1

DEPARTMENT OF HEALTH AND HUMAN SERVICES

FOOD AND DRUG ADMINISTRATION

CENTER FOR DRUG EVALUATION AND RESEARCH

ARTHRITIS ADVISORY COMMITTEE

Tuesday, July 30, 2002

8:00 a.m.

Holiday Inn Bethesda

Versailles I and II

8120 Wisconsin Avenue

Bethesda, Maryland

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PARTICIPANTS

Gary S. Firestein, M.D., Chairman

Kathleen Reedy, R.D.H., M.S., Executive Secretary

MEMBERS

Jennifer Anderson, Ph.D.

Kenneth D. Brandt, M.D.

Leigh F. Callahan, Ph.D.

John J. Cush, M.D.

Ildy M. Katona, M.D., CAPT, MC, USN

Susan M. Manzi, M.D.

Wendy W. McBrair, R.N., M.S., C.H.E.S.

Yvonne S. Sherrer, M.D.

GUESTS

ARTHRITIS ADVISORY COMMITTEE

Steven B. Abramson, M.D.

Raymond A. Dionne, D.D.S., Ph.D.

Janet D. Elashoff, Ph.D.

Clifford J. Woolf, M.D.

ANESTHETIC AND LIFE SUPPORT ADVISORY COMMITTEE

Michael Ashburn, M.D., M.P.H.

Nathaniel P. Katz, M.D.

Mitchell B. Max, M.D.

NONPRESCRIPTION DRUGS ADVISORY COMMITTEE

Alastair Wood, M.D.

INDUSTRY REPRESENTATIVE

Charles H. McLeskey, M.D.

GUESTS

David Borenstein, M.D.

John T. Farrar, M.D. MSCE

Vibeke Strand, M.D.

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C O N T E N T S

PAGE

Call to Order and Introductions,

Gary S. Firestein, M.D. 4

Meeting Statement,

Kathleen Reedy 6

Welcome,

Lee S. Simon, M.D. 9

Comments, Charge,

Lawrence Goldkind, M.D. 10

ABC Metrics of Acute Pain,

James Witter, M.D., Ph.D. 11

Estimates of Dosing Intervals,

Lawrence Goldkind, M.D. 28

Edward D. Bashaw, Ph.D. 30

Lawrence Goldkind, M.D. 41

Safety Databases for Acute Analgesics,

Lourdes Villalba, M.D. 59

Discussion Points #1, 2, 3 77

Open Public Hearing:

Eugene Laska, Ph.D. 113

Nijab Babul, Pharm. D. 125

Further Discussion of Proposal for Criteria to

Obtain a Chronic Global Pain Indication 132

Responder Index, a Model,

Vibeke Strand, M.D. 174

Discussion Point #4 208

Summary,

Lee S. Simon, M.D. 230

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1 P R O C E E D I N G S

2 Call to Order and Introductions

3 DR. FIRESTEIN: Good morning, and welcome

4 to the second day of the Arthritis Advisory

5 Committee meeting. I am Gary Firestein still. I

6 think because there may be some people here today

7 that were not here before we can just go around the

8 room again quickly with introductions since this

9 represents a separate meeting. Then, we can have

10 the meeting statement from Kathleen Reedy. Again,

11 I am Gary Firestein.

12 DR. SHERRER: I am Yvonne Sherrer,

13 rheumatologist.

14 DR. CUSH: Jack Cush, rheumatologist,

15 Presbyterian Hospital, Dallas.

16 DR. CALLAHAN: Leigh Callahan,

17 epidemiologist, University of North Carolina,

18 Chapel Hill.

19 DR. WOOD: Alastair Wood, Vanderbilt.

20 MS. MCBRAIR: Wendy McBrair, nurse and

21 health educator, consumer representative, with

22 Virtua Health in New Jersey.

23 DR. WOOLF: Clifford Woolf, Harvard

24 Medical School and Massachusetts General Hospital.

25 DR. DIONNE: I must have said something

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1 offensive yesterday because they took my mike

2 away\--

3 \[Laughter\]

4 \--but I am Ray Dionne. I am a clinical

5 pharmacologist, from NIDCR.

6 DR. WITTER: Jim Witter, from FDA.

7 DR. GOLDKIND: Larry Goldkind, FDA.

8 DR. SIMON: Lee Simon, Division Director

9 550, FDA.

10 DR. MCLESKEY: Charlie McLeskey, from

11 Abbott Labs, and serving as the industry

12 representative.

13 DR. STRAND: Vibeke Strand,

14 rheumatologist. I teach at Stanford and I am a

15 consultant.

16 DR. BORENSTEIN: David Borenstein,

17 rheumatologist, clinical professor, George

18 Washington University.

19 DR. FARRAR: John Farrar, neurologist,

20 Instant Pain Management at the University of

21 Pennsylvania.

22 DR. ELASHOFF: Janet Elashoff,

23 biostatistics, Cedars-Sinai and UCLA.

24 DR. ASHBURN: Michael Ashburn,

25 anesthesiologist, University of Utah, Pain

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1 Management Center.

2 DR. ANDERSON: Jennifer Anderson,

3 statistician, Boston University Medical Center.

4 DR. KATZ: Nathaniel Katz. I am a

5 neurologist from Boston.

6 DR. MANZI: Susan Manzi, rheumatologist,

7 University of Pittsburgh.

8 DR. ABRAMSON: Steve Abramson,

9 rheumatologist, NYU Hospital for Joint Diseases.

10 DR. KATONA: Ildy Katona, pediatric

11 rheumatologist from the Uniformed Services

12 University.

13 DR. BRANDT: Ken Brandt, rheumatologist,

14 Indiana University.

15 MS. REEDY: Kathleen Reedy, Food and Drug

16 Administration.

17 Meeting Statement

18 And, this is the meeting statement for the

19 Arthritis Advisory Committee meeting of July 29th

20 and 30th, 2002. It is the same one; you can sing

21 along if you like.

22 The following announcement addresses the

23 issue of conflict of interest with respect to this

24 meeting and is made a part of the record to

25 preclude even the appearance of such at this

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1 meeting.

2 The Food and Drug Administration has

3 approved general matters waivers for the following

4 special government employees which permits them to

5 participate in today\'s discussions: Gary

6 Firestein, Kenneth Brandt, Ildy Katona, Yvonne

7 Sherrer, Susan Manzi, Jennifer Anderson, John Cush,

8 Alastair Wood, Nathaniel Katz, Michael Ashburn,

9 Janet Elashoff, Mitchell Max, Raymond Dionne,

10 Steven Abramson.

11 A copy of the waiver statements may be

12 obtained by submitting a written request to the

13 agency\'s Freedom of Information Office, Room 12A-30

14 of the Parklawn Building.

15 In addition, Leigh Callahan, Frank

16 Davidoff and Wendy McBrair do not have any current

17 financial interests in pharmaceutical companies,

18 therefore, they do not require a waiver to

19 participate in today\'s discussions.

20 We would like to note for the record that

21 Ms. McBrair\'s employer\'s interests in two drug

22 companies are exempt under 2640.203(g).

23 The topics of today\'s meeting are issues

24 of broad applicability. Unlike issues before a

25 committee in which a particular product is

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1 discussed, issues of broad applicability involve

2 many industrial sponsors and academic institutions.

3 The committee participants have been

4 screened for their financial interests as they may

5 apply to the general topics at hand. Because

6 general topics impact so many institutions, it is

7 not prudent to recite all potential conflicts of

8 interest as they apply to each member, consultant

9 and guest.

10 FDA acknowledges that there may be

11 potential conflicts of interest, but because of the

12 general nature of the discussion before the

13 committee these potential conflicts are mitigated.

14 We will also like to note that Dr. Charles

15 McLeskey is participating in today\'s meeting as a

16 non-voting industry representative. As such, he

17 has not been screened for conflicts of interest.

18 In the event that the discussions involve

19 any other products or firms not already on the

20 agenda for which FDA participants have a financial

21 interest, the participants\' involvement and their

22 exclusion will be noted for the record.

23 With respect to all other participants, we

24 ask in the interest of fairness that they address

25 any current or previous financial involvement with

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1 any firm whose product they wish to comment upon.

2 DR. FIRESTEIN: Thank you very much. Now

3 Lee Simon will welcome everybody again.

4 Welcome

5 DR. SIMON: I think that yesterday was an

6 intriguing day for the committee members and I

7 think certainly for us, over here at the agency.

8 Again, I would like to thank you all for making the

9 effort to come and participate even for the second

10 day. I am even more impressed\--everybody is still

11 here and suffering through the heat wave we are

12 having, although I am told it is not so much the

13 heat wave; it is the expectation of Washington.

14 I would like to make mention of two

15 things. One is that, again, this is a combination

16 committee from 170, OTC and the Arthritis

17 Committee. So, there are members from everywhere

18 and I think it is very important for us to have a

19 mixture of people commenting on these particular

20 issues.

21 Secondly, as we had a meeting with the NIH

22 and the FDA in March, we are proposing to have

23 another meeting in some months on the issue of

24 function, healthful quality of life and outcomes in

25 pain, both acute and chronic. Ray Dionne and Jim

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1 Witter are planning to apprise the wonderful

2 experience we had previously, and I have been

3 advised to inform everyone here in the audience of

4 that. In fact, for the companies\' benefits, the

5 sponsors\' benefits, this meeting will include your

6 participation so that we can truly get opinions

7 from all aspects of interest in this particular

8 field. So, look forward to receiving invitations

9 for this particular upcoming meeting sometime this

10 winter.

11 Back to you, Gary.

12 DR. FIRESTEIN: Thank you. There will be

13 some comments and discussion of our charge from Dr.

14 Goldkind.

15 Comments, Charge

16 DR. GOLDKIND: Thank you. Again, I want

17 to thank the committee members for taking time out

18 of their schedules to spend two days with us.

19 Yesterday we dealt with a lot of

20 conceptual issues primarily related to chronic

21 pain. While there wasn\'t unanimity and closure on

22 every point, the discussion we had was very helpful

23 and, hopefully, enlightening for you as well.

24 Today we will be shifting a little bit and talking

25 primarily about acute pain, probably a little more

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1 detailed in terms of study design and analysis, and

2 we look forward to another fruitful and stimulating

3 day.

4 DR. FIRESTEIN: Thank you. In addition,

5 at some point during the day, probably during the

6 10:45 to 11:45 block, Lee has asked us to revisit

7 some of the issues from yesterday strictly with

8 regard to global pain indications, and we are going

9 to end up going around the table and soliciting

10 two-minute opinions. That goes for everybody,

11 two-minute opinions on the two questions of how

12 many indications might be required and how many

13 domains do you think would be important. So, we

14 will come back to that a little bit later on this

15 morning.

16 The first speaker today is Jim Witter, who

17 is going to talk about ABC metrics for acute pain.

18 ABC Metrics for Acute Pain

19 DR. WITTER: Good morning. Kathleen, I

20 was looking for the bouncing ball before so I could

21 follow you!

22 \[Slide\]

23 As Larry said, we are going to have a

24 little bit of a shift today and we will start off

25 talking about acute pain and, hopefully, go from

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1 there. But we will be transitioning eventually

2 back to chronic pain by the time the day is over.

3 \[Slide\]

4 In terms of acute pain, the argument I

5 guess could go that what we need to do is to be as

6 informative\--again, we are discussing labels so we

7 want to be as informative as possible about the

8 information that goes into the label for something

9 to treat acute pain. We had a discussion yesterday

10 about acute pain versus treatment in an acute

11 situation.

12 But what we have I think are really two

13 scenarios. We have an outpatient setting and an

14 inpatient setting where we might find ourselves in

15 need of acute analgesics. For example, for

16 outpatient settings, most of us have experienced I

17 think minor injuries, such as a sports injury.

18 Some of us have experienced dysmenorrhea.

19 Hopefully, fewer of us have had a major injury such

20 as a motor vehicle accident. Then, some of us

21 actually volunteer to have surgery. Now, the

22 analgesics that are applied in these situations are

23 for the most part oral, not exclusively but mostly.

24 On the other hand, in an inpatient setting

25 we again are looking at surgical settings and these

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1 are of the non-elective and the elective type.

2 What I have indicated here by the stars are some of

3 the models or some of the clinical situations in

4 which drugs have been studied and ultimately have

5 been approved so this isn\'t that we are taking a

6 major change of course here.

7 \[Slide\]

8 I would like to take a second and talk

9 about the analgesic box. Some people would call it

10 the analgesic black box. What I have tried to

11 depict here is a pain relief curve. There is some

12 event over here that causes one to have pain and

13 you take a drug and, at some point in time then

14 there is this concept known as onset of relief.

15 The pain relief continues and goes to a certain

16 amount. This has been described in the old 1992

17 guidance document and in the EMA document as the

18 peak. We talked about it yesterday as the pain

19 curve, the whole thing, and today I am now calling

20 this the effect size. So, this pain relief goes up

21 and lasts for a period of time and then it ends.

22 We should be able to, particularly in a

23 single-dose experience, really define these

24 parameters of onset\-- what I am calling here effect

25 size, and duration quite accurately if we do our

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1 homework.

2 \[Slide\]

3 For acute pain the needs are to look at

4 these concepts of the onset of meaningful pain

5 relief, its duration, the effect size and we should

6 establish these then in circumstances of acute

7 inpatient and outpatient settings.

8 \[Slide\]

9 That leads us then to what we have termed

10 the ABC\'s of acute pain metrics, that, in fact, you

11 may not be able to accomplish all of these tasks in

12 one trial and you may need to break this up. So,

13 that is what we have done.

14 The A component is really getting at the

15 concept of onset of meaningful pain relief. What

16 we need to do is, to the best of our ability,

17 establish this time very accurately. This onset

18 should occur more frequently in drug versus placebo

19 patients. It should be established in a variety of

20 outpatient and inpatient settings, as I have

21 described. And, this is really the single-dose

22 experience.

23 \[Slide\]

24 I have depicted here a pain by time curve,

25 a little bit different than the other presentation,

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1 the other slide. We have pain intensity which is

2 decreasing in a general sense. I have depicted two

3 patients here, patient 1 and patient 2 and at some

4 point along this curve these patients will let us

5 know that they have established the onset of

6 meaningful pain relief.

7 This is something that is not necessarily

8 the same for everybody. So, I think what we need

9 to do is make sure that while we are measuring pain

10 intensity we also, particularly in the beginning,

11 are measuring pain relief so we know how these two

12 correlated because this is really a patient-derived

13 outcome.

