DR. ZAREBA: Yes.

DR. LINDENFELD: So fewer of the total numbers of beats can be counted.

So I guess I wonder if you\'ve thought about whether or not that
introduces any artifact into the measurement. In other words, at an RR
interval of 500, that\'s twice as many beats at a heart rate of 60 and
you have way fewer complexes.

DR. ZAREBA: Again, we are looking at the comparison of QT at specific RR
intervals, and if we look at, let\'s say, fewer beats versus higher
beats, of course, we may have some little bit different results, but all
together this will provide an overall good representation of behavior
every 10 milliseconds.

So I understand your point that it might be that if we have one bin
dominated by 3000 beats and another will just have 50 or 60 beats, this
other one might be not fully representative. But still this lower
threshold of 50 beats provides me with some comfort of why I\'m saying
that if we speak about 10-second standard 12 ECG, we usually have no
more than 10, 12 beats, and we rely all clinical decisions on this small
strip with 10 seconds, and we are comforted. Over here, we put a
requirement of having at least 50 beats for each bin, which is I think
pretty stringent.

DR. BORER: Can I just ask in follow-up? I\'m not sure that JoAnn\'s
total question was answered. I\'m given confidence by what you say. But,
JoAnn, I thought you were suggesting that in these RR interval regions
where there are fewer beats because the heart rate is, in fact, faster,
it\'s more likely that they will be rejected beats, and therefore that
the beats your actually sampling, even if there are 50, will be less
representative of the totality of what happened at that RR interval than
at slower rates where a smaller percentage and a smaller number of beats
would be rejected, and there might be some distortion in the results
occurring because of this differential rejection. I don\'t think you
specifically responded to that. Is that an issue?

DR. ZAREBA: Again, I generally agree with you that, of course, if we
have a smaller number of beats, especially if there are more of them
rejected, they will be less representative. The rejection rate over here
was very small. Why? Because of supine position. I agree with what was
commented before. In ambulatory conditions, this will contribute to more
rejection. But in the supine position, we had really a very limited
number of rejected beats.

DR. LINDENFELD: Again, it will be math off the back of the envelope
here, but it seems like six times as many beats were rejected. If you
look at an RR interval of 500, you only have 100 beats there.

DR. ZAREBA: It doesn\'t mean they\'re rejected. They simply were
limited. So you may not have patients reaching specific RR. This graph
doesn\'t mean that you have all of them rejected. We have simply the
number limited at specific heart rates. If you speak, for example, at
100 beats per minute, we had more or less 100 or 120 beats because these
subjects didn\'t present much more.

DR. KOWEY: Can I just put this in some perspective? We\'re talking about
measuring hundreds of beats, which is a standard ‑‑ we rarely have seen
that number of beats being measured. Granted, there\'s a differential
between the numbers you\'re measuring at high and low heart rates, but
we\'re still talking about an incredibly large sample size, which is not
anything like what we usually see.

And I just had a follow-up question. Your T wave question was very, very
important. If you could just clarify some of the methodology. Who looked
at the T wave morphology? Were they blinded? Did they have criteria for
calling what they called abnormal T waves? And was it done from a
12-lead ECG or just from a single lead from the Holter?

DR. ZAREBA: I think I will ask Dr. Pierre Maison-Blanche who performed
this work to comment on it because this will be probably the best source
of information. T waves were screened and he performed this analysis, so
I will ask him eventually to comment on it.

DR. MAISON-BLANCHE: Thank you, Dr. Zareba.

The T wave morphology analysis was based on 12-lead ECG analysis. A
slide which has been shown to you is coming from a 12-lead ECG analysis.
So the T wave categorization was made on all 12-lead data. That is my
first answer. And that has been done by a central lab service. Only the
Holter data has been analyzed by an academic core lab.

So how deep the persons were trained in the core lab is as follows. I
was personally in charge of training the physicians in charge of T wave
categorizations. So that was done with predefined menu and people were
trained to identify notched T wave, flat T wave, and U wave.

DR. KOWEY: And that was blinded analysis, blinded to the treatment?

DR. MAISON-BLANCHE: Both the Holter data analysis and, of course, the
12-lead ECG analysis was totally blinded.

DR. FLEMING: A couple of issues. First, if we could go to slide 51, I\'d
like to understand your results relative to what\'s in the FDA briefing
document and also what\'s repeated in the questions to the committee in
question 5 of the FDA.

These are the results from 5105, and they seem to differ from the
results that are presented to us in the FDA briefing document and the
questions. For example, if we look at these 10 milligram results for
Bazett, it\'s 3.3. I think FDA has 10.2. Fridericia, you have 1.6; FDA
has 4.9. Could you clarify?

DR. ZAREBA: Yes. I will ask Dr. Sylvain to clarify these differences.

DR. DURRELMAN: I\'m Sylvain Durrelman from biostatistics in
Sanofi-Synthelabo.

I would just like to clarify this point. The 12-lead ECG analysis was a
secondary analysis in these studies. Actually two analyses of these
12-lead ECG data were performed, one at the time of Cmax, and this is
the one that the FDA has selected in their briefing document. We have
also performed an analysis which covers the same time period as the
Holter period, that is time T7 to T11. That covers the time of maximum
plasma exposure with five ECG data points. This is what we have selected
in our main presentation as it is a good reference to compare with the
Holter bin method that is evaluated along the same period.

However, in our company\'s briefing document that was submitted to you,
we have provided, of course, the two analyses. And on page 54 of
Sanofi-Synthelabo\'s briefing document, you will find the time of Cmax
analysis for the 12-lead ECG, and the numbers are exactly consistent
with the FDA analysis. Overall, the numbers do not change by a great
deal, and the ordering is always the same with the effect at the top
dose of alfuzosin 40 milligrams being about half of what is observed
with moxifloxacin, with some minor numerical differences.

DR. FLEMING: Actually it looks like the numbers are, in fact, somewhat
different.

Let me go on to another question because the time is short, and the
essence of my question is on page 54. Could you go to slide 54? I\'d
like to make sure I understand the methodology you\'re using here.

Suppose you have a patient who has at baseline a heart rate of 55 and on
alfuzosin their heart rate is 60, and let\'s say they\'re on alfuzosin
40 milligrams. Their data point would be represented under the 60. Is
that correct?

DR. ZAREBA: It\'s every 10-millisecond bin. So it depends. In this
particular graph, we just selected bins which are representative. They
are not overlapping over here. So, of course, you will have five bins
between 950 and 1000. So for clarity, we didn\'t present them all.

DR. FLEMING: Well, let me just be specific. Suppose a patient had at
baseline a heart rate of 55, so they\'re at 1100. And suppose on 40
milligrams of alfuzosin their heart rate is 60. Then with their heart
rate at 60 on alfuzosin, you measure the QT. Correct? And so they would
enter into the column there that corresponds to 60.

DR. ZAREBA: Correct.

DR. BORER: Can I just interrupt one second? Maybe I\'ve completely
misunderstood, but any individual has a variation of heart rate from
second to second, minute to minute, hour to hour. If heart rate was
measured at 60 at the measurement moment and you actually did multiple
measurements over time or did a Holter, which is what you did for this
list mode bin method, then although the measured rate at the instant of
measurement for profiling here might have been 60, 2 minutes later on
the Holter, it might have been 57 or 56.

DR. ZAREBA: That\'s correct.

DR. BORER: And that patient\'s information would be categorized at 57
when it was 57, at 60 when it was 60, at 63 when it was 63. Is that
correct?

DR. ZAREBA: That\'s correct. It\'s the Holter bin method. It tries to
look at QT and specific heart rate. Whether it\'s 5 beats apart or 3
beats apart, we only establish this 10-millisecond range of overlap.
Otherwise, they are considered separately because of the dynamic nature
of QT.

DR. FLEMING: So you\'ve got a patient now that has a heart rate of 60,
and what we\'re computing here is the QT change is approximately, if I
can eyeball this, 2.5 seconds for those with a heart rate of 60. That is
precisely computed in what way? We\'re looking at the QT for this
particular patient at this point with a heart rate of 60 and we\'re
adjusting that regarding the placebo in what fashion?

DR. ZAREBA: I have this methodological slide from the main presentation
which shows the method.

DR. FLEMING: While you\'re pulling up the slide, my understanding is you
are, in fact, with this analysis adjusting for the fact that there is,
as you showed in that one slide, a definite relationship between QT and
heart rate.

DR. ZAREBA: Yes, slide 37 please.

As it was mentioned, there is this process of combining QT ‑‑ the QRS
complexes are generally beats from specific 10-millisecond bins. They
are combined and they may come from neighboring RR intervals, but they
may come from distant RR intervals, just to create a bin of 1000
milliseconds or 1010 milliseconds. They are averaged to represent
specific heart rates. On this average beat, we have measured QT manually
and blinded. So we speak right now not about just single beats which
represent a moment or an instantaneous change, but we speak about a
group of beats which is transferred into some average complex which is
representative for the entire class there.

Why is that? Because of potential influence of noisy beats or some
outliers, this signal averaging allows us to really demonstrate the good
reproducibility of the method.

DR. FLEMING: You still haven\'t gotten to my question. Essentially what
you\'re trying to do, going back to slide 54 ‑‑ what is intended here is
to understand what the change in QT is that is influenced by alfuzosin
beyond the element of what change should be if you simply looked at the
change in the heart rate. Is that correct?

Essentially what we realize is alfuzosin is changing the heart rate.

DR. ZAREBA: Yes.

DR. FLEMING: That intrinsically could change the QT.

DR. ZAREBA: That\'s correct.

DR. FLEMING: But we also know in untreated patients, if the heart rate
changes, the QT changes, and we\'re attempting to adjust that out.

DR. ZAREBA: That\'s correct.

DR. FLEMING: So if we look at the 60 data, for example, patients on
alfuzosin at 40 milligrams who, in fact, have a heart rate of 60 will
have a given QT or a given QT change. Is there, in fact, a subtraction
here when you compute this blue bar that is factoring out ‑‑ if somebody
started at 55 and went to 60 in their heart rate, you realize that their
QT, in fact, would have changed on the placebo. And you\'re subtracting
that out. So this represents the excess change in QT beyond that that
you would ascribe to a placebo change in QT or a natural population
change in heart rate.

DR. VILLAUME: Maybe Dr. Durrelman can clarify the method a little bit
along with, if necessary, Dr. Maison-Blanche who was the reading
cardiologist.

DR. DURRELMAN: Yes. Let me try to clarify from the statistical
standpoint first.

I would like to make the point that in the slide 54 that we have here,
you must understand that the subjects contribute to several of the
batches. Right?

DR. FLEMING: Sure. Not a problem.

DR. DURRELMAN: So if we can have the backup slide 44.

You have in this slide the distribution of subjects by RR bins. So
depending on the bins you are at, you have a sample size that is more or
less larger or smaller. Around the interval from 800 to 1200 that we
have decided, we have about all the sample size equals all subjects\'
experiences RR bins.

Now, when we go back to the main slide I think 54, what we do is to
classify the various bins during the run-in placebo period, time 7 to 11
hours at day 2, and on the other hand, classified the RR bins for all
subjects also during the treatment period at day 3. And for a given RR
bin corresponding to a certain heart rate, we do the comparison, and
then between this run-in placebo period and the treatment period. And we
do that then for all of the four treatment groups: placebo, two arms of
alfuzosin, and moxifloxacin 400 milligrams. Then we would be able to
plot this, adjusting for placebo.

DR. FLEMING: So am I correctly interpreting this, that if we focus on
the 60 heart rate column, what we\'re saying here is a patient that is
at 60 on alfuzosin would have about a 2.5-millisecond higher increase in
QT than you would expect from natural history adjustment for the
relationship that exists between heart rate and QT. Is that correct?

DR. ZAREBA: That\'s correct, using this placebo run-in method exactly at
7 to 11 hours.

DR. FLEMING: And then your overall reported summary for the increase at
40 is a weighted average of all of these blue bars. You\'re coming up
with an average of ‑‑

DR. DURRELMAN: 2.9 milliseconds.

DR. FLEMING: 2.9 and that\'s a weighted average.

DR. DURRELMAN: 2.9 milliseconds in the prospectively defined QT1000
parameter, which corresponds to the heart rate of 60, and that\'s a
weighted average. Right.

DR. FLEMING: A weighted average of the blue. So what we realize is that
the actual increase in QT relative to what you would expect it to be,
adjusting for heart rate, is in fact specific to heart rate, and you\'re
taking a weighted average of these.

I guess the last point in interpreting this, though, is if, for example,
somebody came in with a heart rate of 55 ‑‑ and that\'s the people over
here to my left ‑‑ and on alfuzosin those people would become a heart
rate of 60, the people here on my right, then essentially what this is
doing is it is looking at the alfuzosin person here that was on my left
and they\'re putting them in the bin over here on my right, with all of
these placebos who are now like them at 60, and it\'s making the
fundamental assumption that you\'re no longer comparing this person to
their true colleagues, their true randomized colleagues. You\'re putting
them in a systematically different bin under the assumption that the
only thing that really matters on QT is heart rate. It\'s the right
thing to do if the only thing that matters is heart rate. But if there
are other things that influence QT, this person who really belongs on my
left is not being compared to the comparable to people.

So that\'s a fundamental assumption to this approach that has to be
recognized that this approach is not pristine. It\'s in fact violating
the assumptions that we would typically look for of keeping people with
their colleagues with whom they\'re truly intrinsically the same, and
it\'s only valid if the only thing that matters about QT is heart rate.

DR. MAISON-BLANCHE: You\'re absolutely right, sir. But there is a
\"but,\" and my answer is a \"but.\" We have some time match. We
compared T7, T11 on the treatment to T7, T11 placebo, which means that
we tried ‑‑ at least we do our best ‑‑ to compensate for circadian
variations. I am not aware of such big efforts to do that in the past.
So we try to compensate for also the night influences. So first we try
to get rid of circadian influences. Then all the patients are in supine
positions on the run-in placebo and on the treatment. So in addition to
the circadian variations, which are non-negligible, we tried to
compensate for daily activities. We cannot compensate for multi-stress.
We cannot compensate for respiratory sinus arrhythmia. That\'s true. But
we did our best to compensate for the other influences.

Do I answer clearly your question?

DR. FLEMING: I understand but the concerns that I have which I think are
intrinsically unavoidable is that you\'re having to make assumptions
here, and I just want to make clear what those assumptions are.

DR. ZAREBA: I think we are in agreement with only this additional piece
of information. As we showed, on drug and off drug, there was
substantial overlap of RR intervals, allowing us to have, as I mentioned
before, at least 50 beats for each class, which allows us to really
demonstrate the representative QT interval for a specific heart rate.

DR. BORER: Tom Pickering and then Dan.

DR. PICKERING: Yes. I wanted to bring up the issue of respiratory sinus
arrhythmia that you just mentioned. These are young people who were
supine and probably breathing relatively slowly, and vagal tone tends to
be high in younger people I think. So one of my questions is, to what
extent is the RR variation due to sinus arrhythmia where you would just
have one very long RR interval per breath, whereas in an older
population taking the drug for therapeutic reasons where upright vagal
tone is probably going to be much lower and sinus arrhythmia are also
much less?

DR. MAISON-BLANCHE: Thank you for your question. Yes, it\'s true. So
back to my previous answer. We are dealing in this population with a
relatively high respiratory sinus arrhythmia. As far as I know, I
(unknown words) to get rid of that is that we are basing which is an
invasive technique which we usually cannot apply in this setting. So we
have to do something with respiratory sinus arrhythmia.

Among the two techniques which we investigated to compensate for
hysteresis, we manipulated the heart rate variability analysis to select
those beats which may be affected by the hysteresis phenomenon related
to respiratory sinus arrhythmia. In that population, what Dr. Zareba
said is true. We found that the rejection rate was 75 percent because
they have a significant respiratory sinus arrhythmia. Not only do you
expect but our findings in the elderly population, the rejection rate
will be smaller because they will have less respiratory sinus
arrhythmia.

So if we try to compensate for hysteresis, we will eliminate 75 percent
of beats. If we do not, if we put into the bins all the data, and I
analyze the presence of sinus (unknown word) phenomenon by the way in
the setting of 10 seconds of ECG strips, who knows what happens before
and after. At least from continuous ECG monitoring ‑‑ that may be part
of the discussion later on, but at least continuous ECG monitoring has
potential solutions. 10-second snapshots do not.

DR. BORER: Dan?

DR. RODEN: I don\'t know if I have a question or just a comment. Could
you put up your slide 39?

Tom, as a statistician, has come up with the fundamental problem that
the relationship between QT and RR is I think inevitably or terminally
confounded. You can\'t possibly sort out a true relationship. If you
have a drug that affects only QT, you might. If you have a drug that
affects RR through multiple mechanisms, QT through multiple potential
mechanisms, then trying to come up with a number is not going to work.
So I like this approach with the caveat that as long as it\'s being
analyzed in a way that\'s not rejecting systematically beats.

So I wonder, Wojciech, whether the bar that you show on the slide that
Dr. Fleming didn\'t like ‑‑

(Laughter.)

DR. RODEN: No, no. I can\'t remember what number that was.

DR. ZAREBA: Slide 54.

DR. RODEN: Don\'t go back to 54 yet.

But each individual has one line on drug and one line on placebo. So
there\'s a delta at any given QT that you want to select. Then you can
go on and you should be able to show us the delta QT with a standard
deviation or with a confidence interval, each derived from an individual
subject. Maybe that\'s what was bothering Tom.

DR. ZAREBA: These data are just mean change, and you may remember from
the main presentation I mentioned that the upper confidence interval was
5.5 milliseconds. So, of course, there is some range.

DR. RODEN: If it\'s not on the slide, I don\'t remember.

DR. ZAREBA: Yes, I understand. But if you go in the main presentation to
slide ‑‑ I don\'t have it here in front of me, but I am speaking about
the slide showing data for 40 milligrams, the table for 40 milligrams.

DR. RODEN: 53 I think actually.

DR. ZAREBA: Slide 52 please.

If you look here, we speak about QT1000. I understand that slide 54
showed different other heart rates, but if you look at this particular
situation, if you look at the confidence interval, the upper limit is
5.5 milliseconds. This is what we are aware of, that of course, there
will be patients who will show 4 milliseconds, some others 1
millisecond, and some of them even 5 and higher milliseconds, which is
still very modest prolongation.

DR. BORER: Ed Pritchett, do you have anything to ask of this speaker?

(No response.)

DR. BORER: I think we\'ve totally lost the hookup now.

DR. PRITCHETT: Can you hear me, Jeff?

DR. BORER: Now I can hear you.

DR. PRITCHETT: No. I\'m actually able to follow this remarkably well,
given the technology I\'ve got here. I have enjoyed this.

I like this Holter bin method. I just would have one comment, though, as
we try and struggle with how to use it, and that is, why do we think
that the QT interval is something to worry about? And it\'s because
historically we have learned that drugs that prolong the QT interval are
associated with a higher risk of this arrhythmia that we call torsade de
pointes. Most of what we know about the QT interval for those drugs was
measured with 12-lead ECGs. It\'s what we know from studies of quinidine
and sotalol and more recently dofetilide and drugs like that.

What we\'ve got here is a very interesting assay for QT interval
effects, but we don\'t know what predictive value it has because we
haven\'t done lots of drugs to see if they\'re studied with the Holter
bin method, whether it predicts the occurrence of QT. But as an assay
for QT interval, I find this to be quite an interesting idea and quite
attractive. End of my comment.

DR. BORER: Thank you.

DR. ZAREBA: Just in reply to this comment, I want to emphasize that, of
course, as I mentioned, we analyze our data not only using the Holter
bin method, but we use traditional 12-lead with very recently proposed
subject-specific correction. So we try to address this from both angles.

DR. PRITCHETT: Yes, I agree.

DR. BORER: Jeremy, how many minutes is your presentation approximately?

(Laughter.)

DR. RUSKIN: I\'ll try to stay under 10.

DR. BORER: Okay. The reason I\'m asking is that I want Steve to have the
opportunity to comment after you present. Well, do you have any comments
you want to make before Jeremy?

DR. NISSEN: I just had one. Could I see that slide 54 again?

(Laughter.)

DR. ZAREBA: It\'s a popular slide.

DR. NISSEN: Yes, it\'s a popular slide.

I guess the question I would ask the panel more than you is, is the
relevant number the average change across all heart rates, or is the
most relevant number for this analysis what the worst case scenario is?

Given the fact that what we\'re really trying to do is to determine
whether a drug that\'s used for a nonlethal condition has the potential
for a lethal side effect, my argument would be that if we\'re going to
use this method, we might want to look at what is the worst case. At
what heart rate is the change the greatest as a security blanket, if you
will, to make certain that we\'re not in a range where there\'s a lot of
risk because clearly heart rate does change from moment to moment. What
we really want to know is what is the risk that this drug is going to
cause harm.

And so when I look at the data, it looks to me like people that are
around 60, 57, 55, if they get a lot of exposure, will be in the range
of 4 or so milliseconds prolongation. Now, what does that mean? That\'s
another question entirely.

But in terms of the analysis, I think one could make a case here that
it\'s not really quite fair to average this across every imaginable
heart rate and then sort of throw it into a great big gemisch because
that\'s not really what an individual patient experiences in terms of
risk. So that\'s a comment before I exit.

DR. ZAREBA: I think it\'s a very valid point that we have to take into
account that variation and possibilities that the response will be
different. But to my knowledge, we don\'t know of a drug that produces
arrhythmia and has QT increase properties at any given heart rate at the
5-millisecond range.

DR. NISSEN: And that will be discussed later, but in terms of what
number we actually use as we think this through, my argument might be
that we use the worst case number if we\'re going to use this kind of
bin method.

DR. KOWEY: Just since you addressed it to the committee, I\'ll take a
shot at this. But I think we\'re looking obviously, at central tendency
here, and you did present data on outliers. When you said the word
\"worst case scenario,\" the thing that always comes to my mind is an
outlier analysis. They did two kinds of outlier analyses. They did one
looking at the worst QTs and then they also did the one with the worst
plasma concentrations. In both of those, \"what\'s the worst thing that
could happen\" scenarios, we didn\'t really see a strong signal of a
problem.

So I agree with you. I think that we were getting riveted on central
tendency measurements, and obviously they\'re very important. But in
real life what we want to know is what could happen in the worst case,
and I think that question is very germane. But I think that the
information at least has been presented. We can debate whether we like
it or whether we don\'t like it, whether we find it reliable, but it\'s
there.

DR. BORER: Tom.

DR. FLEMING: I\'d just like to reinforce two points that I think Steve
has made. One is, as we look at these results, it\'s very important to
know whether there is an interaction between heart rate and age, for
example, or another way of saying this is if these tables were generated
in a younger population, are these exact same associations seen in an
older population, which is a very fundamentally important assumption
we\'re having to make.

The second point that comes to mind on what Steve\'s saying is if, in
fact, you had 1 percent of the population in whom the increase was, in
fact, 20 and the rest of the population, the increase is 0, and you\'re
looking at the weighted average, you\'re going to see something that\'s
trivially small that wouldn\'t concern us.

But if it\'s 20 in 1 percent of the population and it would induce a
high rate of torsade in that subgroup, the challenge we\'re running into
here is if we\'re dealing with efficacy that\'s in a life-threatening
setting, then you accept a small risk of life-threatening adverse
events.

On the other hand, if you\'re not looking at that for benefit, then you
have a very low threshold and it does become critically important not to
look at averages, but to, in fact, look at outliers because it\'s
unacceptable to have 1 percent of the population that in fact would be a
very high level.

DR. ZAREBA: In this study, there was no evidence for outliers which
would be of major concern using both classical methods and using even
Bazett correction method. Again, I think that there are no data in
post-marketing studies indicating any increased risk. I understand that
we do not have a heart rate for this post-marketing data, but across the
board there is no signal indicating this drug or other drugs of alpha
blockers are associated with increased proarrhythmia.

DR. BORER: Now we can move on to Jeremy.

I\'d like to make one point ‑‑ two points actually as you\'re coming up
here. This doesn\'t presuppose any final comments that this committee
will make.

While we\'re all concerned about outliers, et cetera and all the points
that have been made, I think it\'s important to reinforce what comes
across in the book that you gave us and in that slide which is that you
had a positive control. We\'re focusing on the blue bar, but look at the
red bar, a positive control, a drug that affects QT but doesn\'t seem to
cause arrhythmias, and it caused more of an effect on QT than this drug
did. And I think that\'s important for us to remember as we go forward.

The final comment is that Sanofi-Synthelabo has its headquarters, I
think, somewhere outside the United States, so I have to make the point
that Massachusetts in the United States has 4 S\'s not 5.

(Laughter.)

DR. BORER: Thank you.

DR. RUSKIN: Thank you, Jeff.

Mr. Chairman, ladies and gentlemen, I\'ll try to keep my comments very
brief. I\'m just going to offer a couple of summary statements about the
limitations of correction formulae, the adequacy of the study design in
5105, the results of that study, one comment about pharmacovigilance and
one about safety margin.

This slide shows you four different correction formulae used in the 5105
data. These are data points from the population in study 5105 showing
you the relationship between the corrected QT interval and the RR
interval, that is, the heart rate. These are data that are familiar to
all of you by this point, both prior to and during this discussion, and
that is, that the goal of a correction formula is to eliminate any
correlation between heart rate and QTc.

A number of comments have been made, important ones, by panel members
about other influences on the QTc, but by far the most important, the
most potent influence on QT is the heart rate. So the goal in any
development program is to correct for heart rate, to achieve a 0
correlation between heart rate and the QTc. In general, what\'s done is
to try to correct the QT for what it would be at a heart rate of 60.

When these data are corrected using the Bazett correction, you can see
that as the cycle length decreases, that is, as the heart rate
increases, there is a rather dramatic over-correction of the corrected
QT interval. So there\'s a correlation here between heart rate and QTc
that should be there.

This is somewhat mitigated by use of the Fridericia formula which brings
the slope of that regression line a little closer to the optimum of 0.

Much better corrections are achieved using either a population or an
individual subject-based correction in which the correlation becomes
close to 0. That is, the QTc becomes a near constant interval.

The Holter bin method, about which you\'ve heard and about which
there\'s been a lot of discussion already, avoids entirely the need for
rate correction by using the bin method and by comparing QT intervals at
comparable heart rates before and after the drug.

Importantly, the results in this trial, which you\'ve just heard,
correlate very closely both with the group and subject-specific
individual corrections using standard 12-lead ECGs. What you\'ve also
heard from Dr. Pritchett and others is that there\'s limited experience
with this technique in drug trials.

With regard to the study design of 5105, I want to make just a couple of
points. The first is that the study covered a 4-fold dosage range, 10
milligrams and 40 milligrams, and at the 40 milligram dose, exposures
exceeded those seen with maximum metabolic inhibition with 400
milligrams of ketoconazole, as well as exposures seen in patients with
renal impairment.

In addition, a substantial percentage of healthy volunteers experienced
postural hypotension at the dose of 40 milligrams.

The study also used a well-studied positive control, moxifloxacin, for
which an effect size has been determined in many other drug studies, to
demonstrate the ability of this design to detect small changes in QT
intervals induced by a drug.

And finally, using 12-lead ECG measures known to everybody here, there
is internal validation within this study of the Holter bin method.

Just to reiterate what you heard from Dr. Oppermann about exposures, the
40 milligram dose of alfuzosin provides exposures that are roughly
4-fold those seen with the standard therapeutic dose of 10 milligrams,
and these exposures exceed what is seen with maximum metabolic
inhibition with 400 milligrams of ketoconazole.

These are the QT and QTc results in 5105 for alfuzosin 10 and 40
milligrams and a standard therapeutic dose of moxifloxacin, 400
milligrams. As you can see, the QT1000 correlates very closely with what
was observed using both individual or subject-specific and group
correction formulae with standard 12-lead electrocardiograms. And this
effect size at the standard therapeutic dose is, at least to my
interpretation, essentially undetectable.

At four times that exposure, again exceeding exposures achieved with
maximum metabolic inhibition, the effect size, regardless of the
correction formula on the 12-lead ECG or using the QT1000 method, is
below 5 milliseconds and it is half that seen with a standard
therapeutic dose of moxifloxacin, a drug in wide use.

This slide compares for you the effect sizes seen in the two studies
that used the Holter bin method, 4532 and 5105, and despite very small
numerical differences in the effect size at 10 and 40 milligrams, I can
see no statistically detectable difference in the effect size at these
two doses between the two studies.

With regard to outliers defined as a QTc greater than 450 milliseconds
or a change in QTc of greater than 60 milliseconds, there were none with
any correction formula other than the Bazett formula. And all the QTc
Bazett outliers occurred in association with significant increases in
heart rate, that is, in patients who had changes in heart rate ranging
from 18 to 49 beats per minute.

There were no outliers defined as a QTc greater than 500 milliseconds in
any study with any method used, and there was no QT or QTc greater than
440 milliseconds by any correction method in subjects with
concentrations exceeding five times dose therapeutic, that is, in the PK
outliers. And these outlier analyses were alluded to by several members
of the committee earlier with regard to their significance in detecting
some signal of risk.

In 15 years of use and an estimated 3.7 million patient-years, there has
not been a single case of torsade de pointes reported with alfuzosin.

This slide summarizes for you, as you saw earlier, the IC50s for hERG
and the IC50 to Cmax therapeutic concentrations for drugs known to cause
torsade de pointes compared to alpha 1 blockers. Specifically with
regard to alfuzosin, you can see that the IC50 for hERG is three to four
orders of magnitude higher than with these drugs, and the ratio of IC50
to Cmax is two to four orders of magnitude higher than with drugs known
to cause torsade de pointes.

Shown graphically, if one plots the IC50 on a linear concentration scale
shown here and compares it to exposures seen with alfuzosin 10
milligrams, 40 milligrams, and in a number of clinical scenarios,
including renal impairment, elderly age, and a combination thereof, you
can see that in fact you simply can\'t detect the exposures here in
relation to the IC50 for hERG on a linear scale. If you plot this on a
log scale, these concentrations or these exposures do become evident and
you can see again that alfuzosin 40, which produces the largest exposure
of any of these scenarios, is at least two or more orders of magnitude
below the IC50 for hERG.

Just a couple of comments about drug known to cause trouble, the
paradigm for difficulty with a drug that has a small effect size at a
standard therapeutic dose, terfenadine, an agent which is well known to
everybody on this committee.

Terfenadine, when taken at standard therapeutic doses, at peak has a
QTcB effect of about 18 milliseconds, and it\'s a lot lower than that at
non-peak, probably about 8 milliseconds. However, when exposed to a
metabolic inhibitor at standard therapeutic doses, a non-peak increase
in QTcB exceeding 80 milliseconds is observed, and we don\'t know what
that effect size is at peak.

It\'s important to contrast this with the observations on alfuzosin
which at standard therapeutic concentrations has a virtually
undetectable effect on QTc using an appropriate correction formula, and
at an exposure four times that of the 10 milligram dose and exceeding
what is seen with maximum metabolic inhibition, the effect size remains
under 5 milliseconds. So there\'s no way to get from here to here with
this drug.

Questions have been raised about other patient populations, high risk
subsets. With regard to age, the primary issue that arises in that
circumstance is one of increased exposure, and we\'ve seen from the data
presented by Dr. Oppermann that increased age is associated with an
exposure that goes up about 1.3-fold. So it\'s not comparable to the
4-fold increase that\'s seen at the 40 milligram dose, data for which
there is QTc information, and that change remains under 5 milliseconds.

With regard to patients with heart disease, particularly advanced heart
disease, hypertrophy, congestive heart failure, issues raised by Drs.
Kowey and Nissen, those substrates are clearly inherently unstable, high
risk substrates, and they can be viewed as effect amplifiers. But I know
of no situation in which a drug with a very small effect size, even
under conditions of maximum metabolic inhibition or maximum exposures
exceeding those achieved with maximum metabolic inhibition, in normal
volunteers has been unmasked to exhibit a huge effect when given to
patients with underlying heart disease. I\'m not aware of a single
situation in which that has occurred. So there\'s no question that risk
will be increased for anything related to arrhythmias in patients with
advanced heart disease, advanced hypertrophy, congestive heart failure,
but we\'re talking here about an effect size that is so small that even
a multiple of that would not, based on any experience we have to date,
be associated with risk for torsade de pointes, very different from the
kind of situation we see here. Again, this was unmasked in healthy
volunteers.

So in conclusion, the QT effects of alfuzosin are very well
characterized. Even at exposures four times those seen at the standard
therapeutic dose and exceeding exposures achieved with maximum metabolic
inhibition, the effect size is less than 5 milliseconds, and this occurs
at a dose associated with postural hypotension in 20 percent of normal
volunteers. The effect size at this 4-fold exposure is about half that
seen with a standard therapeutic dose of moxifloxacin. There are no
outliers using appropriate correction methods, and in 15 years of
clinical use and experience exceeding 3.5 million patient-years, there
has been no case of torsade de pointes reported.

Thank you.

DR. BORER: Thank you very much, Jeremy.

We\'re going to take a break in a moment. Before we do, if there are any
questions that have to do with clarification of what\'s been presented,
let\'s raise them now. Otherwise, if we\'re going to get into the
philosophy and judgments about what we\'ve seen, let\'s hold it until a
little bit later.

Dan and then Blase.

DR. RODEN: Just two tiny questions. Jeremy, I don\'t think you\'re the
one to answer this, but maybe you are.

Does the agency or anyone know or can they provide information on the
safety of moxifloxacin, number one?

And number two, is there overdose experience with alfuzosin?

DR. RUSKIN: With regard to the first answer, I think I would defer to
FDA for that information because I\'m sure they have more than we do.

There is some overdose experience with alfuzosin. It\'s small but the
company can provide that.

DR. RODEN: And 3.5 million patient-years is 1 patient for 3.5 million
years or?

(Laughter.)

DR. RODEN: How many patients?

DR. RUSKIN: Actually it\'s 2 for half that.

(Laughter.)

DR. RODEN: How many patients?

DR. SALLIERE: Good morning. I\'m Dominique Salliere. I\'m the head of
pharmacovigilance in Sanofi-Synthelabo.

To answer your questions concerning overdosage, maybe I can have slide
number 2. We received during the last 15 years only 5 cases of
overdosage, but it is interesting to note that the patient had taken
between nearly 40 milligrams up to 100 milligrams, and 4 out of these 5
patients were over 75 milligrams. And no cases of arrhythmia,
ventricular arrhythmia were reported. And one severe hypotension was
reported. This is expected with the ingested dose, and in all cases, the
outcome was favorable. So I think that up to 10 times the recommended
therapeutic dose, no ventricular arrhythmias were reported.

DR. CARABELLO: The 3.5 million patient-years safety data are, if robust,
to my mind very compelling because they would account for all the
vagaries that we discussed here this morning between age and the
presence of heart disease, changes in barometric pressure, and so forth.
How robust are these data? Is it simply that dead men don\'t talk?

(Laughter.)

DR. CARABELLO: Or is the reporting structure in the countries from which
the data come robust?

DR. SALLIERE: To calculate this number, we have taken the number of
tablets sold with the mean recommended dose. So we determined the total
number of patients exposed at this for 1 year.

Alfuzosin is marketed in Europe and pharmacovigilance has been set up
for a long time, and there is active pharmacovigilance in all countries
where alfuzosin is marketed. Periodic reports are submitted to the
health authorities and no questions related to ventricular arrhythmia
were raised by any health authorities and no variation of the labeling
was requested.

DR. BORER: Doug, I assume that in the FDA presentation, you\'ll be
covering the issue that was raised by Dan about the data about a
positive control. Is that right?

DR. THROCKMORTON: Well, I don\'t want to speak for the other speakers.
I\'m not sure or not. It\'s true that we monitor the reports of torsade
for moxi, and without getting into specifics of those, I think it\'s
safe to say that we see no clear signal for a ‑‑

DR. MacCARTHY: This is Paul MacCarthy from Bayer Medical Lab. We will
cover some of the moxifloxacin safety data in our presentation.

DR. BORER: Okay, great. Thank you.

Then we\'ll take a 15 minute break. I\'m sorry. We have a question
before we take a break. Tom.

DR. FLEMING: A question for Jeremy, and while he\'s getting up to the
microphone, just a curiosity on slide 17. I have no question terfenadine
has a higher effect. It\'s curious that you presented the Bazett having
just been lectured on the fact that that\'s an overestimate.

(Laughter.)

DR. FLEMING: I want to understand. I thought you were saying something
to the effect that, yes, as Steve was mentioning, there is in fact some
particular concern that people could be at high risk, people with
ischemia, heart disease, whatever. Did I understand that what you were
saying was that, however, for other interventions that would induce the
level of QTc change that we\'re seeing here, there\'s no evidence that
it has induced adverse effects in such patients? Could you repeat the
essence of your message there?

DR. RUSKIN: Let me try to answer the first question or the first comment
first. With regard to presenting the data for QTcB, I presented it
because that\'s the data that\'s available for terfenadine. That\'s how
it was analyzed and published, and there\'s no way to present it with
any other analysis.

In addition, terfenadine, while it has a small effect on heart rate, is
not close to what you see with alfuzosin, but I certainly agree that
Bazett is not the optimal formula for any drug.

With regard to what I was saying, which was simply a comment, because
nobody has data in tens of thousands of patients with heart failure to
know exactly what magnitude of increased risk one may see with a
QT-prolonging drug in that population. The comment I was trying to make
was that we know that that is an effect amplifier, but there\'s no
evidence with any drug that it has the kind of impact that you see with
drugs that have metabolic liability, the drugs that can have a very
small or modest effect size at standard doses that can then go up by an
order of magnitude when their metabolism is inhibited. And that\'s the
commonest paradigm for getting into trouble. It\'s true of cisapride.
It\'s true of terfenadine. It\'s true in a number of situations.

DR. FLEMING: I had thought what you were addressing was the setting of
where we would have people who are at intrinsically higher risk with
ischemia, heart disease, et cetera in whom there may be, in fact, other
drugs such that you can have drug-drug interactions that would
exacerbate the problem because of their effects on metabolism, and that
in essence you were saying for such settings with other agents that
would have modest increases in QTc, there\'s no evidence that that in
fact translates into substantial higher risk.

If that\'s what you were saying, it just sounds like potentially an
absence of evidence doesn\'t mean evidence of absence type of scenario
here. Do we really know? And I\'m not criticizing. I\'m just recognizing
the intrinsic limitations of really getting reliable data as to what the
effects would be in such people.

DR. RUSKIN: No, I hear you and I agree with what you\'re saying. There
is no way to get a scientific answer to that, particularly the
interaction problem, the pharmacodynamic interaction problem, which is
very difficult to study and hard to get a handle on in any population.

I think the best that you can end up with is pharmacovigilance which we
know has very significant limitations, but the fact is that this drug
has been marketed for 15 years in many millions of patients with no
labeling restrictions whatsoever in a population that has a prevalence
of heart disease of around 50 percent. They\'re older people with heart
disease. And there have been no signals, not a single case of TdP
reported, and no sense of a proarrhythmia signal that has come to light
in any of the countries in which it\'s been marketed. Now, that is
highly imperfect data. I would be the first to admit that, but I think
it\'s about the best that one gets in this kind of situation.

DR. FLEMING: But where I would expect under-reporting would be precisely
the setting where the kinds of outcomes that I would care about are, in
fact, not rare due to natural causes in those populations.

DR. RUSKIN: That\'s exactly correct.

DR. FLEMING: So if in fact we\'re increasing by 5 percent, we may not
see that reported at all because this is a setting where those events
should occur even in the absence of an intervention.

DR. RUSKIN: You can\'t exclude that possibility. Absolutely.

DR. BORER: With those comments well in hand, we\'ll take a 14-and-a-half
minute break, and we\'ll begin exactly at 11 o\'clock.

(Recess.)

DR. BORER: We\'re now 6-and-a-half minutes behind schedule. So if we can
reconvene please.

We will go on to the presentation from Bayer, and we\'ll deal with any
residual questions about either product when we get to our discussion in
the afternoon. The presentation with regard to Levitra will be
introduced by Mary Taylor, who is the Vice President for Regulatory
Affairs in North America of Bayer.

MS. TAYLOR: Good morning, ladies and gentlemen, Dr. Borer, members of
the advisory committee, and FDA. We are pleased to present to you today
our product, Levitra, vardenafil hydrochloride, NDA 21-400. This product
has been co-developed and will be co-promoted by Bayer Pharmaceuticals
Corporation and GlaxoSmithKline.

I\'m Mary Taylor, Vice President of Regulatory Affairs for North America
for Bayer Pharmaceuticals Corporation.

The agenda for today is I will provide a brief introduction to the
product.

This will be followed by an assessment of QT, QTc, effect of vardenafil
by Dr. Tom Segerson. Tom has been with our program for a long time and
is now Vice President of Medical and Scientific Affairs for Bayer
Canada.

Dr. Joel Morganroth will follow that with an assessment of QT study
designs, heart rate correction factors, and arrhythmias associated with
QT-prolonging drugs.

We have with us a distinguished panel of consultants. Dr. Joel
Morganroth is from the University of Pennsylvania and eResearch
Technology. He has been an advisor for FDA and HPB.

Dr. John Camm is a professor of clinical cardiology at St. George\'s
Hospital in London, also a well-known cardiologist and an expert in QT
assessment.

Dr. Gerald Faich from Pharmaceutical Safety Assessments is an expert in
epidemiology and post-marketing risk assessment and former head of drug
safety at FDA.

We have Dr. Gary Koch, a professor of biostatistics from the University
of North Carolina, and Dr. Udho Thadani, Professor of Medicine from the
University of Oklahoma, an expert in ischemic heart disease.

These individuals will be available for questions, as well as people
from Glaxo and from Bayer.

Our proposed indication for Levitra is for erectile dysfunction. The
starting dose is 10 milligrams which may be titrated up or down as
necessary.

The NDA was submitted in 2001. This was followed by an approvable letter
in July of 2002. The application is currently under review at FDA.

It is approved in 34 countries: UK, Germany, and 13 other European
countries, as well as Australia, New Zealand, and several Latin American
countries. The product has been on the market since March of this year.

You can see here we started our phase III development program in
approximately the year 2000. There were numerous changes in the
methodologies to assess QT prolongation during that time. As you can see
here, as mentioned earlier, there were several guidances and proposals
issued post the development of our phase III program. Health Canada, the
ICH, and as Dr. Throckmorton mentioned, the FDA issued their draft
concept paper in November 2002.

This brings us to the current topic of today. In our clinical
pharmacology program, we showed an equivocal effect on the corrected QT
interval. FDA was concerned about what could potentially be observed
with supratherapeutic doses and asked us, therefore, to conduct a
definitive QT study. We are here today to talk about our clinical trial
design, approaches to correction factors, and the risk of cardiac
arrhythmia.

We have worked very closely with FDA on this clinical trial, and we
would like to take this opportunity to thank them for the excellent
collaboration.

We would also like to take this opportunity to thank the entire
GlaxoSmithKline team for the conduct of this study.

Next I would like to introduce Dr. Tom Segerson who will present the
QT/QTc effect of vardenafil. In conclusion, we hope you agree that we
have conducted a definitive study which shows no clinical concern.

DR. SEGERSON: Thank you, Mary.

Good morning. In my presentation I\'d like to present some background
information on vardenafil. Specifically I\'ll talk about the
pharmacology and mechanism of action, the efficacy and adverse event
profile, and some pharmacokinetic data from humans.

In addition, I\'ll provide some information that is specifically
relevant to evaluation of the QT interval from our preclinical studies,
clinical pharmacology studies, and also from the phase III clinical
studies.

And finally, I\'ll discuss the results from a study which was
specifically and rigorously designed to evaluate the effect of
vardenafil on the QT interval.

Vardenafil is a potent inhibitor of phosphodiesterase type 5 with an
IC50 of approximately 1 nanomolar. Vardenafil is also highly specific
for the subtype of PDE which, when inhibited, leads to the accumulation
of cyclic GMP in smooth muscle cells of the corpus cavernosum of the
penis and potentiates thereby the erectile response.

PDEs of several types are also distributed throughout the vascular
tissue and thus effects on blood pressure and heart rate are expected
with these compounds. In fact, we have observed in our clinical
pharmacology studies transient effects on both blood pressure and heart
rate after a dose of vardenafil which peak around the Cmax, or maximal
concentration, and have a duration of approximately 1 half-life. The
magnitude of the effect we\'ve observed is up to about 7 millimeters of
mercury reduction in systolic and diastolic blood pressure and about a
mean increase in the heart rate of approximately 4 beats per minute.

Vardenafil has also been shown to be efficacious in the treatment of
erectile dysfunction in our clinical studies, and shown here are data
from studies from the general erectile dysfunction population. In
addition, we have demonstrated efficacy in populations that are
typically more resistant to treatment. Shown in these figures are data
from this pivotal study in the general population where doses of 5, 10,
and 20 milligrams of vardenafil were both clinically and statistically
superior to placebo as measured by the Erectile Function Domain of the
International Index of Erectile Function. This is a validated
questionnaire which is a standard and accepted endpoint for the
establishment of efficacy in these compounds.

In addition in a study in diabetics, doses of 20 and 10 milligrams were
also superior to placebo.

The next slide shows a summary of the safety data from our clinical
program. This is looking at the incidence of adverse events in
placebo-controlled trials. Shown here are the adverse events of
vardenafil compared to placebo. In the vardenafil group, approximately
half of patients reported an adverse event compared to approximately
one-third of patients in the placebo group. And if we look at the most
common adverse events that occurred more commonly in vardenafil, those
were headache, flushing, rhinitis, and dyspepsia, which are adverse
events that are commonly observed in trials of PDE5 inhibitors.

The pharmacokinetics of vardenafil demonstrate that it\'s rapidly
absorbed and eliminated from plasma as shown here in the pharmacokinetic
profile in a clinical pharmacology study in men after a single dose of
20 milligrams. The maximal concentration is achieved at approximately 1
hour, half-life is approximately 4 to 5 hours, and at 24 hours, there is
only about 1 to 2 percent of the maximal concentration present in
plasma. This, therefore, indicates that with a minimal interval of 1
day, of exactly 1 day, the chance for accumulation of vardenafil is
small. Moreover, these data suggest that to evaluate any effect on the
QT, a single-dose study is appropriate.

The elimination of vardenafil from plasma occurs by hepatic metabolism
principally and to a lesser degree by renal excretion.

The next slide shows the result of hepatic metabolism which results in a
series of metabolites, and here showing the pharmacokinetic profile of
those metabolites compared to vardenafil, the parent enzyme, in a
logarithmic scale to demonstrate the similarity in both the time to
maximal concentration and also the elimination profile of these
metabolites. This, therefore, suggests that also for evaluation of
potential effects of the metabolites on the QT interval, a single-dose
study is appropriate and also that the potential for accumulation of
metabolites is approximately the same as with the parent enzyme.

The metabolites themselves are formed by hepatic metabolism through
largely cytochrome P450 CYP3A4 as well as CYP2C9 and thus the
pharmacokinetics of vardenafil are susceptible to inhibitors of CYP3A4.
We, therefore, evaluated a number of such inhibitors and the most potent
effect or the greatest magnitude of effect that we observed was with
ritonavir, an HIV protease inhibitor, which is both a very potent
inhibitor of CYP3A4 but also an inhibitor of CYP2C9. Thus, we concluded
that the co-administration of ritonavir would represent the scenario of
maximal metabolic inhibition.

The next slide shows data from a study where we sought to determine a
single dose of vardenafil that would achieve levels in plasma that match
or exceed those under maximal metabolic inhibition. The parameter we
evaluated was Cmax, with the assumption that the maximal effect on QT,
if present, would vary instantaneously with the concentration of
vardenafil and thus maximally occur at Cmax.

Moreover, we studied a dose of 5 milligrams in combination with
ritonavir, with the agreement of the FDA, as this is the highest dose
recommended for concomitant use with potent CYP3A4 inhibitors and thus
covers the proposed labeling for concomitant use of these compounds.

These data are crossover data from the same subjects showing the mean
Cmax and individual Cmax data after a single dose of vardenafil 5
milligrams, after a dose of vardenafil 5 milligrams plus ritonavir at a
maximal clinical dose, and after a single dose of vardenafil 80
milligrams. And the mean Cmax after the single dose of 80 milligrams
exceeds both the individual as well as the mean values observed after a
dose of 5 milligrams of vardenafil on the background of ritonavir at
steady state. Thus, the dose of 80 milligrams of vardenafil would
represent and cover the scenario of maximal metabolic inhibition.

In addition, I should mention that we did study doses higher than the 80
milligrams, specifically 120 milligrams, and this dose was not well
tolerated in normal volunteers.

Also, I should mention that ultimately when we studied the single dose
in the QT study that I will present subsequently, the distribution of
Cmax values mirrors that we saw in this study.

Next, I\'d like to cover some of the data that we developed during
development to assess the potential for effects on the QT interval for
vardenafil. These include preclinical data. In vitro we evaluated the
effect of vardenafil on the hERG potassium channel which encodes the IKr
potassium current, a component of the late repolarization phase of the
myocardial action potential and also the target for all known drugs to
affect QT and produce torsade de pointes.

We compared the results of vardenafil and sildenafil in vitro, and the
IC50s for both of these compounds were relatively similar, 30 micromolar
for vardenafil, 47 micromolar for sildenafil, and compared to the free
concentration after maximum clinical dose, which we would consider the
relevant comparison to in vitro conditions in the absence of protein,
both compounds had IC50s for hERG which were at least 1,000-fold above
the free concentration after maximum clinical doses, 100 milligrams of
sildenafil and 20 milligrams of vardenafil.

In vivo we also evaluated the effect of vardenafil on the QT interval in
beagle dogs, which is a recommended preclinical model for this
evaluation, and moreover, in the case of vardenafil, the metabolic
pattern of vardenafil in the beagle dog is very similar to humans.

In our safety pharmacology studies in both anesthetized and conscious
beagle dogs at doses up to 10 milligrams per kilogram, we observed no
effect on the QTc interval, and the concentrations that we achieved with
these doses were with respect to the maximal clinical dose at levels
achieved after 20 milligrams in humans, 100-fold greater, and with
respect to the concentrations of metabolites after a 20 milligram dose,
at least 10-fold greater.

In our clinical pharmacology program, although we did not have a study
that was specifically designed to evaluate the QT, we did have in six
placebo-controlled studies paired electrocardiograms pre and 1 to 2
hours post dose that were part of the standard clinical safety
assessment. They included studies evaluating doses up to 80 milligrams.
If we looked across the results from these studies, which as I said,
were not specifically designed to evaluate the QT, we saw what we would
interpret as equivocal changes on the QT and QTc intervals with no
obvious dose-response relationship.

In our phase III program, we also did not have specific design in those
studies to evaluate QT pre and post dose because of the interval use. We
had very little electrocardiographic data that correlated with a recent
dose of vardenafil. But even in examining those limited data, we did not
observe any consistent effect on the QT interval.

We could, however, evaluate the incidence of adverse events which may
signal an occult ventricular arrhythmia in the sample size from our
clinical trials at least, and these specifically are syncope, dizziness,
palpitation, and seizures. In the case of syncope, dizziness, and
seizures, these events were not very common, but we didn\'t observe any
difference between placebo and active. In the case of dizziness, there
was a greater incidence than in placebo, but given the vasoactive
effects of vardenafil, we would not consider this a very sensitive or
specific adverse event for occult ventricular arrhythmia. We did not
observe torsade de pointes in our clinical trials with vardenafil.

If we examine the circumstances of death that occurred in our clinical
trials with vardenafil, I should say up front that we had 9 deaths that
have occurred in patients after enrollment in the study but before
receiving treatment. 7 of these deaths were actually cardiovascular in
origin, and that underscores the risk for death in the population that
we studied in our clinical trials.

In our completed clinical trials, we have observed 7 deaths. This shows
the treatments under which those deaths occurred: 1 on placebo, 1 on
sildenafil, a total of 4 on vardenafil, and 1 in a patient who was
randomized to vardenafil but then was diagnosed very soon thereafter
with bronchogenic carcinoma and had a massive hemoptysis and apparently
did not take drug.

In all of the cases of death on vardenafil, there was either no temporal
relationship to the dose with respect to the event that led to death or
the death itself or information that suggested an alternative cause for
the death. That correlates with the assessment of the investigators, as
well as their own drug safety group, that none of these deaths was
related to vardenafil treatment.

So we then embarked on a study to evaluate specifically the QT effects
of vardenafil and the scenarios that we chose to evaluate were both the
effects at therapeutic doses, at supratherapeutic doses, and at plasma
concentrations following maximal potential interaction with CYP3A4
inhibitors. This approach and design was discussed with and agreed with
the FDA, and it was performed by the clinical pharmacology and
statistical groups at GlaxoSmithKline.

The primary objective of this study was to exclude a greater than
10-millisecond effect in the Fridericia corrected QT at the 1-hour
post-dose time point after a dose of 80 milligrams of vardenafil.

Secondarily we evaluated the uncorrected QT, as well as both the
corrected and uncorrected QT, at Tmax for the evaluated compounds, as
well as the maximal change from baseline for QT and QTc over the 4-hour
period of evaluation.

The study was a six-way crossover study, single-dose evaluation,
controlled by placebo. The doses that we evaluated, the period of
evaluation, the choice of a positive control, and the statistical
analysis were all discussed with and agreed with FDA.

These are the treatments that were included in the study. They started
with a vardenafil 80 milligram dose, which as I\'ve demonstrated,
achieves concentrations of vardenafil in plasma which exceed those of
strong metabolic inhibition. We also studied the recommended starting
dose of vardenafil 10 milligrams, and this therefore represents an
8-fold difference in these doses evaluated for vardenafil, and in fact,
in terms of plasma concentration, a 12-fold difference.

We correspondingly compared with the recommended starting dose for
sildenafil, 50 milligrams, and an 8-fold multiple of that dose, 400
milligrams of sildenafil.

Moxifloxacin 400 milligrams was chosen as the positive control and this
is because of the well-described effect of moxifloxacin on the QT
interval and also the extensive post-marketing and safety database. And
all of these active treatments were compared to placebo.

We derived data for evaluation of the QT from a total of 59 healthy
subjects that ranged in age from 45 to 60 years of age. The QT interval
was determined by a validated central laboratory which was blinded to
the treatment assignment. The QT interval itself was determined by
manual digital measurement of an average of 3 beats in a single lead,
lead II. The end of the T wave was identified by the return to baseline
or, if this was not possible, by tangent method. Subjects were
maintained non-ambulatory, supine, and fasting during the study to
reduce variability in the QT interval measurements.

This shows a schematic of the study design. We had three time points
that were evaluated before dosing, ranging from a half an hour up to the
time point immediately before dosing. At each of these time points,
there were a total of 6 electrocardiograms taken and they were taken 1
minute apart over a time period of approximately 6 to 10 minutes which
would be expected to cover a range constant concentration of the
compounds evaluated.

Immediately before dose and after the electrocardiograms, a
pharmacokinetic sample was obtained. And then post-dose time points from
one-half hour out to 4 hours post dose were evaluated again with 6
electrocardiograms at each time point 1 minute apart, and a
pharmacokinetic sample at each time point taken after the
electrocardiograms were performed.

Shown here are the data for change from baseline after placebo treatment
looking at the raw or uncorrected QT interval, the heart rate, and the
QT interval corrected for heart rate with the Fridericia formula. We
observed a mean increase in the raw QT of 6 milliseconds and a
corresponding reduction in the heart rate of 3 beats per minute. When we
correct for that change in heart rate, we observed after placebo a QTc
of 0 milliseconds at the mean.

And if we then did a comparison of the active treatments to the placebo
change, showing here the placebo-subtracted mean change from baseline
and 90 confidence intervals at 1 hour, again looking at raw QT, heart
rate, and QTcF, we can see that for the doses of vardenafil 10 and 80
milligrams, as well as for both doses of sildenafil, there was a mean
reduction in the raw QT interval of 1 to 2 milliseconds, and that
contrasts with moxifloxacin where there was a mean increase of 3
milliseconds. This corresponds to a differential effect on heart rate of
the PDE5 inhibitors and moxifloxacin showing, in the case of vardenafil
and sildenafil, a 4 to 6 average increase in the heart rate compared to
a lesser magnitude of effect for moxifloxacin of 2 beats per minute.

The corrected QT interval using Fridericia for the primary analysis of
80 milligrams showed a mean difference from placebo of 10 milliseconds
at 1 hour, with an upper limit of the confidence interval of 11
milliseconds. These confidence intervals are very similar to what was
observed with the high dose of sildenafil, 400 milligrams.

In both the case of vardenafil and sildenafil, the difference in the
effect from 80 milligrams to 10 milligrams and 400 milligrams and 50
milligrams was very small, that is, a 2- to 3-millisecond difference in
the effect on the QT interval despite an 8-fold difference in dose.

And with respect to moxifloxacin, we observed a mean difference from
placebo of 8 milliseconds prolongation of the QT interval which is very
comparable to the effects seen in previous studies in the range of 5 to
10 milliseconds.

As I said, primarily we used an evaluation of the Fridericia corrected
QT, and this sort of evaluation assumes a constant relationship of the
heart rate and QT interval across the population, but as has been
stated, typically we observe a lot of variation in this relationship
from individual to individual. And thus, it has been suggested that one
also apply an individual correction to the heart rate or RR-to-QT
relationship.

In our study, we used off-of-treatment data from both the baseline
evaluation, as well as from data during placebo treatment, which in this
case covers the time frame of the active treatments, and with those
data, had electrocardiograms, 138 in number, for each subject.

We used two approaches in this evaluation, one a linear relationship
where we derive the slope of the linear regression for each individual
and use that for correction of the QT, as well as a nonlinear
relationship which uses an exponential formula similar to what\'s used
for Fridericia and Bazett, but instead of a square or cube root, the
individual exponent is derived and used to correct for heart rate. And
for both of these approaches, we performed the same analysis as we had
for Fridericia corrected QT.

Shown here graphically are the results of the QTci, or individual
correction, using the linear relationship, compared to the data I\'ve
just shown you for the changes at 1 hour for QTcF. What we can see is
that the magnitude of the effect, in the case of vardenafil and
sildenafil, is reduced compared to what we observed in the Fridericia
correction, down to the lower end of the 5- to 10-millisecond range or
even below that range. That\'s in contrast to the effect on moxifloxacin
where there\'s very little change in the magnitude of the effect from
the two correction formulae.

I should also note that there\'s very similar effects still, as we saw
for QTcF, for sildenafil and vardenafil and, again, a very narrow
dose-response range. We can see that numerically in the next slide. We
show these data that I just showed you graphically, and here we observe
again the linear relationship for QTci and we see a magnitude of effect
in the range of 4 to 6 milliseconds for both vardenafil and sildenafil,
both doses, a very shallow dose-response of 1 to 2 milliseconds, and
again not as great a change in the magnitude of the effect of
moxifloxacin between the two correction formulae.

These are the data, as I said, from the linear relationship, and Dr.
Morganroth will discuss and present the data that we have from the
exponential relationship or nonlinear relationship, and they are very
similar to these data.

We also evaluated, in addition to the QTcF at 1 hour, the QTcF at Tmax,
or time of maximal concentration, for each of the active treatments
compared to the matched time in placebo, as well as the maximum QTcF
change that occurred over the 4-hour evaluation period, compared to the
maximum QTcF change after placebo. And that was not time-matched,
whereas the change after placebo would not necessarily occur in the same
time after active.

But if we look across these different approaches to the evaluation, the
magnitudes of effect for each of the tested active compounds, this is
very similar regardless of the evaluation, with largely overlapping
confidence intervals, and again, a very shallow dose response for all of
these evaluations, very similar effects for vardenafil and sildenafil.

In our outlier analysis, we saw no uncorrected QT values that were 500
milliseconds or greater, no value that was corrected for QT heart rate
with the Fridericia formula that was 450 milliseconds or greater, no
change from baseline in the QTcF that was 60 milliseconds or greater.
And in the case of change from baseline of 30 milliseconds or greater,
we observed only 1 subject, as it happens, after sildenafil 400
milligrams with a mean QTcF change of this magnitude at any time point,
and this was based on an average, as I said, of 6 electrocardiograms
over a period of 6 to 10 minutes, a range of time that we\'d expect
constant concentration of both of these compounds.

We also modeled the effect of the QT interval, in this case QTcF, to the
concentration of vardenafil, sildenafil, and moxifloxacin. Shown here
are the observed data plotting the QTcF against the vardenafil plasma
concentration, and what we can see is there\'s a lot of scatter in the
observed data. And this is from the large intra-subject variability, as
well as day-to-day variability.

We did, however, observe that in the majority of subjects the maximal
effect on QT did occur at the time of maximal concentration, and thus a
direct effect model was appropriate for testing. A number of such effect
models were tested, and an Emax model best described the relationship.
That\'s shown by this red line where we can see that the QTcF, across a
very broad range of concentrations out to the far end of the data points
here, shows essentially a constant relationship for QTcF.

And if we look at the inset, the concentrations at lower concentrations,
which would represent concentrations observed after the 10 milligram
dose, we again see a relatively constant relationship of QTcF to
vardenafil plasma concentration. Thus, this very shallow or even flat
concentration-response relationship mirrors the shallow dose-response
relationship that we saw from the primary analysis.

So in summary, in clinical trials, we have shown vardenafil to be both
safe and effective in the treatment of male erectile dysfunction. Our
preclinical studies that were performed to evaluate potential for
effects on the QT interval would not have predicted an effect on the QT
interval at clinically relevant concentrations, and we did not see
evidence for torsade de pointes in our clinical development program.

A study that was performed to specifically evaluate the effect on QT
with 10 and 80 milligrams had the following results. The primary
analysis did not rule out an effect greater than 10 milliseconds, at the
upper confidence interval, 11 milliseconds, but overall the data for 10
and 20 milligrams in this study, performed in accordance with current
regulatory guidance, showed an effect in the range of 4 to 10
milliseconds of mean maximum change in the QT corrected for heart rate.

After vardenafil, we observed actually a shortening in the uncorrected
QT, and this is in contrast to moxifloxacin which lengthened the
uncorrected QT.

The concentrations that we achieved in this study cover the range that
would be observed with strong metabolic inhibition.

The relationship of the effect on QT at both vardenafil doses and
concentrations was very shallow, specifically a 2-millisecond increment
with an 8-fold increase in dose, 12-fold increase in concentration.

Finally, the effect that we observed for vardenafil was very similar to
the effect that we observed after sildenafil, an approved drug in the
same class.

It is the opinion of Bayer and GSK that the magnitude of effect that we
have observed in this study is of no clinical consequence. We are,
however, committed to ensuring the safe use of this product and have a
large pharmacovigilance program planned for the post-marketing period,
which we\'ll be happy to share the details of that with the committee if
they so desire.

In terms of the relevance of this effect to clinical risk, Dr.
Morganroth will now discuss that, as well as critical evaluation of the
design of this study and approaches to correction of the heart rate. Dr.
Morganroth?

DR. BORER: I think there will probably be a number of questions about
how these things were done, but maybe we should defer those until after
Joel has presented because he\'s going to talk about them, as I
understand.

However, at this point we\'ve seen a big presentation book and we\'ve
heard a summary of it. Does anyone have any questions specifically about
the factual evidence, not how it was obtained, but about the data
themselves? Dan?

DR. RODEN: The QTci measurement relies on generating a graph of RR
intervals versus QT intervals over some range of RR intervals generated
by this series of 18 electrocardiograms at baseline. Can you give us a
sense of how much RR variability there really was? I would imagine these
guys are lying around. They\'ve been lying around for a long time, and
the RR intervals can\'t possibly vary all that much.

DR. SEGERSON: Dr. Morganroth will address that.

DR. RODEN: Joel, if you\'re going to address it later, then that\'s
fine.

DR. MORGANROTH: I\'m going to address it.

DR. PICKERING: Could you tell us in what substantial ways vardenafil
differs from sildenafil in its general actions? It seems to be very
similar.

DR. SEGERSON: Well, they\'re both PDE5 inhibitors. Vardenafil in vitro
shows greater potency and greater selectivity of the PDE5 enzyme. In
terms of other comparative data, that\'s all we can say.

DR. BORER: Peter.

DR. KOWEY: You showed us Cmax for 5 milligrams, 5 milligrams plus
ketoconazole, and 80 milligrams, but 5 milligrams isn\'t the dose that
you\'re giving. Do you have Cmax for 10 milligrams plus ketoconazole?