14 \[Slide\]

15 If we take an individual responder

16 approach to this situation and this would seem to

17 make sense\--process analytical technology for an

18 analgesic and for pain because pain is such an

19 individual experience. So, the individual

20 responder approach then focuses on a single person,

21 not the group. It allows efficacy assessment to be

22 very individualized, which we will be talking about

23 later as well. It has the potential of eliminating

24 imputation. We talked yesterday about forward

25 filing of diaries. Michael Hufford talked to us

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1 about that, and we all thought that was almost

2 comical. We heard from Dr. Lu about last

3 observation carried forward and other metrics to

4 complete data. But if we can eliminate this, I

5 think we all agree it would be better.

6 \[Slide\]

7 An individual response then for acute pain

8 in terms of onset and duration for a single dose\--I

9 think the argument could be made that pain

10 intensity should be measured throughout the entire

11 trial. This includes not only the beginning but

12 also at the end, when a patient either rescues or

13 is censored, so we understand what is going on

14 throughout the trial. Pain relief probably should

15 be measured at least early to establish meaningful

16 pain relief. If we do this properly, we should be

17 able to really capture 100 percent of information

18 on the patient\'s response to the analgesic,

19 particularly during the single-dose experience.

20 \[Slide\]

21 What I have tried to do here is give us

22 some idea of what I guess might be meant by the

23 effect size. I have drawn some theoretical lines

24 here. This says threshold; this says complete

25 response. What I have depicted is the placebo drug

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1 which crosses this threshold and goes to a certain

2 point. We then have a drug which crosses the same

3 threshold but goes beyond where the placebo

4 response was and ends here. This is the concept of

5 complete pain relief which is not happening,

6 obviously, in this case.

7 But can we say then that the difference

8 between the two blue lines here is really what we

9 mean by the effect size? In fact, the difference

10 between this line and this line is what we mean by

11 that concept of a minimally clinically important

12 difference. This is what we are searching for

13 really because that is the difference from placebo.

14 Can we, in fact, then really quantitate this

15 response in a meaningful way?

16 \[Slide\]

17 The B of the ABC really refers to

18 duration. What it is attempting to do in these

19 series of studies would be to define the dosing

20 interval, again, based on clinical data once more

21 from outpatient and inpatient settings. So, here

22 we are talking about the day 1 experience but it is

23 the multiple-dose experience on day 1 if that is

24 applicable for this particular drug.

25 We would then need to factor into these

18

1 metrics the concept of rescue in an outpatient

2 setting or the use of concomitant medication such

3 as opioids in an inpatient setting.

4 \[Slide\]

5 The C component is really meant to give us

6 an idea of the minimally effective dose, and that

7 is important because, you recall, yesterday one of

8 the things that we discussed was our concern about

9 carrying forward with analgesics, particularly

10 analgesics studied in an acute setting, where the

11 doses may be different than the doses that are

12 carried forward in a more chronic setting.

13 If we have compounds which are not always

14 going to be applicable and utilized, for example

15 something like NSAIDs which we know are going to be

16 used for the most part for something like OA, but,

17 if we have medicines that have a very narrow

18 therapeutic window but are really intended for an

19 acute setting, we want to be sure that if they are

20 used in what really would be off-label use that we

21 have the lowest effective dose to be used in that

22 situation. So, that is what the C portion of the

23 studies are really intended to do.

24 Again, this is not intended to really

25 inform chronic use. If there is a reason that

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1 these compounds can be used in a chronic setting,

2 we would encourage sponsors to do those studies and

3 go for the indication. Again, establishing this in

4 two settings, outpatient and inpatient, and this is

5 a multiple dose over several days and the metrics

6 may need to change in the sense of what we are

7 interested in, as Dr. Lu had talked about

8 yesterday, the area under the curve versus the

9 onset peak duration mentality.

10 Once again, we are trying to establish the

11 safety and efficacy here and we begin on day 2.

12 So, day 1 in this particular series of studies is a

13 time frame where we wouldn\'t have to be looking at

14 any components of efficacy. These patients could

15 take basically anything that they wanted. The

16 randomization would then begin on day 2. So, what

17 we are most interested in is from day 2, day 3 and

18 on.

19 \[Slide\]

20 Acute pain has special issues with it,

21 some of which we talked about yesterday. Pain is

22 not equal in intensity or duration in various

23 settings. For example, the pain after a dental

24 extraction is not necessarily the same as after

25 having bypass surgery, although maybe Leigh might

20

1 disagree. Pain does tend to improve with time.

2 That is something we discussed yesterday. We will

3 hear more today from Dr. Bashaw, but PK estimates

4 in clinical results may really describe different

5 aspects of pain relief in that PK may be more

6 informative about early onset, for example, and may

7 also then inform us about safety later. What I

8 mean here is that if we have a compound that

9 supposedly has a short half-life but in fact hangs

10 around, for whatever reason, for days, and days,

11 and days and has a very narrow therapeutic window,

12 if the pain scores suggest that needs to be dosed

13 more than once day we may have an issue of

14 toxicity. In fact, we are faced with such issues.

15 \[Slide\]

16 So, the label in an acute pain setting

17 should be as informative as possible and should

18 contain information regarding onset, duration and

19 minimally effective dose from two clinical

20 settings, outpatient and inpatient.

21 \[Slide\]

22 If we cast in stone, so to speak, these

23 concepts of acute and chronic, and if this were a

24 river of pain I guess we are concerned about the

25 bridging that needs to be done here because it may

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1 be a time, as has been argued, that there is a

2 transition from acute to chronic, wind up,

3 plasticity, those types of issues. So, we should

4 be paying attention to this interval between here

5 and not lose sight of it.

6 If studies are conducted properly we may

7 be able to support meaningful labeling claims for

8 safety. We may, in fact, be able to get something

9 for chronic pain if the studies would be supportive

10 to push in that area, and we would encourage that

11 if it makes sense. Or, this may also be

12 informative for mechanistic claims that we talked

13 about yesterday. So, it may be that this is the

14 perfect time to be studying for some of these

15 mechanistic claims, this time interval.

16 \[Slide\]

17 Why all the concern? Why don\'t we just

18 leave things the way they are? Things have been

19 working okay. Here is a drug that is in the PDR.

20 I have given it the designation of X just to

21 anonymize it a bit. This is the clinical study

22 section. This is the entire section. It says: \"In

23 single-dose studies of post surgical pain

24 (abdominal, gynecological, orthopedic) 940 patients

25 were studied at doses of one or two tablets. Drug

22

1 X produced greater efficacy than placebo\" and I

2 have left out a few words here just to try to

3 maintain the blind, \"no advantage was demonstrated

4 for the two-tablet dose.\" So, this looks like one

5 tablet is pretty effective.

6 \[Slide\]

7 Elsewhere in the label, under dosing and

8 administration, it says that this is \"indicated for

9 the short-term (generally less than 10 days)

10 management of acute pain.\"

11 \[Slide\]

12 \"The recommended dose of drug X is one

13 tablet every 4 to 6 hours, as necessary. Dosage

14 should not exceed 5 tablets in a 24-hour period.\"

15 The question is how did the clinical

16 trials inform this dosage and administration

17 scheme? There seems to be a gap here. This is an

18 approved compound.

19 \[Slide\]

20 Could we make the case then that some of

21 the ideal characteristics for a pain metric in this

22 situation should be that it should be easy and

23 understandable to patients and clinicians in the

24 labeling and in clinical trials. It should be

25 applicable across studies to facilitate IND

23

1 development and eventual NDA approval. It should

2 define a clinically meaningful result so that it is

3 a useful addition to our pain armamentarium. It

4 should be valid in a variety of pain conditions,

5 and it should be achievable with current meds, but

6 also we need to think about having some kind of a

7 tiered structure, which we have been talking about,

8 so that we can really define and acknowledge

9 important differences in drugs as they are

10 developed.

11 \[Slide\]

12 Taking a responder analysis plan into a

13 pain setting, it has the potential to characterize

14 pain, as I have said, at an individual level in

15 both acute and chronic situations, and Dr. Strand

16 will be talking about the chronic situation later.

17 This may then be useful to allow a

18 comparison of relative efficacy. This is against

19 placebo or standard of care, not between drugs, in

20 clinical trials in acute pain and in chronic pain.

21 \[Slide\]

22 If the hypothesis is correct, if it is

23 properly constructed and validated, a responder

24 analysis could be a major advance in clinical

25 analgesia because it is currently not used. Later

24

1 we will be having more discussion about the concept

2 of outcomes and domains, but I will discuss them

3 here too. I think what we can say at this point is

4 that if we can come to an agreement on outcomes or

5 domains, we can do that even if we don\'t

6 necessarily have the instruments because we can

7 develop the instruments later. But if we can agree

8 on the domains, that is definitely a step forward.

9 \[Slide\]

10 Just to step back for a second and look at

11 the responder analysis that we do have in the

12 division, the ACR, American College of

13 Rheumatology, 20 responder analysis, and this is

14 for rheumatoid arthritis, and this is really in a

15 lot of ways a symptomatic responder analysis. What

16 you have then to be approved for the indication of

17 the signs and symptoms of rheumatoid arthritis, if

18 you are successful with this metric you can then be

19 approved, assuming you are safe. So, what you have

20 to do is have a 20 percent improvement in swollen

21 and tender joint counts. Those are required

22 endpoints for this particular analysis. Then you

23 can have three of the five following, a patient or

24 physician global, a pain score, a modified health

25 assessment questionnaire or some kind of an acute

25

1 phase reactant.

2 As Lee had mentioned and we talked about

3 yesterday, we had the NIH-FDA workshop back in

4 March. At that meeting we had a discussion of the

5 responder approaches and certain domains were

6 discussed. These included pain, rescue medication,

7 patient global, health-related quality of life,

8 physical function/disease specific measures,

9 economic organ damage concerns, the issue of

10 suffering which you heard about from Dr. Verburg

11 yesterday, and adverse events. These were

12 discussed as possible domains to be in some kind of

13 an analgesic responder approach.

14 \[Slide\]

15 For the discussion this morning, I have

16 whittled these down to the following that we should

17 maybe be considering if we want to take this

18 tactic, pain, concomitant medications, rescue

19 medications, patient global, health-related quality

20 of life, physical function, adverse events. Those

21 are the ones that maybe make the most sense in this

22 particular situation.

23 \[Slide\]

24 Were we to take this approach, could we

25 begin to think about fashioning a responder

26

1 analysis by looking at our studies, our A, B and C

2 type studies, and thinking through what needs to be

3 applied or characterized in those settings? For

4 example, for pain intensity the argument would be

5 that that should be in all these studies. Pain

6 relief, maybe more so in the onset and dosing

7 interval. It may not be as important in the

8 multiple-day use settings. Patient global might

9 apply in all the settings, and continuing along.

10 So, we may be able to already begin to get a sense

11 of what a responder analysis might look like in an

12 acute pain setting.

13 \[Slide\]

14 Let\'s just take a hypothetical example.

15 It might be a bit hard to see. It is an AR20/12.

16 So, AR then would imply that analgesic relief has

17 been established. With an NSAID type compound that

18 has generally been within an hour, but that time

19 frame isn\'t necessarily applicable, for example,

20 were we to develop a compound that would treat

21 neuropathic pain, something that occurs

22 sporadically like trigeminal neuralgia. That might

23 not be the right kind of a time frame but, in any

24 event, AR20 would refer to percent pain relief over

25 the standard of care/placebo, and 12 would refer to

27

1 the hours of relief.

2 \[Slide\]

3 So, let\'s take a hypothetical drug that

4 has two forms. This comes in a 100 mg and 300 mg

5 variety. This is what a future potential trial

6 session might look like and it would describe in

7 there then the A, B and C, how the onset dosing

8 interval and lowest effective dose were actually

9 established in outpatient and inpatient settings.

10 \[Slide\]

11 So, this drug at the 300 mg strength in

12 the indication section may look something like

13 this: Drug X is indicated for acute pain. It is

14 described as AR90/24 so it is a pretty potent

15 medicine; it lasts for 24 hours. See the details

16 in \"clinical trials\" and daily use should not

17 exceed five days. Again, what we are trying to

18 establish here is that in acute setting with some

19 of these medicines, they may not be able to safely

20 be used in a more chronic setting.

21 \[Slide\]

22 With the 100 mg strength of this

23 particular compound, it may look as follows. It is

24 also indicated for acute pain. Here, it is

25 described as an AR20/24, and it would say daily use

28

1 should end when the pain has resolved or can be

2 managed in another way, getting at this idea that

3 acute pain for the most part resolves.

4 \[Slide\]

5 Without further delay, I would like to

6 introduce Dr. Goldkind, who will be talking to us

7 more, along with Dr. Bashaw, about the uses of dose

8 and dosing interval. Dr. Villalba will be talking

9 about some of our experience with certain compounds

10 in the division. Dr. Strand will be giving us some

11 more thoughts about the responder analysis,

12 particularly in a chronic pain setting. Then, our

13 own Dr. Simon will wrap everything up for us later.

14 Estimates of Dosing Intervals

15 DR. GOLDKIND: Thank you, Jim. I want to

16 highlight the extent to which our discussions and

17 our talks today are really aimed at labeling

18 information. A lot of Jim\'s talk and, hopefully,

19 mine will really focus not only on minimum

20 requirements for approval but actually what kind of

21 data we should be collecting to inform the label.

22 \[Slide\]

23 I will be playing tag with Dr. Bashaw, who

24 is the team leader that is affiliated with our

25 division. He is in the Division of Pharmaceutical

29

1 Evaluation.

2 \[Slide\]

3 An ideal analgesic is one that would be

4 once a day, 100 percent effective in 100 percent of

5 patients without adverse effects. Unfortunately,

6 most drugs available today don\'t meet those

7 criteria. Most of the time we have multiple doses

8 per day that are needed in the acute setting,

9 suboptimal pain relief and dose-limiting

10 toxicities.

11 \[Slide\]

12 Therefore, the majority of patients and I

13 imagine everybody in this room as a patient, if not

14 as a prescribing physician, has been faced with

15 patients or oneself has had several critical

16 questions to ask when their pain recurs or doesn\'t

17 respond in the first place. \"What do I do till the

18 next dose? Do I change medications? Do I call and

19 get a new prescription? Do I simply redose early?

20 Do I take another drug concomitantly with unknown

21 synergy or safety concerns?\"

22 The reality is that there is no ideal dose

23 interval in our current world, but the goal is to

24 optimally characterize, particularly as I will be

25 speaking of duration of drug effect, and have that

30

1 in labeling and be sure that that is not associated

2 with toxicity that is unacceptable.

3 \[Slide\]

4 So, the question is how, in the real

5 world, do we generate dose interval instructions?

6 I will be using dose interval and dose duration

7 somewhat interchangeably. The first step in drug

8 development is pharmacokinetics and I will turn

9 this over to Dr. Bashaw.

10 DR. BASHAW: I would like to thank the

11 previous speakers, both Dr. Goldkind for the

12 introduction and Dr. Witter, for their fine

13 presentations, and also the fact that most of what

14 I am going to speak of today, the groundwork has

15 been laid yesterday in our discussions about

16 chronic pain and pain metrics.

17 For the most part, as has been talked

18 about already, PK/PD and analgesic response has

19 been primarily geared towards onset. The dental

20 pain model is certainly very good for that. As you

21 go from no pain to almost instantaneous pain very

22 quickly it is very reproducible for all those

23 factors we have talked about. But there are some

24 problems with its duration because eventually pain

25 does resolve in that model in a very short period

31

1 of time relative to most chronic pain.

2 During my presentation I am going to

3 briefly go over some data from a dental pain trial

4 as it relates to onset and dose optimization, and

5 contrast it to where we are going with chronic pain

6 and also with duration metrics. However, because

7 it is still early in the morning, or relatively

8 early in the morning, I promise I will not take you

9 through any model derivations or any model

10 simulations because that is way beyond the scope of

11 the time of the talk this morning.

12 \[Slide\]

13 As I said, we basically have very good

14 single-dose metrics looking at blood level onset

15 and pain relief. One can pretty much look at a

16 successful development of many OTC analgesics and

17 even prescription analgesics and see that we do

18 have a very good handle on onset, and the next step

19 is where do we go from there when we need a second

20 dose, and how we get from it.

21 \[Slide\]

22 This is what one typically sees. In this

23 particular case we have a dental pain trial where

24 we are comparing three different doses of a

25 nonsteroidal. Here we have what is calculated to

32

1 be a no effect dose; what was assessed to be a

2 mid-range dose; and what was expected to be an

3 antirheumatic dose but was put in the trial just to

4 see what the performance would be for a new

5 analgesic.

6 You can see this is where we would start

7 off with pharmacokinetic data, concentration versus

8 time. From this type of material one can get the

9 standard pharmacokinetic analysis of varying the

10 curve, Cmax, Tmax and those parameters which we

11 normally work with.

12 In terms of making the next step, linking

13 this to some kind of effect, analgesia being

14 duration or whatever we are looking for, one has to

15 make the next step as to how one combines this

16 information with the dynamic response.

17 \[Slide\]

18 This is one representation I have. I

19 tried to make it as simple as possible. Basically,

20 what our theory is, is that we pretty much have

21 optimized input rate. Input rate gets into the

22 blood, gets into the plasma and then we have drug

23 migrating into some effect site concentration that

24 then exercises the effect.

25 The dynamic compartment is a theoretical

33

1 compartment. We tend to draw it as a separate box

2 but in reality the effect site is subsumed within

3 the central compartment within the blood and within

4 the plasma. But for modeling purposes it is much

5 easier to have this over here because it explains

6 some of the things we see with the drug onset in

7 terms of lag time, in terms of dose response

8 issues.

9 Primarily what one needs to just remember

10 from this slide is that effect site concentrations

11 is what we are really trying to look at. However,

12 we can\'t measure them directly. We can measure

13 plasma blood levels, but we cannot measure the

14 concentrations at the effect site. These are all

15 theoretical and based on our simulations. However,

16 we do know that the rate constant, if you model it

17 this way, the Keo value, is equilibration between

18 these two compartments. It is what is going to

19 drive duration. It is what is going to drive the

20 redosing issue because it is going to control time

21 to accumulation at the effect site; time to onset;

22 and also time for levels to go back in the plasma.

23 So, that is really what we are trying to look at in

24 terms of driving this situation.

25 \[Slide\]

34

1 Here is what we normally see. Again, we

2 are taking our dental pain example. We have taken

3 our concentrations and now plotted them against a

4 dynamic effect. In this particular situation this

5 PID score and placebo are corrected. Here is our

6 no effect dose, some effect but not very much.

7 Here is our mid-range dose which is getting a PID

8 at maximum of about 1. Here is our antirheumatic

9 dose which is getting up there but there is some

10 lag time here.

11 This pretty much shows one of the problems

12 you have when you try to direct correlations

13 between concentrations and effect. You can see,

14 for example right here with the mid-range dose,

15 that we have concentrations of approximately 5

16 ng/ml and you get a PID change of only 0.2. Yet,

17 up here at 6 hours you have the same drug, same

18 dose and the same concentration but it has a PID

19 change of 1.

20 What is going on there? How can you have

21 the same concentration giving two different

22 responses? Part of that is due to the fact, again,

23 of the model. It is 6 hours in the dental pain

24 model and pain is starting to resolve. So, even

25 though your concentrations have dropped you are

35

1 seeing resolution of their pain relief because of

2 other factors, which again shows the limitations of

3 this model.

4 \[Slide\]

5 One of the things we do with this data in

6 trying to develop a relationship is we try to

7 collapse these responses. We call these hysteresis

8 loops because or their curvolinear nature. This

9 particular nonsteroidal is very typical of what you

10 see, counter-clockwise hysteresis, as one sees

11 here. This is basically due to one of three

12 reasons: There is a significant time lag between

13 drug entering the central compartment and going out

14 to the theoretical effect site. Possibly also it

15 would act on the metabolite if you were just

16 following the parent and the activity is due to the

17 metabolite. That is also going to give you a

18 disconnect which is going to result in

19 counter-clockwise hysteresis.

20 And, important for a situation with

21 nonsteroidals, it is due to the fact that we are

22 not having a direct effect here but a secondary

23 effect due to the effects of arachidonic acid.

24 Nonsteroidals, unlike opiates which work on mu

25 opioid receptors, kappa receptors, etc. and have a

36

1 direct pain activity, nonsteroidals, of course,

2 have to work through the arachidonic acid cascade

3 and that is going to cause a lag time because it

4 takes time first to use up those factors that have

5 already been formed, and then when the drug wears

6 off it takes time for the cascade to reestablish

7 itself. This also results in that disconnect

8 between concentration and effect, which is one of

9 the problems we have in modeling this data.

10 \[Slide\]

11 But if one continues on with the same

12 dental pain trial and you collapse the loops, this

13 is what you can derive. You can derive a

14 relationship, shown in this particular case using

15 an Emax model, and you can make a response between

16 dose and effect. You do see noise out here and

17 this, again, is due to the duration issues. But

18 one can see in this particular case that we do have

19 effect of concentration. There is an Emax of about

20 1.2 PID units, which is about what you are going to

21 see for maximum effect.

22 From a response like this, one could then

23 go back and look at your doses, look at your dosage

24 form and pick a dosage that would give you the

25 efficacy you want, depending on how you define it.

37

1 Once you have a PK/PD relationship, you can look

2 back and say you want to have a certain duration, a

3 time above a certain EC50 or EC75. If you want

4 what Dr. Witter was talking about, a 90 percent

5 change or 75 percent change depending on what

6 metric you are using, if you are using a quality of

7 life metric or if you are using PID scores, or

8 whatever, it is very analogous to how you go back

9 and do this and look at time above for duration.

10 These are analogous to what is done in the

11 surgical area where you use neuromuscular blockade

12 and you have a train of 4 measurements, where you

13 are looking at a pharmacological response in terms

14 of muscle blockade and you must calculate your

15 duration based on how long you want to have

16 neuromuscular blockade, and a train of 4 is a way

17 of doing it. It is very analogous to trying to

18 look at duration of action issues with analgesia,

19 except that we don\'t have as well defined a metric

20 or observation.

21 \[Slide\]

22 As I said before, one of the primary

23 reasons you have counter-clockwise hysteresis is,

24 of course, the fact that one has this cascade of

25 pro-inflammatory precursors and pro-pain precursors

38

1 that have to be used up in the modeling. The time

2 it takes up for these precursors, both to ramp up

3 in the case of the drug wearing off and to be

4 consumed and onset, is what affects our hysteresis

5 loops. It really is the modeling problem for

6 duration.

7 For onset we have very good metrics. We

8 have shown that and pretty much we have optimized

9 drug delivery to deal with the onset. But what

10 about duration? How can we deal with that in the

11 drugs that don\'t have direct response?

12 \[Slide\]

13 We can model duration of action using

14 indirect PK/PD models that allow for downstream

15 activities. However, it requires, as I think has

16 been reiterated before, an understanding of the

17 underlying physiology; an understanding of the

18 dynamics of the response; patient factors; and does

19 require a large number of PK and PD observations

20 across a number of doses.

21 With this kind of information together,

22 understanding exactly whether or not it is, as Jim

23 pointed out this morning, moderate or severe pain

24 from a dental pain trial or from coronary-artery

25 bypass graft pain, you have to understand the

39

1 underlying physiology of the pain. You have to

2 understand the dynamics of response of the patient

3 factors and how the patients are going to perceive

4 their pain; how they are going to relate it back to

5 you in terms of its intensity or their degree of

6 pain relief. Then, from a calculational

7 standpoint, you do have to have a large number of

8 observations, both PK and PD, so that you can make

9 predictions across a number of doses.

10 \[Slide\]

11 What one can get from an analysis such as

12 this\--this is some simulated data we worked on for

13 an intravenous analgesic and what basically one can

14 do when one has enough data. This is the

15 probability of obtaining a certain PID score over

16 time for a certain dose of the drug. You can do

17 this for many different doses. What we see here is

18 that if you are looking for a PID change of 1, we

19 have a very good onset and we have maintenance of

20 that PID score for at least an hour and a half.

21 Right there is the last observation in this trial.

22 For this trial, here, the probability of a PID

23 score of 2 is about 0.5 and then it starts dropping

24 off when you start getting out to 40, 45 minutes.

25 PID score 3 is really not going to happen here.

40

1 But using simulations, using PK/PD and

2 understanding the models one can, using indirect

3 modeling, develop probabilities using a Monte Carlo

4 simulation that can then be related back to

5 duration of effect and the maintenance of effect

6 over time. If one has enough data\-- this is

7 obviously for one particular dose level\--one can

8 take multiple doses, plot together and actually do

9 three-dimensional response surface mapping and look

10 at the effect of various factors, concentration,

11 effect, time, duration, etc. and decide what is an

12 optimal dose that can then be tested in clinical

13 trials.

14 \[Slide\]

15 Before I hand it back to Dr. Goldkind,

16 from a pharmacokinetic standpoint looking at

17 exposure response analysis, you know, with opiates,

18 because of their mechanism of action where they

19 have direct binding to receptors, we have good

20 assessments of onset and we can do pretty good work

21 with duration because it is a direct receptor

22 interaction situation. With nonsteroidals, the

23 mechanism of action being indirect and they don\'t

24 actually have pain relief themselves but work

25 through other mediators, through a cascade effect,

41

1 we certainly can do onset. We have actually done a

2 lot of work over the last couple of years

3 optimizing drug delivery for onset.

4 Duration is more problematical, as we have

5 said this morning. It is model dependent. It

6 requires an understanding of the physiology. It

7 requires an understanding and identification of

8 relevant patient factors. Also, it requires

9 certainly a good amount of data to work with

10 because if you don\'t have the data your simulations

11 and your work just won\'t have the power you want to

12 have to make proper dosing selections.

13 With that, I will turn it back over to Dr.

14 Goldkind.

15 DR. GOLDKIND: Thank you.

16 \[Slide\]

17 We now know that PK can take us so far in

18 assessing dose duration, but only so far and the

19 question is how do we add to that with clinical

20 data? I will be talking about the endpoints that

21 are used in adding value to PK data in assessing a

22 dosing interval.

23 First I would like to go through the

24 guidance that we have, both from the FDA as well as

25 from EMEA. The 1992 guidance, in the section that

42

1 does deal with metrics for assessing the duration

2 of analgesia, and I quote directly: Similar onset

3 of analgesia, there are various approaches to

4 defining the duration of analgesia. Examples

5 include from the onset of study drug or the onset

6 of analgesia until either intensity of pain returns

7 to baseline; the patient indicates that analgesic

8 effect is vanishing, which are similar; patient

9 requests rescue, and the time to rescue is

10 sometimes designated as TTR, can either be measured

11 in the mean or the median; and the percent of

12 patients who do not rescue during the specific

13 interval. You can look at the converse, the number

14 that do and the specific interval can be over a

15 longer period than you anticipate a dose interval,

16 or the dose interval you anticipate and end the

17 study at that point.

18 \[Slide\]

19 The European Medicines Evaluation Agency\'s

20 draft guidelines from 2001 state that a real effort

21 should be made to obtain data on the best dose and

22 interval regimen, time to onset of peak effect and

23 duration of effect. The endpoints that are

24 referenced a little bit further on in that document

25 refer to duration of analgesia, which isn\'t a

43

1 metric per se but just reiterates that that issue

2 needs to be dealt with, and time to rescue is

3 mentioned as a metric.

4 \[Slide\]

5 I would like to go through the different

6 metrics now and discuss them. The return to

7 baseline pain metric, I believe, is a flawed one.

8 \[Slide\]

9 This graph, which is taken from real data

10 but the specific drugs are not relevant, is a good

11 example and reflective of what we see in I would

12 say most curves for analgesics. The top two lines

13 are both active drugs and the lower curve is

14 placebo. As we all know, there is a substantial

15 placebo effect. There is an onset for placebo as

16 well as the active drugs. But what you see as you

17 go out is that pain relief is pretty much steady

18 going all the way out to 12 hours. Interestingly,

19 the placebo response drops a little bit but nothing

20 comes down to baseline. That is not uncommon in

21 the studies that we see.