DR. SEGERSON: As I said, the 5 milligram dose is the maximum dose that
we have recommended for use in combination with strong CYP3A4
inhibitors, and thus, in agreement with the FDA, that was the dose that
we chose to evaluate in the study.

DR. KOWEY: But you know that\'s not going to work. Okay. You know that
somebody is going to be on a regular dose of the drug and get
ketoconazole. So that isn\'t going to flush.

DR. SEGERSON: I\'ll ask my colleague, Dr. Sundaresan, to address that.

DR. SUNDARESAN: The left half of this graph shows the data that has
already been shown earlier, which is the ritonavir interaction results.
As mentioned earlier, what they\'re showing is the effect on Cmax, and
what was studied was vardenafil alone, the 5 milligrams, vardenafil plus
ritonavir, and then compared to that is the 80 milligrams alone of
vardenafil. As was pointed out, the 80 milligrams very well covers the
ranges that are reached with the 5 milligrams of vardenafil plus
ritonavir, which as indicated, is the maximal recommended dose for use
with potent CYP3A4 inhibitors.

Now, what we have shown on the right side is we have done simulations of
1,000 patients on what\'s likely to happen if the dose was 10 milligrams
or if the dose is 20 milligrams and the ritonavir is given under those
circumstances. As you can see, this is the results with the 10
milligrams plus ritonavir, and these concentrations are also well
covered by the 80 milligram dose. The 20 milligrams plus ritonavir is
less well covered, but as you can see, there were concentrations that
reasonably at least ‑‑ 10 percent of the concentrations still cover not
the median as well as expected, 10 to 90 percent range.

DR. KOWEY: I misspoke in my question. I meant ritonavir, and that
answers the question. Fine. Thank you.

DR. RODEN: Wait a second. Those are simulation data. To get to 20 and R,
you multiply 5 and R by 4 I guess.

DR. SUNDARESAN: No. Sorry.

DR. RODEN: That\'s certainly what it looks like from here.

DR. SUNDARESAN: No. See, what happens is what you do is you have the
population results from these and you simulate for 1,000 patients and
you get the median and the range.

DR. RODEN: You\'re making an assumption about linearity of disposition
which is not justified by anything that you\'re showing us. It may be
true, but you can\'t just multiply by 4 and say that\'s the way it\'s
going to work.

DR. SUNDARESAN: I agree with that limitation.

DR. BORER: Any other issues of fact here? Tom?

DR. FLEMING: I\'d like to understand the active control. Moxifloxacin is
here basically, as I would say, just to get a sense of sensitivity of
this assay, of this approach. It\'s interesting. If I look on page 31,
you\'ve indicated that basically, as the briefing document says, there
aren\'t any subjects that had a QTc measured by the Fridericia method
that had more than a 30-millisecond increase. We saw another report
earlier this morning that indicated that with moxifloxacin, you would
expect 10 percent to have that level of increase. That would have meant
I should have expected 4, 5, 6 people. Any comment on why we shouldn\'t
be surprised that there weren\'t any increases of 30 milliseconds?

DR. SEGERSON: I\'ll ask Dr. Morganroth to address that question.

DR. MORGANROTH: The ability to detect outliers depends on all the
parameters in the design of the trial, the number of ECGs obtained, the
precision of the ECG measurements, the sample size, et cetera. I believe
that the vardenafil trial had short of 17,000 ECGs in a sample size of
59 subjects, as you saw, 6 replicates at each time point with very
accurate digital manually derived determination in a very powered study
at 59 subjects.

Probably that accounts for the fact that the moxifloxacin central
tendency effect was exactly ‑‑ well, within a millisecond or 2 of what
was seen in the moxifloxacin NDA in their clinical pharmacology trials
that were designed to look for QTc versus when one uses, let\'s say,
less robust designs, the moxifloxacin would expect to be perhaps larger,
as was seen in the earlier trial. I think that accounts for the
differences in outliers. The central tendency is, I believe, the most
reliable method of determining assay sensitivity.

The percentage of outliers is, again, determined by numbers of ECGs done
at baseline and on therapy and time courses. I\'m going to discuss that
by showing the percent of observations as a method of looking at the
definition of outliers as the FDA has in the briefing book versus the
percent of patients that have definition of outlier. And those numbers
become very confusing depending on the approach that you use.

DR. FLEMING: So are you saying then that you would expect there should
have been no increases of 30 milliseconds using the Fridericia method
when we look at moxifloxacin?

DR. MORGANROTH: The answer is yes, and the basis for my guess that
that\'s what should have been found is on the fact that in the trials
previously that have looked at the clinical pharmacologic effect on QT
of moxifloxacin, the magnitude of the ECG numbers and sample sizes were
far smaller than that that was used in the vardenafil trial, and
therefore one would expect more noise, more variability to be detected,
more people that will randomly on placebo go to 30 to 60.

In fact, if you look at most phase III trials that have one baseline and
one ECG here are there on treatment and you look at the percent of
subjects who go 30 to 60 milliseconds on placebo, it\'s usually at least
10 percent and it can be as high as 60 or 70 percent. The 30 to 60 is
very non-specific. It\'s too sensitive almost, a too-sensitive cut point
for outliers if in fact you have infrequent ECGs.

Now, if you have a lot of ECGs on drug and only one baseline, which
sometimes people design trials that way ‑‑ they only get one baseline
and have an ECG every week and month during a clinical trial. And your
variability of the QTc is about, on average, 75 milliseconds a day. So
if your single ECG at baseline happened to have been taken towards the
365 versus the 440 part of the cycle, 440, the upper limit of normal,
and you do many measurements on drug, what\'s the likelihood that one of
them might be 30 milliseconds higher than that single baseline?
Obviously, the more ECGs you obtain, the more that likelihood is, and it
can be as high, as I said, on data sets that I\'ve seen, over 50 percent
to 75 percent of patients that might even meet that kind of criteria.

In this trial with 18 at baseline, 30 on drug, in 58 subjects, I
couldn\'t predict. I had expected it to be very low. Actually, as you
remember from the briefing document, the percent of actual ECGs out of
placebo and baseline ‑‑ there were about 10,400 ECGs.

DR. FLEMING: Correct.

DR. MORGANROTH: And of that number, there were only 30. Well, it depends
on the correction formula and the approach you take. But using the
individual correction formula, QTci, as I recall the data, there were
only 30 subjects that had ‑‑ excuse me ‑‑ 30 EKGs out of 10,400 ECGs
that had 30 milliseconds more.

I think that attests to the fact that moxifloxacin is not a very potent
QTc prolonger. We will show you in a moment that the post-marketing
surveillance is pretty clean, if you will, in terms of incidence of
torsade on moxifloxacin, a point that Dr. Borer made earlier. Therefore,
one wouldn\'t expect a lot of outliers because one would expect more of
a signal in the marketplace of a lot more torsade.

DR. FLEMING: Let me pick up on the point you\'re just making. I can\'t
help but contrast a little bit from what we\'ve seen with alfuzosin
where it looked there that the effect on QTc there was less than
moxifloxacin. It looked like, if I follow, on slide 22, your intention
was essentially to be able to show a similar pattern in this trial. You
were designing the trial to rule out a 10-millisecond change. In fact,
not only rule it out, your data suggests a 10-millisecond change using
your primary endpoint specified Fridericia method.

If we then go on to slide 26, your point estimates for the average
change are in that right-hand column basically the same or higher than
moxifloxacin, again clearly consistent with the hypothesis you were
trying to rule out, that you would have less than a 10-millisecond
increase.

Finally, if I go to those 10,440 measurements that you were talking
about and use your Fridericia method, there are 62 that were outliers,
and the two arms that had the highest number were moxifloxacin and your
80 milligram dose, both of which had 16.

So you designed the trial to rule out 10, trying to establish it was
much less. You actually have data suggesting it\'s 10 by your primary
specified endpoint, data that suggests it\'s the same as moxifloxacin,
and outlier data that suggests that you have greater than 30
milliseconds with the same frequency of moxifloxacin. Am I
misinterpreting anything?

DR. MORGANROTH: I think everything you said is correct in terms of the
numbers that you just went over, and what I\'d like to do in the next 10
or 15 minutes is sort of put that in a clinical perspective to try to
answer the question which correction formula gives you the more accurate
estimate.

DR. FLEMING: Of course, that\'s a little bit post hoc. You, in fact, did
prespecify the Fridericia method was your ‑‑

DR. MORGANROTH: Well, one of the questions this panel will be addressing
this afternoon is exactly that issue. Should, in fact, sponsors when
they do definitive QT trials, prespecify a correction formula and a plan
‑‑

DR. FLEMING: So in helping to understand that, can you give us the
rationale that you used for choosing this prior to seeing the data?

DR. MORGANROTH: I wasn\'t involved but I understand that the FDA at that
point requested this objective to be specified in the protocol despite
the company wanting to, in fact, say that our objective is like the
alfuzosin this morning, to evaluate the QTc effect of the drug without
trying to prespecify a magnitude of an effect or a correction formula.

Again, one of the questions you all will be addressing is whether or not
for definitive trials should such prespecified correction factors and
limits be part of the definitive trial or should one take the approach
to do as adequate a design as possible with placebo and positive
controls and have the ability to look at various correction factors and
find the one that provides the best correction for heart rate, a major
influence as you talked about this morning, and then use a statistical
plan that is appropriately looking for not only central tendency but
outliers, and then, after looking at the totality of the data, determine
what the magnitude of the effect is, what the magnitude of outliers is,
and what the potential clinical risk is from that trial. That\'s a
question the FDA has posed to you because obviously there isn\'t a
uniform consensus in the world as to how one should go.

My personal opinion is that in our level of what I\'ll call
misunderstanding about the relationship of QT to QTc to clinical
outcomes, as you all were inferring this morning correctly, that I do
not believe one should have a prespecified correction formula in trying
to rule out 10 milliseconds. I think you have to look at the dose
effect. 5 milliseconds at 3 times the dose, going up to 15 milliseconds
may be a very different kettle of fish than 5 milliseconds 8 times the
dose and 12 times the concentration going up only by 2 milliseconds.
Because that really addresses what may happen in the clinic when you get
the drug used in a patient as discussed this morning by Dr. Kowey and
others, the patients with hypertrophy and ischemic heart disease, et
cetera. That\'s my opinion.

You all have to make your opinion and answer the question regarding this
issue, but I think this is what the issue is, whether one should
prespecify or not.

DR. FLEMING: Well, we\'ll discuss this later on, although just briefly
to follow up, clearly, yes, you would look at all data. Generally,
though, we would hope that sufficient forethought is put into designing
a trial that what we target as the primary endpoint is at least as, if
not more, representative of what we really care about than the other
measures. So it\'s a little perplexing when we define a primary
endpoint, don\'t see what we want to see, and then we move away to other
measures, wondering how much that\'s driven by the true, legitimate
science versus the interest in being able to get a conclusion we wanted
to reach.

DR. MORGANROTH: Yes, I think that\'s a generally good principle; that
is, you should not stray away from your primary objective in a clinical
trial in post hoc analysis. I 100 percent agree with that in general.
The only problem is when you\'re trying to determine the QTc effect of a
drug, because of all the problems that were discussed this morning,
which correction is the factor is the better, has the assay sensitivity
performed correctly, your control groups performed correctly, et cetera,
I\'m not so sure we know enough about this field to be able to say a
priori prospectively what a correction factor, what limits, et cetera
should be applied to any particular drug. Even this issue about
single-dose versus multiple-dose studies and pharmacological coverage is
not easy to grapple with, as obviously the comments have alluded to.

DR. BORER: Susanna and then Paul.

DR. CUNNINGHAM: I noticed on slide 23 you said you used the tangent
method to determine the end of the T wave, and yet there was an article
that we were given by the other company written by Drs. Malek and Camm
which specifically says that the tangent method wasn\'t necessarily the
best one for estimating the end of the T wave. So could you comment on
your choice?

DR. SEGERSON: I\'ll leave that to Dr. Morganroth as well.

DR. MORGANROTH: Yes. The standard, as Dr. Segerson pointed out in the
slide, is not to use the tangent method, to use the end of the T wave
and try to distinguish a QT and note very critically abnormal U waves or
notched T waves as another ‑‑ we\'ll call that a morphologic phenomenon
rather than a quantitative effect.

There are some cases, however, in which the U wave obscures the end of
the T wave, and that is very uncommon, in fact, did not occur in this
trial. So in this trial, it\'s a 0 incidence because there were only 4
patients who had any T wave abnormalities and those T waves were a
slight flattening. Frankly, that\'s because of the way the study was
conducted, as I\'ll point out.

I always expect at least 1 or 2 patients who are going to have
inversions, even though they\'re healthy people, relatively healthy.
This was a mean age population of 53, so I would have expected some more
T waves. But I think the conduct of the study tried to eliminate ‑‑

DR. BORER: We\'re not going to call that old now, are we, Joel?

(Laughter.)

DR. MORGANROTH: Yes. I\'ve got to be careful, don\'t I? Very careful.
I\'m not 30. I\'d like to claim I am, though.

DR. ARMSTRONG: In the positive control, moxifloxacin, as depicted in the
tables 1 and 2 with the questions to the committee, coming back to
Tom\'s point, if we\'re going to use that as the reference point to
establish the two drugs of interest, the QT data for the same dose of
moxifloxacin is quite different. It\'s unclear to me how much of that
represents the sample size or other issues. But if we\'re going to
reference this to a positive control, the positive control between the
two studies is substantially different, and I was just looking for
insight as to why that was.

DR. MORGANROTH: I commented on that a moment ago, but let me expand on
it just a bit. I think that the purpose of the positive control is assay
sensitivity. The magnitude of that positive control, according to the
FDA concept paper, is to be in the 5- to 10-millisecond range, not
therefore to use a drug like sotalol that might give you 30
milliseconds. It\'s too easy to see that because you want to make sure
that if the placebo and the new drug under consideration look identical,
that in fact, in that assay in the whole trial all the design features
were such that your positive control hit a 5- to 10-millisecond effect,
which is sort of the threshold that the concept paper suggests is
something that\'s desirable to know about.

I believe that ‑‑ at least I didn\'t hear this morning the numbers of
12-lead ECGs that were done by the first moxifloxacin data set that
you\'re referring to because the vardenafil data set does not have
Holter monitoring, which is a very intriguing and very interesting
method and I think deserves more attention. But we don\'t have that in
both trials. We only have standard ECGs in the vardenafil trial to
compare to the standard ECGs that were done in the alfuzosin trial.

So I don\'t know if they had a magnitude of ECGs that were comparable to
the magnitude in this trial, which was 17,000 in 59 subjects. If they
had 45 subjects and had far fewer ECGs, my guess would be that\'s a
reason for why there was a difference in the magnitude.

Number two, another reason might be the differences between the
measurement techniques. They were both done digitally but in different
laboratories, and there are differences between laboratories, even
between people within a laboratory. So one might expect a difference
there, the conditions of the study, in terms of how well people were
really kept from having effects on heart rate, et cetera.

So to answer which is the right number, I think one has to go to the
biggest set of data, and that biggest set of data comes from Bayer\'s
NDA and post-marketing clinical pharmacology program. I think if one
looks to the label of moxifloxacin, I believe the number is 6
milliseconds. So I think that as long as you\'re between 5 and 10
milliseconds, that you\'ve hit the gold standard of the method which is
all of their data put together.

As we do more and more of these phase I definitive QT trials with
moxifloxacin, we\'ll see how they come out in terms of whether it makes
it identical to the NDA. I\'ve been involved in about a dozen such
trials in the last year and I\'ve seen all of them come between 5 and 10
milliseconds. So I would think that the differences we\'re seeing here
are probably solely design issues.

DR. KOWEY: Paul, when we had this discussion at DIA about positive
comparators, it specifically was for this problem that you point, which
is extremely important, which is because of differences in patient
population and methodology and just the way you do the studies and how
you make the measurements and given all the vagaries of all that you\'ve
heard about the measurement, that having a positive comparator group,
which is difficult to do in these kinds of trials, as you can imagine,
to tell somebody in a clinical trial we\'re going to give you a drug
that we know prolongs QT interval as a positive comparator ‑‑ even
though it\'s difficult, we thought that it was probably a reasonable
thing to do so that we wouldn\'t have difficulty interpreting any
individual study. In other words, if you just looked at the moxifloxacin
label and said, well, 6 milliseconds, you wouldn\'t have predicted in
the first study that we saw that the QTc change was really much greater.

But it\'s the assay sensitivity issue that is important here, and I
think these two studies actually point out exactly why having a positive
comparator is so very, very important. I think the point that you raise
is germane to that argument.

DR. BORER: If there are no other questions of fact ‑‑ oh, I\'m sorry.
Tom.

DR. PICKERING: I just wanted to ask, was this study done only in men? I
don\'t think you specified. And I ask because I could see that it might
be used in women unlike alfuzosin.

DR. SEGERSON: The study was performed only in men.

DR. BORER: Joel?

DR. MORGANROTH: Thank you very much.

I\'ve been asked by the sponsor to comment on, in a critique manner, the
design features of the trial that they did in terms of what was good,
what wasn\'t good, what the interpretation of the correction factor data
provide us in terms of recommending one correction factor approach over
another in definitive QT trials, and finally to give you some comments
if I were asked the question, well, how do you determine what the risk
of 5 to 10 milliseconds is? What are the methods and the data that we
have in order to judge whether that\'s an issue or not an issue for
approvability or for labeling or what have you.

Most of my comments and I think most of the concepts that we\'ve been
talking about today really come from the November 2002 concept paper in
which the principal message, I believe, is that it\'s very important to
get this right. We need to understand for non-cardiac drugs whether they
have a QTc effect or not, and to do that, we need to use careful
consideration not just in this definitive phase I trial, but in all of
the trials with specific design recommendations using central validated
methods as a way of determining the QT effect in the pharmacology
studies, phase I, as well as in the clinical trials.

I think the important issue for today is the comment in that document
that goes to say that all bioactive compounds should undergo a
definitive phase I trial, irrespective of what the preclinical data are.
Even if you think you have a negative preclinical, a phase I definitive
trial is needed.

Therefore, the real question is how does one determine whether the
design is adequate enough to be definitive, that is, so that you can
really believe in this trial that you have answered the question of have
you ruled out a false negative or a false positive due to this huge
spontaneous variability in the QTc duration, not QT. The QT has huge
variations with heart rate, as we all know, but how do you deal with the
QTc.

Well, these principles that I believe are fairly straightforward are
mostly detailed in the concept document. I want to just give you my sort
of experience and viewpoints about each of them very quickly in terms of
what are the sources of QTc variability and how do you design a trial in
order to eliminate those sources as much as possible so that you can get
a drug effect, a treatment effect and not be subject to a false result.

Well, the first is, obviously, that the study is adequately powered in
order to detect a small QTc effect. The definition of small is given in
the document, which is, as we\'ve talked about, 5 to 10 milliseconds.
And the sample size usually to do that, because of the variance is so
high of the QTc measurement, is at least 30 to 50. In the trial you\'ve
seen today in yellow, which is my comment about the vardenafil QT trial,
it was 59, so it was adequately powered. It was very well powered in
fact. Usually 30 to 50 subjects will do that.

Now, clinical pharmacologists are not real happy about that or used to
that because most of the trials run 6 or 12 or 20 people, and those are
ones that are not going to be very definitive.

The next thing is how often you measure the parameter under
consideration; i.e., how many EKGs do you do?

DR. BORER: Excuse me, Joel. I\'m sorry to interrupt you in the middle
here, but I don\'t understand that statement that 30 per arm provides
the power to detect a modest QTc change. I would think that that would
have to be coupled with and would be a function of the number of
observations per patient, and I know that that is not in that document.
On what basis do you say that?

DR. MORGANROTH: Well, that\'s a good statistical question. Maybe I\'ll
ask Tom to answer it.

It\'s my understanding ‑‑ and I\'m not a biostatistician, as you know ‑‑
that the principal determination of power to detect 5 milliseconds is
based on the variance of the QTc measurement in a population. That
variance tends to be somewhere between 8 and 20 milliseconds depending
on the number of ECGs that you obtain. Unfortunately, I believe most
statisticians ‑‑ and maybe Tom could answer this ‑‑ generally don\'t
have enough data regarding numbers of ECGs to variances so that they
assume an average variance and then calculate a power of usually 80 at
least, if not 90, with an .05, which usually drives a sample size in the
30 to 50 range.

But you\'re right. To be precise about it, you\'d like to know in the
population you\'ve selected to study, whether it\'s 53-year-old men, as
in this trial, or whether it\'s men and women with a mean age of 27 in a
typical trial of this nature, you need to sort of know in that
population if there are a lot of vagotonic patients. And if they\'re
athletic, they\'re going to have a different heart rate spectrum, and
probably because of their autonomic tone being different in people who
aren\'t as athletic ‑‑ in other words, the variance of the QTc in the
measurement, which laboratory you use, which method you use. You\'re
right, but it\'s very complicated in terms of getting very precise about
that.

Therefore, in my experience, which is all I\'m trying to suggest here,
is that it usually takes 30 to 50 patients versus the 8 on drug and 4 on
placebo or 6 and 2 that most phase I trials are generally conducted by.
And that\'s the only point I mean to make.

DR. BORER: Okay. We\'ve seen the data from the 59 patients. There were a
large number of measurements made. The data looked pretty good.

Tom, can you comment on that please?

DR. FLEMING: I\'ll just make one brief comment. Certainly it depends on
what measure you consider to be adequate to judge whether or not
there\'s an increase in QTc. If you\'re looking at the average increase
in QTc, measured by the approaches that we\'ve seen today using
population or individual adjustments or Bazett or Fridericia, basically
with this sample size, you\'re going to be able to estimate changes
where basically it\'s 2 standard errors or plus or minus 2. So I think
this statement is in fact proper if that\'s the measure you consider to
be sufficient to make your judgment.

If you consider outliers to be important, what are the fraction of
people that have values above 450 or values above 500 or changes of at
least 30 or 60, these sample sizes are strikingly inadequate to be able
to understand those issues.

DR. MORGANROTH: Yes. Let me just say I totally agree with that, but
again, it becomes practicality. To do these trials with 250 subjects in
an arm, when most people are used to doing it with 8 in an arm, is mind
boggling.

I think Jeremy Ruskin made this point ‑‑ and I think I agree with him ‑‑
that you don\'t really get outliers isolated from a central tendency,
meaning that if you don\'t have some evidence that you affect the QTc
duration in a mean change from baseline, placebo corrected with a
positive assay, and if you had 0 milliseconds or 1 millisecond and you
have a big outlier frequency, you\'ve got something funny going on that
isn\'t in the experience that most people have.

Again, that may be because of the small sample size, and that\'s the
point you\'re making. I think that\'s another answer I should have given
you before. The sample size being small, you get sort of spurious data
for outliers. It\'s not very robust.

The frequency is important and I need to dwell on this just a little bit
because the typical phase I trial often has, well, I\'m going to do 3
EKGs, which the guidance document says, at baseline. I think that\'s
wholly inadequate because what you need to do is be able to cover the
concentration of parent metabolites, diurnal variation, et cetera. You
need to do a lot of ECGs at baseline and you need to do a lot of ECGs on
drug. My general experience is you need to do them about the frequency
you do a PK analysis, which means about 10 to 15 to 20 ECGs, over the
period that you would want to look at a PK as an analogy, might be the
right number to do a QT assay.

You need to have measurement precision. The document says, digital
process, manual method, core laboratory, 3 beats in lead II. The
attraction to the Holter method is you get a lot more beats, and Peter
made that point and I agree with him. That\'s what\'s attractive about
it.

The other issue is, of course, the digital process allows for the
potential of using new methods. As was pointed out over here, one could
take all 12 leads and put them on top of each other, and maybe that
gives you a better measurement than only looking at 3 beats in lead II.
There is some data that I\'ve seen from Pharmacia that suggests that
doesn\'t actually work, to my surprise, because I would have thought
intuitively it would be better. But right now since the CPMP document in
1996 and through all subsequent documents, 3 beats in lead II seems to
be what we\'ve all, sort of out of pragmatism more than out of any other
reason, settled on.

Now, population is a very important thing. You\'ve already noted that in
your questions or comments. Generally, the tug of war is between wanting
to really get the population at risk. You\'d like everybody with heart
failure that\'s going to have, as Jeremy pointed out, the maximum
magnitude of effect in and of itself because of these issues. But the
problem with that is if you use people that are older with heart disease
and variations and you\'re going to have, say, 35-40 subjects in a
group, you have so much heterogeneity, even if they all have heart
failure or if they have ischemic heart disease, that you add so much
variability into that equation, that you can, in fact, not get a very
precise signal.

So these generally should be done, in my opinion, in healthy men and
women volunteers with the assumption that if you study a
supratherapeutic dose and you don\'t have a magnitude of central
tendency of concern, what\'s the likelihood that you\'re going to have
one when you have magnifiers of effect? Dr. Ruskin pointed out that if
you can cover the supratherapeutic dose and you know that the magnitude
at the supratherapeutic dose isn\'t very much and then you use the
clinical dose in someone who\'s very sick, maybe you\'ll get up to that
supratherapeutic dose. Hopefully, you\'ve picked a supratherapeutic dose
that will cover that possibility.

Now, in this particular vardenafil trial, all men were chosen and they
used the target population, the same mean age versus what was in their
phase III program.

The conditions of the ECG recording we\'ve already talked about. I\'ll
skip for the sake of time. But the subjects need to be controlled from
heart rate changes because hysteresis and looking at heart rate
differences, as people go up and down, can have an important magnitude.

The supratherapeutic dose we\'ve talked about. That\'s a very important
issue. You need to make sure you cover the maximum range. In my
experience, that\'s usually 3 to 5X the clinical dose, if you want a
ball park, but it really needs to be done the way it was done in both of
these trials we\'ve heard about, that is, by careful consideration of
what the metabolic pathways are and sort of figuring it out
pharmacologically. Though, if you for some reason can\'t or don\'t, 3 to
5 tends to be a good thing.

We\'ve talked about the need and importance of the positive control to
interpret the data and placebo.

The correction factor, of course, is very important, and the statistical
plan, being able to look at not just central tendency but also outliers.

The other thing that was specific to the vardenafil trial is to ask the
question was the 4-hour sampling time appropriate and was, in fact, a
single dose versus the more natural multiple dose to steady state, which
I think most of definitives trials will be done by ‑‑ I think that in
this particular drug, vardenafil used as a single dose intermittently
and with the PK that showed that its metabolites and its parent ‑‑ you
have a 1-hour Cmax and fairly rapidly go away with nothing at the end of
24 hours so that a 3-day washout period would work very well ‑‑ I think
that that\'s all appropriate.

Now, if one is going to do a crossover trial versus a parallel trial,
it\'s my opinion that unless you\'re certain that the parent and
metabolites are really not going to be present and you know the
metabolites and you know their time course, then the risk of a crossover
study is you\'re going to have the potential of carryover. And then how
do you deal with the baselines? Well, that often says, well, use only
the first baseline before any treatment and we\'ll apply that to all the
groups, or I\'ll average them, or you get lots of different cuts at the
data that gets very complicated. So a crossover trial for vardenafil was
fine because of the PK, but PK needs to be known if you\'re going to do
that.

Finally, if you know drug affects heart rate from other studies, your
earlier phase I trials, it\'s very important to consider the special
procedures known for heart rate correction, for all the reasons that
were talked about this morning and I won\'t reiterate them.

I think I want to make a couple of comments. The Fridericia formula I
think was first used at the Cardio-Renal Advisory Committee about five
years ago on the drug cilostazol. Prior to that, no one ever thought but
to use Bazett\'s and that\'s why the terfenadine data that Jeremy showed
was by Bazett\'s. It was a trial in which we didn\'t even think of using
anything else but that. Now, since the last really five years, because
of that precedent in which this committee agreed with the Fridericia
approach, seemingly better than the Bazett\'s approach, that has become
sort of, I think, by consensus the best factor, which is why I think the
FDA and the sponsors of vardenafil chose QTcF because of very little
experience with QTci, even population formulas.

The population formula is recommended in the guidance document to be
done at the time of an ISS, when you have enough patients that you\'ve
studied on baseline and placebo to actually calculate that parameter. I
think it was first done by Dr. Burkhardt who was at Neuropharm at the
time when he did it for the schizophrenic population for the atypical
antipsychotics. His factor at that point was .37. Many people in
neuropharm go to the QTcN, N for neuropharm, which equals an exponent of
.37. It\'s just a historical note.

Clearly the individual corrections, as in the guidance document, which
is the first one that actually suggests using that, has some important
limitations that have to be considered. The question asked a moment ago
is important. What is the heart rate range at baseline you\'re studying?
Is it appropriate in order to look at the effect of heart rate? Really
what that drives is the common experience that you need at least 50 to
100 ECGs in order to make this assessment of an individual correction.
So if you\'re doing a parallel trial, that means you\'ve got to do 50 to
100 ECGs at baseline, not 7 or 10. You\'ve got to do 50. If you can
afford pharmacologically to do a crossover trial so you can use all
those baselines because you\'re using the same patient over and over,
then obviously you can get up to 50 to 100 pretty easily.

In this particular trial, they had 138 ECGs in each patient because they
went through 6 times 18. Right? Plus, they had 108. Plus, they had 30
when they were on the placebo arm. Because you have 108, the FDA very
cleverly said, well, what if you don\'t use the placebo and just use the
baseline and how does that compare to using the baseline and placebo?
That\'s that whole part of the document about QTci.2 I think it\'s
called, which is trying to answer the question does it matter whether
you use the placebo and how does it affect it or not.

Now, what happens here in this trial is that we have the ability to look
at the relationship of QTcF to QTci based on a very powerful trial with
lots of samples. With QTcF versus QTci, you see that the pattern is
pretty much the same. The relationship of the two drugs, vardenafil and
sildenafil, and the doses are not very different. A flat dose response
remains. Moxi, which doesn\'t affect heart rate, pretty much was within
1 millisecond by the two different approaches. Whereas the difference
for the PDE5 inhibitors that increase heart rate is a clear reduction in
the QTc duration, closer to this sort of 5-millisecond rather than
vardenafil which is closer to the 10-millisecond when you use the QTcF.

That\'s, of course, a critical question. Which is believable? Which is
the one you should use if you then want to apply some recommendations as
to what magnitudes relate to risk?

Well, the way I think you approach that is statistically. You ask the
question which of these correction factors gave the best fit so that no
heart rate influenced the QT? Let\'s look at the clouds.

I\'m sorry. I\'m one ahead of myself. But I did want to make the point
that there are two ways of doing this QTci measurement. One is using
linear regression and the other is using exponential techniques. It
doesn\'t matter. They come up with the same data, in this data set at
least with this design.

Now, here are the clouds. If you look at the Bazett formula ‑‑ and you
didn\'t even see data on Bazett for sake of time ‑‑ you see exactly what
was shown to you this morning. Now, I\'ve used heart rate here because
most people presumably in the audience do not think about RR. What you
see is, as you increase your heart rate, you get the over-correction. So
in this data set, like this morning, you have exactly the poor
performance of Bazett which is why generally it doesn\'t help very much.

But look at Fridericia\'s. That looks pretty good. That\'s a pretty flat
cloud.

Now, if you look at the QTcF and the QTci, I\'m choosing X instead of
linear. They really come out identical. It\'s exponential and this is
exponential. At first blush, it would appear that the QTci is not good.
It\'s not the best correction formula to use. It looks like the QTcF
would be the one you would want to believe. That I think is principally
driven by these points right out here because if you can mask them from
your eye, you will see that these curves look pretty identical. So I\'m
a little suspicious as to whether, really, the QTcF is better than the
QTci, and it wasn\'t worth all that extra ECG frequency to bother with
the QTci.

What you\'re really, however, trying to do in this analysis is you want
to look at each individual and you want to find out if in fact for every
individual in the trial the relationship of the heart rate to the QTc
stays constant.

And the next slide shows you what I call, instead of a cloud
performance, a pick-up stick equivalent. This is what the pick-up stick
model looks like for the QTcF. What you see is here is the individual
lines. Now, this tells you the range of heart rates. The range of heart
rates, like this morning, went from 40 to 90 or so, the same rate you
saw this morning. And that\'s what happens when you take a mixture of
healthy people, older or younger, maybe more likely in the older I
suspect because they\'re more likely less athletic, and you put them in
a supine position and their heart rates are going to vary. Now, some
people don\'t vary much at all, where others vary a lot.