22 \[Slide\]

23 As Dr. Bashaw mentioned, acute pain

24 resolves and that is just part of the model. So,

25 you really rarely get a true return to baseline in

44

1 these studies. Therefore, this metric would give

2 you a bias, extending the apparent dosing interval,

3 if we were to use a return to baseline. In

4 addition, during acute pain studies you typically

5 have repeated questioning every 15 minutes, half

6 hour, for the first short interval, and then every

7 hour after going out variable periods of time. So,

8 it is actually quite an artificial setting to

9 collect data to begin with. I would imagine that

10 as you ask patients what pain relief they have now

11 compared to one hour ago, compared to two, three

12 and four hours ago you really introduce a lot of

13 bias and there is a lot of suggestibility. So, a

14 return to baseline pain inherently is problematic.

15 In fact, I think most pharmaceutical companies

16 realize this, and this metric is rarely used in

17 drug development, although it is mentioned in the

18 guidance.

19 \[Slide\]

20 So, how do we generate dose interval

21 instructions in clinical trials? Well, the first

22 thing I will say is that true dose interval ranging

23 studies, meaning to test out what you would get at

24 fixed intervals, fixed doses rather than waiting

25 for a sense of rescue or \"I can\'t wait any longer\"

45

1 are actually not done. Metrics primarily come from

2 single-dose studies. There is some qualitative

3 data that I will mention briefly later that does

4 come from multiple dose studies but this is limited

5 in amount and applicability.

6 \[Slide\]

7 Getting back to the other possible metrics

8 from single-dose studies and, again, I want to

9 reiterate that what these metrics describe are

10 rescue, not optimal. Percent of patients who

11 rescue during a study period is largely affected by

12 the study design and the study execution.

13 What I mean by that in study design is

14 quite fundamental. If you have a study that is

15 explained to an investigator and a patient as a

16 12-hour study, let\'s say, and you tell them that if

17 they need rescue to let you know, as they approach

18 that 12-hour period they may well see the 12-hour

19 mark as a threshold, as a success point, and simply

20 hold out to ask for remedication. If it is a

21 24-hour period, that will affect how it is

22 perceived. Likewise, a short study interval\--if

23 somebody knows that the study is going to be over

24 in four hours, they may wait to that point.

25 Actually, the last hourly acute pain

46

1 measurement is kind of a flip side of the study

2 duration. In most studies you will have hourly

3 pain measurements up to a period of, let\'s say, 12

4 hours and then there will be a final pain

5 measurement session at 24 hours if the study is

6 designed that way, if the thought is that possibly

7 it is a 24-hour drug. If it is a much shorter

8 acting drug the last measurement may be at 12

9 hours, with a gap of these hourly measurements.

10 There are expectations that are

11 transmitted to the patients through the very trial

12 design that affects their behavior. We have

13 actually seen this in studies, particularly the

14 shorter intervals. A study that has hourly

15 metrics, going out to four hours, with a follow-up

16 later on, has a tremendous rescue rate right after

17 that fourth hourly measurement. It is very

18 profound when you see how the study design affects

19 the patient responses.

20 In terms of the execution, simply the

21 monitor behavior and how encouraging or

22 discouraging the monitors are of rescue, whether it

23 is called remedication or rescue, the very presence

24 of a monitor\--does the monitor walk around if there

25 is more than one patient in the center? Do they

47

1 leave the room? Is the medication left on the

2 table to take truly ad lib or do you have to come

3 up and ask the monitor that may look like Nurse

4 Ratchet or may look like an inviting personality?

5 \[Slide\]

6 The time to rescue varies also depending

7 on the setting. Major surgery is different than

8 minor surgery; is different than dysmenorrhea. I

9 will actually show some case examples of this in a

10 little bit. Whether you are measuring the time

11 from the dose or the time from the onset of relief

12 obviously changes the metric.

13 The statistic you use, whether you use the

14 median or the mean\--the median is obviously less

15 susceptible to outliers and the mean will shift

16 responses towards the shorter interval based on

17 patients who simply don\'t respond to the analgesic

18 to begin with.

19 \[Slide\]

20 I will be talking about this population

21 for analysis a little bit more. Let me define

22 things better so I don\'t confuse what I mean by

23 responder and responder analysis that will be

24 discussed later.

25 If you use the all-treated population to

48

1 analyze a dosing interval, then you are including

2 patients who either rescued within an hour and who

3 didn\'t rescue at all. This usually shifts the

4 dosing interval towards the shorter time period,

5 particularly in models of severe pain where there

6 is a high rescue rate. So, we could call that

7 either the all-treated group which does, as I say,

8 include people who had no response; we could call

9 it the ITT population.

10 The responders that I am referring to are

11 those subjects who register some form of pain

12 relief early on in the study, and there is

13 variability, in fact, at that point as well. You

14 can be defining a responder as somebody who had

15 analgesia and, therefore, they are a valid subject

16 to capture information on how long that analgesia

17 that they obtained lasted. You could do it by time

18 to onset of relief, and that can be broken down

19 into either perceptible, meaningful, adequate or

20 some prespecified either VAS or categorical

21 improvement. So, you may want to say a patient

22 doesn\'t really enter the analysis of duration of

23 their drug effect if that drug effect didn\'t at

24 least meet some minimal level. It could either be

25 subjective or you can try and objectify it with,

49

1 let\'s say, a pain relief score of at least 1 or 1.5

2 on a scale of 4.

3 \[Slide\]

4 As I mentioned earlier, there is

5 variability based on the clinical setting. What we

6 have seen is not surprising. The percent of

7 patients who rescue is highest in general surgery

8 settings, whether it is orthopedic or gynecologic.

9 Dental rescue rates tend to fall below surgery.

10 Dysmenorrhea rates are very frequently very low,

11 regardless of whether you are looking at 12 or 24

12 hours and almost regardless of the drug or placebo,

13 and we will see that. The median time to rescue

14 medication which in a sense is derived from the

15 same database as the percent who rescue, obviously,

16 then has the converse. Dysmenorrhea studies have

17 the longest dosing interval based on time to

18 remedication; dental, a little shorter; and

19 surgery, shorter yet.

20 \[Slide\]

21 In summary, there is a lot of variability

22 in the metrics that we use. At this point in time

23 they are not well standardized. So, we see

24 different analyses presented by different sponsors.

25 The study design, the study conduct, which

50

1 statistic is used, what population is analyzed, the

2 definition of relief, the setting and, actually I

3 didn\'t discuss this earlier but I put it in the

4 summary, even from trial to trial in the same

5 model, roughly same study design has variability,

6 as you would expect in nature.

7 \[Slide\]

8 Now I am going to go through some case

9 studies. The first ones will deal with this issue

10 of the population that is included for analysis.

11 The stopwatch technique is very frequently used.

12 What that means is that it can be either a single

13 or a double stopwatch. The patient is given a

14 stopwatch and when they feel that they have gotten

15 perceptible, meaningful, adequate relief, they

16 click that stopwatch. A two stopwatch technique

17 attempts to differentiate perceptible from

18 meaningful. So, the first stopwatch click is \"I

19 feel something is happening\" but it may not be very

20 meaningful for them. The second one is when \"gee,

21 this is significant for me.\"

22 \[Slide\]

23 In this dental pain study, median time to

24 remedication and, again, the drug isn\'t really

25 relevant but the half-life is worth noting because

51

1 we will talk later about how much there is or there

2 is not correlation between PK and clinical results.

3 Placebo I will call zero half-life. We could

4 debate that. This is the all-comers or the ITT

5 analysis. You can see that placebo has almost a

6 2.5- hour median time to remedication. A 2-hour

7 drug has a 6-hour median time to remedication; and

8 a 17-18-hour drug has a 9.5-hour median time.

9 When you only look at those who responded,

10 based on the perceptible definition of response,

11 you see that this stretches out. If you were to

12 base a dosing interval instruction for a label on

13 these data, you would have to ask yourself do I go

14 with just onset, those who had onset? Just the

15 ITT? Some kind of a gestalt approach between the

16 two?

17 \[Slide\]

18 I am just going to show a slide

19 demonstrating variability from study to study even

20 in the same model. There is a second dental pain

21 study added to this slide. Within study 1 and

22 study 2, which really were conducted identically,

23 there is some difference that you see in the two

24 studies. Is that tremendous? Is it surprising?

25 No, that is variability that you see, but if you

52

1 were interested in drug Y, you wouldn\'t really know

2 whether to push this to Q8 hours. Should this go

3 to Q8 hours? Should it go to Q12 hours? Then, if

4 you are guided by the analysis of only those with

5 onset, do you go to 12 to come up with some kind of

6 a combo here, or do you go to the Q24-hour

7 interval? I think that we would all agree that it

8 is kind of difficult to know from these data what

9 is the ideal dosing interval. For drug X, it is a

10 2-hour half-life. Is it a Q4-, 6- or 8-hour? For

11 drug Y, is it Q8, Q12, Q24?

12 \[Slide\]

13 In summary, for dental pain studies we see

14 that there is an effect of the population you are

15 using for analysis. There is a limited

16 relationship between PK and clinical data. The

17 time to rescue and the percent who rescue within an

18 interval are informative but not definitive. Then

19 the question that, in a sense, we are asking

20 ourselves, asking the committee for input, is would

21 there be benefit in studying a multi-dose in the

22 sense of at least a minimum of a second dose where

23 you actually look at a fixed dosing interval to get

24 an idea of whether, beyond the placebo effect,

25 there actually is a pharmacodynamic effect of an

53

1 earlier dose compared to a longer dose that may be

2 chosen based on convenience and perception of

3 safety?

4 \[Slide\]

5 We will look briefly at dysmenorrhea. As

6 I mentioned earlier, these are two studies. This

7 is a 12-hour drug Z and a 17 to 18-hour drug Y. As

8 you can see, the median time to remedication is

9 very long even in placebo. The percent who rescue,

10 and this was within 12 hours, you can see is quite

11 low. Obviously, the greater than 24-hour median

12 tells you that at 24 hours it remains very low.

13 What this slide tells us is that

14 dysmenorrhea is not generalizable to other

15 settings. I don\'t think we would want to apply

16 these data to the label in a generic way. And, it

17 tells us that dosing interval for dysmenorrhea is

18 not going to be well guided by this.

19 \[Slide\]

20 Just looking briefly at postoperative

21 models, and this is an orthopedic study begun day

22 after surgery or when the patients came off patient

23 controlled analgesia and when they reached a

24 certain VAS of pain, I believe it was the

25 threshold when patients where entered into the

54

1 study.

2 We have placebo, drug Z 12-hour half-life,

3 drug Y 17 to 18-hour half-life. I only have the

4 ITT population analysis for this study but you can

5 see it is very short. It doesn\'t even resemble the

6 other two models. The percent who rescue in 12

7 hours is extremely high in all groups. Again, if

8 you were going to use this model to generalize to

9 dysmenorrhea and dental, it would be problematic.

10 We do see this across studies and across other

11 major surgery models. Do we need a totally

12 separate dosing structure for postop pain? Is drug

13 Z a Q4 hour drug? Is it a Q6 hour drug? Is Y a Q4

14 or Q6?

15 \[Slide\]

16 As I mentioned, the surgical setting is

17 quite different than the dental and dysmenorrhea.

18 The question is how do we establish dose interval

19 for postoperative pain and, again, if drugs Y or Z

20 can\'t be safely given during that shorter interval,

21 what do we do? Do we contraindicate it? Do we

22 indicate it for postop pain but in conjunction with

23 a rescue medication that should be available

24 because we know that the interval will be short?

25 \[Slide\]

55

1 Now I will just briefly talk about the

2 qualitative data we get for multi-dose studies to

3 add to the single-dose study metrics I have

4 discussed. Use of supplemental or rescue

5 medication over a period of time is frequently

6 collected. Patient global evaluation over

7 subsequent days is frequently collected, as is

8 average pain intensity scores over a period. These

9 endpoints generally are not really sensitive and

10 informative enough to give us information on a

11 dosing interval.

12 \[Slide\]

13 Let\'s not forget risk/benefit. We could

14 say take the drug every hour but that will have its

15 problems. We are reminded of this in this \"B.C.\"

16 cartoon, \"What\'s the strongest over-the-counter

17 pain killer you got?\" And, the answer is a mallet

18 over the head. Is it effective? Yes. Is there

19 going to be remedication at all? Probably no. But

20 is this the ideal analgesic? Obviously not.

21 \[Slide\]

22 We need to balance safety and efficacy,

23 and that is an issue that we need to directly

24 address in labeling. Obviously, you want

25 convenience. You want adequate pain relief,

56

1 optimal pain relief, but you have to balance safety

2 and metrics, whiich particularly in the acute pain

3 setting, for safety are usually not very

4 informative. If you have a drug that has a very

5 high toxicity during a short-term period, you don\'t

6 have a drug. So, it is hard before marketing to

7 really know how that will play out. If you make a

8 drug a BID instead of once a day, you are not going

9 to see in that safety database, even if you collect

10 it for a week, substantial differences that you may

11 see in safety after it is marketed. Increasing the

12 dose may well increase efficacy but it also

13 increases adverse effects.

14 \[Slide\]

15 I am just going to discuss a case study of

16 attempts in labeling to optimize that information

17 on risk and benefit. It is the tramadol label. In

18 the clinical trial section it states that Ultram

19 has been given in single doses of 50 mg, 100 mg,

20 150 mg and 200 mg in patients with pain. In the

21 dosage and administration section it states that

22 for patients with moderate to moderately severe

23 pain, not requiring rapid onset of analgesic

24 effect, the tolerability of Ultram can be improved

25 with the following titration schedule, and it goes

57

1 on describing a titration schedule that has been

2 studied, and describing in some detail the extent

3 to which it spared some toxicities.

4 \[Slide\]

5 A little bit later in the dosage and

6 administration section it states that for the

7 subset of patients for whom rapid onset of

8 analgesic effect is required and for whom the

9 benefits outweigh the risks of discontinuation due

10 to adverse events associated with the higher

11 initial doses, Ultram 50-100 mg can be administered

12 as needed for pain relief every 4-6 hours. There

13 is a statement that clearly says not to exceed 400

14 mg per day.

15 \[Slide\]

16 So, we have a label that really attempts

17 to put in all the different metrics and information

18 available, and it really is a juggling act for the

19 prescribing physician. This is an example,

20 frankly, of what you would need to try to cull from

21 any label. You need to ask yourself what is the

22 best starting dose for my patient? Shall I give

23 them a loading dose that is high, or are they going

24 to tolerated it better if I start lower? What

25 timing interval should I give them? That, to an

58

1 extent, is left to patients. There is nothing

2 wrong in saying take it every 4-6 hours depending

3 on how you need it. But then you have to deal with

4 the maximum dose over a 24-hour period. You have

5 kind of taken from Peter to pay Paul. If you want

6 a high dose in the beginning you are going to have

7 to lower it later. Of course, there is titration

8 of dose which is frequently an issue with opioids

9 particularly.

10 \[Slide\]

11 In conclusion, the duration of analgesia

12 is guided by PK data. The return to baseline pain

13 metric is not an adequate endpoint to assess dose

14 interval. The clinical setting affects the

15 apparent duration of analgesia and remedication

16 use.

17 \[Slide\]

18 The analysis of time to remedication is

19 dependent on what population you are analyzing,

20 those who have some onset versus those who are

21 enrolled in the study and may well not have onset.

22 The percent who rescue is informative, but it

23 doesn\'t distinctly and clearly define any optimal

24 dosing interval. The current metrics, as I have

25 described them with the limitations, are not

59

1 standardized.

2 \[Slide\]

3 Additional information on dosing interval

4 is needed. More formal study of dosing schedules

5 may further characterize optimal dosing intervals,

6 and different acute pain settings may need to be

7 addressed in labeling.

8 I do want to say at this point that, with

9 the second point on this slide, we are kind of

10 venturing into a new area here. We don\'t really

11 know what those studies will tell us if we ask for

12 them, and that is one of the questions for the

13 group this morning, to discuss how valuable such

14 studies might be. Thank you.

15 DR. FIRESTEIN: Thank you. The next

16 speaker is Lourdes Villalba, on safety databases

17 for acute analgesics.

18 Safety Databases for Acute Analgesics

19 DR. VILLALBA: I am a medical officer in

20 the Division of Anti-inflammatory Analgesics Drug

21 Products.

22 \[Slide\]

23 Throughout our presentations at this

24 meeting, we have tried to emphasize how important

25 it is to collect adequate data to write a label

60

1 that is informative to patients and physicians.

2 \[Slide\]

3 I am going to talk about the kind of

4 safety databases that we would like to see. I

5 think my talk actually was titled safety in acute

6 analgesia trials, but I need to spend some time

7 talking about chronic requirements. Actually,

8 instead of chronic, this should be long-term use.

9 \[Slide\]

10 We do have some guidelines. We have the

11 ICH, International Conference Harmonization

12 guidelines that were published in 1995 and refer to

13 the use of products intended for long-term in known

14 life-threatening conditions. Long-term is defined

15 as continuous or intermittent use for six months or

16 more.

17 The minimum requirements are 300-600

18 patients for 6 months, and 100 patients for a year,

19 and a total exposure of 1500 patients including

20 single-dose and short-term multiple dose studies.

21 These numbers are given as a minimum guidance, and

22 exposure should be available at clinically relevant

23 doses or doses intended for clinical use.

24 However, the same guidance has said that a

25 larger N or longer-term safety databases may be

61

1 needed. That is in the case when there are

2 specific safety concerns. For example, if during

3 drug development in preclinical studies or early

4 Phase I for some reason we may identify some

5 specific event, or we may think that some adverse

6 event may be more frequent with time and that the

7 hazard rate will increase with time, in that case

8 we may need larger and longer safety databases.

9 Or, when there is need to make risk/benefit

10 decisions such as in the case when a new drug has a

11 tiny effect size and, therefore, even if an adverse

12 event is not very frequent we need to quantitate

13 how often that happens in order to make those

14 decisions.

15 \[Slide\]

16 As I mentioned, the guidance says that

17 exposure should be in doses intended for clinical

18 use. However, one of the safety concerns that we

19 do have, which applies to all analgesics, is the

20 dose creep phenomenon. Dose creep is the use of

21 medications at doses above the recommended dose.

22 That means doses above the demonstrated doses that

23 are effective and safe in clinical trials.

24 We do have an example of the dose creep

25 phenomenon from the Celebrex NDA. In the

62

1 randomized controlled trials part of the NDA,

2 Celebrex showed efficacy in osteoarthritis at the

3 100 mg BID dose and efficacy in rheumatoid

4 arthritis at the 200 BID dose. There was no

5 obvious efficacy advantage of higher doses of 200

6 mg and 400 mg respectively. Of course, they were

7 also efficacious but there was no major advantage

8 of higher doses.

9 In the open-label part of the development

10 program patients were allowed to increase the dose

11 up to 200 mg BID in the osteoarthritis study and

12 400 mg BID for the rheumatoid arthritis patients.

13 Actually, it was shown that most patients, 70

14 percent of the patients increased the dose and most

15 of them moved to a dose twice as high as the

16 initial dose even though there was no evidence of

17 worsening efficacy right before they increased the

18 dose and there was no evidence of improvement in

19 efficacy after they increased the dose. So, this

20 is just an example and the good news is that there

21 were no major safety concerns observed with these

22 increases in dose.

23 \[Slide\]

24 Therefore, out of a summary regarding

25 exposure requirements for long-term use, more than

63

1 fulfilling a minimum number, what we want to see is

2 an adequate safety database that will address

3 specific issues that may arise during drug

4 development. We want to see minimum ICH guidelines

5 at the highest labeled dose. We also want to see

6 special populations addressed, particularly the

7 elderly and the pediatric populations.

8 \[Slide\]

9 Now I am going to talk about exposure

10 requirements in acute or short-term use. The

11 approach that we have had in the division for the

12 last several years is to require as much as if it

13 were intended for chronic use. The reason for this

14 approach is that we know, I think everybody is

15 aware, that drugs are used for longer than

16 approved. There is no analgesic that is going to

17 be used only once. Even if the label states that

18 the recommendation is for short-term, they are used

19 for longer term.

20 I have two examples here. One is from the

21 Vioxx database and the other is Duract, bromfenac

22 sodium.

23 \[Slide\]

24 This slide was presented at the advisory

25 committee meeting in February of last year so it is

64

1 a little outdated but it makes the point. Vioxx 50

2 mg was approved for the treatment of acute pain.

3 It was recommended in the label to be used for five

4 days. This dose is twice the dose approved for

5 chronic use, the highest dose approved for chronic

6 use in osteoarthritis and twice the dose approved

7 for rheumatoid arthritis.

8 At that time, the total number of drug

9 appearances was approximately 13 million. Of

10 those, 5 percent were for the 50 mg strength. Of

11 those, one-fifth were for more than 30 days. So,

12 this is just to show you some numbers because with

13 the next example, which is actually much more

14 dramatic because of the public health issues that

15 came with it, we do not have numbers or

16 denominators.

17 We have also seen with Vioxx that there

18 are some patients who used the 50 mg dose twice a

19 day, that is, 100 mg a day. That actually is very

20 unwise, I would say, because there are very limited

21 data on the 100 mg dose in long-term exposure.

22 \[Slide\]

23 This is the next example. This is an

24 unfortunate example but very enlightening for us,

25 for the division and for the agency. Bromfenac was

65

1 a nonsteroidal anti-inflammatory drug approved in

2 July, 1997. There was a voluntary withdrawal in

3 June, 1998 due to reports of hepatic failure.

4 This is a very interesting example because

5 the original development program was towards acute

6 pain, dysmenorrhea and osteoarthritis and there

7 were also some rheumatoid arthritis studies. The

8 proposed dose in the original NDA was 25-50 mg

9 every 6-8 hours up to 200 mg a day.

10 At filing, it was noted that there was

11 insufficient exposure for the osteoarthritis

12 indication. Therefore, the osteoarthritis

13 indication was withdrawn but chronic safety data

14 from the chronic studies was submitted.

15 \[Slide\]

16 I want to show you the size of the

17 database which is actually a very good size if you

18 look at total numbers. The total exposure was

19 close to 2200, with 1000 patients exposed in the

20 acute pain studies, close to 400 patients in the

21 multiple dose, up to one week studies. There were

22 also some dysmenorrhea studies of 250 patients and

23 the chronic exposure was about 900 patients in

24 osteoarthritis and rheumatoid arthritis. So, if

25 you look at the total numbers these look very good.

66

1 \[Slide\]

2 However, if you break it out by dose and

3 duration of exposure\--this is the dose in

4 milligrams a day and this is the duration in days

5 of exposure, you see that the number of patients

6 exposed to the 200 mg dose for a year or more were

7 only 24. The bulk of the exposure was at doses

8 below 150 mg.

9 At the safety update there were more

10 patients, and when we get to the 900 patients

11 exposed for more than three months\--I do not have

12 the breakout of these numbers but it was mentioned

13 in the medical officer\'s review that there was

14 sufficient exposure to support the 150 mg dose a

15 day and, again, the dose was 25-50 mg up to three

16 times a day.

17 \[Slide\]

18 I don\'t want to go into details but just

19 to show you that this was a very good database in

20 the sense that there were placebo control studies,

21 active control studies up to one year with several

22 comparators. They used fixed dose, as I said,

23 25-50 mg BID, TID and four times a day but in fixed

24 dose, not in flexible dose. There was a good

25 number of patients with OA and RA, and there also

67

1 was an open-label experience up to four years and

2 that involved flexible dose, some of them up to 225

3 mg a day.

4 \[Slide\]

5 Therefore, the safety review showed that

6 acute pain studies that were conducted at the 50 mg

7 and 50 mg single doses, and also in short-term

8 multiple dose studies conducted with the 25 mg and

9 50 mg a day dose, showed absolutely no safety

10 concerns. There was some nausea, some vomiting, a

11 little allergic reaction but there was not even

12 mention of any liver effects.

13 \[Slide\]

14 However, the chronic studies showed a flag

15 for hepatotoxicity. This is what the NDA review

16 showed regarding liver function test elevations, 15

17 percent of patients had mild elevations, that is

18 less than 3 times the upper limit of normal, and

19 2.8 percent had clinically significant elevations

20 of LFTs, 3 times the upper limit of normal or

21 higher. Of note, the NSAID template mentions that

22 LFT elevations in clinical trials of NSAIDs are

23 usually seen in 15 percent of patients. Therefore,

24 the number of patients with mild elevations of LFTs

25 was nothing outstanding. The clinically

68

1 significant elevation was higher than what the

2 template says, which is 1 percent but, again, it

3 was not something terribly dramatic here. This

4 number is actually similar to what was observed in

5 the diclofenac NDA.

6 The elevation of LFT particularly

7 clinically significant events were dose related.

8 They were observed at the 100 mg dose but most of

9 the cases were at higher doses. Most of them were

10 reversible after drug discontinuation. Some of

11 them were reversible even without drug

12 discontinuation. The majority occurred within the

13 first 90 cays, but the important observation was

14 that the earliest occurred around day 30.

15 \[Slide\]

16 Based on those observations, the drug was

17 approved with warnings for risk of hepatic effects.

18 Short-term use for pain should be less than 10 days

19 and, because of the risk of hepatotoxicity, if

20 longer therapy is needed, LFTs should be monitored

21 after 4 weeks. So, we think it was pretty clear

22 that there was some concern with liver toxicity

23 here. In addition, the maximum daily dose would be

24 limited to 150 mg a day, and there was removal of

25 any reference to treatment of osteoarthritis,

69

1 chronic pain and dysmenorrhea.

2 \[Slide\]

3 Within months the agency started to

4 receive postmarketing reports of liver toxicity,

5 including hepatic failure, need for liver

6 transplantation and death. Most of the reports

7 were at doses within the labeled dose, but most of

8 them were exposed for longer than 10 days. The

9 majority was for 2-8 months, and some of them were

10 exposed for a couple of years.

11 We have this unfortunate example, but I

12 think that reflects something that everybody knows,

13 which is that drugs are used for longer than

14 initially intended. As was discussed yesterday, if

15 a drug is approved for acute use but somebody

16 thinks that it may work for chronic pain physicians

17 are going to use it.

18 \[Slide\]

19 In summary, short-term safety studies are

20 certainly insufficient to address safety concerns

21 that may come up with some patients who will be

22 using the drug for longer than intended.

23 Drug development for acute pain drugs

24 should address the potential safety concerns of

25 dose creep, use for longer than the intended, and

70

1 potential for abuse which is another whole issue.

2 We propose that for a short-term

3 indication, unless there is a contraindication

4 based on safety, formal efficacy studies should be

5 done in a chronic setting. I think this is the new

6 concept that we would like your opinion on. We are

7 not saying that off-label use needs to be addressed

8 for every indication because that is impossible,

9 but for a drug that belongs to a class that is used

10 for a chronic indication it is very reasonable to

11 ask for some efficacy studies. If it doesn\'t work,

12 if it is not efficacious in the chronic indication,

13 then we can put that in the label, that this

14 doesn\'t work for chronic pain; do not use it. So,

15 we think that this would be a way to address the

16 possibility of off-label use and also allow us to

17 do a better risk/benefit assessment. That is the

18 end.

19 DR. FIRESTEIN: Could I ask a quick

20 question? Do you think that that final

21 recommendation would essentially nullify

22 yesterday\'s discussion about having separate acute

23 and chronic indications? I mean, if for an acute

24 indication you are going to require formal chronic

25 safety and efficacy what is the value then of

71

1 having separate tracks?

2 DR. VILLALBA: Well, we are not going to

3 require replication in three different models for

4 the chronic indication. What we want is at least

5 to have some efficacy studies. For example, for a

6 new NSAID or a COX-2 inhibitor, if someone would

7 come with only the acute pain indication, then we

8 would ask for osteoarthritis studies to see if that

9 worked in the chronic setting. That would provide

10 also better safety data because safety data

11 collected in an open-label way is not the same as

12 safety data collected in a controlled way, with

13 placebo control and active control studies. But we

14 actually would like to hear your opinion. Thank

15 you.

16 DR. FIRESTEIN: Are there any other

17 comments or questions from the group?

18 DR. MAX: I have some questions regarding

19 the dosing interval. I think a lot depends upon

20 what you want to tell people about. My question is

21 has the FDA studied what percentage of patients

22 whom you are trying to inform who are taking acute

23 analgesics take two doses total versus three doses

24 or four doses? Because if you mostly want to tell

25 people about the second dose, single-dose duration

72

1 is enough. If there is a large number of people

2 who take three doses, the second dose is important,

3 and so on.

4 DR. GOLDKIND: That question will really

5 depend on what studies show the dosing interval

6 should be. There may well be off-label usage TID

7 for a BID drug, but if the best studies have

8 identified a twice a day regimen, actually PK and

9 some Phase II clinical studies should give you an

10 idea of the ball park. I mean, we don\'t have

11 examples of every two-day drugs or drugs that are

12 taken very infrequently. I think, as you pointed

13 out, you need to at least get data on doses going

14 out beyond the first interval that you would be

15 prescribing in terms of usage data on how many

16 patients go beyond the frequency advised. We don\'t

17 have that.