In the QTcF, a lot of people aren\'t very well corrected. They\'re
over-corrected. Some are under-corrected. Some are pretty flat. And the
overall cloud looks flat. So maybe the cloud isn\'t the best way of
looking at it. Maybe what you really want to do is the individual
regression lines.

And the FDA has done that very nicely in their briefing book. Instead of
using pick-up sticks, they use dots, about how you vary from 0, but
it\'s exactly the same analysis.

Of course, this is going to be much more flat because every patient is
designed to make them flat, so by definition they\'re flat.

Next slide.

DR. FLEMING: Just before we leave that point, though, obviously if you
fit a model for how the adjustment should be and then you apply it to
individuals, there\'s going to be some randomness so that the model
doesn\'t predict the individual person perfectly; whereas, if you use
the individual person to fit the model, of course you\'re going to fit
that individual person perfectly. But are you overfitting the data? So
the right looks great, but I can always get the perfect model by using
an enriched model and fitting it to the data.

The essence of what makes me choose one or the other is which one of
these particular approaches more accurately reflects people who are at
increased risk of what I clinically care about. Obviously, we don\'t
have that data.

DR. MORGANROTH: Yes, we don\'t have that data, nor do I think we\'ll
ever get that data because to do that, you need a prospective trial
looking at torsade as the endpoint, frankly, because you can\'t use a
surrogate, and that\'s an infeasible study.

So the concept on the table is that the reason you have to correct for
QT and you cannot use QT ‑‑ take an antibiotic. A person has a fever.
Their heart rate is fast. The QT is short. You give them an antibiotic.
It cures the pneumonia. Their heart rates come down to normal. Their QTs
are going to be long. So you absolutely have to correct the QT for the
QTc for any drug or condition treated by a drug that changes heart rate,
which turns out to be an awful lot. You saw the difference in moxi, even
though it technically doesn\'t. There could be a couple beats per minute
that could influence the data.

So if you agree with the assumption that the correction formula should
try to correct best so that at any heart rate you have the same QTc ‑‑ I
mean, that is the assumption. If you buy that assumption, then this is
the model that by definition should be the best. That\'s what we\'ve all
thought. And the real question is do you gain enough for all the extra
resources.

Now, that doesn\'t answer the clinical question. It doesn\'t answer the
question if in fact by doing a good correction like this, the heart rate
doesn\'t affect it, that you can predict the events that occur in the
high-risk patient population. That was your point I thought, and I agree
with you. It doesn\'t mean this is the right way to go. Absolutely. We
just don\'t know the clinical impact of that. But in an ignorant state,
when we have no way of going, I think it\'s intuitively more obvious to
use this approach than it is to use Fridericia\'s or clearly Bazett\'s.

But one could argue that maybe Bazett\'s is fine because we\'ve learned
about terfenadine with Bazett\'s, but I have a reason to disagree with
that concept, that Bazett\'s is the only thing we should be using.

DR. FLEMING: Let me make one more attempt. I\'m not saying the right or
the left is better. I\'m saying the fact that the right looks perfectly
horizontal does not mean it\'s better. There could be many factors.
Clearly one of them that\'s very important is heart rate that affects
QT. There could be others, and I\'m allowing the full richness of my
data set to factor in a lot of other factors to get parallelism on the
right-hand side. Some of that may be noise. I may be overfitting the
data. The truth may be the left, and then other unrelated things are
coming in, are influencing creating that noise on the left.

DR. MORGANROTH: On the other hand, we have a lot of sources that affect
the QTc, the power of the study, the frequency of the measurements, the
quality of the measurements, the population that\'s selected, the
ability to correct QT to QTc best. So you\'re right. We\'re only looking
at 1 of 10 or 20 features that are important to consider in a clinical
design, and I think to make the judgment of which correction factor to
use I still think the one that produces the least effect on heart rate
seems intuitively ‑‑ all it is is intuitively ‑‑ better to me.

But as you point out, you have all kind of other factors that may be
influencing this model. I think heart rate is the very predominant
effect of that model and it\'s not the only thing.

DR. RODEN: I\'m sorry. I want to hear Tom and Joel talk about ‑‑ you
talked about the cloud and you sort of said this cloud looks better than
that cloud, but this other cloud doesn\'t look so nice, but you\'re
being distracted by these 14 points up here in the corner. Are there any
measures of goodness of fit for any of these things?

So the pick-up sticks on the left there are shown as lines, but those
are lines through 18 or 138 or some number of data points. It\'s
entirely possible to me that each one of those pick-up sticks represents
a little cloud that contributes to your big cloud. It wouldn\'t surprise
me if your regression line through that big cloud was vertical instead
of horizontal.

(Laughter.)

DR. RODEN: You just can\'t say that stuff.

And the Bazett thing looks bad because of 14 points in the upper
left-hand quadrant.

My biggest concern about all this is this is all baseline data, and when
you get a drug on board that affects the heart rate, you\'ll get one
effect. If you get a drug on board that affects QT, you\'ll get a second
effect. If you have a drug that affects both QT and RR, I think this is
inevitably confounded. You will make no conclusion. And the only
conclusion that counts is what predicts torsade.

DR. MORGANROTH: I don\'t disagree with you. I think what you\'re saying
is very much what Dr. Fleming said, that the statistical method, whether
it\'s one that\'s going to look at a cloud with a regression line or
whether it\'s one that\'s going to look at individual regressions, the
ability to know by evidence-based, prospective data that that correlates
with anything clinically that\'s better or worse than something else ‑‑
we have no data on that. Therefore, it is incorrect to be dogmatic that
one method is by definition better. And I agree with you.

DR. RODEN: I don\'t think we solve the problem by just getting a whole
lot more data. I think you can get as much data as you want. When
you\'re faced with drugs that have multiple effects, this kind of
extensive analysis at baseline I don\'t think can possibly make you
smarter. It\'s inevitably doomed. One of the things we\'re supposed to
discuss, Doug, is how to get out of this morass that we\'ve gotten
ourselves into, and getting more ECGs at baseline I don\'t think solves
that problem. It\'s obviously a discussion we can go on to later.

DR. MORGANROTH: It clearly gives you better precision. The question is
does it predict any better than getting one EKG at baseline or none. We
won\'t answer that easily.

Because of time, I want to finish up real quickly with one other
concept. Let\'s skip this issue because it\'s not important.

(Laughter.)

DR. MORGANROTH: It\'s important but we\'re just going to dig ourselves
into a deeper hole.

I want to make two points here that I think are important. Central
tendency is very important and often people want to do a time match.
They want to go Cmax because they think at Cmax is where all the action
is. If you know the Cmax of your metabolites and your parent, that might
be where all the action is, but you better know about the time course of
your metabolites. So often one wants to go to a mean maximum change by
picking a point that you have the longest QTc, the worst case analysis,
that sort of mechanism by which you define an outlier.

The concern I would have for precision is that if you only have one ECG
at hour 2 or hour 7 and you go back to your baseline and take the single
ECG at hour 7, you\'re really having no different than a 1 and 1
comparison. You lose all of the power and the frequency of measurement
issues. So often what you want to do is take the mean of your baseline
as the best point estimate for that person and look at the time point of
interest, and if you only have one ECG, that\'s all you have.

The particular study done by the vardenafil definitive had 6 ECGs at
each time point, which gave them the ability to go and have more
precision at any particular time point. And they showed you the 1 hour
to the Cmax, the Tmax, et cetera. And I think those numbers are more
valid because they had more measurements at those time points.

There are technologies, the 12-lead continuous Holter, that when you
post hoc find the time point of most interest, you can go back and do
more ECGs at a time point.

The other point is what\'s the definition of an outlier. There\'s a lot
in your briefing book about whether one should use observations or
patients. I think that conceptually to me an outlier is show me a
patient who, because maybe they have forme fruste congenital long QTc
syndrome, as Dan Roden calls repolarization reserve, problems ‑‑ you
want to find that patient. You need a large sample size to really find a
lot of them. And that\'s the outlier.

To look at the number of ECGs above a certain level to me is more of a
statistical method of trying to define whether you have a drug effect of
a central tendency. You have more changes on various drugs ‑‑ suggests
they really have a QT effect. It doesn\'t really to me tell you the
outliers, the real risk of outliers. I think the outlier risk is 60
milliseconds, not 30 to 60. I think that\'s the specific data. It comes
from our terfenadine database of placebo. Clearly people who have new
500s or new T-U waves, these are the three parameters that to me are the
ones to look at for outliers. Everything else is sort of difficult.

We\'ve already discussed this, so I\'ll skip this. I think this is all
that we\'re really looking at there.

So, finally, I think this vardenafil trial in my opinion is valid. I
think the results are reliable. I make that statement for two or three
simple reasons.

One is placebo came out to 0. That\'s very unusual because usually
there\'s enough spontaneous variability, and the 0 milliseconds is just
very comforting.

Moxifloxacin hit the number it should. It\'s in the 5- to 10-millisecond
range. So that\'s what I would expect for a positive control. So we have
assay sensitivity and a placebo group that really looked like placebo.

No matter how you look at the totality of the data, F, i, 1 hour, Tmax,
Cmax, et cetera, all the data hang together within a couple
milliseconds.

And the very interesting result of this trial, which is generally not
seen for most hERG blockers or drugs that affect the QT, is the extreme
shallow dose-response curve with 8X dosing or 12X concentration.

The other thing that was interesting in this trial is the inclusion of
not just four arms, but six arms, and two of those arms being a low dose
and a supratherapeutic dose of sildenafil, the drug that is on the
market that has a lot of clinical experience because here you have a
drug, vardenafil, that has only recently been on the market. There\'s
not a great deal of data about it post-marketing, and so I think that\'s
an issue.

Finally, you have vardenafil and sildenafil shortening the uncorrected
QT if you believe that the QT is something to look at irrespective of
the QTc. Moxi, of course, lengthens it, and I think there\'s no evidence
of any outliers on vardenafil.

Finally, I want to just say a few things about how do you make a
decision of whether 5 milliseconds, 10 milliseconds is a good thing, a
bad thing, it\'s a risk, not a risk. How do you make a judgment like
that? What\'s the basis of doing that? Well, clearly the best basis is
if we had a prospective trial in which we had torsade as the endpoint
with various degrees of QTc duration done by a certain standard method.
That\'s never going to happen in this field.

So the basis of making a decision is what\'s been our experience with
other drugs that affect the QT like terfenadine, cisapride, ziprasadone,
moxifloxacin. What has been this post-marketing surveillance data? This
was discussed earlier in terms of what are the signals of risk on
moxifloxacin. And in this case, since the vardenafil and sildenafil look
so identical in terms of their preclinical hERG, as well as in this
definitive QT trial, their QTc central tendency, and outlier analysis,
one might be able to say that this PDE5 inhibitor might react similarly
because the QT effect is so similar.

And then finally, what do regulators think about this? They have a
tremendous amount of experience in all kind of therapeutic drugs and all
kinds of decisions over the years, and some of them have published their
opinions like Dr. Shah and the FDA concept paper.

You\'ve seen this data and it\'s meant to point out that a 5- to
10-millisecond effect like vardenafil or sildenafil is not the same as
terfenadine, even if you discount the issues of design, et cetera,
because of that 18 milliseconds.

The other thing is, is moxifloxacin the same as vardenafil? They both
have about the same 5- to 10-millisecond range. So why shouldn\'t we
look at them the same? Well, there\'s a big difference. The hERG
concentration blockade for IC50 is equal to or very close to the
clinical concentration, very different in the 1000X difference on
vardenafil.

Number two, if you use 400 milligrams of moxifloxacin, you get the 5- to
10-millisecond range. What if you double the dose? We have data on that.
You get doubling of the effect. So you get a very sharp increase in
dose-response.

You have minimal effect on heart rate, where you have an increase in
heart rate on vardenafil. Therefore, there\'s a clear difference between
moxifloxacin and vardenafil in terms of its QT dynamics.

We now have reasonably good data on moxifloxacin. It\'s been out long
enough. The company did two simple post-marketing observational studies,
one in Germany, one in the U.S., about 25,000 subjects each, in which no
signal for torsade or risk in a clinical condition of community-acquired
pneumonia. Most of these people are sick, elderly, have lots of
cardiovascular and pulmonary disease by definition.

And if you look at the post-marketing surveillance data through May 7,
2003, moxifloxacin has been used in 19 million patients, over 400,000
patient-years, and there have been 12 reports to the sponsor of torsade
de pointes. Of those 12, Dr. Faich looked at each one of them very
carefully and determined that all of these 12 cases, except for 2, had
major confounders, meaning people with fresh infarction, hypokalemia, on
sotalol, et cetera. Now, that doesn\'t mean that moxi didn\'t contribute
to the torsade by any means, but I think it\'s confounded. You can\'t
really have any idea of how much, if at all, moxi contributed.

There are two cases, however, one of which there was no clinical data
and one of which does not appear to have any confounding factors.

If you look at the rate of torsade, using apples to apples, that is,
take the rate of the U.S. because that\'s one reporting system, take the
four cases, irrespective of the confounding, take the number of patients
who have gotten oral moxifloxacin in the United States, that number is 4
per 7.7 million. And that\'s about exactly the same rate that Brinker
from the Office of Drug Safety reported compared to all kinds of other
antibiotics, many of which no one thinks has any QT effect.

Finally, we have the sildenafil database to look at and compare that
because of the reference I made. This is from the FDA Adverse Event
Reporting System in which there are close to 39 million sildenafil
prescriptions from 1998 through December of 2002 and 0 cases of torsade.
Obviously, is it under-reported? Are some of the deaths torsade? We
don\'t know, but at least there\'s no signal in these databases as there
was not one, as we saw this morning.

Finally, in my final one or two slides, is what\'s the regulatory
opinion? Well, the regulatory opinion from the Europe and the U.S. is
pretty much the same. Dr. Rashmi Shah in the CPMP and the concept paper
both have provided what we\'ll call statements of risk from their
experience.

Now, this was provided at the Shady Grove Meeting in January by Dr.
Temple. This is the slide he used, which I took off the FDA web site,
and he graded 5 to 10 as no clear risk, which is very similar to Dr.
Shah\'s classification. And he points out, however that this is a
surrogate, and we know that there is good evidence from antiarrhythmic
drugs and terfenadine that the size of the effect relates to the
incidence of torsade. But could there be other properties that mitigate
this risk or enhance this risk?

So the next slide says what are the factors on vardenafil that might
mitigate this no clear risk to make it even less than a no clear risk in
terms of concern. I think one is it\'s going to be used in men, assuming
the labeling, which one has to assume for this analysis of mitigating
factors. It\'s going to be used in men. And clearly the risk of
drug-induced torsade de pointes is less in men. Almost two-thirds of the
torsades are in women or an even higher percentage.

Number two, you\'re not giving a drug chronically for months or years.
You\'re giving an intermittent drug.

Number three is ‑‑ and this is very important ‑‑ this extremely shallow
dose-response curve, which even if one wants to argue that the 80
milligram dose ‑‑ maybe they could have given a higher dose if the
people would tolerate it, which is a question ‑‑ could be equivalent to
people with all kinds of things going on and they take an overdose of
vardenafil, the very flat dose-response curve, instead of having an
8-millisecond, would probably go up, because they\'ve modeled in their
slides on this, if you want to see it, to like 8.6 milliseconds or call
it 10 milliseconds. It\'s not going to be an 8 going up to 80 or some
major effect.

Finally, the fact that this drug increases heart rate, as has already
been mentioned, I think is a mitigating factor versus drugs that don\'t
affect heart rate or particularly those that slow heart rate.

So, in conclusion, I think that we do have a definitive study. We\'re
dealing with the QTci, which I think is the best measurement for this
data set, though not necessarily for all data sets, of 5 milliseconds.

By the way, the QTci exponent is about .20. For the population-based
study, it\'s about .33 which is equivalent to Fridericia\'s. So the
population data, which you haven\'t seen, is really identical to
Fridericia\'s.

The magnitude is generally considered not a clear risk. There\'s no
clinical outliers, no signal in the post-marketing surveillance. Thus, I
think the QTc effect of vardenafil for all these reasons should not pose
a cardiac risk.

Thank you very much.

DR. BORER: Thank you very much, Joel.

I\'m going to hold any discussion at this point. I think that much of
Joel\'s presentation was, as he said, a critique, and we\'re going to
get into that when we actually do the discussion surrounding the FDA
questions.

So at this point, we\'ll break for lunch. There are tables being held in
the restaurant downstairs. We\'ll get back here and start around 1:35 or
1:36 with the FDA presentation.

(Whereupon, at 12:43 p.m., the committee was recessed, to reconvene at
1:35 p.m., this same day.)

AFTERNOON SESSION

(1:39 p.m.)

DR. BORER: It\'s now, by my watch, 1:39-and-a-half, and we were supposed
to have started at 1:36. So we\'re 3-and-a-half minutes behind and
counting.

We\'ll begin the afternoon session with public comment before the FDA
presentation. We have two requested presentations, one from Pfizer,
which will take 10 minutes, and one from Dr. Culley Carson, which will
also take 10 minutes. So if we can begin with Pfizer please. It\'s Dr.
Sweeney.

(No response.)

DR. BORER: Well, we\'ll reverse the order then. Is Dr. Carson here?

MR. CLARK: This is Bob Clark from Pfizer. Dr. Sweeney will be here about
a minute.

DR. CARSON: My comments will be considerably less than 10 minutes. I\'m
Culley Carson. I\'m a professor of urology at the University of North
Carolina, but I\'m here as President of the Sexual Medicine Society
which is a society that represents urologists and other clinicians that
are interested in investigation and treatment of erectile dysfunction.
We\'ve been looking at erectile dysfunction for many years.

Really, one of the reasons I\'m here is so that we don\'t lose sight of
the fact that many patients are well treated for erectile dysfunction by
the drugs that are being proposed and the drug that\'s currently
available.

I personally have experience in the clinical trials with all three of
the new PDE5s, sildenafil, taldalafil, as well as vardenafil, and have
had excellent results with all of these drugs with very little side
effects.

I think really one of the issues is that erectile dysfunction is a huge
problem in this country. There are an estimated 20 million American men
who suffer from erectile dysfunction. Only about 10 percent of them are
treated currently. Erectile dysfunction, which may seem trivial to many
people who don\'t have it, is not trivial because it does have an impact
on the patient\'s self-esteem, on couple\'s problems, on depression, on
the compliance that they have with other medications, especially
antihypertensives, antidepressants, and even antipsychotics. So clearly
there\'s a major issue with erectile dysfunction, and really the PDE5
drugs are the only ones that are clearly effective and safe for the oral
treatment of erectile dysfunction with very minimal invasiveness.

To date, sildenafil has been used for more than 5 years in the United
States, more than 7 years in trials. As you saw earlier today, there are
more than 10 million prescriptions written by greater than 600,000
physicians around the world. And the incidence of death has been
minimal. Indeed, there are a number of studies looking at a comparison
of cardiac events and deaths comparing placebo-treated patients in
trials, expected numbers from matched populations, and patients treated
with sildenafil, and the numbers are no different in any of those
groups. Similar studies have been carried out with taldalafil and
vardenafil with very similar results. So clearly the data show that
cardiac events and cardiovascular events, indeed, are very few, far
between, and certainly with very minimal impact on the total number of
patients that are treated for this very difficult condition.

Why do we need newer drugs? Well, we need newer drugs because there are
still only 10 percent of patients that are being treated currently, yet
many of them have significant distress from their erectile dysfunction.
I think newer drugs, in addition to the market, will increase the number
of men who can be treated and will be treated, and it will increase the
individual\'s choice by drug profile and type of agent available to
them.

And this is important because we know that men\'s health is a major
issue that\'s not been focused on as much as it should be by our
national health system. It has a limited focus throughout the United
States, and this treatment class encourages men to seek medical
attention for ED which allows them to see their physician and perhaps be
treated for other conditions. Indeed, we know from a number of studies
that ED is a harbinger of other more serious vascular events later in
patients\' lives.

So I would just encourage everyone to remember that there is a large
number of patients who have been successfully treated who are
enthusiastic participants in the trials and users of these agents to
restore their erectile function and, indeed, much of their marriage.
Thank you very much.

DR. BORER: Thank you very much, Dr. Carson. I think it\'s a point well
taken that we\'re talking about consideration of a drug that does have
very real benefits that have to be balanced against the ‑‑

DR. KOWEY: Jeff, can I just ask one quick question?

DR. BORER: You can. Let me just get one thing done first, if I may.

Dr. Carson, just for the record, though, you need to tell for the
recorder if you had any support in coming up here or if this is just for
the ‑‑

DR. CARSON: No. I came up here as President of the Sexual Medicine
Society.

DR. BORER: Okay, great. Thank you.

Peter?

DR. KOWEY: Just a quick question, Dr. Carson. I\'m totally naive to this
question, so it\'s not a trick question. Tell us what the benefit of
this drug is over current therapy.

DR. CARSON: That\'s a good question. There are no head-to-head studies,
so we really don\'t know. You\'ve seen what the biochemical profile is
in brief today. It\'s more biochemically potent than sildenafil. Whether
that\'s going to translate into an advantage clinically or not, I don\'t
think anyone really knows, and until either the market determines that
or head-to-head studies are available, we really won\'t know.

DR. BORER: Thank you very much, Dr. Carson.

Now we\'ll have the planned presentation from Pfizer. Dr. Sweeney.

DR. SWEENEY: Thank you, Mr. Chairman, for the opportunity to discuss
Viagra\'s extensive database, particularly with reference to QTc. We
particularly welcome this opportunity because we\'ve been cited in the
study conducted by Bayer earlier today and extensively in the FDA
document.

As the committee is aware, QTc is a surrogate for the propensity for the
causing of ventricular arrhythmias, particularly torsade de pointes.
It\'s really essentially used with drugs in the investigational phase
prior to approval.

A much better estimate of the propensity to cause arrhythmias is
real-world clinical experience in millions of patients ‑‑ and that\'s
what we have with Viagra ‑‑ to exclude a risk for ventricular
arrhythmia.

Before I talk about Viagra in particular, I just want to follow up from
what Dr. Carson was saying about the context of ED and cardiovascular
disease. ED is primarily a vascular condition. In most patients, it\'s
usually arteriole disease. The risk factors for ED are pretty much
identical to the risk factors for coronary artery disease: age,
hypertension, diabetes, hypercholesterolemia, and the classic lifestyle
factors of smoking, obesity, and sedentary lifestyle. If I could paint a
picture for everybody, the typical ED patient is a man of over 50 with
multiple risk factors and/or overt cardiovascular disease, coupled with
multiple concomitant medications.

The other thing to keep in mind is these patients have cardiovascular
disease and these patients have cardiovascular events. There are
approximately 400,000 sudden cardiac deaths occurring in the United
States each year. That\'s about one every minute, and the overwhelming
majority of these patients have coronary artery disease.

The baseline risk of myocardial infarction in the typical patient of 50
years old, is 1 to 2 percent a year while the ED patient, has
approximately twice this risk based on epidemiological evidence. Add on
to that the fact that sexual intercourse itself raises the risk of
myocardial infarction about twofold in the 2 hours following sexual
intercourse. Therefore, cardiovascular events are both expected and do
occur in the ED population. So that\'s the background of the population
of patients we\'re dealing with with this condition.

The Viagra experience. Viagra was approved by the Cardio-Renal Division
of the FDA in March 1998 and is currently approved in 120 countries. In
5 years, we\'ve had over 20 million patients treated. More than 1
billion doses of Viagra have been taken. And Viagra has been under
clinical research for more than 10 years now. There have been more than
13,000 patients studied, for a total of 13,000 patient-years of
exposure. In addition, there are a separate 26,000 patients studied in
real-world practice, a cohort followed in the UK. There are 200
independent studies involving up to 10,000 patients in the literature.
Overall, Viagra is the most extensively studied drug ever in sexual
health.

I want to talk particularly about the post-marketing data first of all.
As I have mentioned, we\'ve treated 20 million patients. Most have
cardiovascular risk factors. Despite this, we have not had a single
report of torsade de pointes anytime in the 5 years, and we have had
only two cases reporting QT prolongation, and both are temporally
related to concomitant medications known to cause QT.

I\'d like to consider them first in detail. The first case is a consumer
report of a man who had been taking Viagra for 2 years and cisapride for
7 months who reported that his QT had been prolonged from 205
milliseconds to 235 milliseconds. This was not confirmed by a health
care practitioner.

(Laughter.)

DR. SWEENEY: We obviously have patients who are very interested in their
health in our population.

(Laughter.)

DR. SWEENEY: The second one referred to in the FDA document is of a
health care professional reporting a QT prolongation in association with
sotalol in a patient 3 weeks after they had taken their last dose of
Viagra. Viagra is essentially cleared from the body in 24 hours. We
regarded that cause being excluded because there is not a Viagra
molecule left in the body after 3 weeks. Hence, we feel that there are
no cases relating Viagra to QT prolongation.

Post-marketing data analysis, of course, is a highly specialized area
and one which has many caveats attached. There are limitations in
interpreting this data, but above all, we should keep in mind that the
purpose of this data is to generate signals of possible safety issues.

A recent publication of an analysis conducted by Wysowski and colleagues
from the FDA Office of Drug Safety had many caveats, but within these
caveats, they concluded that reports of death in men prescribed
sildenafil that were submitted to the FDA led us to conclude that there
did not appear to be an increase in deaths due to MI above expected
numbers.

Moving up the hierarchy now of scientific rigor, the cohort
observational study in clinical practice completed was a prescription
event monitoring study in the UK. The PEM study as conducted by the UK
National Health Service sends a copy of every prescription for Viagra
written to the unit that conducts these studies, who then send a form to
every physician who wrote a prescription and asked them what events
occurred in the observation period. And it\'s done on an ongoing basis.
There\'s normally about a 55 percent response rate and events are sent
in irrespective of causality.

We had 26,000 men followed in this study, for a total of 42,000
patient-years of observation. Again, not a single case of torsade de
pointes or prolonged QTc was reported in this study, and the rates of
cardiovascular events overall, including MI and sudden death, were
consistent of those well documented in the UK population, even taking
into account any under-reporting in the PEM study.

I\'m sure as the panel agrees, the gold standard for the assessment of
safety and efficacy of pharmaceutical products is the controlled
clinical trial. We have completed over 100 controlled clinical trials to
date with 13,000 Viagra patients and 6,000 placebo patients for
comparison. The rate of MI and cardiovascular adverse events were
comparable between the two. There is no difference. There is no evidence
that in controlled studies Viagra in any way precipitates cardiovascular
events. The number of sudden death cases was well within the
epidemiological prediction. There are so few that we were unable to do
valid statistical comparisons, but well within what would be expected
from epidemiological evidence.

I now want to talk briefly about study 10929 that was presented this
morning, firstly to state that Pfizer had no input into the design of
the study and we only saw the results when it was posted in public on
the FDA web site. As such, our comments are from the last 24 hours when
we have reviewed this data.

The first thing to note is that sildenafil has an absolute
bioavailability of 40 percent. It\'s about 3 times the bioavailability
of vardenafil. It\'s the most potent 3A4 inhibitors because of the high
bioavailability, increased Cmax less than 4-fold. So the 400 milligram
sildenafil dose which you saw, 4 times recommended dose, leads to peak
plasma levels that exceed those encountered in normal clinical practice.

Despite this, there\'s no evidence of a clinically significant QTc
effect. The mean change was less than 10 milliseconds for a dose well
above what would be encountered in clinical practice and is consistent
with no preclinical signal and no reports of torsade de pointes being
received.

To summarize the Viagra experience, there are no cases of torsade de
pointes in 20 million patients, no clinically relevant change in QT or
QTc in clinical studies, an incidence of cardiovascular events very
similar to placebo in 13,000 patients. There is no evidence in Viagra\'s
extensive clinical trial program and post-marketing of a relevant effect
on cardiac repolarization.

Viagra has a wide margin of safety. It has a relatively high
bioavailability, and the differences between the drugs are all in
pharmacokinetics. It has high bioavailability and a short half-life. In
addition, the extent of 3A4 inhibitor interaction is less with Viagra
than some other PDE5 inhibitors, and it does not compromise its overall
safety.

As such, the safety and efficacy profile of Viagra may not be applicable
across compounds with different PK and structural characteristics.
Further data would be required to make that extrapolation.

Viagra is the only PDE5 inhibitor with extensive real-world data in
millions of patients showing a lack of proarrhythmic effect through 5
years following FDA approval.

Just some final thoughts now. By necessity, I\'ve talked essentially on
safety, but we have to keep in mind that the benefit-risk ratio for
Viagra in patients with cardiovascular disease is very positive. It\'s
being used extensively for the treatment of ED in patients with
cardiovascular disease, even patients with heart transplant. In
addition, it\'s now being investigated for patients with heart failure
and other serious cardiac diseases, and we\'ve had encouraging efficacy
data in adult and pediatric pulmonary hypertension with no new safety
signals, and that is an ongoing research program that we hope to file
with the agency in future years.

So, again, thank you, on behalf of Pfizer, for this opportunity to
discuss our safety and also to keep in mind that Viagra has improved the
lives of millions of men with ED and their partners, and this is
particularly prevalent in cardiovascular disease. Thank you.

DR. BORER: Thank you very much, Dr. Sweeney. Do you have another
presentation from Dr. Falk?

DR. SWEENEY: Yes, Dr. Falk is just going to make a few comments.

DR. BORER: Okay.

DR. KOWEY: Dr. Sweeney, before you leave the podium, experience in women
with sildenafil?

DR. SWEENEY: We have conducted an extensive clinical trial program with
female sexual arousal disorder and the safety profile is essentially the
same as men. We conducted a drug interaction study with oral
contraceptives in healthy female volunteers, and although the study
wasn\'t specifically set up to investigate QTc, there was no QTc effect
seen.

DR. KOWEY: Can you give us some ball park idea of how many women have
been exposed to sildenafil?

DR. SWEENEY: It\'s around about 800 to 1,000, but that program is
ongoing and there\'s an ongoing discussion with the agency.

DR. BORER: JoAnn?

DR. LINDENFELD: You have a lot of impressive data. I wonder if you could
just tell me what the risk profile is of men with coronary disease who
take Viagra compared to those who don\'t?

DR. SWEENEY: As far as we can see, it\'s exactly the same. The only
additional risk is the additional epidemiological risk for erectile
dysfunction patients because they seem to have about twice the risk of
myocardial infarction than patients without erectile dysfunction largely
because ED is a visible manifestation of covert coronary artery disease.

DR. LINDENFELD: You might just wonder if slightly healthier patients
choose to use Viagra and whether or not you could be missing a signal
there. You have lots of impressive data, so I don\'t want to emphasize
that too much.

DR. SWEENEY: I think Dr. Falk is going to address that particular
question about missing signals.

DR. BORER: Thank you very much.

DR. FALK: Members of the committee, ladies and gentlemen, I have no
slides and I will be brief since the hour is late.

I\'ve been asked by Pfizer to give my opinion on some of the data that
is in the FDA document regarding the adverse events reported in patients
who have been taking Viagra and who either died suddenly or who have had
seizures or loss of consciousness, and I will limit my comments to that.

I\'m a clinical cardiologist at Boston University School of Medicine and
I\'m also affiliated there as their cardiology consultant to the Boston
University Sexual Health Program run by Dr. Irwin Goldstein.

Looking this over, I wanted to put it into perspective or my
perspective, and that is, in the United States it is estimated that
there are approximately 11 million people, men and women, with coronary
artery disease. There are about 1.3 million to 1.5 million myocardial
infarctions per year in the United States, and somewhere between 300,000
and 350,000 cases of sudden death, some of whom will be associated with
myocardial infarction, the majority of whom will be associated with
coronary artery disease.

It has been estimated in epidemiological studies both from the United
States and from Europe that somewhere between 1 and 3 percent of
patients who sustain a myocardial infarction do so shortly after having
sexual intercourse. So out of 1.3 million per year in U.S., that\'s
about 1,300 people per year, up to 5,000 a year. And in the period that
has been surveyed, which is a four-year period, we\'re talking between
5,000 and 12,000 myocardial infarctions, some of whom, as I said, will
die related to sexual intercourse.

The cases that the FDA has raised their eyebrows at are approximately
192. Less than 80 of these have died and they\'re reported between 1998
and 2002. There are no reported cases of torsade. These are all
patients, of course, who at some time have taken Viagra, not all
temporally related. There are two QT prolongations, which we\'ve heard
are of dubious association.

There are 88 patients who had either syncope or a seizure, and we are
told in the FDA review that patients with normal electrocardiograms
recorded were excluded.

So the question is, could these 88 and could these sudden deaths in
patients who have taken Viagra be related to torsade? Could some of
them? If they were, then I would suggest that one might find QT interval
prolonged in patients who had had syncope. We don\'t know precisely how
many patients had syncope. There were 88 with syncope and seizures. We
are told that normal electrocardiograms were excluded, ergo those who
had ECGs had abnormal ones. We are also told that there were no
prolonged QTs other than the two that have already been dealt with. So
that makes it unlikely in that group.

We would also anticipate, as with drugs such as cisapride, that some
patients who don\'t have significant structural heart disease, perhaps
have left ventricular hypertrophy, would have had sudden death. We
don\'t see all the reports in the FDA documents, but the ones that are
highlighted all have very severe coronary artery disease. So I think
that in terms of a signal, the things that we would look for do not jump
out, but of course, a signal perhaps could be there.

However, in looking at the information in these 192 cases, again less
than 80 deaths in 4 years, I would suggest that a better way of
understanding this is what we are seeing is what might be anticipated in
a relatively high-risk population or in a high-risk population for
sudden death. That is, these are patients with erectile dysfunction, and
the ones reviewed have significant disease in the cases. Patients with
erectile dysfunction we know have an increased risk of coronary artery
disease. Death is expected in coronary artery disease. Death during or
after sex is a well-recognized phenomenon in coronary disease. In fact,
the two studies I quoted you were performed before Viagra or any other
similar drug was available. So there was no cause and effect there. 1 to
3 percent.

We have had no, as I\'ve said, association of syncope with any report of
QT prolongation in 88 syncope/seizures, and I would suggest once again
that the data that we\'ve seen in these small number of patients over 4
years is entirely consistent with patients dying of the natural history
of their coronary artery disease coincidentally around the time of
sexual intercourse. I feel from my review of this that a signal for
torsade is a much, much less likely factor than just a statistical
association between sudden death and sexual intercourse.

Thank you.

DR. BORER: Thank you very much.

Are there any questions or comments from the panel?

(No response.)

DR. BORER: No. If not, thanks very much, Dr. Falk. That\'s useful
information.

Is there any other public comment, any other comment from the public?

(No response.)

DR. BORER: If not, we\'ll move ahead with the FDA presentation, which
will be introduced by Dr. Griebel.

DR. GRIEBEL: Good afternoon. My name is Dr. Donna Griebel. I\'m the
Deputy Director of the Division of Reproductive and Urologic Drug
Products. The division would like to extend our thanks to you all for
agreeing to meet here today to discuss two urologic drug products.

We are going to be merciful this afternoon and we have created a
Reader\'s Digest, Cliff Notes version of our talks. So we\'ve really
honed it down to just a few slides, and it should be relatively quick.
But I won\'t guarantee that it will flow very well.

The first slide is the review team. It lists the people who worked very
hard getting the briefing document together and preparing for this
meeting. The clinical team was led by Dr. George Benson. The clinical
pharmacology team was led by Dr. Ameeta Parekh. The Office of Drug
Safety was very important in our review. They helped us identify the
post-marketing adverse events that you found in our briefing document.
They were led by Dr. Debra Boxwell. And our biostatistics team lead was
Mike Welch.

Again, in the interest of time, we are just going to move straight
forward with the alfuzosin review by Dr. Venkat Jarugula.

DR. JARUGULA: Good afternoon. I\'m Venkat Jarugula, clinical
pharmacology reviewer for the alfuzosin NDA.

This morning we have heard about the results of the alfuzosin study in
detail. So I\'m just going to focus on a few important slides of my talk
to highlight the results of the alfuzosin study, PDY 5105.

What I have here is a table giving a comparison of the mean QTc change
from baseline versus placebo for different methods of correction for the
alfuzosin 10 milligram dose, 40 milligram dose, and the moxifloxacin 400
milligram dose.

As we can see here, different methods of correction give different
results on the mean QTc change for alfuzosin, as well as moxifloxacin.
The Bazett method gave the highest QTc effect ranging from 10
milliseconds to 14 milliseconds. The Fridericia method also gave higher
QTc changes, higher increase in QTc\'s ranging from 5 milliseconds to 8
milliseconds, compared to the population and individual methods where
you see only a 2- to 4-millisecond increase. In fact, this is about half
of the effect that you see with the Fridericia method. The Holter
monitor method, on the other hand, showed the lowest effect on the QT
interval.

As we can see from this slide, there is a dose-related increase with
alfuzosin 10 milligrams and 40 milligrams with all the correction
methods and also with the Holter monitor method, although the magnitude
of these QT changes are up for discussion later on.

One thing that I would like to point out regarding the Holter monitor
method is the time course effect on the QT interval was not captured
with this method because the QT intervals were classified into RR bins
and averaged in each RR bin and compared between the baseline and the
treatment group. As a result, there is no time course effect that can be
captured with the way the study was conducted with this Holter monitor
method.

Next I\'m going to show the number of outlier subjects again with each
correction method. As one can expect, based on what we discussed so far
and what we know, the Bazett method yielded the highest number of
outliers for all the outlier groups.

Just to focus on the outlier group that was not mentioned this morning
and that was also discussed somewhat to be sensitive, the delta QTc
between 30 milliseconds and 60 milliseconds group, with the Fridericia
method there were 9 outlier subjects with a 40 milligram dose and 1
outlier with the 10 milligram dose, compared to 2 outlier subjects with
the population and the individual correction method at the 40 milligram
dose, and 0 with placebo with all these methods of correction.

For outliers of delta QTc greater than 60 milliseconds or QTc greater
than 450 milliseconds, you have virtually 0 number of outlier subjects
with all the methods except for the Bazett method of correction.

Again, you can see there is some dose-related trend, especially if you
look at the Fridericia method.

What this slide shows is a concentration of alfuzosin and QT
relationship calculated by the individual correction method. What I have
here is a panel of 45 subjects that participated in the study, that
completed the study. Each panel represents 1 subject in the study. On
the y axis, I have QTc values plotted against the plasma concentrations
of alfuzosin on the x axis. The red colored trend line is the individual
trend line, and the blue line is the population line which is the same
for all subjects.

As you can note here, there are some subjects, this one, this one, here,
here, that have increasing QT intervals with increasing plasma
concentrations. Please note that when you pool all these data and plot
in one single plot, the individual trends may be masked and you may see
a plateau. So that is a point we want to make on this slide.

So these are the highlights of the results that I want to bring into
perspective before we go into the discussion. I want to point out the
main review issues that arose from the review of this alfuzosin QT
study. I\'m going to read my review issues from the slide that I\'m not
going to show here.

So the main issues that were identified and to be discussed in the
questions are, which QT interval correction method is most appropriate
for assessing the proarrhythmic risk of alfuzosin? I guess this will
equally apply to vardenafil also. How should the QT data derived from
the Holter monitoring method be interpreted? Is a single-dose study
adequate to assess QT prolongation?

Thank you very much and Dr. Leslie Kenna will present on vardenafil.

DR. KENNA: Good afternoon. I am Leslie Kenna, and I was one of the
clinical pharmacology reviewers for the vardenafil submission.

Today I will just highlight the results of the drug-drug interaction
studies with vardenafil and also concentration-response analyses.

First, the impact of the pharmacokinetic interaction between various
clinically relevant CYP3A inhibitors was studied, including concomitant
administration with ketoconazole and two protease inhibitors, indinavir
and ritonavir.

One reason the protease interaction studies are important to consider is
that a series of small studies have reported a higher incidence of
sexual dysfunction, including erectile dysfunction in patients with HIV.
The incidence of erectile dysfunction ranges from 33 to 50 percent.

Cross-sectional studies have also shown that patients with HIV,
including those on triple therapy, use PDE5 inhibitors.

This bar plot demonstrates ritonavir\'s effects on exposure to
vardenafil as measured, one, here in orange, by maximum concentration,
or Cmax, and two, this blue bar here, area under the concentration time
curve, or AUC. What this shows is that ritonavir causes a 12.7-fold
increase in vardenafil\'s Cmax and a 48-fold increase in vardenafil\'s
AUC. It is unknown whether AUC or Cmax correlates better with QT
interval.

There was a question raised during the morning session regarding the
nonlinearity of vardenafil pharmacokinetics. Vardenafil has a nonlinear
pharmacokinetic profile for doses greater than 40 milligrams.

This plot shows how the 80 milligram dose of vardenafil investigated
relates to the case of a drug-drug interaction with ritonavir.
Vardenafil concentration is plotted on the y axis and time is plotted on
x axis. The green line, this little one down here, shows the average
concentration of vardenafil as a function of time after administering a
single 5 milligram dose of vardenafil alone. The blue line shown here
shows the concentration of vardenafil as a function of time after a
single 5 milligram dose of vardenafil is co-administered with 600
milligrams of ritonavir taken b.i.d. The red line shown here shows the
average plasma concentration of vardenafil as a function of time after a
single 80 milligram dose of vardenafil.

As expected, based on the previous graph shown, the Cmax reached when
the 5 milligram dose is taken with 600 milligrams of ritonavir is
approximately 13 times higher than when the 5 milligram dose is taken
alone. The average maximum concentration of vardenafil observed after an
80 milligram dose is administered is nearly 3 times greater than that
observed for the interaction with ritonavir. This shows that the choice
of the 80 milligram vardenafil dose covers the Cmax expected when dosing
600 milligrams of ritonavir with 5 milligrams of vardenafil.

Note, however, that this red line dips below the blue line at about 5
hours. So this says that the area under the curve observed during this
interaction was not covered by this study design.

And note again that it is unknown whether Cmax or AUC is better
correlated with the response to vardenafil.

Note also that the sponsor collected data on concentration, QT and RR up
until 4 hours after dosing.

This is my final slide. The sponsor presented results of a
concentration-response analysis this morning suggesting that the average
response plateaus within the range of concentrations of vardenafil
tested. As the sponsor also pointed out, there is large inter-individual
variability in concentration and response.

This slide shows individual data plotted separately. Here are 59 plots
of QTcF and concentration. So there\'s one plot for each subject after
10 and 80 milligram doses of vardenafil. The black dots are the data
points. The blue line in each panel shows the linear trend through the
data when all the data are pooled. The orange line shows the individual
trend in that particular panel. We are not suggesting that there is a
linear relationship between concentration and response. However, the
point of this slide is that although some subjects have a shallow
concentration-response relationship, others may not within the range of
doses tested.

So just like the former speaker, I\'m just going to summarize the review
issues that were raised by study 10929.

In evaluating the risk of QT prolongation, first, should the results
with respect to one particular correction method be favored over
another? Second, were the vardenafil doses investigated adequate? Third,
was the duration of concentration and response sampling adequate? And
finally, is it appropriate to set the 90 percent or some other
percentage level upper confidence limit for the mean change in QTc from
baseline relative to placebo at 10 milliseconds or some other cutoff
value?

Now, Donna Griebel will provide concluding remarks.

DR. GRIEBEL: Well, it\'s not exactly concluding. I\'m going to give a
quick, abbreviated version of Dr. Marcea Whitaker\'s post-marketing
review that was presented in a lot of detail in the FDA briefing
document. I would like to just focus on the torsade events, the torsade
categories, and I\'m going to go through the two drug classes. I just
want to do that to put into perspective what was reported this morning
for moxifloxacin in post-marketing for torsade.

For the alpha blockers, we\'ve pooled at the top of this slide IMS data
that we had, estimated sales since 1998 for all three of the drugs that
are listed at the top of the three columns, and over 110 million
prescriptions have been sold since 1998 according to a sample in the IMS
data. Of those, you see for terazosin, two cases; doxazosin, three; and
tamsulosin, one. The dates of approval for these drugs were 1987, 1990,
and 1997.

Viagra we\'ve heard discussed this afternoon as well. At the top we have
58 million prescriptions up to December of 2002 in the United States.
There were only two cases reported of torsade, and as we\'ve heard
discussed, and I think that we made clear in our briefing document,
these were dubious cases when you read the narrative.

Then if you look at moxifloxacin, here we have Bayer reported 19 million
patients exposed, and this is patient exposure as compared to
prescriptions sold in the previous slide. Those were a sampling of
prescriptions.

There were reported to ODS in our search, or the Office of Drug Safety
at the FDA, 15 cases of torsade, and one of those the sponsor is seeking
additional information to clarify the report. 9 were U.S., 6 foreign.
There were risk factors in these patients. The majority of them were
female; age greater than 70, 9. Some confounding factors or potential
risk factors for developing torsade included underlying cardiac disease
and electrolyte abnormalities and concomitant drugs in 5 that included
amiodarone in 2 and the other 3 were diuretics. These 15 cases were
temporally related. Most of them ranged 1 to 3 days. There was one that
occurred 8 days after starting dosing.

We were struck by that number 15 after we had gone through all of those
reports that we had talked about in our post-marketing review. We
believe that may indicate that the moxifloxacin active control does
indicate that it is an active control in these studies.

The moxifloxacin label does contain a bolded warning about QT
prolongation and it includes a patient package insert of information to
provide to patients on clinical events that they need to report to their
physicians, as well as reporting their concomitant medications and
medical histories. I don\'t know if that was a component to the
heightened reporting that you might have seen with moxifloxacin, but it
was of interest.

Bayer did mention that they had a pharmacovigilance plan for vardenafil
and we would be interested in hearing that.

I think this concludes our comments and our presentation. We do look
forward to hearing your discussion of our questions this afternoon, and
we\'ll be happy to take any questions regarding our reviews. Thanks.

DR. BORER: Thanks very much, Dr. Griebel.

We may have some questions for the FDA, and we\'ll also go into
additional questions we may have for Bayer and for Sanofi-Synthelabo.

Beverly?

DR. LORELL: Yes. I have a question that relates not just to
post-marketing, but to clinical development. We heard this morning from
both sponsors data regarding a lack of any signal of torsade de pointes
during clinical development trials, phase I to III. Can you or perhaps
another member of the panel or the audience put that into perspective?

If one were to look at ‑‑ let\'s just take three examples of drugs that
are known to have a heightened risk of torsade de pointes. Let\'s take,
for example, two cardiac drugs, sotalol and amiodarone, and a noncardiac
drug cisapride. Was there any signal whatsoever in clinical development
of a risk of torsade de pointes, or can you give us those numbers to put
that piece of safety into perspective?

DR. GRIEBEL: I\'m going to call on Doug Throckmorton to see if he can
help me out here with that.

DR. THROCKMORTON: The cardiac drugs, you said sotalol and amiodarone?

DR. LORELL: Yes.

DR. THROCKMORTON: I can\'t give you the amiodarone NDA. Its rate of
torsade is pretty low. Even in post-marketing, it\'s been hard to show
clearly that it\'s a torsadogen. Sotalol had clear torsade. No problems
at all.

Another compound a little closer to home here might be bepridil, which
was an anti-anginal drug that was developed. That again had cases of
torsade in the NDA, but it prolonged the mean QT 50 milliseconds,
something like that. It had a different level of signal perhaps.

Cisapride had no signal in its NDA database. Its first hints were a
post-marketing report of rapid heart rates in an Australian study that
came out shortly after it was published, as I recall.

DR. BORER: Beverly, did you have a follow-up to that?

DR. LORELL: No. I think that\'s a little bit of a useful perspective.
Certainly I think if one saw unsuspected, even a cluster of cases during
clinical development, that would be very worrisome. But I just wanted
to, I think, make sure that I understood correctly that the lack of a
signal is not useful.

DR. THROCKMORTON: The occurrence of a case of torsade in a development
program, outside the antiarrhythmic world, really is a signal that we
take very seriously. I can think of it occurring on two occasions in the
time that I\'ve been familiar with this problem, and in both cases it
was a real thing that was taken seriously. It\'s pretty rare.

DR. BORER: Tom, then Peter, then Paul.

(Laughter.)

DR. FLEMING: One of the questions that I had, listening to Joel
Morganroth\'s presentation, I think has been ‑‑ relevant additional
information has come from FDA. Bayer\'s slides 58 and 59 were comparing
what was known from our post-marketing surveillance for occurrences of
torsade de pointes with moxifloxacin and with Viagra. On slide 58, there
was an indication that there were 4 cases in 7.7 million. That seems to
be fairly consistent with what we just heard from FDA of 15 cases in 19
million. That\'s 1 per 2 million cases from the sponsor\'s review; 1 per
1 million cases in the FDA review.

Then for Viagra on slide 59, they had said there were no cases reported
in 39 million prescriptions of Viagra, and similar figures were given by
Pfizer saying 20 million patients receiving a billion doses have had no
cases of torsade.

Statistically those are strikingly inconsistent rates that you would
have no cases in 20 million to 40 million versus 15 cases in 19 million.
Either it tells me that the Pfizer passive surveillance system is
leading to a gross underestimate of torsade or it tells me that in fact
their experience does represent natural history. The cases are, in fact,
incredibly rare and that moxifloxacin is, in fact, clearly an agent that
induces an increased risk of torsade. Only one of those two statements
can be true. Either moxifloxacin does increase or it doesn\'t, and the
Pfizer surveillance is grossly under-representing cases of torsade when
they exist. Any insights?

DR. KOWEY: Tom, is it possible, just as a question, that generally
Viagra is not given to women, which is an issue in torsade? And the
other is that Viagra is given for a very short period of time,
intermittently, and the time of exposures would be grossly different
between the two compounds. I\'m just speculating, but there are very big
differences in how these drugs are used.

DR. RODEN: We don\'t know how many of those cases for moxi were in
hospital in monitored patients, which is not the way Viagra is ever
given.

(Laughter.)

DR. FAICH: Mr. Chairman, I\'m Jerry Faich. I actually reviewed the
moxifloxacin cases and maybe let me just elaborate on them to give you a
better picture.

I looked at 12 of them. Four of them were in patients who were getting
intravenous therapy and those patients were severely ill and were
monitored. So you have a different patient population that I think you
have to consider. So that\'s a major factor in doing this.

Also, I think it\'s fair to say that there\'s a reporting artifact here.
You\'ve got torsade in the label of moxifloxacin, and that may well
stimulate reporting. I have no way to measure that.

I would point out for the 8 oral cases that I went through, actually 6
of them have severe cardiac disease, a pacemaker in place and prior
syncope, for example. Two of them were immediately post MI and post
resuscitation. A couple of them were congestive heart failure and sick
sinus syndrome. So these were patients with severe cardiac disease.
There are two exceptions to that. One of them we have no information on
and the other might be a less confounded case.

So it looks like the patient population may well be markedly different.
These are patients who have pneumonia in large part. Some of them have
bronchitis.

DR. KOWEY: How many were women, Jerry?

DR. FAICH: You know, I didn\'t tabulate. I would point out that almost
all of them were in their 70s and 80s, and I think ‑‑ there we go. All
but one were female. I hope that\'s helpful.

DR. BORER: Thank you, Jerry.

Paul?

DR. ARMSTRONG: Two questions, perhaps the first to the FDA and the
sponsors, if they want to respond. The heterogeneity in the kinetic and
the QT interval data on those individual plots was interesting, and
these are in healthy male volunteers, I guess, as I understand it, who
are between 18 and 40 years of age. I understand they\'re between 50 and
90 kilos. So I guess the question was, do we have any information dosing
by weight, or is there other information about baseline laboratory data
amongst these admittedly normal but perhaps heterogeneous individuals
that might give us some insight into the heterogeneity of those
individual plots?

And the second question. I don\'t know whether we\'re going to get more
information on the blood pressure or heart rate that we raised this
morning, Mr. Chairman. But ketoconazole, which was administered
concomitantly with the alpha blocker, as I understand it, is also
approved for prostatic cancer, 400 milligrams t.i.d., and this was a 400
milligram single dose. So does the sponsor have information on
concomitant use in the large population outside the United States who
would presumably have prostatic retention but potentially also have
prostatic cancer where the opportunity for both drugs might lead to
potentially problematic results?

DR. GRIEBEL: With regard to the first question, we can\'t answer the
weight question.

In terms of the laboratory, if you\'re talking about were there
electrolytes, they were required to have normal electrolytes to enter
the trial.

Perhaps the sponsors could address the weight and population issues.

DR. DURRELMAN: Sylvain Durrelman again.

We have not looked at the weight effect on the PK of alfuzosin in our
study of 45 subjects that were in a range of rather homogeneous
populations.

We were not surprised, however, by the different pattern that we saw on
the FDA slide earlier today because we think that if you look at 45 data
plots that start with a few data points per subject, you would have some
natural random fluctuation around the mean. We believe that it\'s what
is the biological variations.

But we have not seen any strong effect on weight and we have not done a
subset analysis on that.

DR. BORER: Dan?

DR. RODEN: A couple of comments and then a question.

The first has to do with the issue of whether a single dose is, of
necessity, safer than multiple doses. I\'d just point out there are data
in the literature that suggest that the extent of QT prolongation after
a single dose of a QT-prolonging drug ‑‑ and we haven\'t decided that
these are or not ‑‑ is sometimes greater than the effect seen during
chronic therapy. There are data for sotalol, for example. So I\'m not
sure how much reassurance to take over the fact that we\'re looking at
single doses.

At the same time, the issue of heart rate. There are data also in the
literature that if you manage to monitor someone who\'s going to have
drug-induced torsade, for the half-hour or so before they have an event,
their heart rates actually increase. So there is this complex interplay
among adrenergic activation and direct effects of drug on QT and
indirect effects of drugs through blood pressure mechanisms perhaps on
the heart rate and QT. So I think again the heart rate stuff is a little
bit more complicated than may have been perceived this morning.

My question ‑‑ I am not sure who to address this to ‑‑ is, is it a
surprise that the extent of QT prolongation with 80 milligrams of
vardenafil is not 8 times higher than it is with 10 milligrams of
vardenafil or the same with the 400 versus 50 milligrams of sildenafil?
The drugs, if anything, would be expected to achieve higher peak
concentrations. We just saw that. Yet, the QT effect is almost trivially
‑‑ I mean, they seem to be the same.

So does that say something about a heart rate effect?

Does that say something about some other mechanism of action that is not
being factored in here?

Does it say something about some artifact of the way the studies have
been conducted? I just don\'t know but it\'s clearly something that\'s
unexpected and needs to be explained.

DR. MORGANROTH: We might get an insight into that very flat
dose-response curve because that is unexpected. With moxifloxacin, as
was pointed out, you double the dose, you double the effect, which is
true for terfenadine, et cetera. Very linear, very clear.

These PDE5 inhibitors have the opposite effect. You give huge increases
in dose and concentration, it looks it\'s hard to detect a change.

It may be, in fact, related to the effect on hERG because vardenafil was
not able to produce a 50 percent inhibition of the current. I think it
only made it up to about 30 percent and one had to extrapolate to 50.
Perhaps what that might mean is it\'s such a weak hERG blocker, assuming
that\'s the mechanism, that in fact what we\'re seeing is a weak effect
that really isn\'t linear and dose-related.

I mean, that\'s my guess. The answer is it was a surprise to us too. It
was a surprise to me to see that very flat dose-response. You usually
don\'t see it, and it either suggests this is ‑‑ I don\'t want to call
it an artifact, but clearly a totally different kettle of fish than
we\'re used to for QT-prolonging drugs like moxi and others.

DR. RODEN: I would actually think along the lines that Paul Armstrong
has been suggesting, and that is, with the high doses, you probably
produce vasodilation and you get sympathetic activation. That, in turn,
shortens the QT no matter how you correct for it. That may be playing a
role as well. Something like that.

DR. MORGANROTH: Against that theory would be that if you do use the
individual correction which does show you that at the higher heart rates
achieved at the 80 milligrams, meaning the 60, 70, 80, 90 beats per
minute, you designed it not to have an effect on the QTci. Presumably
that\'s the value of the QTci. So I\'m not sure it\'s purely a heart
rate effect.

DR. ROEHRBORN: My name is Claus Roehrborn. I\'m a urologist at UT
Southwestern, and I\'m here as an expert on BPH on behalf of Sanofi. I
just wanted to provide a comment and correction on the issue of
ketoconazole in prostate cancer.

I\'m not sure ketoconazole is approved for the use in prostate cancer,
as was stated. But it has been found, when used at 400 milligrams q 8
hours, to reduce serum testosterone level to castrate level within a few
hours. It is used only in extremis if a patient presents with advanced
metastatic prostate cancer, and if that patient for some other reason
cannot at the time undergo a bilateral orchiectomy, which is the
standard treatment in those kinds of cases to prevent, for example,
spinal cord compression and paralysis. So it is in very extremely rare
cases used and, if so, only until the patient is stable enough to an
orchiectomy. I just don\'t think that those are the same kinds of
patients treated with either an alpha blocker, certainly not with
vardenafil at the time.

Thank you.

DR. BORER: In the planned studies that were performed by the sponsor,
there\'s been a fair amount of investigation of PK type interactions,
which is very valuable. We didn\'t see any planned effort or direct
effort to assess PD type interactions. Now, Beverly Lorell raised this
point during a break, and maybe she wants to take it forward.

But I understand from Dr. Griebel\'s comment that patients who started
out with electrolyte abnormalities were excluded from study, and that\'s
fine. However, I assume there were patients in the database who had
hypertension, who were on diuretics, and whose electrolytes were
monitored, and the electrolytes may have varied.

Obviously, there were no studies planned to create hypokalemia, for
example, but on sparse sampling or some other assessment, there may have
been patients whose electrolytes were abnormal at one point or another.
And one might like to know whether there was a clustering of effects in
terms of QT prolongation in those patients while they were on
experimental drug versus placebo versus active comparator. Do we have
any data at all that would give some insight into that kind of issue?

DR. SEGERSON: I think in terms of the vardenafil database, we haven\'t
looked specifically at hypokalemia for a clustering of either adverse
events that might be signals or other pharmacodynamic effects in our
studies.

DR. BORER: I wasn\'t really thinking of adverse events because I think
there were very few. I was thinking about the primary endpoint. If you
think that there could be a deleterious interaction between drug and
disease or between drugs, that\'s not a metabolic and elimination
interaction, which is the interaction you studied. If you think there is
such a thing, then presumably we might see it by looking at the
surrogate. I\'m just wondering if you have such information.

DR. MORGANROTH: Well, in the vardenafil trial, things are so tightly
controlled in these definitive QT trials, the chance of having someone
develop hypokalemia would be an unusual if not an impossible thing to
happen.

DR. BORER: Right, but some subpopulation could drop over time from 4.5
to 3.6 or something. They\'d still be normal. One might be able to look
at that to see an effect, if it\'s there. I don\'t know.

How about for alfuzosin?

I\'m sorry. Please say your name when you come to the microphone so that
the transcriptionist can get that.

DR. SALLIERE: Dominique Salliere from pharmacovigilance in
Sanofi-Synthelabo.

I can give you some information related to the co-prescription in
post-marketing experience with alfuzosin. These data come from IMS and
were collected in five European countries. May I have slide 27, please?

So for alfuzosin, 50 percent of the patients, as expected in this age
group, receive a co-prescription, and 50 percent of these
co-prescriptions are cardiovascular drugs.

May I have slide 29?

Among these cardiovascular drugs, maybe it is not easy to read, but
nearly 10 percent of these co- prescriptions are related to diuretics
and some others combined with particularly beta blockers. So you can see
that patients, nearly also in 10 percent, received beta blockers. From
the larger post-marketing experience, no clinical interaction was
suspected despite the large use that we have had in more than 3.7
million patient-years.

DR. BORER: Thank you.

Beverly, this was an issue that you raised. Do you want to carry this
any further?

DR. LORELL: Yes, I would like to carry it a bit further.

I think one of the themes that\'s come out in the morning\'s really
excellent discussion and presentations has been the uncertainty about
the ability to use QT interval, no matter how we slice or measure it by
any of the methods that have been discussed, to predict a very rare but
catastrophic event of torsade de pointes.

I\'d like to actually discuss a little bit further and particularly get
comments from our two cardiology speakers this morning discussing risk
about the issue of whether we shouldn\'t be focusing more or thinking
about ways to focus on higher risk backgrounds in looking at a
relationship between Cmax and QT corrected by whatever method.

We heard two perturbations this morning that made sense. One was looking
at the relationship to RR interval itself, and the second was looking at
a background with a drug that inhibits metabolism.

I would suggest that there are two populations that we know may be of
higher risk from experience in very high risk groups with QTc
prolongation, and one background includes mild intranormal fluctuations
in potassium and magnesium. So I\'d enjoy hearing some discussion at the
microphone as to, if no bad effect is seen in normal 20-, 30-, or
40-year-olds doing the kind of studies that were seen this morning,
whether a next step might not be in a controlled, highly ethical,
clinical environment to deliberately modestly reduce potassium and
magnesium to lower limits of intranormal range, which can usually easily
be done with diuretics.

And a second related question is whether or not there should be a
consideration in the future as to specifically looking at populations of
women and older women since this is a group that clearly is at some
higher risk in many long QT syndromes.

So I\'d welcome your thoughts about whether we should perturb
metabolites and how should we look at women.

DR. BORER: Doug, did you have a comment there?

DR. THROCKMORTON: Yes. Beverly, that is an important part of what we\'re
interested in hearing, but let me frame that a little bit. Let me tell
you the way these studies were thought about.

The studies were, in essence, designed to ask a question, does the drug
affect repolarization, yes or no? In that context, we perhaps mistakenly
thought that a normal volunteer population would inform that question,
not whether there would be additional risk factors that would make
someone at higher risk or not, but just simply whether or not the drug
affected repolarization. A normal volunteer population would inform that
question, as well as a population that\'s at higher risk. You heard this
morning from one of the speakers that we don\'t have any reasons to
believe that that\'s in error, that is, that there might be a drug that
didn\'t do something to normal volunteers that did to a high risk
population.

But I\'m interested. Is that what you\'re suggesting? That is, that for
a reason that I\'d like to hear some comment about, a normal volunteer
population doesn\'t provide you enough assurance as to the absence of a
potentially relevant effect on repolarization.

DR. LORELL: Doug, I\'m not sure that I would even pretend to know the
answer to that.

I guess I would look at it in a slightly different way, and that is, one
might postulate that one would always start with a normal, highly
controlled population, but that that may be necessary but not
sufficient, given what we know already clinically about the specific
issue of risk of torsade with QTc prolongation, and in particular, that
a heightened vigilance might be necessary to deliberately test a
perturbation which is extraordinarily common clinically and that we know
enhances risk, and that is intranormal perturbations in potassium and
magnesium.

I guess the separate question that\'s related to your thinking about
this is the issue in women, whether the gender issue needs to be
somewhat independently addressed rather than sort of mixed in as part of
a broad population.

DR. THROCKMORTON: The latter is a good question. These are typically
men.

Again, the structure we\'ve been using has been that normal male
volunteers would adequately answer the question of whether or not there
was an effect on repolarization. If the answer was yes ‑‑ and you\'ll
tell us later how to decide when there\'s an effect or not, what that
magic number is ‑‑ then all those studies would be things that would be
very important so you can think of development programs that have
uncovered such effects and then had to look in phase III to look at
interactions by race and interactions with other drugs and that kind of
thing. But the notion was that absent an effect on that male healthy
volunteer population, those looks were less rigorous, were less
structured.

So I\'m asking again, is that something that you\'re suggesting we need
to rethink? Because I\'d need to know why.

DR. LORELL: Yes, I am putting forward the notion that it may be useful
rethinking about what is done in phase I-II in a very rigorous way in
comparison with and complementing but not the same as prospectively
looking at much noisier data in phase III.

DR. KOWEY: Beverly, Doug said ‑‑ and I think he\'s correct ‑‑ there are
two questions that are being asked. The first one is, is there
fundamentally an effect on repolarization? Actually, Doug, I think that
if you had a drug that you weren\'t just going to give to men, which is
what these two drugs ostensibly do, you wouldn\'t do a phase I trial in
normal volunteers in just men, would you? Wouldn\'t you do women too?

DR. THROCKMORTON: I think we have not said that you needed to do both. I
don\'t believe we\'ve made specific statements about that one way or the
other.

Tell me why I should require women, which is what you\'re suggesting?