18 DR. MAX: Yes, my question is have you

19 studied general use of analgesics for acute pain

20 and how many people just have one day treatments or

21 one dose treatments, or two day, three day

22 treatments?

23 DR. GOLDKIND: We don\'t have that, no. In

24 clinical studies it is hard to get a model that

25 will get you out multiple days. So, I think that

73

1 answers the question to some extent. Most people

2 only take acute analgesics in the postoperative

3 setting or acute injury setting for several days on

4 a regular basis.

5 DR. MAX: But do you understand what I am

6 referring to?

7 DR. GOLDKIND: If I do understand, we

8 don\'t have usage data to tell us how many days

9 patients take acute analgesics for most

10 indications. I don\'t know if that is available. I

11 don\'t know if IMS data could give us that.

12 DR. FARRAR: As somebody who has focused

13 primarily on chronic pain as an area of study, I

14 would admit to this being the first time that I

15 have sort of seen the full scope of the approval

16 process for acute pain. I commend the FDA for

17 reexamining the entirety of the approval process

18 because I think there are a clearly a number of

19 issues that can be addressed that aren\'t currently

20 being addressed, some of which were being hinted at

21 by Dr. Max.

22 One of the things that strikes me is that

23 I have never, ever seen a drug that is used as a

24 single dose, ever. It may be tested that way; it

25 may be used that way perhaps in a hospital setting,

74

1 but if it is over-the-counter it just doesn\'t

2 exist. Therefore, I think it is probably necessary

3 to study certainly the effect of several doses over

4 a period of time. I think that that would clearly

5 generate a completely different set of data

6 perhaps.

7 The second issue that I will just raise,

8 and I am just raising all of these and I think they

9 would need discussion at length in a different

10 setting, but the second issue relates to the safety

11 data. Dr. Goldkind showed very nicely sort of the

12 need to look at risk/benefit ratios. It seems to

13 me that it doesn\'t make obvious sense to look for

14 safety day in use over six months and not look at

15 least in some way at efficacy data over the same

16 period in terms of just thinking about how a

17 medicine is going to be used in terms of the

18 general public.

19 What that raises is really the last point

20 that I want to make, which is that we know that

21 these drugs are going to be used in a variety of

22 different ways by different patients and different

23 physicians. And, I think it is imperative that we

24 look at the way in which the drug is going to be

25 used and use that information to guide us in terms

75

1 of both the safety and the efficacy data that we

2 would want prior to or following approval.

3 There are two points that were made in the

4 last presentation which I think really speak to

5 this. With the Celebrex example, the fact that 70

6 percent of people increased their dose when allowed

7 to do so tells you two things. It tells you, one,

8 that that is the way it is going to be used. It

9 also tells you that even though the study was not

10 large enough to show that a larger dose provided

11 better efficacy, or that there was some development

12 of\--I don\'t want to call it tolerance but getting

13 used to the medicine, whatever you want to call

14 that, that over time an increased dose was more

15 beneficial. The patients were telling you that.

16 The patients said when given the option I will take

17 this medicine at a higher dose because it works,

18 number one and, number two, doesn\'t cause acute

19 side effects. That really is telling and indicates

20 that there needs to be at least some approach to

21 the concept of if given free access to the

22 medication, if it was placed at the bedside so the

23 patient can take it without asking the monitor, be

24 that person nice or not nice, then they will use it

25 in the way in which they would probably use it at

76

1 home and that would perhaps dictate the way in

2 which a study could be conducted.

3 The very last thing that I would like to

4 point out is that we need to keep in mind with all

5 of the PK data, all of the time to effect data, all

6 of the time to return to baseline although I think

7 I agree that that is a lousy measure, time to

8 remedication, those are all mean values. What a

9 mean value indicates is that there are 50 percent

10 of the people who did either better or worse. I

11 don\'t think that 50 percent is the number we are

12 actually targeting in terms of what a reasonable

13 dosing schedule would be. I certainly would never

14 treat my patients and allow 50 percent of them to

15 suffer for an hour or two before I gave them a

16 second dose.

17 I think that needs to be dictated very carefully by

18 the risk/benefit or the minimum amount that they

19 can take to be effective and the maximum amount

20 they can take and still be safe.

21 DR. FIRESTEIN: I think actually you are

22 referring to median, not mean. Actually, the

23 points that you raise bring us to the first point

24 of discussion. I think based on what we have heard

25 and our own clinical experience, it is reasonable

77

1 to expect not single-dose studies but at least

2 multi-dose studies involving a variety of metrics.

3 I would like to open this for discussion with

4 regard to what sorts of metrics people might feel

5 would be appropriate. Susan?

6 Discussion Points \# 1, 2 and 3

7 DR. MANZI: I just wanted to make one

8 other comment first. I agree that I think the

9 purpose of clinical trials is to accurately

10 simulate clinical practice. As I was listening to

11 these talks, I said I can\'t even imagine where you

12 would use single-dose analgesic even in the most

13 acute situations. So, I would agree with multiple

14 dosing.

15 The only other point, and I guess this is

16 the epidemiologist\'s hat that I wear, is that when

17 you are looking at how to figure out dosing, you

18 really learn a lot from the outliers. It is the

19 people who extend beyond the bell curve where you

20 get the most information. My point would be that

21 if you look at time to rescue, you shouldn\'t

22 exclude the non-responders in that because in

23 clinical practice we can\'t predict who those

24 non-responders are going to be and when they are

25 going to need some additional dosing. I think most

78

1 people don\'t take a drug and say \"it didn\'t work;

2 I\'m not going to try it for another dose.\"

3 So, my point is that I would assume the

4 most narrow time based on the outliers for time to

5 redosing and test safety of that in that setting.

6 DR. FIRESTEIN: Clifford?

7 DR. WOOLF: To come back to the issue of

8 onset and duration, Dr. Witter\'s presentation, the

9 context of when even a single drug is given,

10 whether it is given pre- or postoperatively may

11 profoundly change both of those metrics.

12 DR. FIRESTEIN: Coming back to the

13 question of what the appropriate metrics might be,

14 a series of possibilities were raised, and I can\'t

15 remember in which presentation it was but is the

16 gold standard for an acute pain medication going to

17 be quality of life, or is it simply pain?

18 Somebody?

19 MS. MCBRAIR: I would go for pain relief.

20 I don\'t think we are worried as much in the short

21 term about the quality of life, especially for a

22 post surgical patient. They are going to be,

23 hopefully, in a hospital setting and well

24 monitored, and they need pain relief and we would

25 not hold it back from them.

79

1 DR. CUSH: I would also say that when

2 looking at the metrics you should rely upon,

3 obviously, pain is where we are going to go.

4 Unlike other diseases where our metrics are maybe

5 multivariate where we are going for a disease

6 response, here we are looking for a symptom

7 response across many different diseases, and having

8 a multivariate definition of response might be very

9 difficult to arrive at, as we discussed yesterday.

10 But if we had an acceptable measure of pain relief

11 that was universally agreed upon, we could go for

12 the variables that Jim was looking for. For

13 instance, if you defined an acceptable response of

14 50 percent, pain relief of 50 percent, you could

15 then define the time of response and the percentage

16 of patients actually receiving that response in a

17 placebo population and in an active treatment

18 population and then also maybe even define the

19 duration of response with a PR 50, or something

20 along those lines.

21 DR. FARRAR: I think the point about

22 quality of life as a measure in an acute pain

23 process brings up an important point, which is that

24 the quality of life is defined differently in

25 different circumstances. I would argue that

80

1 adequate pain relief postoperatively is, in fact, a

2 very good measure of a postoperative six-hour

3 period of quality of life.

4 But I think ultimately that pain is the

5 primary outcome. What I would like to point out

6 though is that it is not a single measure of pain

7 that is paramount. Certainly, in treating

8 postoperative patients, clinicians are aware that

9 the onset of action is vital to the control of pain

10 and you certainly would not give a medication to a

11 postop patient who is writhing in pain a drug that

12 would take two hours.

13 So, the onset of action is of extreme

14 importance, as well as the duration of action only

15 inasmuch as it dictates dosing. The duration by

16 itself\--you know, a long-acting medication may well

17 be of benefit but if you have a short-acting

18 medication, as we know, in terms of intravenous use

19 of various short-acting opioids, they can be very

20 effective and the short-actedness can be overcome

21 with either an infusion or multiple dosing.

22 So, I would argue that there needs to be

23 pain measurement as a primary outcome with at least

24 two issues. One is the onset of action and then

25 the duration of action as it dictates the use of

81

1 the drug.

2 DR. KATZ: Just to continue the discussion

3 of appropriate metrics for onset, first of all, I

4 wonder if somebody could explain to me what the

5 relevance is of placebo response to measuring

6 onset? That doesn\'t seem to make any sense to me

7 at all. If you are lying there in bed, looking up

8 at the nurse giving you the medication, you want to

9 know how long it is going to take this thing to

10 work. You don\'t want to know when is the

11 pharmacodynamic of the response of this medication

12 going to separate from placebo. That is a

13 completely noon-intuitive and clinically irrelevant

14 measure. I would propose that for onset we look at

15 actually onset, when the medication starts to work

16 as opposed to when it separates from placebo.

17 The second issue I have with onset is that

18 it is not at all clear to me why we are only

19 interested in drugs that have onset within one

20 hour. There are other characteristics of onset,

21 aside from time to onset, that are also relevant.

22 For example, in an NSAID I don\'t know what the

23 typical rate is of responders that you see, but if

24 you see that, for example, 60 percent of your

25 patients will respond within an hour, I also might

82

1 be interested in a drug where 95 percent of

2 patients respond but it takes an hour and a half

3 and there are other ways to bridge the gap. So, I

4 am not sure why we have this rigid notion that you

5 have to meet your onset criteria, whatever that is,

6 within an hour.

7 DR. FIRESTEIN: Can you clarify your point

8 about differentiating from placebo? You don\'t

9 think it is important to differentiate from placebo

10 during that first hour?

11 DR. KATZ: Let\'s say, for example, that

12 you give your drug to a group of patients and the

13 median time to onset of the drug itself is one

14 hour. In other words, you have a clinical sense

15 that it is going to take on average an hour for

16 that medication to work. If it doesn\'t separate

17 from placebo for an hour and a half, what is the

18 difference?

19 DR. FIRESTEIN: Because then you could

20 just treat with placebo.

21 DR. KATZ: No, no, no, that is not true at

22 all. The confusion I think is between looking at

23 measures of efficacy of the drug compared to

24 placebo versus looking at onset compared to

25 placebo. Obviously, you have to show that your

83

1 drug is better than placebo in some way\--a SPID or

2 one of your measures that has been shown to be

3 effective for that. But in terms of giving

4 clinically important information about when the

5 drug works, the clinician wants to know when the

6 drug works; he doesn\'t want to know when the

7 placebo works. So, whether the drug separates from

8 placebo within that hour or it takes an hour and a

9 half or two hours, or what-have-you, is a

10 completely separate question, and I don\'t think the

11 separation from placebo is a clinically useful

12 metric of onset. The drug works when it works.

13 The effectiveness of a drug is a combination of its

14 pharmacological effectiveness and whatever placebo

15 or non-specific effect it brings to bear, but in

16 the real world both of those issues are operative.

17 DR. FIRESTEIN: One would wonder if you

18 can\'t distinguish it from placebo whether or not it

19 is truly a pharmacologic effect.

20 DR. KATZ: No, no, no, that is not my

21 point at all.

22 DR. FIRESTEIN: I understand. Dr. Ashburn

23 and then Janet.

24 DR. ASHBURN: I hesitate to speak before

25 the biostatistician speaks, but I just have a

84

1 couple of issues that I wanted to point out or

2 bring to the table. First of all, I want to remind

3 folks that pain measurement in the acute pain

4 setting needs to be both at rest and with movement,

5 particularly in patients who are undergoing major

6 operations, because that has been predictive of

7 good quality of outcome.

8 The other one is onset, and in an acute

9 pain setting I would reinforce Dr. Katz\'s remark.

10 There is not necessarily a limit of one hour with

11 regard to meaningful analgesia in the acute pain

12 setting. There are medications that can be given

13 preoperatively that do have a longer duration of

14 effect, which is no longer relevant if you are

15 trying to use a long-lasting medication and

16 prophylax, if you will, for analgesia at the end of

17 the operation. So, a one-hour onset may not

18 necessarily be important when looking at a

19 medication still intended for acute pain use.

20 Duration of effect, depending on the route

21 of administration, may be very important. A

22 24-hour duration of effect in a patient who is

23 going to be NPO for the first hour after surgery

24 may actually be a very meaningful, important aspect

25 of a different medication.

85

1 The other one is that adverse side effects

2 tend to be overlooked with regard to blending that

3 in with safety. Adverse side effects can be very

4 important in a postoperative period. If a

5 medication has a very low incidence of nausea and

6 vomiting, for instance, that will be perceived as a

7 marked advantage over parenteral opioids which do

8 have a fairly high incidence of nausea and

9 vomiting.

10 Of course, safety is paramount in these

11 areas because one would tend to not tolerate a

12 medication that even has a fairly low incidence of

13 a catastrophic event. A medication that is

14 relatively safe, that doesn\'t have opioid-induced

15 risk of respiratory depression may actually have

16 marked advantage even if it is equally as good as

17 an opioid analgesic.

18 DR. FIRESTEIN: Excellent points. Dr.

19 Elashoff?

20 DR. ELASHOFF: I wanted to comment on the

21 issue of what was being called separation from

22 placebo, which I assume means statistically

23 significant separation from placebo, which is a

24 combination of whatever the true separation is and

25 the sample size that you used to look at the issue.

86

1 So, the whole issue of when they get far enough

2 apart is both the issue of a clinically meaningful

3 separation and the issue of whether the study is

4 actually big enough to address that question.

5 DR. FIRESTEIN: Thank you. I always enjoy

6 being chastened by the biostatisticians! Yes?

7 DR. KATONA: Just looking at the world

8 from the pediatric point of view, even in other

9 situations we do not like to do placebo-controlled

10 trials. I am just wondering, in the acute pain

11 situations, especially the postop pain, in special

12 circumstances like with the children and the

13 elderly, is that something that we need to compare,

14 the active drugs with placebo, or could we do some

15 other designs? I personally even wonder about the

16 general population, if we could design these

17 studies as comparison studies or some other ways.