DR. KOWEY: Because I think that if you\'re looking at repolarization ‑‑
I agree, that\'s the experiment you\'re doing in phase I ‑‑ that women
fundamentally have a different repolarization response than men. I think
it\'s fairly clear that they do. And if you only did men in phase I and
came up with nothing, you would still probably not have your fundamental
experiment concluded. That\'s why.

DR. THROCKMORTON: Could I ask for some comment from the rest of the
QTers around the sponsors and the table, please?

DR. BORER: Dan, do you have some comment?

DR. RODEN: I think the question is whether a drug that has absolutely no
signal in a normal healthy volunteer population could, in fact, generate
a signal of concern in a more at-risk population. Another population
that has been used actually, Bev, is the heart failure population who
often have these electrolyte abnormalities, and even if they don\'t have
longer and funnier looking QTs. That was actually done in the
terfenadine experience, and at high dose terfenadine in that widely
cited study, there was actually a fatality at 300 milligrams twice daily
of terfenadine. So you can push that trial design and cover those kinds
of events. I don\'t think anybody wants to uncover a fatality.

But if the question is, does this drug prolong the QT, then that\'s
adequately addressed by these sort of normal volunteer studies. Then the
question is if I know that the drug prolongs the QT, are there
populations in whom it\'s going to prolong the QT a lot due to metabolic
reasons because they\'re older women who are exposed. That\'s a separate
set of questions. I guess it might be logical to recommend that if you
had a signal, the next step might be to investigate the extent to which
that happens under rigorously controlled conditions in a higher risk
population. I\'m not sure how far to push that to answer a question that
may already have been answered. Do you see what I\'m saying?

DR. LORELL: Well, just to be brief, I think we\'ve already seen an
example of that being done in looking at co-administration with a drug
that inhibits metabolism.

DR. RODEN: Right, and the whole idea of giving higher than normal doses
just to sort of expose ‑‑ but the question there is just to find out if
the drug prolongs the QT. And if it does, then you have a whole separate
set of questions like are there special populations. Terfenadine is a
great example. I think terfenadine is an extraordinarily safe drug as
long as you don\'t give a metabolic inhibitor. There are lots and lots
of people who took it and nothing happened. But if you give it with a
metabolic inhibitor, there\'s a real problem. So you have to ask
yourself are the pharmacokinetics well behaved. Is it likely that a lot
of patients with heart failure or hypokalemia will get this drug? And
those are separate questions.

DR. BORER: Toby?

DR. BARBEY: There is, of course, then the other component of the
perceived benefit from the drug. In other words, when arsenic prolongs
the QT interval but can cure leukemia, you kind of proceed differently.
But I would be more a believer that indeed your phase I studies which
should be ‑‑ I agree with Peter ‑‑ in men and women are designed to
tweak and challenge the system as much as possible to get a flavor for
that propensity. And then you derive some clinical strategies based on
that saying, we will up front be more prudent with this drug in these
situations, rather than necessarily bring in on the research unit. That
would be my instinct.

DR. BORER: Mike, did you have a comment about this particular issue?

DR. ARTMAN: Yes. Getting back to Doug, I think that you\'re right. The
question is does this drug affect repolarization. And if you test it in
healthy young males and there\'s no effect on repolarization, then I
think you can safely conclude that there\'s no effect on repolarization
in healthy young males.

That doesn\'t answer the question whether or not it would affect
repolarization in healthy young women. I think we do know that
repolarization in women is different and they respond to drugs
differently. So I believe that if a drug is going to be used in a female
population, it ought to be tested in females in these phase I tests.

DR. RODEN: At higher doses.

DR. THROCKMORTON: This is not one of the questions, Jeff, but this is
something quite different from what we\'ve heard before. So I\'m sort of
sorry to keep pressing on this, but I\'m seeing nodding heads.

DR. BORER: What I\'d like to do ‑‑ we have Jeremy. We have John Camm.
We\'ve got Joel here. I\'d like to hear from all of them.

DR. THROCKMORTON: I\'m really interested in some conversation about
this.

DR. BORER: Jeremy?

DR. RUSKIN: With regard to the gender issue, most of the phase I trials
that I have heard about in the last year have included women, often
50/50 for specifically the reason that\'s been brought up. And I think
it\'s very important to do.

That said, I don\'t know of a single situation where there\'s a drug
that has no effect on repolarization in men that will have an effect on
repolarization in women. It\'s really a question of relative
sensitivity. There are drugs that have been studied very closely with
regard to gender differences. Some drugs, you can see no gender
difference at all, and others you do. And when the difference is there,
it\'s relatively small but unequivocal.

What\'s very clear is that the susceptibility to drug-induced torsade is
much higher. About two-thirds of reported cases both with antiarrhythmic
and non‑antiarrhythmic drugs are in women and a third in men.

But it\'s very unlikely, almost unimaginable, that a drug that had no
effect in men would have an effect in women. I don\'t know if Dan or
other people agree with that.

DR. KOWEY: Jeremy, just to answer your question, I agree with you in
general terms, but I guess I\'m having a hard time understanding. I
agree that we don\'t know of a drug like that and we\'re not really
talking about drugs with zero effect. We\'re talking about drugs with
some effect. Since we\'re talking about basically screening, as Joel
said in his talk, almost every new chemical entity, I don\'t want to
really get into the situation where we\'re imagining we can tell the
future and that there\'s not going to be some compound sometime that
does that. What is the harm, really, of doing women in a phase I trial?

DR. RUSKIN: None whatsoever, and my opening remark was that all the
phase I trials that I\'ve seen in the last year that have been talked
about and are in design generally include 50 percent women. And they
should.

DR. BORER: John, can you give us your opinion on Joel?

DR. ARMSTRONG: Could I put a question to John as well through you, Mr.
Chairman, since he has written on this dynamic nature and the notion of
association/disassociation between the QT and the heart rate and the
notion are all QT intervals the same and QT prolongation the same?
Clearly, they\'re not, and I wonder if he could address that before we
come to these questions because I must say I\'ve learned a fair bit
today, but I\'m still confused about the multiple causes, whether they
be patient comorbidities, the metabolic substrate, or the drugs or
concomitant medications, all of which can affect the QT interval but may
have different implications regarding, I guess it\'s torsadogen. You
used the word, Doug.

DR. CAMM: Well, thank you very much for that very long list of
questions.

(Laughter.)

DR. CAMM: I think we should start by the issue of the dynamic nature of
the QT interval. Most of what was referred to this morning was related
to the time that it takes for a QT interval to adjust to a new heart
rate. So, for example, a step change in heart rate that might be induced
artificially, for example, with a pacemaker, will be followed by 30 or
50 beats during which there\'s progressive shortening of the QT interval
if the step change was an increase in heart rate. So there is a definite
hysteresis involved.

Of course, changes in heart rate are usually gradual, and the QT
interval changes therefore do tend to keep up relatively well with the
changes of the RR interval, but nevertheless, there is a significant
hysteresis. The way that that\'s dealt with in clinical trial
circumstances is usually by trying to ensure that there\'s a relative
stability of the RR interval before recordings are made from which RR/QT
are measured and QTcs are computed. So that\'s the general issue about
the dynamism of the QT interval.

But there are many more intriguing elements about it than that. For
example, if a patient with bradycardia and a long QT interval suddenly
has an increase of heart rate, the situation that I think Dan was
alluding to a moment ago, that might well be a particularly torsadogenic
situation because the prolongation of the QT interval is not rapidly
attenuated by the change in heart rate that occurs. So the QTc, for
example, would then fairly dramatically prolong, and this, no doubt, is
one of those torsadogenic situations.

I don\'t know if I\'ve dealt adequately with what you asked me, but if I
could turn to the general questions that Beverly has raised. I think
that they are very intriguing possibilities that we could take patient
subsets that are of particular risk. I think you were asking more about
volunteers, and I understand that within the volunteers, clearly we can
choose one gender or another or both fairly easily and we could
certainly measure potassium and perhaps modulate potassium by
co-administration of diuretics.

We have very little information about how an intranormal variation of
potassium would affect the QT-prolonging effect of any drug that blocks
the IKr current or prolongs the QT interval for any other reason. We do
know that more extreme changes in potassium are, of course, very
relevant. Dan Roden, for example, published a paper with quinidine,
heart failure, and hypokalemia in which he managed to demonstrate that
very well. I\'m not sure how in normal volunteers relatively small
changes within the normal range of potassium would amplify the QT
effects, but it\'s certainly something that\'s worth considering.

With reference to whether we could extend that to take vulnerable
patients, I think this then enters a much more difficult arena, taking
heart failure patients, for example, or patients with severe ischemic
heart disease or severe hypertrophy. Reasons for this are practical
reasons, feasibility reasons, and ethical reasons.

Amongst the practical reasons are the fact that patients with some of
these characteristics are often on considerable numbers of
co-medications and it\'s difficult to control for them. They may have
different electrolyte levels, again difficult to control for without
very large studies. Importantly, they often have very distorted
electrocardiograms with T waves that are not particularly stable anyway
because of the disease process, and it becomes a tour de force to try
and measure consistently the QT intervals. So there are definitely
difficulties with this.

Amongst the ethical concerns I think are the issues of whether one can
expose a patient particularly to supratherapeutic doses of any
medication with the notion of trying to use that patient and his
condition as an amplifier to show a potential QT problem. Usually the
IRB comes back to the investigator, when such trials are proposed, to
say, please use a much lower dose of the drug, something less than
therapeutic. And you get involved in a lot of difficulties in
practically trying to promote such studies. Although they are, I agree,
of considerable practical importance, I think they are in practical
terms very difficult to conduct.

DR. LORELL: If I might make, Mr. Chairman, one comment. I think one of
the impressive things that we have heard this morning ‑‑ and I very much
appreciate your comments ‑‑ is that in looking at these rare, isolated
case reports, what are sort of being discussed as confounders are
actually the substrate that we\'re worried about. In thinking about the
earlier presentation with, I thought, the very provocative slide that we
should be looking not just at central tendency, but for ‑‑ the term that
was used was categorical analysis looking for outliers, it may be that
we\'re actually throwing away some of the richness of the data that\'s
terribly important in designing a well-done and ethical phase III trial
by not looking earlier, even with the difficulties you describe, at some
of the groups for the QT prolongation issue that we know may be at
higher risk. So I\'m not sure I can even suggest how to do it, and
clearly there are some formidable challenges.

DR. BORER: Joel?

DR. MORGANROTH: The question regarding the population composition for a
definitive QT trial that was raised by Doug, I agree entirely with
Jeremy. Since we first learned about the enhanced sensitivity of women
compared to men for a QTc-prolonging drug, it seemed common sense to put
men and women, usually 50/50. If you have a 40 group, you\'d have 20 and
20, so it\'s almost enough with 20 not to be totally spurious that you
might have a reasonable good point estimate of the effect. And the
problem with putting women in is that women volunteers are just not very
plentiful compared to men, and as these phase I definitive trials get
more popular and there are large trials, it\'s not anything more than a
pragmatic issue that women are not going to be so easy to put in. So
it\'s a real good question.

I personally think the focus of a lot of the answers to the discussion
in the last few minutes should remember that in this definitive QT
trial, the key group in my opinion is the supratherapeutic dose of the
new drug being investigated. And if, in fact, that dose is really very
high, as it should be, and you see no magnitude of an effect or a very
small magnitude of an effect of a few milliseconds, I have never ever
seen that women, as Jeremy\'s experience is also, gave us any more
information about the degrees of magnitude, number one. Therefore, they
may not be really that necessary to put into these trials if, in fact,
one does employ a proper supratherapeutic dose.

And if you do put in a supratherapeutic dose, that should cover these
issues that are vexing and interesting of what about patients with heart
disease or hypokalemia or other higher risks where clearly those are
going to magnify the effect of a QTc drug. But we don\'t believe that
they\'ll magnify them more than a supratherapeutic dose of the drug
that\'s inducing the QTc. And I\'m talking about using 5-fold, 10-fold
the dose. If you can go to that kind of level and you see whatever that
magnitude is, I can\'t imagine that you\'re going to see much out of
that range by some intranormal changes in potassium or people who happen
to have left ventricular hypertrophy versus a normal heart. So I think
one should gain great comfort in the precision of that.

DR. BORER: Thank you.

I\'d like to make a comment here that is not a conclusion, though it may
sound like one. We\'re musing about possible investigations that might
be helpful in identifying high-risk situations or drugs that may cause
problems. But as I read and hear the data, we really don\'t know how to
interpret much of what we\'re observing. We\'re looking at a surrogate
and we don\'t know how to interpret the surrogate. We don\'t know what
it means. It\'s important to remember that.

That suggests to me that a good deal more, I will call it, fundamental
research, although I don\'t mean that in the sense of basic science, but
a good deal more information is needed so that we can better interpret
these data. If we translate our suppositions about what the
interpretation might be, without a real firm basis for the
interpretation, we will request a large number of studies to be done
that cost a great deal of money and will put some people at risk without
actually justifying that with data that will be beneficial because we
don\'t know how to interpret them.

So I would keep that in mind as we go through these questions here.
There are a lot of things we\'d like to know. There\'s a lot research
that needs to be done, but I think that research needs to be done and we
need to know those things before we mandate certain kinds of studies in
drug development efforts. So that\'s an observation. It\'s not a
conclusion.

Dan?

DR. RODEN: I think I got to talk before Tom because you were looking at
me before him. I\'ll take the opportunity while I have it.

I\'d just like to amplify that, Jeff. It seems to me I would be the
advocate of basic science and there are some interesting things in basic
science that might shed some light on this, QT morphology kind of
issues. But I think we\'re a long way away from that.

But there is an experiment that is going on as we speak and that is the
ongoing examination of the moxifloxacin outcomes, the ongoing
examination of ziprasadone outcomes. So we ought to be able to, at some
point, get a sense of whether a 6-millisecond increase in a
well-characterized normal volunteer population can be translated into
some estimate of risk of torsade de pointes, and then the question will
become whether the risk is so vanishingly small at some level as to be
ignorable.

It seems to me we put ourselves into an awkward position when we say
here\'s a drug where we\'re quite confident the incidence of a really
serious adverse event is going to be one in a million. It\'s tough to
weigh that in the grand risk-benefit scheme, but it does make you
uncomfortable because you have the confidence that you\'re able to say
that. Obviously, that\'s tempered by what population you\'re studying
and all those other things. The data that we need are the real clinical
outcomes data, and I don\'t think anything short of that is going to
help very much.

DR. BORER: Tom.

DR. FLEMING: I think my question for the FDA and comments are a further
amplification of this and maybe even further discussion of the gender
issue.

My own sense as well is that what I really care about here is are these
interventions associated with meaningful increased safety risks on
clinically tangible outcomes. They may be. It may be sudden death. It
may be cardiac arrest or other events that unfortunately happen with
sufficient frequency in the untreated population that being able to
discern what\'s truly causally related increases in those risks in a
passive surveillance setting is going to be almost impossible unless we
do large randomized trials or unless we look at events that are, in
fact, so profound when they occur that we can reliably assume they\'ll
be reported, which is possibly the role of torsade.

Which is why I\'m struggling with still trying to understand the 20
million patients that we have data presented to us from a number of
sources today with moxifloxacin and the 20 million patients that have
received Viagra where in one case we have 15 torsade cases, in the other
we have 0. Given that in the Viagra setting, if I understood, it was a
billion doses, so that means that\'s quite a bit of exposure for each of
those 20 million. So that doesn\'t seem to explain it.

I don\'t know what the actual rate should be of torsade in the natural
population. Is it unusual that the Viagra reporting experience is too
low for what I should expect? I\'ve heard gender as one possible
explanation for this difference, although I\'ve heard a statement that
maybe two-thirds of torsade cases would be expected in women. I\'m still
left with a very striking difference here, and I\'m trying to understand
it because it\'s one of the few clues that I\'ve got here about whether
the measures that we\'re looking at are relevant to clinical endpoints.
So I need to understand this.

Has the FDA torn this apart? Have you looked at these 18 cases in 19
million exposures to moxifloxacin versus the Viagra experience to be
able to see whether it\'s explainable by gender? Or is there something
real here that would give us a clue to be able to say, okay, for the
experience that we\'ve seen with moxifloxacin, there probably is a
relationship that\'s causal at a rate of, let\'s say, one in a million?

DR. GRIEBEL: The answer to your question is we today had similar
questions that you raise. We have not torn the data apart. I think our
briefing document outlined the difficulties in interpreting voluntary
reporting which is what we have in the AERS database. Certainly we can
go through what was reported in the case report forms and in some
instances ask for additional information. Bayer mentioned that they were
asking for more information on one of the cases. Certainly the majority
of them were female, and that\'s the kind of information that you get.

But at the end of the day, it is voluntary reporting and I don\'t know
that we would be able to answer the question that you have because what
we have in this AERS database, which is post-marketing reports that come
in from safety, is what somebody decides to report. Some of them can be
a pharmacist. It may be a reporter that heard something, a drug rep
who\'s detailing in a physician\'s office. You are at the mercy with
that system of what is voluntarily reported.

Now, there was a pharmacovigilance study that\'s going on with
moxifloxacin that I\'m not aware of.

DR. RODEN: I didn\'t mean to imply that there was a formal study going
on.

But in my opinion ‑‑ and I can be corrected by the agency ‑‑ the agency
is in the middle of conducting an experiment ‑‑ they may not want to
call it that ‑‑ where they say, here\'s a drug that prolongs the QT
interval by 6 milliseconds ‑‑ that\'s the number that\'s in the package
insert ‑‑ let\'s see whether we get any signal. And I think that\'s a
legitimate experiment. And ziprasadone may fall into a similar kind of
category. So there\'s not an experiment, but I think you guys are pretty
sensitized to looking at the reports as they come in to see if that
becomes a problem or not. That\'s the only way to work forward from
this.

DR. BORER: Jerry?

DR. FAICH: I\'m Jerry Faich again.

Just to expand a little bit on the moxifloxacin post-marketing large
studies, there were two of these done, one called the ASA study and one
in Europe. The combined number of patients who were followed was 55,000
patients. There were 4 sudden deaths. It turned out they were all in
patients with underlying cardiac disease. All the deaths and all the
hospitalizations and all the syncopes were carefully followed. So if
we\'re talking about estimates of risk, getting a numerator and a
denominator and following populations and characterizing them, that\'s
probably the best we\'re likely to do between, on the one hand,
well-done controlled preapproval studies and, on the other hand, AERS
data which are difficult to interpret.

One can also look at epidemiologic databases, but for this particular
endpoint, it\'s not likely to be diagnosed in any way that you\'re
readily going to be able to follow up on it. It will present as either a
sudden death or an MI and it won\'t actually enter into a diagnostic
code. So that\'s simply a way of saying probably the best estimates are
going to come out of large, simple safety studies, and of course, FDA
has recently talked quite a lot about those.

That was done in the case of moxifloxacin. The exercise was one to look
for assurance. Will it help the unusual complicated patient with lots of
underlying reasons to have a torsade anyhow, and then you observe that
patient who has it and also has an exposure to moxifloxacin, and you try
to tease apart which is it, and has moxifloxacin, or whatever
QT-prolonging drug it is, contributed to it? I think that\'s just a
conundrum that we\'re not likely to be able to solve in using the usual
kind of causality assessments either in an individual case sense or in a
statistical sense of saying do we have more than we expect.

DR. FLEMING: Could I just follow up? Certainly the levels of rigor that
we feel we need to undertake for assessing safety will depend on the
nature of the efficacy and benefit-to-risk, and we haven\'t gotten into
those discussions yet. But if we perceive benefit to be of a substantial
nature, then uncertain levels of risk that would be profound but
incredibly rare could readily be acceptable even without our knowing
exactly what level they are. On the other hand, when benefit is less
profound, then we have to worry seriously about whether, even if it\'s
very rare, there are profound adverse events that are occurring.

It seems to me what I\'m hearing, just in response to the FDA response,
is that if we\'re looking at somewhat more frequent and very important
endpoints such as sudden death and cardiac arrest, et cetera, the
concern about using passive surveillance for those is that they could
readily be under-reported because of the frequency of occurrence in
natural history. But a randomized trial of the size of 20,000 to 50,000
could readily provide a sensitive measure assuming that the safety risk
in the context of benefit is of such a level that you would consider
that justifiable and very often you wouldn\'t.

But if we wanted to rely on passive surveillance and we said an endpoint
like torsade, however, is so rare and so profound that we could, in
fact, rely on passive surveillance, I\'m hearing from FDA, maybe not.
Maybe not even torsade would necessarily be reported with the level of
capture that could make us confident that passive surveillance would be
adequate.

DR. BORER: Before you go on, Alan, because you had a comment to make, I
think I would just reemphasize something that Jerry suggested earlier in
response to the concern about the 15 out of 20 million and 0 out of 20
million issue that you raised earlier, Tom.

The people who take sildenafil generally do that at night. An event that
might occur would either be fatal or it wouldn\'t be perceived. The drug
washes out rapidly and therefore it\'s unlikely that the event, if it
were an arrhythmia, would be repeated in the morning when it would be
more likely that someone would seek medical attention, and a fatal event
would be more likely to be attributed to natural history than to
anything else. I\'m troubled by the fact that there\'s a discrepancy,
but I think that there may be an explanation for it that is plausible
beyond the fact that maybe sildenafil does nothing. So I\'d just offer
that for what it\'s worth.

DR. FLEMING: And I\'m with you on that. I\'m just saying my logical
conclusion from what you\'re saying is that even an event such as
torsade in passive surveillance could go readily unrecognized.

DR. BORER: Exactly.

Alan?

DR. HIRSCH: Just to emphasize that point again, I think following Bev\'s
comment and Dan\'s comment, what we have here in my perception is a real
de-linking between what we understand about the biology of the drugs on
QT interval, their impact in a population at risk, and the trigger for
torsade. I\'ve been bothered all day by not knowing how to interpret a
healthy male or female population\'s events in a short-term trial with
what would happen in real life.

Again, before we get to the major discussion, we\'re talking about drug
classes that are widely used, the billions of prescriptions utilized, so
that the effects are important.

I\'ve been trying to think, Tom, about this surrogate issue. To me an
effect on QTc that is brief in a young male volunteer group is sort of
similar to looking at a 2- to 5-millimeter blood pressure increase in a
young healthy volunteer and then extrapolating to patients with heart
disease who might over years of use, over 2 or 4 years, have a sudden
heart attack.

I just can\'t help but believe that the small phase I trials are
critical. We had an advance in technique of understanding how heart rate
and concomitant conazole use might affect QT interval, but the
inevitable next step, as you were sort of implying, to try to get an
estimate of what that would be like in a somewhat disease concomitant
drug, LVH or heart failure population because I don\'t trust the
post-marketing surveillance.

Though I don\'t want to burden sponsors and FDA with large,
50,000-patient, 5-year trials, I think it\'s inevitable that the next
step in our understanding of the biology is to take drugs with ambiguous
signals and follow them in relevant populations so we can get some
reasonable estimate of risk before these drugs are more widely used.

Thank you, Mr. Chairman.

DR. BORER: 50,000 patients in surveillance is different from 25,000
randomized to one drug and 25,000 to another.

DR. HIRSCH: I\'m only 25 and naive, so I\'m just estimating.

(Laughter.)

DR. BORER: Udho.

DR. THADANI: Thadani. I was on the FDA committee when sotalol was
approved and we saw the noise there even in patients who were getting
exposed during the trials. I think, Jeff, you were on bepridil too, and
we were doing angina studies. The QT just got long. They got very
cardiac. So I think the whole relevance ‑‑ I\'m not sure that any of us
understand that QTc of 5, 10, 12 has any clinical relevance.

When your incidence rate is one in a million, how on earth can you
detect it? A patient passes out. He has a syncope. You can\'t be sure
it\'s not due to QT prolongation or torsade because a few hours later,
his ECG could be totally normal. All of us have seen the ECG, even on
sotalol, the patients don\'t keep on getting torsade. Sometimes they
have it and sometimes they don\'t because of autonomic influences,
potassium channels, or whatever.

So I think the only way to address the issue ‑‑ I realize that you have
to study the population at risk, and the only way you can address it is
by a larger database in the population at risk, not necessarily
measuring very expensive technology or 20 Holters. You look at the event
rates. I think the data they showed you on vardenafil in 2,000 and some
patients, the event rate is .1 percent, the same on placebo, 800
patients. And the sildenafil database ‑‑ at least that gives you some
reassurance. It doesn\'t answer the question whether you have torsade or
not. I think it\'s absolutely impossible, when you\'ve got a one in a
million chance of getting it, to be absolutely sure whether it happened
or not.

DR. HIRSCH: But to follow up on that, my point would not be to be
reassured by the sildenafil database alone, but look at precedent for
all the other drugs that are coming down the pipeline where we may have
differential mechanisms on both QT and torsadogenic foci.

DR. THADANI: I think you\'re absolutely right. That\'s why I said
vardenafil has been used in patients who have ED. A lot of these
patients are about the age of 50 or maybe a younger population as well,
and a lot of them are on concomitant therapy. If you look at the
database on concomitant therapy, they\'re on ACE inhibitors, beta
blockers, et cetera. In them the incidence of serious adverse outcome ‑‑
I\'m not talking about dizziness ‑‑ is no different.

We have even looked at patient with stable angina, put them on the
treadmill, and produce ischemia. Small numbers, 30-40 patients are on 10
milligrams, and we actually saw improvement in ischemic ECG changes, and
exercise tolerance doesn\'t get worse. That\'s a very small observation.
And the same with 20 milligrams, but at least it reassures you during
ischemia, which is very equivalent to sexual performance in ED patients,
you\'re not producing a problem. But that doesn\'t say that if you did
thousands or a hundred thousand patients, you won\'t see an incident.
All you could do is the control studies.

I think we have been burnt again. Look at the estrogen study. Even the
observation studies produced totally conflicting results. We did
angiograms and we said, well, it is cardioprotective, and you do a
definitive study, it goes the wrong way. Today on the morning news,
estrogen has been shown it doesn\'t even improve Alzheimer\'s.

So I think we have to be very careful when we\'re dredging data which is
just dragged out by reporting. I may not report the incident. He might
report it. So you know that physicians don\'t report all adverse events.
So unless you\'ve got mandated by the FDA and by each hospital every
adverse event should be reported, we are going to under-estimate and not
know the true results.

DR. BORER: Doug?

DR. THROCKMORTON: I just wanted to make a general observation.
Interesting course, the last few minutes here.

I might agree that I don\'t know as much as I\'d like to about the
relationship between mean QT and risk. I\'ve got no troubles with that.
I think anybody that said they did probably I\'d disagree with. But
let\'s not behave as though we know nothing about that relationship or
that, in fact, we have no post-marketing data that we can look to, or
that we\'re uninformed at all as regards to the relationship between
prolongation of QT with all its vagaries and risk.

Drugs that prolong by large degrees have universally caused torsade.
There\'s not an example I\'m familiar with that I can\'t explain by
other pharmacology, amiodarone or something like that, where a clean
QT-prolonger didn\'t kill people. That\'s just an observation. You go
over 30 or thereabouts, that\'s the world you\'ll be living in.

I don\'t know where you stop living in that world. Dan, you pointed that
out or Alan or someone, that you wish you knew where the bottom end of
that is. In a sense, that is the fundamental question that you\'re being
asked today.

The agency, with Health Canada, with the regulators as a whole, has
looked at the available data sets, for better or for worse, and
identified a low threshold of around 5, looking at moxifloxacin with its
good data and its lack of data that you might like, data from
terfenadine, data for cisapride, and said, these drugs inform us as to
the effects of small mean effects, prolongations in QT. Now, you can
disagree with that or agree with that, but that is the mechanism. Those
data are the way that lower bound was arrived at. It has to be. I agree
with you. That has to almost be the way that you arrive at that because
you can\'t otherwise make inferences from mean changes.

I take your caution, but it\'s not as though we know nothing here.

DR. BORER: That\'s a wonderful introduction.

DR. BARBEY: Before we leave, though, could I just, Mr. Chair, ask?

DR. THROCKMORTON: I\'d like to hear from Toby because he had a
particular experience with post-marketing sort of detection with
torsades that I think might be useful.

DR. BARBEY: Thank you, Doug.

The only thing I would have said is that, yes, pooh-pooh-ing the quality
of post-marketing surveillance that we have ‑‑ it\'s true in a way, but
if you think back to terfenadine, the index case was much better
understood and put in perspective, thanks to finding other cases and is
actually what has altered. So that\'s very likely why drug interaction
and women are included in these trials in such phase I studies now. So
as imperfect as our system is, it does influence some. It would be
ideal.

But indeed, to understand what the threshold is ‑‑ and we haven\'t
discussed that ‑‑ where you\'ll be worried, and maybe having women who
get a little longer ‑‑ help you a little bit, worry you a little bit
sooner. But unfortunately, these events are often rare enough in these
ambivalent drugs where mortality is not the valid endpoint. You can\'t
just say we\'ll follow 100,000 people. So you actually need a fairly
proactive and complex analysis of the cases.

I had a chance to review cisapride cases. That\'s what Doug is alluding
to. Of the 500-plus cases reported as possible, there were probably
100-plus that were clearly torsade and others who were much more
ambiguous. In that situation, the risk-benefit considerations played a
big role because the drug was not beneficial enough to make that risk
acceptable. A label of fatigue was the other thing that these findings
suggested a strategy that you could use the drug more safely, but after
23 Dr. Doctor letters, nothing was happening.

So there are limitations, but there are some things that you can learn
from that. It needs to be kept at a high standard, people who look at
these events and understand them, not just say somebody died and that\'s
it.

DR. LORELL: May I ask a question of information? In thinking about those
two experiences, was there data for those two drugs such as what we\'ve
been discussing this morning in normal volunteers? Was there any data
looking at Cmax and QT corrected by any method? In other words, is there
any data at all in those two examples that a strategy, such as we\'ve
heard a lot about this morning, might have given some kind of a signal
either as general behavior or as presence of outliers?

DR. BARBEY: Doug probably knows. My impression is no. However, the
blueprint that was used to understand the problem with terfenadine was
then preemptively applied to other antihistamines of the same class and
we like to think that that has worked pretty well.

DR. THROCKMORTON: Yes. Moxi would have that sort of combination I think
that you\'re asking about. Terfenadine had it. I could obtain it maybe
later on. Cisapride did not have any that I\'m aware of.

DR. FLEMING: Just to follow on the same, it\'s such a key point. You\'ve
pointed out, Doug, that we do have some insight based on prior
experiences of agents that, in fact, have induced serious safety
concerns. Of course, part of the problem is we\'ve heard this morning
that there is a wide array of different ways that we might want to
measure these adverse effects.

My question is you put forward a preliminary concept paper that we\'ve
been provided, in fact, we were provided by the sponsor, and it gave the
kinds of categorizations that you were just referring to, Doug. If
values are less than 5, then I think it was coded as no association with
torsade; 5 to 10, clearly associated; 10 to 20, of concern; more than
20, substantial likelihood of being proarrhythmia. Yet, it\'s not clear
to me. Is that based on Bazett? Is that based on Fridericia? If we\'re
told to use different measures and different measures, in fact, give
very different scales, how am I supposed to use it?

I like your logic, and that is let\'s go back to the wide array of
agents that we know are proarrhythmic and that we know aren\'t, and then
let\'s apply ‑‑ of course, I think the answer is we don\'t have the
ability to do it ‑‑ all these various measures and find out what, in
fact, is a highly sensitive and specific indicator. Is it above 500? Is
it above 450? Is it a certain change on Bazett or on Fridericia or
population? What do we know about that? And specifically your guidelines
are based on what? Bazett?

DR. THROCKMORTON: Two parts. First off, we need to be clear about what
the preliminary concept paper is, which is that it\'s not a guidance and
it doesn\'t have any sort of regulatory standing. So you need to
understand that it\'s a thing that we\'re working on. It\'s a thing that
we\'re asking people to think about. A number of people in this room
have helped craft that. Obviously, there have been some changes to it
and some things that are in an ongoing discussion.

The document currently doesn\'t have the categorization you\'re talking
about, Tom. I think those are categories that come from a place other
than the document. The document refers to a power to detect a
5-millisecond mean change. It says that you need to be able to exclude
that you would miss that.

DR. FLEMING: I don\'t think so, Doug. I think it\'s much more specific
than that. And you\'re correct. This shouldn\'t be interpreted, I guess,
as a guidance. It\'s a preliminary concept paper.