18 DR. WOOD: Gary, I wanted to return to the

19 point that you were raising right at the beginning

20 of this discussion, and that is how long do we need

21 safety data for, and how will that duration of

22 safety data affect the potential for indications.

23 It seems to me that we have excellent

24 data, going back to the question Mitch was asking,

25 to say that labeling changes are not very effective

87

1 and are generally not followed. I mean, if we

2 think of the example of fen-fen, the example of

3 truplidazone, or the example of even Accutane,

4 which has extraordinarily rigid labeling,

5 physicians and/or patients are still not following

6 these. Certainly with truplidazone the liver

7 function tests were ratcheted down week by week and

8 with relatively little effect.

9 So, the lesson from all of these, it seems

10 to me, is that even a drug that was approved

11 exclusively for acute use, such as one that was

12 limited eventually to ten days\' use in the example

13 that was shown, was used for much longer than that.

14 So, common sense would dictate that we should have

15 safety data that extends for a much longer period

16 than just a single dose.

17 If that is the case, you have to then say,

18 well, how are you going to get that safety data?

19 You could give patients or volunteers an analgesic

20 for a long time for no indication which would seem

21 to me to be dubious ethics and you are probably

22 unlikely to get lots of volunteers. So, it seems

23 almost inevitable, therefore, that if you are going

24 to look for safety data that goes longer than the

25 acute setting, you are going to insist de facto

88

1 that you look at chronic pain relief even for a

2 drug that you might initially be looking at for

3 only the acute setting.

4 I don\'t see a way around that, and you

5 sort of touched on that in your question but I

6 think we need to return to that because that

7 actually is pivotal to how we think about this

8 whole issue of development, perhaps not labeling

9 but certainly how you develop it. If you are

10 unable to go forward without chronic studies, then

11 that is important to think about in terms of how

12 you pitch your development program.

13 DR. FIRESTEIN: Would you require

14 efficacy?

15 DR. WOOD: I would.

16 DR. FIRESTEIN: For the acute indication?

17 If you propose that you would look for efficacy

18 endpoints simply as a safety study, would you

19 require efficacy in the chronic study in order to

20 have approval for an acute indication?

21 DR. WOOD: Well, let me rephrase the

22 question, if I may. I don\'t think the question is

23 would I require efficacy data in the chronic safety

24 study necessarily. I think it is improbable that a

25 company or that you would advise a company to not

89

1 do an efficacy study if they were collecting

2 chronic data because, otherwise, you would be doing

3 a study in which you are giving an analgesic to

4 somebody chronically for no very obvious reason,

5 and I think it would be tough to get volunteers for

6 that, frankly. Therefore, for relatively little

7 additional cost you could get the efficacy data. I

8 think most people would do that.

9 If someone came to you and said we don\'t

10 want to do that, you would almost wonder why. I

11 mean, is the reason that they don\'t want to do that

12 because they have data that suggests it doesn\'t

13 work chronically or it is toxic chronically? As a

14 regulator, it would make me very uncomfortable if

15 someone was adamant that they didn\'t want to do an

16 efficacy study chronically when you were telling

17 them they had to collect safety data chronically.

18 DR. SHERRER: I think that goes back to

19 one of the original questions for why we came, and

20 that is should we really then be dividing into

21 acute and chronic pain? Because if we say that we

22 are going to give these drugs for acute and chronic

23 pain, in a sense we are saying that they work for

24 both. Maybe the dosing is different but, in fact,

25 the drugs work for both acute and chronic pain. In

90

1 practice that is really what is happening. So,

2 does that go back into the mechanistic differences

3 again, and are we really back to saying well, pain

4 is pain? You know, we treat one way for acute and

5 a different way for chronic.

6 DR. WOOD: Well, I think my point is a

7 little more than that. I think that even if we

8 could divide it into acute and chronic pain, and

9 even if we really thought that that would be a good

10 division to make\--and I am not arguing for or

11 against that\--de facto, we have come to recognize

12 that physicians and their patients are relatively

13 poor at following that advice. And, it is not just

14 true of pain; it is true of lots of other drugs.

15 You know, fen-fen was taken for much longer than it

16 was supposed to be. Truplidazone was taken without

17 the appropriate liver function tests being done.

18 Dosage creeps occurred with other drugs.

19 That is not a criticism; that is the

20 reality of the marketplace. That being the case,

21 it seems to me foolhardy to say that we are going

22 to ignore all that data and say if a drug comes in

23 only for acute pain we are not going to require a

24 safety database that goes beyond that, even if we

25 could make recommendations about how it should be

91

1 used and hope that it would be used in that way.

2 DR. FIRESTEIN: Dr. Max and then Dr.

3 Farrar.

4 DR. MAX: I would like to comment on the

5 metrics in the multi-dose studies. I think now the

6 standard metric in looking at doses past the first

7 dose is the choice of the patients when to rescue.

8 I see nothing wrong with that because you are

9 really using that just to tell patients when to

10 expect to do that. The problem is this, I have

11 spent many horrible afternoons sitting with drug

12 companies, trying to massage a bunch of repeated

13 dose data into some meaningful information and you

14 can\'t get anything out of it generally because

15 there are PRN doses with one regimen. The beauty

16 of dose response studies is that you make the dose

17 regimen the independent variable, and when you have

18 the dose also be the dependent variable you muck it

19 up completely.

20 So, I heartily endorse what I hear in your

21 talks. Should we use the dose response type

22 regimen and take multiple different regimens,

23 either doses or times, and try to stick to it and

24 use some other drug for rescue and find out what is

25 too high, what is too low, and what is just right

92

1 for Goldilocks? That is the way to go about it.

2 There is one other finer point, and I

3 think you have to define whether your main

4 orientation is towards exploring the clinical

5 pharmacology or usage study. That gets to the

6 issue of whether you include placebos. Say you

7 want to compare a six-time a day regimen of the

8 same drug with three-time a day, there are some

9 studies I have seen where they give placebos

10 intermittently and then people say, well, the

11 placebos gave analgesia and you really can\'t count

12 them. It may be that if you really want to mimic

13 usage, you want to do it unblinded so you get the

14 full impact of the placebo effect of taking extra

15 pills. But I think you need to spell this out so

16 sponsors won\'t go ahead and use placebos or not use

17 placebos and have the study be voided.

18 DR. FARRAR: I would like to pick up on

19 something that Mitchell just finished with and get

20 back to something that was said before. There are

21 designs that are possible and completely valid to

22 look at the way in which patients use medications.

23 Two of them that are specific, one of which our

24 group has suggested to some drug companies in terms

25 of ways to look at long-term use but have not been

93

1 adopted.

2 The first one is in terms of the onset of

3 effect and the efficacy, and that has to do with

4 whether a patient at the end of the pharmacologic

5 time period where they should have their maximal

6 effect, whether or not they decide they need

7 something else to treat that pain. That is very

8 clinically oriented and it is a valid measure of

9 whether the drug is ever effective.

10 The second thing has to do with long-term

11 use. I think it was suggested before that giving

12 patients drugs for a long period of time with no

13 indication is a problem. What I would like to

14 suggest is that one possible mechanism for dealing

15 with that is, in fact, to do a very tight and

16 carefully controlled study for a period of 4, 6, 8,

17 10, 12 weeks, whatever seems to be appropriate for

18 the drug. In the long-term study it is possible

19 simply to continue to give patients the medication

20 as long as they want to take it. That sounds a bit

21 odd perhaps, but ultimately what we are asking is

22 how are patients going to use that, and is the drug

23 safe for the period of time that they use it? If

24 you want to study it long term, as in a safety

25 study, you would give them the medication; follow

94

1 them as long as they are willing to take it,

2 meaning if it still helps them, they claim it helps

3 them for whatever reason; and look at the safety

4 data over that period of time.

5 There is actually a more elegant way to do

6 that which would in fact, be to continue to give

7 the patients the medication in a blinded fashion

8 long term. One of the arguments against that has

9 been how can you possibly give somebody a placebo

10 over the long term? My argument is to reverse that

11 and to say if the placebo is providing real relief

12 for the patient, then why not give it long term?

13 One of the ways of knowing whether a drug,

14 in fact, works better than the placebo long term

15 would be simply to give it blinded for a long time

16 and follow, as was suggested yesterday, the number

17 of dropouts.

18 DR. WOOD: But how would that differ from

19 a placebo-controlled, long-term study? I mean,

20 giving a placebo and an active drug for long term

21 in a blinded fashion sounds to me like a

22 placebo-controlled, randomized, controlled trial,

23 which is what I am saying we need to do.

24 DR. FARRAR: Right, it is. The difference

25 is the following, which is that in most of our

95

1 placebo-controlled trials there is a monitor that

2 calls you every day and says, \"have you used the

3 drug? Did you write in your diary? Did you use

4 your electronic diary?\" What I am suggesting is

5 that over a brief period of time, 4, 6, 8, 12

6 weeks, whatever is decided, that is reasonable.

7 But what you want to then study is the

8 actual use of the medicines. So, what you want to

9 do is to give them the medicine for, let\'s say, two

10 weeks or a month, a month\'s supply and have them

11 come back to visit you, and nobody calling them in

12 between and finding out whether they took it or

13 not; whether they filled out their diary. The

14 issue is you use simply the continued use of that

15 medicine and metrics that you measure once a month

16 to determine whether or not they actually used it.

17 There is very clear evidence, as I think

18 was suggested earlier, that if the monitor is

19 somebody who makes you feel like you want to do

20 what is right, or scares you into doing \"what\'s

21 right\" you may use the medicine in a way that is

22 very different than the chronic, normal use of that

23 medicine.

24 DR. FIRESTEIN: Dr. Strand?

25 DR. STRAND: I just want to comment that

96

1 that is a rather standard design in, say,

2 rheumatoid arthritis trials, and that is that

3 patients are allowed to continue if they have had a

4 response, open-label treatment for continued safety

5 analysis.

6 But another thing that we have also done

7 with placebo-controlled trials is that the

8 responders, not unblinded, are allowed to continue

9 treatment and that treatment is maintained blinded.

10 We have actually had patients take placebo for as

11 long as three years who respond clinically.

12 DR. CUSH: The limitations of that are as

13 far as recruitment. I mean, I tell patients up

14 front that you may be on placebo for three years

15 and that is somewhat of a deterrent.

16 DR. STRAND: I think we say not that but

17 that on or after a certain period of time, if you

18 are not responding, you are allowed to go to active

19 treatment. Then, all responders can go on to

20 continued treatment and that way we don\'t imply

21 that they will be on placebo for a long period of

22 time.

23 DR. FIRESTEIN: Dr. Woolf?

24 DR. WOOLF: I would like to come to the

25 issue of dose creep and the relevance of that for

97

1 the primary outcome measure, which I think we have

2 all agreed should be pain. But I think the fact

3 that patients tend to take higher doses than have

4 been demonstrated to be effective might be a

5 reflection of the fact that our measurements of

6 what is effective are insensitive, and that

7 patients may be getting a greater benefit than we

8 can actually detect.

9 So, while primary pain outcome measures

10 clearly are appropriate, there may be other aspects

11 of the treatment that are making the patient feel

12 better in a way that we are not detecting.

13 DR. FIRESTEIN: Yes, Dr. Brandt?

14 DR. BRANDT: Fundamentally I agree with

15 what is being said about long-term placebo studies.

16 But, as Vibeke said, there are practical problems

17 with IRBs that are very significant in being able

18 to do this.

19 DR. STRAND: It is not that they were told

20 that they had to be on placebo; it is that everyone

21 was offered to drop out for documented lack of

22 efficacy, and only those people who responded

23 stayed in and, therefore, we selected for a small

24 group of patients who were placebo responders.

25 I would say part of any of these designs

98

1 would be the same thing, and that is people could

2 not continue treatment beyond, say, the blinded

3 time of the trial unless they were responders. But

4 you can maintain a blind and find out some

5 interesting information.

6 DR. FIRESTEIN: And even open-label

7 extensions with safety rather than efficacy as a

8 primary endpoint would not raise the bar that much

9 higher for an acute indication.

10 There were a couple of other issues that

11 were raised that the agency has requested that we

12 discuss. One has to do with the parameter used for

13 assessing dose intervals for acute analgesic drugs.

14 The other, item three, is the issue of how one

15 measures clinically important differences.

16 Actually, I think Dr. Katz yesterday used a quote

17 that I think I am probably going to put on my

18 slide, which is if a difference doesn\'t make a

19 difference, then what is the difference? Or some

20 variation of that.

21 What I would like to do is try to steer us

22 towards addressing those two issues right now. One

23 is if anybody has specific thoughts on what sort of

24 dosing interval studies would be required, or

25 whether that is appropriate. Dr. Elashoff?

99

1 DR. ELASHOFF: Specifically with respect

2 to 2(b), which is median time to rescue, and to (a)

3 as well, which is the T 1/2, part of what was

4 remarked earlier is that just looking at the mean

5 or just looking at the median is not bringing in

6 variability from patient to patient. One kind of

7 thing which could be helpful in that is looking at

8 the 25th percentile or the 75th percentile, that

9 sort of information as well to help characterize

10 how typical, in some sense, the median is of people

11 and to try and get into the variability from one

12 patient to another issues.

13 DR. KATZ: I am happy to say I was

14 actually going to say the same exact thing. We

15 have been talking a lot about how to get a precise

16 estimate of duration by whichever metric, whatever

17 that will wind up being, 8 or 11 hours, but to have

18 some sense of how variable that is I think is very

19 important. If two-thirds of your patients are

20 within an hour of that, that is different than if

21 two-thirds of your patients are within 4 hours of

22 that and informs clinical practice better I think.

23 DR. FARRAR: I agree with what has been

24 said, and I think what was just being suggested is

25 actually best described as a box plot. It is a

100

1 very simple mechanism for actually displaying in an

2 understandable format the 25th, 50th and 75th

3 percentiles.

4 I think what it brings to mind is a second

5 issue which is that patients are really quite

6 different. In trying to help physicians understand

7 how to use the medication what we really need to

8 tell them is what is the minimum time that a

9 patient should wait before they take an additional

10 dose. That really is dictated by safety data. The

11 question really is if a patient only waits an hour

12 to take a second dose, an hour to take a third, and

13 an hour to take a fourth they are clearly going to

14 take much more medicine than if somebody waits

15 three or four hours.