But it says fairly clearly in wording that to date drugs that prolong
the mean by an interval of 5 to 10 seconds have not been associated.
Drugs that are 10 to 20, it\'s of concern, and drugs that are more than
20, there\'s a substantial increased likelihood. So there seems to be a
very relevant attempt here to say in the context of our experience with
previous agents, if we then look back to see what the changes were, what
are the associations?

DR. THROCKMORTON: Yes. I just reviewed in rough outline the data set
that we have. I think you could add ziprasadone to that maybe, as far as
places where we have reasonably substantial post-marketing for drugs
that prolong the QT in the range, something less than 20.

DR. FLEMING: And are these values Bazett or are they Fridericia or?

DR. THROCKMORTON: Historically ‑‑ cisapride, for instance. All of the
data we have are uncorrected because the original data ‑‑ we don\'t have
the RR intervals on. Terfenadine I can\'t speak to. It would be
Bazett\'s is my guess. Ziprasadone, a mixture of things I would guess,
Fridericia a little bit.

I\'m not sure that getting terribly hung up on the corrections is going
to matter, again, in the context of the kinds of trials that we\'re
talking about. If we\'re talking about a trial where you have a
reference agent that you\'ve included in a drug that you believe you
understand the pharmacodynamics of well enough, the exact number that
you get there may differ from trial to trial. We saw that this morning
from the moxifloxacin. You might say that the correction matters less in
that you\'re able to have an anchor in a sense to provide you a way to
interpret those previous data.

Both of these sponsors did an admirable job, I think, of conducting a
series of analyses, in addition to whatever analysis they chose as their
primary. That gave reviewers, maybe you an ability to think about those
effects in the context of the other drugs that you might have more
clinical familiarity with, more understanding. So if Bazett\'s was
something that you believe in your heart of hearts is really terrific,
you could look to the Bazett\'s experience that\'s been reported from
some of these other agents. That\'s part of the reason why that series
of corrections was suggested by the sponsors, and I think they did a
good job of conducting those corrections.

DR. FLEMING: Well, the last brief comment. I think your point is well
taken, that there is some insight that comes from a wealth of experience
in pervious agents. But I\'m persuaded by what I\'ve heard this morning,
that it matters on what scale QTc and QT have been measured, and one has
to be aware of that when you look at these associations.

DR. BORER: Last comment from the audience because we\'re going to go on
to the moment you\'ve been waiting for, Dr. Throckmorton and Dr.
Griebel, answering the questions.

DR. SHELL: Dr. Shell, Laboratory Industry Services.

There are a set of cisapride Holter data analyzed by bin methodology
with placebo control that show a dose-response relationship between
central tendency, mean QTc, and the dose-response curve.

DR. BORER: You\'re asking here, FDA, for our best judgment because
clearly we don\'t have sufficient data, as you\'ve heard, to draw firm
conclusions, but we\'ll do our best.

This voting is a little bit complicated here. This response is a little
complicated. I want to tell everybody on the committee that if you look
at the questions, where you see questions that have yeses and noes in
them, we need individual votes for the record. That\'s number one.

Number two, if you want to give a reason for your vote, that would be
good, but if the reason has been given already and you\'re 13th up, you
don\'t have to repeat it all. Just say yes or no for the reasons already
indicated.

Then we have to respect the conflicts issues with regard to who can
vote. John and Dan, unfortunately, cannot vote on anything. Beverly can
vote on alfuzosin, but not on Levitra. With all those caveats, we\'ll
begin. So, Bev, when you do vote, please specify which drug you\'re
voting about.

Number one, the alfuzosin and vardenafil studies evaluated the effects
of a single dose on QT/QTc. Were the studies for alfuzosin, a drug that
will be dosed daily, adequate to evaluate the drug\'s effect on QT? Yes
or no, and a reason if you like. I will expect to hear 14 votes. I\'m
not sure that we actually will have that. Steve is gone. It\'s 14, okay.

Mike, why don\'t we begin with you?

DR. ARTMAN: My answer is yes. As the first one, I guess the slate is
clean so I can explain my answer. I think it\'s based upon the pretty
comprehensive pharmacokinetic data that were presented both for
conventional dosing and with super-maximal doses. So I think that the
data were clear and solid, so I can vote yes.

DR. BORER: Blase?

DR. CARABELLO: Yes, I also vote yes. I thought that the data were
convincing that steady state had been reached, and although the argument
was raised that perhaps there was a difference between the steady state
effects on drug concentration versus those on the QT, there was no data
presented to suggest that that was the case. So I say yes.

DR. BORER: Toby?

DR. BARBEY: I say yes also based on the conglomerate of the data. I was,
as a clinical pharmacologist, still disappointed that the study was only
single-dose, but the data that are available override this regret that I
have. So I would have preferred it to be in terms of metabolites, but I
don\'t think it would have changed by vote, but I just regret it.

DR. BORER: Alan?

DR. HIRSCH: Sort of mimicking Toby\'s answer, yes, for this drug with
the panoply of data offered. I think in general for these classes of
agents, multi-drug dosing would be superior.

DR. BORER: Tom?

DR. PICKERING: Yes, I agree with the last speaker. And I\'m not sure how
well the stability of the plasma levels reflects what\'s going on in the
tissues with the long-term dosing.

DR. BORER: Paul?

DR. ARMSTRONG: Well-done studies, but for me, Mr. Chairman, once is not
enough. So I vote no.

DR. BERNITSKY: I\'m going to abstain on voting since I don\'t believe I
was asked to be here as a cardiologist or from the perspective of
cardiology.

DR. BORER: Beverly? Remember, we\'re only voting about alfuzosin.

DR. LORELL: Yes. For alfuzosin, my answer would be yes.

DR. BORER: Susanna?

DR. CUNNINGHAM: My answer would also be yes.

DR. BORER: JoAnn?

DR. LINDENFELD: Yes, but I also would have preferred to see a
multiple-dosing study.

DR. BORER: I\'ll vote yes. I want to reemphasize Tom Pickering\'s point
about the desirability, had they been available, of tissue levels, at
least in an experimental setting, because of the lack of information
about temporal relationship of blood level and effect. And I understand
the FDA concern about the AUC issue, and I think that\'s important. But
nonetheless, the overarching impression is that this would be
sufficient.

Tom?

DR. FLEMING: In a certain context, yes, I believe the studies are
adequate to give us an assessment of what the average change in QT is.

In a very important sense, though, no, because the studies really are
not adequate to get at outliers. It\'s really not adequate to understand
what the effects are on QT in terms of changing by large amounts by 60
milliseconds or the frequency at which QTc values might be in the
right-hand tail. I\'ve become persuaded that that\'s a very important
aspect of what we need to understand, and these studies were not, by
design, powered to address those issues.

DR. BORER: Phil?

DR. HANNO: I would vote yes, with the caveat that this is a drug that
will be used in women for several reasons, for pelvic floor dysfunction,
elderly women who don\'t completely empty their bladder, and it doesn\'t
look to me like the studies in women were done.

DR. BORER: Peter?

DR. KOWEY: First of all, I think that the QT interval is just a really
rotten way of measuring repolarization.

(Laughter.)

DR. KOWEY: It is. It\'s a surrogate that nobody really likes very much.
It doesn\'t really reflect what we really want to know.

There are really two ways to answer this. Tom\'s idea of having real
outcomes data, and Beverly said the same thing. That\'s really,
obviously, very, very important, very hard to do.

The other way is to have a better way of measuring repolarization. So, I
don\'t know who it was that said earlier that we need better science. I
think it was Jeff. I can\'t emphasize enough to people in the audience
that although that this is clearly by us all voting yes, this becomes a
way of going through the process of finding out about repolarization for
new chemical entities, I don\'t want anybody to walk out of here
thinking that we like this because I really don\'t like it very much.
The biggest part of the problem here is that we just don\'t know how to
measure the thing that we really want to know which is repolarization
abnormality, repolarization reserve, individual susceptibility, all
those things that scientists are still working on. So I would encourage
people in the audience not to take this as the door is getting shut.
It\'s just opening I think.

So the answer, Jeff, is a long-winded yes.

DR. BORER: Thank you.

What\'s the number that we have? We did it.

Okay, now we\'ll go to the second part of this question where we should
only have 13. Were the studies for vardenafil, a drug that will be dosed
intermittently, adequate to evaluate the drug\'s effect on QT? Peter,
why don\'t we start with you this time.

DR. KOWEY: I\'m going to vote yes again because I think that that\'s
appropriate.

I was a little disappointed that when the sponsor presented the
information with single dose, that we didn\'t see the area under the
curve data that the agency brought to us. I think that\'s a very
important analysis because one of the big questions that we\'ve wrestled
with all day is whether Cmax really reflects the time or the way of
looking at the worst case scenario in terms of what the drug is doing at
membrane level, and area under the curve may be just as important.
Obviously, there\'s a big difference between Cmax and area under the
curve for those two analyses. I was a little disappointed that we
didn\'t get that from the sponsor, but got it from the agency. Well,
maybe I should be happy that that happened.

But in any case, despite that, I think that the study design was
adequate and it did answer the question that it sought to answer. So I
would answer yes.

DR. BORER: Phil?

DR. HANNO: I\'ll answer yes. I think it\'s so difficult to make a
decision on any of this listening to all of the arguments just because
the marker is so poorly characterized and we don\'t really know what
we\'re aiming to get here or what it means. So I had a lot of trouble
with that, but I would say, as far as we can do it, yes.

DR. BORER: Tom?

DR. FLEMING: Well, I think the response is the same as I gave for
alfuzosin. The only thing that I would add is that in the vardenafil
trial, I\'m also struggling to know whether the answers that we\'re
getting ‑‑ it\'s, I think, one of Beverly\'s earlier points ‑‑ in this
population in which the study was conducted are relevant to the target
population that we\'re going to be treating. I\'m struggling as to how
much that compromises the interpretability of this result.

DR. BORER: I will vote yes also, and I\'d like to echo Peter\'s point,
the several points that he made. But nonetheless, I think my overarching
opinion is that we do know how this drug affects QT, for whatever
that\'s worth.

JoAnn?

DR. LINDENFELD: I\'ll vote yes as well for the same reasons.

DR. BORER: Susanna?

DR. CUNNINGHAM: I\'ll vote yes, but I think being forced to answer
yes/no for these questions is terribly simplistic and actually not
appropriate.

DR. BORER: Gay?

DR. BERNITSKY: Again, I\'m going to abstain on any cardiology issues.

DR. BORER: Paul?

DR. ARMSTRONG: In trying to be consistent, Mr. Chairman, I\'m reminded
that Oscar Wilde said that consistency was the last refuge of the
unimaginative.

(Laughter.)

DR. ARMSTRONG: But I will say that if the question were in normal
healthy volunteers who were male, I would say yes, but because it
isn\'t, I\'m continuing to vote no.

DR. BORER: Tom?

DR. PICKERING: Yes.

DR. BORER: Alan?

DR. HIRSCH: Yes. I\'m going to praise both sponsors for using adequate
but different techniques to assess effects on QTc. Relevant populations
should always be studied.

DR. BORER: Toby?

DR. BARBEY: Like before, I will say yes, but as a clinical
pharmacologist, I\'m disappointed that there was not a higher dose
tested in a drug interaction study. Only the 5 milligram was combined
with ritonavir, and even if the label initially will sort of address
this issue, I think that issue needs to be explored further, how it
should be done. But with the data presented, I would say yes, but I
would like that.

DR. BORER: Blase?

DR. CARABELLO: Yes.

DR. BORER: Mike?

DR. ARTMAN: Yes.

DR. BORER: We\'ve made it through the first question. We\'ll move faster
as we go along.

Number 2, the patients enrolled in these studies were healthy male
volunteers ‑‑ and I think we\'ve begun to discuss this ‑‑ mean age 27,
et cetera, with normal electrolytes and baseline cardiac function, which
I assume means that they had normal cardiac function at baseline. Was
the effect of alfuzosin on QT for the population intended for actual
treatment adequately studied?

We\'ve heard some comments about this already, but I think we need to
hear at least a summary of them again. Let\'s begin with Mike.

DR. ARTMAN: Yes, this is very difficult because, as Doug mentioned, the
question was, do these drugs affect repolarization, and the FDA said the
way to determine that is to take a small group of young, healthy male
volunteers and see if the drugs affect repolarization. But that\'s
clearly not the population that\'s going to receive these drugs. So I\'m
not going to reiterate all the things that have been said by the smarter
people here than I, so I just have to vote no.

DR. BORER: Blase?

DR. CARABELLO: And, of course, that puts me at a disadvantage because
everybody is smarter than I am.

(Laughter.)

DR. CARABELLO: But I would vote no with the caveat of so what.

(Laughter.)

DR. CARABELLO: Surely ‑‑ what everyone said ‑‑ we would like to know
what happens to the poor guy that both has an enlarged prostate and
erectile dysfunction because he\'s on a diuretic that\'s reduced his
potassium to 2. What happens, when he takes both of these drugs, to his
QT? We\'re not going to know that unless we have some very large trial
that encompasses everything.

On the other hand, I believe that the studies that were done have raised
the bar. I suspect we know more about the QT interval in these folks
than any other drug that we\'ve looked at. And the data suggests that
the fact that even though it was tested in healthy people, that the
small changes in QT that occurred there are likely to be replicated in
the study population.

So, yes, we didn\'t study the study population in question, but I\'m not
sure that it\'s a relevant question.

DR. BORER: Toby?

DR. BARBEY: No, but I don\'t believe it\'s a grave concern.

DR. BORER: Alan?

DR. HIRSCH: No. I still believe that other dysrhythmias, including
torsade de pointes, probably are more common, not just with structural
heart disease, which is not relevant in this population, but with other
factors we yet biologically don\'t understand.

DR. BORER: Tom?

DR. PICKERING: No, because this drug is one that\'s going to be used
almost exclusively in people older than the ones studied.

DR. BORER: Paul?

DR. ARMSTRONG: No.

DR. BORER: Gay?

DR. BERNITSKY: Even to me it appears that we didn\'t study it in the
population that\'s going to receive it.

DR. BORER: Beverly?

DR. LORELL: No, I don\'t think it was adequately studied in the target
population.

DR. BORER: Susanna?

DR. CUNNINGHAM: No.

DR. BORER: JoAnn?

DR. LINDENFELD: No, I don\'t think so. And also, even though these drugs
were intended for men, they\'ll be used in women, and this will be used
in women, and it would be nice to have some data there.

I\'m not quite so convinced as everyone else that it doesn\'t matter. I
just would like to see some data that it doesn\'t matter, that this
population reflects what we\'ll see in a population on antihypertensive
drugs and diuretics. And if we just had a body of data that showed me
that, I\'d be much more confident about it.

DR. BORER: I\'m not sure how to answer this question. I guess literally
I\'ll say no, but let me explain why because I agree with what\'s been
said several times here.

Was the effect of alfuzosin on QT for the population intended for actual
treatment adequately studied? The answer is I don\'t know because we
didn\'t really look at QT in that population, so I can\'t say rigorously
that what we saw in the normal volunteers mirrors what we would have
seen in the patients and that there isn\'t some unusual drug-disease
interaction.

Having said that, I think that just as Blase said and just as Toby said,
I\'m not sure that that really matters. I\'m convinced by Dan\'s points
about the value of looking at the high dose in the optimal situation
where you\'re looking at relatively normal membrane function to infer
whether it\'s likely that there will be overwhelming drug-disease
interactions or PD interactions between drugs as opposed to PK
interactions.

So maybe I would have requested that the question be worded a little bit
differently, but I think you get the idea. It\'s either yes or no, but
it doesn\'t much matter because we have, as Blase said, more information
here than probably we\'ve ever had before, and that puts us in a better
position to try to make a best guess about what the likely outcome of
using the drug will be than we would have been before.

So you can count that as a yes or a no.

(Laughter.)

DR. BORER: Tom?

DR. FLEMING: Well, in the absence of having direct evidence to show that
these results in young male volunteers can be extrapolated to the target
population, I have to say no.

DR. BORER: Phil?

DR. HANNO: No.

DR. BORER: Peter?

DR. KOWEY: No. The answer is an unequivocal no. You can\'t tell.

But I do care and I wish I knew, so I can\'t be quite as glib as to say,
so what, Blase. I understand what you said, but my feeling is that you
can\'t do that study. It\'s too difficult. It\'s almost logistically
impossible to do the study in the intended population.

Having no information in that population and knowing what I know about
what these patients usually get in terms of drugs and electrolyte
abnormalities, the committee needs to know very clearly that these drugs
will cause torsade in somebody some day. I don\'t think there\'s any
question in my mind about that. I\'m not grappling with \"if yes or
no.\" I\'m grappling with how many, and I can\'t answer the question.

So the answer is no, I can\'t tell the QT effect, but even worse than
that, I don\'t know what the torsade risk really is, but I know it\'s
not zero judging from what we know about QT-prolonging drugs when you
put them into patients that are sick. So it\'s a concern to me and it
makes me uncomfortable, but that\'s how I would answer it.

DR. BORER: Well, while you\'re answering, why don\'t you go on to the
effect of vardenafil? Was the effect of vardenafil on QT for the
population intended for actual treatment adequately studied?

DR. KOWEY: No. Again, the answer is no and my concern is the same.

DR. BORER: Phil?

DR. HANNO: I agree. No, and for the same reasons.

DR. BORER: Tom?

DR. FLEMING: No, for the same reasons.

DR. BORER: My answer would be the same as before as well, although my
answer was a little more complicated.

Since Peter moved beyond QT to the meat of the issue, which is what QT
is supposed to be a surrogate for, I have to say that I\'m not
unimpressed by the post-marketing data that were presented. That gives
me some degree of comfort and makes me think that I\'m not really
totally off base by suggesting that it may not matter so much that the
effects on QT weren\'t looked at specifically in the population that
would be expected to be at risk.

JoAnn?

DR. LINDENFELD: No, for the same reasons.

DR. BORER: Susanna?

DR. CUNNINGHAM: No.

DR. BERNITSKY: No. I would also like to add, though, that in hearing the
data both on sildenafil and vardenafil, as a clinician I feel much more
comfortable that these are safe drugs in the context that we use them. I
think the context that we use them is very different than moxifloxacin
with a patient in the ICU receiving an IV antibiotic. They appeared to
be pretty safe drugs.

DR. BORER: Paul?

DR. ARMSTRONG: No, and more exposure in women with this one than the
previous one.

DR. BORER: Tom?

DR. PICKERING: I would say yes here. My previous complaint was about the
age. I think it would have been incredibly complicated to try and do it
in people with all sorts of medical conditions and all sorts of other
drugs for an initial phase I study.

DR. BORER: Alan?

DR. HIRSCH: No.

DR. BARBEY: I would say a softer no because everybody who watches the
evening news gets encouraged to use one of these drugs. So there will be
people that age without disease who will take the drug.

DR. BORER: Blase?

DR. CARABELLO: No.

And I\'m sorry if my \"so what\" sounded cavalier. It\'s not that I
don\'t care. It\'s just I know I can\'t have the data as none exists.

DR. BORER: Mike?

DR. ARTMAN: No.

DR. BORER: Doug, those answers were a little convoluted relative to the
way the question was worded. Did you get the idea? Is this good enough
since we all gave reasons?

DR. THROCKMORTON: Yes, I think I heard what you had to say.

DR. BORER: Let\'s go on to number 3. Is it appropriate to use pooled
baseline and placebo exposure data for calculating linear and nonlinear
regression correction formulae? And we\'ll need to explain that.

I\'m going to start at the middle of the table here. Tom, will you give
the initial response to that, please?

DR. FLEMING: I was hoping to follow the chair on this.

(Laughter.)

DR. FLEMING: I\'m assuming this question is specific to the computation
of the individual adjustment. We have the Bazett\'s adjustment,
Fridericia, the population, and the individual. Is this asked in the
context of that individual calculation?

I clearly understand that our goal here, of course, is to understand how
the agent\'s effects on QT are giving us the best clues about what
meaningful safety risks would be and that we have to adjust based on the
heart rate changes. What I struggle with is I don\'t know the truth. And
I think we\'ve heard a lot of discussion here today that we don\'t know
what the truth is for the way you\'re supposed to be adjusting for the
dual effect on heart rate changes and QT in order to get at the best
measure of QTc. And because I don\'t know the truth, I can\'t answer
this question as to what is in fact the best way.

As we\'ve heard earlier, if one is looking for constancy of these slopes
and you\'re looking to use a general formula, a power that\'s the same
for all patients, that power .33 rather than .5, the Fridericia rather
than the Bazett\'s, does seem to give better performance, if that in
fact is what the truth should be.

If the idea is to do even better than that by having a patient-specific
power, which is what I see this is all about, at a certain level,
that\'s appealing. Maybe the power is different for every given patient.
But the data that I\'m going to use that\'s going to capture more than
just the change in heart rate could readily be noise as much as it could
be signal. So philosophically I\'m not saying this individual approach
is worse than Fridericia, but I haven\'t heard enough evidence here
today to convince me that it\'s better.

And given that I\'m not persuaded that it\'s better, it\'s hard to get
into the fine-tuned details about whether, when I\'m doing it, I should
use only the individual\'s baseline data or use the placebo. I think I
understand the issue. The individual\'s baseline data, as Dan was
talking about earlier, may not be sufficiently voluminous to be able to
set what that power parameter should be, so you want to use the placebo
but now you\'re extrapolating to a broader population that may not be
specific to that individual.

So I think I understand the issues here, and yet it doesn\'t leave me in
a position to answer the question because of a fundamental inability of
knowing what the truth is. What is the true way that you should adjust
given the treatment is dually affecting both heart rate and QT to adjust
that nature of the change in heart rate to tell me what the meaningful
residual change on QT is. And until I know that, I couldn\'t answer the
question.

DR. BORER: Well, okay. I\'m to the left of you. I agree with everything
Tom said, but.

(Laughter.)

DR. BORER: I think the way I\'m interpreting this question is that if
you\'re going to use an adjustment, is it reasonable to pool the
baseline data in the individual patients and the data that were obtained
on placebo perhaps by a crossover design in the individual patients, the
way you did it or perhaps some other way? I\'m not sure what other way
you could do it. And it seems to me that if you believe that an
adjustment is a reasonable thing ‑‑ and intuitively I do ‑‑ then I would
try to make the basis of the adjustment as representative as I could,
and I would pool the baseline and the placebo. So I think that that is a
reasonable thing to do if you\'re going to make the adjustment.

I, of course, agree with Tom. I don\'t know what the right thing to do
is. Which technique for defining QTc is best? And we\'ll get to some of
that, I think, as we go along, so I\'m not going to go beyond that
comment. But I would favor pooling the baseline and placebo data. Am I
responding to what you\'re asking here?

DR. GRIEBEL: Yes.

DR. BORER: Okay.

Let\'s go around the table. You don\'t have to give an additional
opinion if it doesn\'t differ from what you\'ve heard. JoAnn?

DR. LINDENFELD: I agree with what you just said. It just seems to me
that pooling the data is a very reasonable thing to do, knowing that we
still don\'t know the best way. I agree.

DR. BORER: Susanna?

DR. CUNNINGHAM: I don\'t know, so I\'ll abstain.

DR. BORER: Beverly, this is not drug-specific. You may vote.

DR. LORELL: Yes, I will abstain too. I don\'t think I have sufficient
expertise statistically to answer this question.

DR. BORER: Sorry, you don\'t have to vote.

Let me just ask. Does anybody else have an opinion that differs from
what you\'ve heard?

(No response.)

DR. BORER: We\'re on number 4.

DR. ARTMAN: Jeff? Jeff, over here. Maybe not an opinion, but I want to
make sure I understand what you\'re asking. Are you asking in an
individual who may have had multiple ECGs at baseline and multiple ECGs
under placebo treatment, is it acceptable to pool that individual\'s
data into ‑‑ okay. So I\'m not sure others were answering that question,
it didn\'t sound like from the discussion.

DR. BORER: That was the question I was answering.

Tom.

DR. PICKERING: The question was actually is it appropriate, not is it
best, and I would say it is appropriate because I think at this stage we
need to look at all possible methods and encourage everybody to do
different analyses. So I would say yes.

DR. BARBEY: I\'m sorry. With the caveat that if the subject is perfectly
still in bed, there will be very few heart rates to work with, which
sort of defeats the purpose of this. If you start to move around, then
you don\'t know the plasticity of all that. So it\'s not easy, but
pooling to get a broader range for each individual would seem
appropriate.

DR. BORER: Paul?

DR. ARMSTRONG: Just picking up on what Mike said, then if we\'re talking
about the baseline from those who would be exposed to drug, plus the
multiple observations from placebo, as long as there\'s not a time-
dependent covariant interaction in the placebo that\'s demonstrated such
that the data in the placebo over multiple points is homogeneous, then
I\'m fine. But that would be the caveat.

DR. ARTMAN: You\'d like to be able to show that if you do a Holter bin
method, that the baseline line lines up with the placebo line. And if it
does, then you have no placebo effect and it\'s perfectly appropriate to
pool those data, but if they\'re separate, then it\'s not appropriate.

DR. BORER: Number 4. Because of uncertainty about an optimal correction
methodology for determining QTc, it is likely that sponsors will submit
the results of multiple correction methodologies. A, should trials
specify and adhere to a primary endpoint, i.e., primary correction
methodology.

This is the issue that Joel raised in his discussion and I guess we need
to get to it. Although it is sort of a statistical question, it\'s more
than a statistical question so I will not begin with Tom this time.
Let\'s go to Peter. Again, everybody does not need to respond to this,
but if you have something that you want to contribute, please feel free.
Peter?

DR. KOWEY: Well, this sort of gets back to something that Tom said a
couple of minutes ago, which is that if you don\'t know what the real
truth is, and you don\'t know a priori what method is the best, then I
always enjoy looking at data, like these tables that we\'re going to be
looking at in a minute, where you get to see the data broken out by
different formulae.

It is obviously a very data-driven decision. I don\'t think that anybody
can really anticipate what\'s going to happen, for example, with the
heart rate in any given trial before you do the trial.

So I really don\'t like the idea of a primary prespecified way of doing
it. I really like the idea of a menu of correction formulae to examine
after the study is finished. So I guess my answer is no to A.

DR. BORER: Tom, since you are our statistician and this strikes at the
heart of statistical purity, let me ask you if you have an opinion here
that differs from Peter\'s.

DR. FLEMING: I don\'t know about the \"differs,\" but I have an opinion.

DR. BORER: Please give us your opinion.

DR. FLEMING: I think it\'s very important in clinical trials to set up
studies in ways that allow for confirmatory analyses and exploratory
analyses and to distinguish between the two, and it\'s in this context
that levels of statistical significance, p values, et cetera are really
interpretable. So if in fact we\'ve designed our trial properly, and if
in fact we\'re in a setting in which we can rationally determine in
advance what is the most clinically relevant endpoint, the primary
endpoint should be chosen to simultaneously satisfy the criteria of
what\'s clinically most relevant, what\'s going to be sensitive to the
treatment effect, if it\'s real, and what\'s measurable and
interpretable. Under those criteria, there may not be a unique answer,
but we should strive to achieve, as best we can, that endpoint that
satisfies those criteria.

And if we\'re going to rely on statistics, then those statistics are
most formally interpretable in the context of the prespecified primary
analysis of that prespecified endpoint. So if we\'re going to rely on p
values and strength of evidence and all these kinds of issues, then it
is important to go through the care in advance to specify a primary
endpoint.

Even in that context, though, of course, we definitely always want to do
exploratory analyses to get as broad a view as possible about benefit to
risk, about primary and secondary endpoints, about safety issues, about
external results, et cetera. All of that is important. The
interpretation of significance levels and all, though, is much more
problematic in those secondary endpoints.

Having said that, in a setting in which it\'s not clear what in fact
should be the essence of the signal we\'re trying to measure here, i.e.,
where you don\'t have a clinical endpoint, where you have a surrogate,
and worse yet, where there\'s a lot of uncertainty about what that right
surrogate should be, then I understand why in these trials the sponsor
and the FDA, in working together, were not able to achieve what I would
call the ideal I would be asking for, which is a very clear
specification up front of what that best endpoint would be. In that
context, and even more so, it\'s going to force us into the exploratory
mode, but then it still leaves us in a setting where we have to
interpret all of these results with much more caution. Data-driven
hypotheses can give conclusions that look very impressive, but in fact
they\'re not nearly as impressive if they are, in fact, suggested by the
data rather than prespecified and confirmed by the analysis.

So what I would want to say is, yes, in general, we absolutely should be
specifying and adhering to a primary endpoint and requiring and adhering
to a formal statistical plan where we in fact then, to the extent that
we care about significance levels and all, are going to be in a position
to adjust our sense of strength of evidence. But here we have a
circumstance, as we\'ve spent the whole day laying out, making it very
clear that it\'s extraordinarily difficult to know whether the
Fridericia method, which was specified in the second setting, was in
fact the best measure.

So I\'m very understanding for why, in this setting in particular,
we\'re giving less focus on the primary compared to the secondaries, but
in fact, that\'s not a carte blanche or a freebie here. My own sense is
all of these analyses are leaving me at considerable uncertainty. I
agree, Doug, they\'re giving us clues, but they\'re not the level of
clues that I would typically have wanted to have seen, and I\'m not
saying that critically because the sponsor and FDA haven\'t given this
thought. These are inherently extremely difficult situations to
understand what is in fact the best measure that reliably represents or
reasonably reliably represents an unacceptable safety risk.

DR. THROCKMORTON: I guess the other distinction you might make, Tom, is
that when we\'re talking to sponsors about clinical outcome trials, if
they propose an endpoint that we know to be not an endpoint that\'s
valuable to us ‑‑ I don\'t know ‑‑ serum porcelain levels or something
‑‑ we say, no, that\'s not a primary endpoint we can understand in a
clinical consequence as beneficial. Here we\'re not in a place where
we\'re able to do that. I think we\'re maybe saying the same thing. Is
that about it?

DR. FLEMING: This may be what you\'re saying. I want to emphasize the
point. As much as I believe strongly that to use statistical inference
in an interpretable way, it should be in a confirmatory sense. If one
elevates to a primary endpoint a measure that, as time goes on, becomes
increasingly clearly inadequate in capturing the essence, then I think
logic has to come forward and dominate our thinking. We can\'t adhere to
a prespecified primary endpoint if, at the end of the trial, we have an
enhanced understanding that would tell us this really was a poor choice.

Now, as the FDA guidance document on monitoring committees, released in
November of 2001, clearly said, one of the great things about keeping
results confidential is that that allows the sponsor and the FDA
throughout the course of the conduct of the trial to refine their
thinking about what the endpoint should be, and so long as that
refinement is separate from the insights emerging in that trial, you are
in a position where you still can view a refined analysis plan or
refined analysis endpoint as being confirmatory.

But the essence of what I hear you saying that I would agree with is if
there is a strong objection to the previously specified primary endpoint
as capturing the essence, then it\'s certainly appropriate for us to
give it less weight than we otherwise would.

DR. BORER: I think Tom has said it all, and I don\'t think that Peter
and Tom are in disagreement here at all. I cannot restate all that as
eloquently as Tom did, but let me just make a short comment.

I think that in a situation like this where the value of the surrogate
in a quantitative sense is not known ‑‑ it isn\'t a qualitative sense,
as you pointed out, Doug, but in a quantitative sense it\'s not really
known, and the best way to measure the surrogate hasn\'t been determined
yet, when you come to us, when the FDA comes to a panel like this asking
these questions, you\'re asking for our best judgment which is, in
essence, a synthesis of our intuitions, our opinions, some data. And
that\'s what we\'re going to give you. By its very nature, the
development program that provided these data was, as Tom said,
exploratory, and it has to be because the answer is not known. The best
method is not known.

So given that, although I think it\'s always appropriate to provide a
formal analysis plan a priori and to adhere to it, I think in a
situation like this, it\'s mandatory that multiple methodologies should
be evaluated. And at the end of the day, a group like this and more
importantly the FDA is going to make its best judgment from what it has
seen, and it is to be hoped that when enough data are gathered of this
sort, with all the methodologies being looked at and all the outcomes
being evaluated, it will be possible, at some point, to define what the
best predictor is and to apply that in the future.

So I\'ve just hit part A and part B, I think. I think we\'re all in
agreement so far.

Does anyone else, Phil, JoAnn, anyone, have any other comments you want
to make that would add to this? Beverly?

DR. LORELL: I have just a short comment. I agree with everything that\'s
been said. I think this still in a transition phase and that it would be
foolhardy to have a single, primary, rigid measure.

I would put forward as a suggestion, given the I think extraordinary,
careful collection of data that we\'ve seen from both sponsors this
morning, that this might serve as a comparator template over the next
year, two years, three years, as we learn more, to say we would like to
see this menu showing data with Bazett\'s, Fridericia, and individual
approach, and perhaps if available, the Holter approach.

And I would suggest there are two more things that might be included so
that a data set collects. One is using moxifloxacin as a positive
control. You have a large database to work with.

And I would suggest a third component. We didn\'t talk very much about
it in Jeremy Ruskin\'s presentation this morning, but I think his slide
72 was sort of a wake-upper for me, and that was the slide that actually
showed the QTc prolongation with terfenadine and ketoconazole. That
actually provides some kind of a signal. We don\'t know how reproducible
it is, but we saw that that intervention caused a QTc prolongation of
about 80 milliseconds.

So it may be, while everyone is learning what this means and how to do
it, that it would be useful to suggest to future sponsors to include not
only this menu, to include a standard positive control, and to include
metabolic inhibition, if appropriate for that drug\'s metabolism, with
ketoconazole.

DR. BORER: Blase?

DR. CARABELLO: yes, I would agree that certainly until we have a gold
standard, we need to use all the standards.

I just want to point out that both the sponsors and we are getting off
pretty lightly here today because all of the data are fairly concordant.
We\'d be in a hell of a mess if particularly Bazett\'s, which hangs out
there, if there had been wide changes in heart rate, said one thing
while the other data said something else. We\'d be in a real quandary
about knowing what to do.

DR. BORER: That\'s true.

Any other comments?

DR. ARTMAN: Jeff?

DR. BORER: Mike?

DR. ARTMAN: Yes, I just would suggest that you encourage the sponsors to
continue to use the Holter bin method. I think that does represent an
innovative, a newer approach that I think is likely to turn out to be
quite valuable.

The other point is I think if they come to you and they say we\'re going
to use Bazett\'s correction as our primary endpoint, I think you should
discourage that. I think that\'s the one that doesn\'t fit very well.

DR. THROCKMORTON: So that would be a bad primary endpoint?

DR. ARTMAN: That would be a bad primary.

DR. BORER: C here is, explain how the totality of the data obtained from
a comprehensive panel of these methodologies should be evaluated to
assure valid conclusions. I think we have discussed that already. So we
won\'t formally respond to that question.

We\'ll go on to number 5. The table below summarizes the mean change of
QT from baseline, both uncorrected and corrected, of alfuzosin 10 and 40
milligrams and moxifloxacin relative to placebo, as observed in study
PDY 5105.

Here\'s a voter again. Are the results of any one correction methodology
more valid than the others? I think we dealt with that.

So let\'s go to B. Do these data demonstrate a clinically relevant QT
prolongation associated with alfuzosin? Okay, this is an important one
and we should vote.

Mike, why don\'t we start there. That\'s B, do these data demonstrate a
clinically relevant QT prolongation associated with alfuzosin. Yes or
no?

DR. ARTMAN: My answer is no.

DR. BORER: Do you want to explain that or is that pretty obvious?

DR. ARTMAN: No, I don\'t want to explain it.

(Laughter.)

DR. BORER: Okay. Blase.

DR. CARABELLO: My answer is no one could possibly know, but I think the
answer is no. I\'m certainly not persuaded that there has been a
clinically significant prolongation of the QT interval.

DR. BORER: Toby?

DR. BARBEY: No, and I don\'t have any great further insight on that.

DR. BORER: Alan?

DR. HIRSCH: No, but with no insights, I have an opinion.

(Laughter.)

DR. HIRSCH: Going back to Doug\'s comment ‑‑

DR. THROCKMORTON: Which we value.

DR. HIRSCH: We have just a small number of drugs where we can really
calibrate a QT change with outcomes. So I think the answer is no, but
until the database is enlarged, I think that range of small, medium, and
incredibly long QT intervals needs to be defined. So I don\'t know how
to define clinically relevant.

DR. THROCKMORTON: Alan, what I heard from Jeff actually helped me
understand your answer to question 2 a bit. What I heard was unhappiness
with the absence of quantitative information. There\'s a qualitative
relationship here that some of you were unhappy with. It\'s that
qualitative nature of it. Is that fair?

DR. HIRSCH: You can\'t define clinical relevance on a QTc alone by any
of the methods. It will be outcome on human clinical events. We don\'t
have that correlation very well defined. We have just a very few data
points in our drug approval data set.

DR. BORER: Tom?

DR. PICKERING: No, and there is the post-marketing surveillance data.

DR. BORER: Paul?

DR. ARMSTRONG: No.

DR. BERNITSKY: Abstain.

DR. BORER: Beverly.

DR. LORELL: No.

DR. BORER: Susanna?

DR. CUNNINGHAM: No. Probably not. How can you say no for sure?

DR. BORER: Okay, that\'s a probably not.

JoAnn?

DR. LINDENFELD: I would say no, and I think of some of the data we\'ve
seen today, including the post-marketing data, helps me say that this
moves me more toward no than I was earlier today.

DR. BORER: I say no also. I\'d like to add one point here, though. I
think that the data in the table are useful. This has been said before,
but I think the fact that there are two comparators to the clinically
applicable dose, one being a relatively high dose, which doesn\'t show
all that much, it seems to me, quantitatively, for whatever that may be
worth, but whatever it shows seems to be less impressive than the
results from the active control.

Given the fact that the active control sounds as if it is not associated
with some overwhelming frequency of horrible events makes me feel more
secure against the backdrop of what we know from the totality of
associations that have been made between QTc and outcomes in other
development programs, makes me feel reasonably assured that a no is a
reasonable answer, although of course, I don\'t have rigorous data to
support that statement.

DR. THROCKMORTON: Jeff, could I ask if that\'s a part of other people\'s
thinking as well; that is, that the numbers were, in a sense, less than
the active control? Was that part of the reassurance that people drew?
Just in a general sense. I\'m not asking for a vote necessarily. Was
that part of the thinking that led to some of the votes previously, just
a nodding-head thing.

DR. BORER: Don\'t talk all at once, or in fact, you can talk all at once
in this case.

DR. ARTMAN: I\'m answering and nodding my head. I think it was
reassuring and it was very helpful to have that active control.

DR. CARABELLO: Yes, the fact that the active control had at least some
signal, albeit small, was very helpful.

DR. HIRSCH: Good job having active control.

DR. BORER: Tom?

DR. PICKERING: Yes, I agree.

DR. BORER: The other Tom, for an answer, a yes or a no.

DR. FLEMING: A comment first.

(Laughter.)

DR. FLEMING: The easy part of it is, is there QT prolongation? Yes,
there is. The important part of this is, is it clinically relevant? I do
want us to take a moment to think through this because this is, I think
the critical issue that we have to address.

The way I would normally think about addressing this is in benefit to
risk, and we haven\'t had a lot of discussion about that today. Here
we\'re talking about BPH. What is the benefit? What is the magnitude of
benefit? Understanding first what that magnitude of benefit would be,
hopefully, would then guide us as to what would be an acceptable level
of risk in the context of that benefit.

So when I see an agent that induces a QT prolongation, my answer as to
whether or not this is a clinically relevant QT prolongation has to take
into account the magnitude of benefit that I know this agent provides
and whether this risk ‑‑ in other words, I\'m saying a one in a million
chance is clinically relevant in one setting but not in other settings
in a manner that depends on what benefit is. So in answering this
question, I would ask that there be careful thought as to what is the
known benefit of this agent in this setting, and in that context, what
would be an acceptable level of risk according to which endpoints and of
what magnitude and frequency would be acceptable.

Then the next question is now how do I assess whether or not I have that
increase in risk. Obviously, I\'m using a surrogate. What is the best
surrogate? How do I know it\'s the best surrogate?

And if we\'re using historical evidence, based on a lot of experiences
of other agents that use QT, back to a point I was saying earlier ‑‑ and
that\'s relevant here to look at that, but if it\'s all based on
Bazett\'s, then I have to translate it, if that isn\'t my current view
of what the best measure is, to be able to assess what is in fact the
safety risk.

So my own assessment of this says, even though we\'ve had a very
informative discussion today, there\'s a lot of answers to questions
that I just mentioned that I don\'t have that technically speaking I
believe I should have to answer this question.

Having said that, my inclination is to say this is a sufficiently modest
increase that in a way that I\'m inadequately informed by not knowing
the answers to a lot of these other questions, I\'m inclined to think
that this is a not a clinically relevant prolongation, but with an awful
lot of uncertainty about those issues that I don\'t know answers to.

DR. BORER: Phil, in giving your answer, perhaps you can add two or three
sentences about the benefits of providing alpha blockade in patients who
have prostatic hypertrophy, because they are important.

DR. HANNO: I think the issue here is these are very useful drugs. For
both of these drugs we\'re looking at today, there are already similar
drugs on the market. So in a way, these are me-too drugs that are coming
out.

I think Tom\'s questions are exactly right, but there\'s no way to
answer whether these drugs have a lower risk from this or an equivalent
risk to what\'s already out there or a higher risk. Without knowing the
comparative risk, if we don\'t move ahead with these drugs, it\'s not
like we\'re preventing people from taking these drugs that are already
on the market and having a risk which is uncharacterized.

So based on the data here, I would say, no, there is no increased
significant risk from everything that I\'ve heard and read. But I really
don\'t think we know whether we\'re helping people or increasing the
risk or lessening the risk because we don\'t know what the risk is of
the similar drugs that are already out there.

DR. BORER: Forgetting for a moment about the relative benefits and risks
of the different drugs in this class that might be used in patients with
BPH, what are the benefits you might expect from drugs like this?
Prevention of surgery that might otherwise be done with all its
attendant risks.

DR. HANNO: I think there\'s tremendous benefit in terms of alleviating
symptoms of BPH, actually preventing the need for surgery, postponing
the need for surgery. The improvement in the quality of life with these
drugs has been very dramatic and has really changed how we approach
outlet obstruction in the last 15 years. So I think this drug class is a
very important class of drugs, and there\'s tremendous benefit.

DR. BORER: Thank you.

Now, what was your answer to the question? Yes or no.

DR. HANNO: No.

DR. BORER: No, okay.

Peter?

DR. KOWEY: No. The answer is no, and I\'m also persuaded a good deal by
the post-marketing information we have about this particular drug.

DR. BORER: Since nobody answered yes, we don\'t have to explain how the
risk might be managed.

Six. The table below summarizes the mean change of QT from baseline,
both uncorrected and corrected, of vardenafil 10 and 80 and moxifloxacin
relative to placebo, as observed in study 10929. Are the results
observed from any one correction methodology more valid than the others?
Again, I think we\'ve sort of dealt with the fact that we don\'t know.

Mike made a comment earlier and I see there is no other place for us to
talk about this, about the list mode acquisition method, the Holter bin
method, that was set forward. Mike made a statement. I\'d like to add a
little bit to it, and if anybody disagrees, then say so.

You asked if any one correction methodology is more valid than the
others, and of course we don\'t know.

What\'s called the Holter bin method, however, as Ed Pritchett said
earlier, appears very attractive. It seems like a very logical way to
approach this problem and to try to determine what the correction really
should be or what the QT really is. Then, of course, we have to find out
what that means, but as a way of determining what the fundamental
characteristic of the QT is, subject to the limitations that Tom said
earlier, this is a very creative and innovative and interesting approach
that sounds intuitively like it should be good.

However, we have no information about the results of that analysis
relates to any outcome because this is the first time it\'s ever been
used.

So I would emphasize what Mike said earlier. I think that in future
studies where you suggest to sponsors that multiple methodologies should
be employed, because we really don\'t know which one is best or how to
relate any of them to outcome, that the sponsors should be encouraged to
apply this new method, together with all the others, because it does
seem intuitively to be good.

Blase?

DR. CARABELLO: Yes, just to amplify on Toby\'s comment. If the Holter
bin method could be applied with a patient up and active ‑‑ that is to
say, if motion artifact doesn\'t preclude its usefulness in measuring QT
when the patient is moving ‑‑ that would seem to me to be the goldest of
all standards.

DR. BORER: Having said those things, I think it\'s important at this
point to reemphasize what JoAnn said earlier, which is that if this
method is going to be applied, particularly in the way that Blase is
suggesting that Toby had suggested, with people moving around, that it
is important to be certain that we have some assessment of the impact of
all that movement on the evaluability of the complexes and what it may
mean in terms of distortion of results if a lot of complexes can\'t be
evaluated. So that still has to be worked out.

Does anybody else have any comments about that? Susanna?

DR. CUNNINGHAM: I have a question. All this discussion is all around QT
intervals, and I wonder if anyone out there is looking at anything
better or different. We\'re all fixated on it because we can measure it,
but just because we can measure it doesn\'t make it the right thing.

DR. BORER: Yes, I don\'t think that people are fixated on it because
they can measure it, but because empirically marked abnormalities in QT
have been associated with bad things. I think that there is research
ongoing that does deal with perhaps developing other ways to look both
in in vitro models and elsewhere. We don\'t have to go into that in
detail here I guess, but I think that that\'s the construct. It\'s not
that it\'s easy to measure, but that somebody measured it and it
correlates with something, qualitatively at least.

DR. CUNNINGHAM: I think that it\'s not just that it\'s easy to measure,
but I\'m still not convinced that it\'s necessarily the right measure.

DR. BORER: Not the best maybe. That\'s for sure.

Tom?

DR. PICKERING: Yes, just a comment about the Holter bin. I also think
it\'s a promising method. I think for the initial studies, though, I
would favor the approach that was used with the subjects supine because
once you have people moving about, you\'re going to have huge
standardization problems, particularly when you\'re trying to compare
the active drug and placebo because the conditions are almost certainly
not going to be the same.

DR. THROCKMORTON: Tom, this study used a single lead. Would that be a
recommendation that you\'d use?

DR. PICKERING: I\'m not the one to answer that.

DR. BORER: Paul?

DR. ARMSTRONG: Certainly 3-lead would be welcome, and the choice of
those leads might be ascertained based on surveillance of the 12-lead
electrocardiogram which would be a standard approach in some other
monitoring studies that we\'ve done.

DR. BORER: JoAnn?

DR. LINDENFELD: I was going to say I think that these studies were done
in the 12-hour daytime period, the Holter studies, and the QT interval
varies. There\'s a big circadian variation, more so I think in women
than men. Just as you explore that technology, I wonder if we don\'t
need to think about when those recordings need to be done. And if we
just look at baseline QT as a measure without a correction, that would
be very different in the nighttime than during the day. So I can\'t make
a specific comment on that, but I think it\'s just something that needs
to be thought about.

DR. BORER: Let\'s go on to B. Do these data demonstrate a clinically
relevant QT prolongation associated with vardenafil?

And for this one, we need a vote. Peter, let\'s start with you.

DR. KOWEY: Well, we could have the same discussion, but I think the
answer is probably no. The answer is no.

DR. BORER: Phil?

DR. HANNO: I would say it\'s very small, but yes.

DR. BORER: That it\'s a clinically relevant QT prolongation. If the
answer is yes, how might this risk be managed?

DR. HANNO: I don\'t think I could answer that.

DR. BORER: Tom?

DR. THROCKMORTON: Sorry. Could you go just a little bit further about
what it is about this that makes you consider it ‑‑ I\'m just interested
is all.

DR. HANNO: It\'s very similar to the moxifloxacin numbers, and
apparently there is a very minor but clinically relevant increase in
that. It\'s higher than the other drug. It\'s in the 5 to 10 range.
That\'s all.

DR. THROCKMORTON: So it is that it\'s closer to the moxifloxacin outcome
‑‑ I\'m sorry.

DR. HANNO: I\'m sorry.

DR. THROCKMORTON: I should have waved my hand. So it is that it\'s
closer to moxi? I don\'t want to put words into your mouth.

DR. HANNO: Looking at this as a urologist with a tremendous interest in
QT intervals, just based on what I have read from everything and what
I\'ve heard, this is in the range where you start to think that there
might be a problem. And I don\'t think the data is there to say for sure
that there isn\'t. That\'s all.

DR. BORER: Tom?

DR. FLEMING: This is a tough issue to resolve here. On the one hand, the
data to me look like the change in QT, QTc by various measures, is
similar to moxifloxacin. The sense I get, at least from what we
currently have put before us, is that moxifloxacin has effects on QTc
that may well, in fact, provide some level of an increased risk of major
cardiac events. Let\'s say, in fact, moxifloxacin is associated with one
in a million in risk of torsade. That, of course, may be related to a
much more frequent risk of sudden death, cardiac arrest, et cetera,
other events. We don\'t know. But on the one hand, I would look at these
data and say that certainly these results are consistent with some level
of increased risk.

On the other hand, I have to look at this as a benefit-to-risk issue and
say, what is the benefit here for a patient with ED and would
participants, in fact, accept this level of risk for the benefit that
they would derive from this? We\'ve seen data that indicated that sexual
intercourse is in fact a risk factor for increased risk of major fatal
cardiac events, and certainly these agents are correlated with an
increase in sexual intercourse. Yet, presumably people would say,
nevertheless, the benefits would outweigh that risk that they are
undertaking or accepting even if this isn\'t adding to that risk through
its proarrhythmic effects. So when I look at it in that regard, maybe if
there is some level of risk, people would, in fact, accept that in a
benefit-to-risk.

So I\'m left with real uncertainty here, and as a result my vote on this
‑‑ pardon the pun ‑‑ is I\'ll abstain.

(Laughter.)

DR. BORER: We have one abstention and maybe more.

I\'m going to vote no. I don\'t think there is a clinically relevant
risk, and I\'ll tell you why I think so.

First of all, the dose of vardenafil that\'s most likely to be used,
forgetting about the higher dose that would encompass the problems that
might occur if a metabolic inhibitor were used simultaneously contrary
to, I\'m sure, what the label would say, I think that the results with
vardenafil 10 milligrams, at least, suggest less of an effect than with
moxifloxacin. But I don\'t see moxifloxacin as having been demonstrated
as associated with important arrhythmic and event risk.

I\'m impressed with the data that Jerry Faich gave us. The torsade
events were predominantly in women, two-thirds. Now, that may be a
problem if this drug is ever going to be applied in women, but for the
moment, that\'s not what we\'re talking about. Two-thirds of the events
were in women. These were people who were hospitalized. They were sick.
They were taking other drugs. There were all kinds of things going on
here. I have a hard time relating the drug moxifloxacin to those ECG
findings. It may be related, but I think that at least in a large number
of those cases ‑‑ and it was 15 out of 20 million ‑‑ that that
relationship is not correct.

So I have less concern about moxifloxacin. I think it\'s a reasonable
positive control, and therefore, if we accept that and we accept the
reasoning that QT prolongation, at least qualitatively, is associated
with problems and this has less QT prolongation than moxifloxacin ‑‑ and
I don\'t think there\'s much of a problem with moxifloxacin ‑‑ I don\'t
think that there is a clinically relevant QT prolongation associated
with vardenafil.

And the final part of that path of reasoning is what Tom said; that is,
that you must look at benefit-to-risk relation. That people might have
events as a result of sexual intercourse is true, but that\'s a choice
that they can make. The perception is that there is an important benefit
‑‑ and I think that there are many, many studies that would support this
‑‑ to enabling sexual intercourse in patients with cardiovascular
disease particularly, because those are the patients I see, who
otherwise might be precluded from having this activity. So I think
that\'s a potentially important benefit and that the risk is, in
absolute terms, probably quite small. I don\'t know if it exists, but
quite small.

Therefore, I think that this is not a clinically relevant QT
prolongation. I answer no.

JoAnn?

DR. LINDENFELD: I agree with what Jeff said. I would answer no.

DR. BORER: Susanna?

DR. CUNNINGHAM: I think maybe I\'d vote a strong maybe. It\'s hard to
tell because we can\'t really tell. So it\'s a little less certain than
the previous one. Because it\'s closest to moxifloxacin makes it a
little more of a concern, so it\'s hard to say an absolute yes or no.

DR. BORER: I\'d like to add one thing. I know I\'m going of turn here,
but there are some perks to being the chairman.

I think that Joel made a very important point about the variability of
these results relative to moxifloxacin and the extent to which you can
interpret the difference that we saw in one study and the difference we
saw in the other study. So that they\'re in the same ball park at least
is something that I would find comforting. I wouldn\'t want to
over-interpret data like this that I\'ve never seen before and from
studies which I don\'t think have actually been done before. So that\'s
just another point.

Anyway, I\'m sorry. Go ahead. Bev?

DR. LORELL: I don\'t get to vote.

DR. BORER: I\'m sorry. Thank you, Jayne. Sorry, Bev.

Gay?

DR. BERNITSKY: I will abstain on the issue of the QT interval changes,
but having said that, I looked at this data very carefully before I came
to the meeting and the data that compared Viagra to the new drug show
almost identical QT interval changes. We have pretty good evidence here
that it\'s been used in very large populations and pretty safely. Again,
I won\'t vote, but I would say if I knew more about QT interval data, I
would probably support this drug.

DR. BORER: Paul?

DR. ARMSTRONG: No.

DR. BORER: Tom?

DR. PICKERING: No.

DR. BORER: Alan?

DR. HIRSCH: I\'m going to abstain with an explanation. We have a QT
change at this clinically relevant dose which is equal to the control.
The control is made to be a control for a reason because it is a signal
of some potential concern even though we don\'t know the actual event
rates associated with it.

And for guidance, since I don\'t have a large clinical experience or an
epidemiologic database, I went back to the FDA concept paper where I\'m
again guided by the less than 5, 5 to 10, or 10 to 20 millisecond rule.
We\'re getting close to the some concern range, but I don\'t know how to
calibrate that concern.

So not being able to calibrate the concern and then not being able to
translate that to event rates, I really can\'t answer the question,
which leads to abstain.

But I\'m going to take the chair\'s words about trusting the patient,
and I\'m going to challenge them. I think when the public looks at our
judgment of risk- benefit and there is an unknown, uncalibratable, I
believe, risk for a drug used for erectile dysfunction, I\'m not sure
that clear, rational, conscious decisions are really made vis-a-vis
concomitant medications, exposure length, et cetera. So I abstain
because I can\'t calibrate the risk.

DR. BORER: Toby?

DR. BARBEY: No.

DR. CARABELLO: No, and I would just add that there really is a
remarkable difference between the moxi data in the two studies between
table 1 and table 2. I don\'t know what that means, and I\'m sure Tom
would think of all the reasons why you couldn\'t do this. But if you
looked at the moxi data from table 1 and compared it to the QT
prolongation for vardenafil, they\'re not close. Anyway, no.

DR. BORER: Mike?

DR. ARTMAN: No.

DR. BORER: Doug, I\'d like to ask you a question here about number 7.
Both A and B ask whether you should look at QT effects in other drugs of
these classes. My intuition is that everybody is going to be in
agreement about this. May I ask that rather than go around the table and
ask for yeses and noes and stuff?

DR. THROCKMORTON: Sure. Let me give you just a little context maybe
around this as well.

One of the things that the concept paper that we heard at the meeting in
January was that if you were a member of a class that you had some
concerns about for whatever reason, and there was another member that
had an effect on QT you needed to compare yourself to, you needed in
some sense understand the relative effects there. That\'s part of where
this question is going. When do we need to understand those kinds of
things? Obviously, in this case, do we need to ask specific questions
about the other drugs in these two classes?

DR. KOWEY: Doug, are you talking about drugs that are already marketed
in this class or drugs that will be marketed in this class? Are you
talking about drugs that are already on the market?

DR. THROCKMORTON: Making no particular pre-judgment, I think we\'d
probably be interested in comments about both situations.

DR. KOWEY: I can start since it sounds like we\'re not going to do it
clockwise or counterclockwise.

The answer for marketed drugs is no, I don\'t think you should. For all
the reasons that you heard today, I think that drugs that are already
out on the market, if we\'re going to ask pharmaceutical companies to do
anything in terms of this issue, it seems to me that it should be better
pharmacovigilance looking for real events in real patients rather than
asking them to go back and look at a surrogate that we have a lot of
difficulty tying to events.

So I guess if you had the ability to ask companies to spend their
resources, I would like to see them spend their resources on two things.
One is very good pharmacovigilance, and the other is very good basic
science so that we can understand this issue better and not have to do
this anymore or maybe not so many more times. So that\'s my opinion.

DR. BORER: What about for ‑‑

DR. KOWEY: For new drugs? I think it\'s clear that for new drugs that
are brought forward, new chemical entities that are brought forward, I
think it\'s fairly clear that this needs to be done.

I have a difficult time generalizing to say that if it\'s a drug in the
same class, that you don\'t because when you say a drug is in the same
class, obviously there can be other pharmacological effects that you
can\'t ‑‑

DR. THROCKMORTON: Very broad. I agree.

DR. KOWEY: Yes. So I\'m a little concerned with saying carte blanche we
don\'t need to do this anymore within this particular class of drugs. I
don\'t think that\'s appropriate. I think it should be taken on a
drug-by-drug basis that you guys have to look at the compound and decide
whether you think that information.

Clearly for new chemical entities, I think this is the standard. And
it\'s also very important ‑‑ and I think it\'s been said likely several
times today ‑‑ but the bar has been raised clearly by the DIA discussion
and now today by these data that are presented in that we should expect
now to see this kind of precision in measurements of QT interval for new
chemical entities. I think it clearly will become the standard way
you\'re going to look at things.

DR. BORER: Paul?

DR. ARMSTRONG: Mr. Chairman, I\'m struck, before we conclude, that the
agency has not asked us about the possibility that the two drugs under
discussion today would be used together, both of which have an effect
that potentially affects the QT. I don\'t know whether this discussion
should be entertained or not, but I wouldn\'t want to leave the table
without raising the fact that the juxtaposition of these two was surely
not by coincidence, and we\'re talking about two medicines which might
well be used in men who are aging for two different reasons. Is that a
question that we should be entertaining, discussing, or is that a
brandy/cigar discussion?

(Laughter.)

DR. THROCKMORTON: Well, I\'m not sure that the two specific drugs ‑‑
we\'d need to discuss whether these particular two drugs would need to
have a formal study. We know very little about the consequences of
concomitant use of two drugs that affect repolarization by however you
measure it. I can think of maybe two studies, one of which I think is an
abstract. Dan, correct me if I\'m wrong. So we know next to nothing
about even the consequences of that concomitant use on this biomarker,
far less whether that adds additional risk or anything like that. You
can make lots of models about any which way you want to.

So when we should ask for that information is a good question. We\'ve
not gotten it even enough to know whether it\'s a concern under, I
believe, any circumstance. Dan, correct me.

DR. KOWEY: Doug, I just wanted to ask you a question, and that is,
hearing what you heard today, what do you think that you\'ll have in the
label for these drugs? Will these drugs be labeled that they should not
be given with other QT-prolonging drugs, or that you need to be careful
about potassium and magnesium? Or what\'s it going to be?

DR. THROCKMORTON: I wouldn\'t want to comment on the labeling of these.
It would not be my decision, and so I\'m not sure that that would be
appropriate.

You could think of moxifloxacin. You might look at the moxi label and
say that\'s a place where we\'ve described the effect on repolarization
and suggested potential pathways to risk management. I don\'t remember
that label well enough to say that I\'m using specific language there.
That might be a path forward. Again, it\'s not my label.

DR. KOWEY: I wasn\'t trying to get you to tell us what the wording was
going to look like, but there clearly is a decision to make. We were
voting on a question that none of us are very comfortable with that said
\"clinically relevant\" or \"clinically significant\" QT prolongation.
And we all voted no. But I think that\'s different from saying that
there isn\'t an effect on repolarization. There is an effect on
repolarization. It just looks like it\'s pretty weak.

I guess then the question is if you believe that, which I believe, what
do you need to tell doctors about the drug? Is it adequate to just
describe what the studies showed or does there have to be more than
that?

DR. THROCKMORTON: Why don\'t you make a suggestion? We\'d be very
interested in hearing your ‑‑

DR. KOWEY: I\'ll start off by making the suggestion that I think it
would be worthwhile to have in the labeling some comment about the fact
that we don\'t know ‑‑ and you said this a few minutes ago. We simply
don\'t know what would happen ‑‑ and this relates to Paul\'s question ‑‑
if you were to put another QT-prolonging drug on top of one another,
whether it\'s these two or others. I think, therefore, in the labeling
it is reasonable to tell doctors that, to tell them exactly the fact
that we don\'t know what the liability of that combination or any of
those combinations would be.

DR. RODEN: Can I just extend that just a little bit? I realize that
maybe my time for saying anything is gone, but we\'re in open discussion
now.

There is one very provocative dog study that suggests that if you use
the appropriate two IKr blockers, you can actually get one to reverse
the action potential prolonging effects of the other. So I think that\'s
a very open question and needs some more basic science.

I\'ll extend what Peter said, though. So I would include something about
using two drugs, both of which prolong the QT. And I\'d extend it to the
idea that there are patients out there who have other conditions that
may predispose them. So not just a drug plus another drug, but a drug
plus bad heart failure, plus severe LVH. Those are the risk factors,
plus a lot of diuretics, plus a history of hypokalemia.

I don\'t think you want to go so far as to say every patient who gets
these drugs needs to have a baseline electrocardiogram. I think that\'s
sort of making you feel better but it\'s probably not going to
accomplish anything. But I think that if you can get clinicians to
identify people who are at very high risk and just avoid them or think
twice about them, that\'s probably as good as you\'re going to get right
now. Off the top of my head.

DR. BORER: Doug, I want to bring closure to question 7 here. I think
you\'ve heard everything. But you\'re asking a question and I want to
make a proposition and we\'ll ‑‑ oh, I\'m sorry, very sorry. Wrong
questioner. Well, in any event, a question has been asked.

The issue is, do the QT prolongation results from these data that we\'ve
seen warrant study of QT effects of other drugs in these classes? I
think we\'ve heard a proposition that that isn\'t the right question,
that in fact preclinical data are not dispositive, and therefore some
clinical data have to be available. And that means study of QT effects
of other drugs. You haven\'t said how, just should you do it.

In the briefing document and the position paper or whatever paper it
was, there\'s an algorithm provided that involves study in phase I in
normal volunteers and then some action or no need for action depending
upon the results.

If in fact we really can\'t draw firm conclusions or inferences from
preclinical data, then I think the class of drugs is not relevant. The
fact that a new molecular entity with multiple pharmacological effects,
some of which we may know and some we don\'t know, is being studied may
be sufficient to warrant obtaining some clinical data. Now, I\'m not
going to say what kind of clinical data, how extensive the studies have
to be.

But I would propose, from what we\'ve heard here, it\'s important to get
some data about QT prolongation in patients when a new molecular entity
is being developed. And that goes beyond the issue of these two classes
or the classes, if we can define those, of which these drugs are a part.
So I would suggest that as a proposition.

If there\'s anybody who disagrees with that, now is the time to say so.

DR. KOWEY: Jeff, I think you said it very, very well. We haven\'t really
spent a lot of time today talking about preclinical signals, but in the
pre-guidance document, if you will, there clearly is a diagram that
talks about what Jeff just said, which is trying to understand early on
in the life of a new chemical entity what the liability is. And I think
preclinical studies actually help you a good deal in making these kinds
of decisions about what you need to do early on in clinical development.
So all those things I think are very important and should guide you in
making these decisions about what kind of an onus you\'re going to put
on a drug company that\'s bringing forward a new chemical entity.

DR. BORER: Dr. Griebel, we have you to thank for convening us today.
Have you received the results that you need?

DR. GRIEBEL: Yes, we appreciate everything we\'ve heard today. It\'s
been very helpful. Thank you.

DR. BORER: Then I will close the session and make two post-closure
announcements immediately.

Number one is that tomorrow morning there\'s a closed session that will
be held in the Chesapeake Room at 8 o\'clock not to consider specific
NDAs.

The second announcement is that if anyone on the committee is interested
in having dinner tonight, we\'re going to try to get together at 6
o\'clock in the lobby at Crisfield\'s to celebrate the departure of our
departing members.

(Whereupon, at 5:05 p.m., the committee was recessed, to reconvene in
closed session at 8:00 a.m., Friday, May 30, 2003.)