16 The example that comes to mind is when we

17 prescribe medications for a patient 2-4 mg every 3

18 hours. What our patients will do sometimes is to

19 take 2 mg but then, because they have taken the 2

20 mg they decide they have to wait the full 3 hours

21 before they take an additional 2 mg, even though

22 the intention was for them to be able to take up to

23 4 mg in that period of time.

24 What I am suggesting really is that in the

25 label what it probably ought to say is something

101

1 along the lines of the minimum time a patient

2 should wait before taking a second dose is two

3 hours, and that would be dictated more by the onset

4 of action rather than the time at which the

5 medication would run out, and that the maximum

6 number of pills allowed in the first 24 hours is

7 such-and-such, and allow physicians essentially to

8 give patients the right to take enough medicine to

9 achieve the relief that they are entitled to get in

10 a safe circumstance.

11 DR. FIRESTEIN: Larry?

12 DR. GOLDKIND: Particularly for an opioid

13 that may be a good model. The problem is if you

14 have a non-opioid, there is a whole different

15 mechanism where the dose response curve is not

16 quite as clean. If you tell somebody, based on

17 safety, you can take another dose in a couple of

18 hours, we don\'t really know that that second dose

19 will benefit other than the placebo effect.

20 DR. FARRAR: Could I respond to that? I

21 agree with that, in which case I think the issues

22 that were brought up before about the 25 percent

23 non-response, or the time point at which 75 percent

24 of the patients still have an effect would be a

25 reasonable dose interval where 25 percent had

102

1 started to take an additional dose, as long as that

2 is a safe dosing regime.

3 DR. GOLDKIND: We do get data submitted

4 that has it in quartiles and the median is simply

5 the one that is highlighted. It doesn\'t really

6 help in decision-making. It may help in terms of

7 approvability. It may help in labeling to have

8 that data displayed so people know when the median

9 will rescue. We would have to deal with the

10 variability of whether, again, it is responders or

11 whether it is all patients. Frankly, in the model

12 are we going to apply the dental pain or the

13 surgical setting to that description? We could end

14 up with a ten-page label if we were as informative

15 as we may discuss here.

16 DR. FIRESTEIN: Dr. Borenstein?

17 DR. BORENSTEIN: To follow-up on that

18 point, I think part of the responder aspect may be

19 the half-life of the drug. While in the label it

20 may be a certain half-life, human biology, when it

21 comes to the clinic, seems to have a much wider

22 range. So, there are some people who say, yes, I

23 can take this drug and it truly is once a day, and

24 other people really say it is twice a day and I

25 need to take it because I really experience the

103

1 lack of efficacy. So, it will have an effect

2 partly on your response, but also if you can get

3 the data which shows the range of what it may be in

4 a variety of patients so you actually can tell

5 that. Tthat actually may make for a better label,

6 that it is a range and that when you have that you

7 have individuals maybe on the short side and the

8 long side. So, you may find with your dosing that,

9 in fact, what may be once a day in some patients

10 may actually end up being twice a day and to get

11 efficacy for those individuals you will need to

12 dose it that way and the drugs will have a wider

13 range of effect.

14 DR. DIONNE: I was going to endorse the

15 proposal that Jim Witter made about acute pain

16 responders as an alternative to doing mean or

17 median responses. We are probably at the point now

18 where we are going to have a better potential for

19 understanding the basis for individual variation

20 due to genetic factors. If we have the data that

21 we are using to analyze the range of responses, we

22 could possibly better interpret what is going on

23 not only on an individual basis due to the genetic

24 variation, but also we would eventually be able to

25 form, I think, more reasonable judgments about the

104

1 safety or efficacy of a drug.

2 If there was a drug that had a very

3 effective median dose, nice duration but one out of

4 a thousand patients had a very serious adverse

5 response, we might be much less willing to see that

6 as a drug for acute pain use or eventually consider

7 it for over-the-counter use versus having the

8 perception that this drug has significant

9 liabilities or significant variabilities that

10 affect its clinical use. So, if we had a formal

11 way of doing responder analysis we could get at

12 that variability.

13 The only problem is I would hope that we

14 would derive that due to some data-driven process

15 rather than just some sort of an opinion-driven

16 process. It might take a couple of years for that

17 to evolve.

18 DR. FIRESTEIN: You mean actually use

19 evidence-based medicine?

20 DR. DIONNE: Something like that.

21 \[Laughter\]

22 DR. FIRESTEIN: Dr. Wood?

23 DR. WOOD: It is important to recognize

24 that the duration of effect is not a simple

25 relationship to the pharmacokinetic half-life. The

105

1 duration of effect would depend on the time for

2 which the plasma concentration is above the minimum

3 effect of concentration. At a high dose that might

4 be very long and at a low dose that might be very

5 short, both of which might not be obviously related

6 to the half-life. So, the pharmacokinetic

7 half-life is not a good measure of the effect and

8 duration, and probably should be ignored, except in

9 the sense that, obviously, a drug with a very short

10 half-life will likely last less time than a drug

11 with a very long half-life unless the drug with the

12 very short half-life can be given at doses that are

13 way above the minimum effect of concentration.

14 DR. FIRESTEIN: Let\'s spend the last

15 couple of minutes talking about point three, which

16 is how does one determine if a difference makes a

17 difference. Would you like to get us going since

18 you are the one who generated that pithy quote?

19 DR. KATZ: Sure. I think it is actually

20 Yogi Berra or somebody like that. But I think it

21 is an empiric question and just needs to be

22 explored empirically in the context of whatever

23 model one is looking at. John Farrar has done some

24 very nice work in looking at clinically important

25 difference in neuropathic pain and I think, John,

106

1 you found that it was about 30 percent reduction in

2 pain.

3 We have done some work in a chronic back

4 pain study that Dr. Borenstein participated in. In

5 the analyses that we have been doing it looked more

6 like 50 percent pain relief was associated with

7 global measures and other signs that were the

8 marker for meaningful pain relief. So, I think it

9 depends on the individual model and it is an

10 empiric question.

11 DR. FIRESTEIN: Vibeke, in the arthritis

12 studies with visual analog scales, what have you

13 found to be something that is significant?

14 DR. STRAND: I will show you this during

15 my talk, but basically we found that it is about 30

16 percent, 30-36 percent, looking at correlations

17 with patient global assessments for various other

18 parameters, such as HAQ, disability index and so

19 on. It is about 18 percent above placebo. As we

20 just talked about, Dr. Farrar\'s work across ten

21 trials, randomized, controlled trials in multiple

22 different kinds of pain was very consistent. It

23 was approximately 30 percent. By VAS, we think

24 that the test/retest variability, if you are using

25 100 mm scale, is about 20. So, when you get to

107

1 about 30 you have a minimum clinically important

2 difference. That seems to work no matter what kind

3 of a VAS scale you are using. Again, I will show

4 you some of that data later.

5 DR. FIRESTEIN: Dr. Sherrer?

6 DR. SHERRER: I might be assessing a

7 rescue medication use because I think that is the

8 patient\'s indirect way of telling us what is

9 adequate if the pain medicine is adequate by itself

10 and they don\'t have to be rescued. If they have to

11 be rescued, no matter what the pain relief was, to

12 me, it was not adequate. It doesn\'t mean that that

13 drug is not useful. It may be useful in

14 combination but, to me, if the patient has to be

15 rescued they are telling us whatever it did, it

16 didn\'t do enough.

17 DR. DIONNE: I was just going to add to

18 the discussion of what is the minimally effective

19 increment of pain improvement. We did a study in

20 the oral surgery model with about 125 patients

21 starting with either moderate or severe pain. We

22 slowly titrated a nonsteroidal anti-inflammatory

23 drug IV until they reached a point where they

24 pressed the stopwatch, and then we had them fill

25 out their category in VAS scales. It was startling

108

1 that it came out to be about 50 percent pain relief

2 across the different types of pain intensity in

3 different scales.

4 DR. MAX: I have two concerns about

5 setting a minimally significant clinical

6 difference. One is that I am afraid of approval

7 creep. Now it is enough, given a reasonable safety

8 record and a sense of clinical usefulness, if you

9 just beat placebo within an acceptable alpha level.

10 I am afraid if you establish that you need to have

11 really 15 percent pain relief, the requirement may

12 creep into being that the studies need to be

13 statistically significant above that level.

14 Alternatively, I want to point out that it

15 really depends upon the context and the side

16 effects. If you had an analgesic that looked safe

17 and had no, say, cognitive side effects, you could

18 add it to most of the analgesics that are sedative,

19 and even if you only got five percent or ten

20 percent additional relief, it is cheap enough and

21 it would be a very welcome addition. So, I would

22 want to leave this to the case by case judgment of

23 the agency.

24 DR. STRAND: Could I just clarify for a

25 minute? I don\'t think we are talking about MCID

109

1 based on one outcome measurement as defining

2 clinical response. That is why I would like to put

3 this off until this afternoon when I present.

4 But I think what we are really trying to

5 talk about is where do we see minimum clinically

6 important differences in various parameters. The

7 way they become useful is if you now combine those

8 parameters that are not closely related into some

9 type of an analysis for responder. All of this has

10 to be done as evidence based.

11 DR. MAX: Yes, and it just depends

12 comparing to the safety profile of the clinical

13 context.

14 DR. FIRESTEIN: Dr. Cush and then Dr.

15 Elashoff, and then we will take our break so that

16 we don\'t have break creep as well.

17 \[Laughter\]

18 DR. CUSH: I just want to go back to

19 Yvonne\'s suggestion, and I agree that the use of

20 rescue medication is certainly an important measure

21 and I think one that is useful for analysis, but I

22 am also bothered in doing clinical trials where we

23 use rescue medicine, especially in osteoarthritis,

24 by the number of patients who refuse to use rescue

25 medication despite their pain. I can\'t quite

110

1 explain that. I know they have pain but they

2 continue to not want to use the analgesic medicine

3 we give them. So, I somehow fear that we may be

4 missing an important outcome if we rely too heavily

5 on that one measure. That needs to be included but

6 I don\'t know that it can be a primary outcome

7 measure.

8 DR. ELASHOFF: Any time one feels one

9 needs multiple measurements in order to understand

10 what is going on, you are either left with trying

11 to sort of put them together after the fact, after

12 they have all been measured, or defining some

13 arbitrary combination of them. There is always an

14 arbitrary character to that, and if you define

15 things ahead of time then you are liable to lose

16 information later on. But there is always a

17 tradeoff. There is no way to totally win this

18 situation.

19 Dr. Cush\'s remarks about the rescue

20 medication issue are certainly important ones. The

21 advantage of that particular type of outcome\--or at

22 least if we don\'t think of it so much as rescue but

23 amount that they would actually take if left on

24 their own, the advantage of that kind of outcome

25 measure is that it is directly related to the

111

1 safety issue in a much clearer way than some of the

2 other outcome measures one might be talking about.

3 DR. FIRESTEIN: Dr. Simon?

4 DR. SIMON: Just before the break, if you

5 will give me a minute, there are a couple of

6 questions that arose in the previous discussion

7 that weren\'t really answered by us. One was Dr.

8 Katona\'s question about were there other

9 alternative designs besides a placebo-controlled

10 trial. That would be appropriate and, yes,

11 obviously an active comparator would be an

12 acceptable way to go for an acute pain trial in

13 children, elderly, in any number of different ways

14 to do that, background therapy, withdrawal therapy

15 as has been done in children before, though I am

16 not that enthusiastic about withdrawal therapy in

17 adults despite what came up yesterday and I am sure

18 we will discuss that part again.

19 Number two, there was an interesting

20 discussion about acute pain, time to onset of acute

21 pain, differentiation from placebo and preemptive

22 anesthesia. I would like to point out that we are

23 willing to consider that as an entirely

24 disassociated issue, meaning, we have to create a

25 label that patients understand how to use drugs.

112

1 We believe the time to onset of an hour

2 may be important to patients as opposed to two

3 hours, although I do not want to get into a

4 discussion, as we did in \'98 on fast, faster or

5 fastest because, in fact, that is not really

6 informing us anything. The reality is that there

7 may be the need for an entirely different

8 indication of preemptive anesthesia rather than

9 acute pain because, in fact, that is a different

10 issue and it would affect different patients.

11 There are not a lot of patients walking around with

12 a toothache who need preemptive anesthesia as

13 opposed to acute pain relief.

14 The third issue is the issue of effect

15 size that Dr. Elashoff referred to before. It

16 refers back to what Dr. Max was talking about,

17 which is that we have to be familiar with MCID

18 because if we don\'t consider that the sponsors, not

19 because they are bad people but because they have

20 accrued a lot of patients in a trial, can then have

21 enough patients to show a statistically significant

22 difference from placebo yet, in fact, the effect

23 size is entirely unimportant.

24 Part of that is bias and a take on how big

25 is the effect size. It might be nice to know that

113

1 an effect size is evidence-based and defined by

2 what is minimally clinically important, and that

3 may be very important because of the number of

4 patients you could recruit. You can\'t just make

5 your study be positive.

6 DR. FIRESTEIN: Thank you very much for

7 clarifying those issues, and we will take a break

8 now. We will start again in exactly 15 minutes,

9 10:45.

10 \[Brief recess\]

11 DR. FIRESTEIN: Can the members of the

12 committee please rejoin us? In this session we

13 have an open public hearing. Then, we are also

14 going to try to clarify or revisit some of the

15 questions that were raised yesterday with regard to

16 chronic pain indications. We have two speakers,

17 Dr. Eugene Laska who has been allocated ten

18 minutes, and then Dr. Nijab Babul who has been

19 allocated five minutes, and I would like to welcome

20 them. Dr. Laska?

21 Open Public Hearing

22 DR. LASKA: Thank you.

23 \[Slide\]

24 This little presentation is sponsored by

25 Merck, whose folks I would like to thank for their

114

1 stimulating comments and stimulating discussions

2 which led to the clarification of several issues

3 among the contributors, their ideas, particularly

4 Al Sunshine whose name I want to mention. The

5 ideas here are ones I have talked about before. I

6 apologize for repeating some of them. Lee Simon

7 and Jim Witter and Ray Dionne also deserve special

8 recognition because they are clearly attempting to

9 open up the box and make the business of

10 registration more transparent. Some day a drug

11 company will know whether they are going to get

12 approved before they make a submission rather than

13 wait for the surprise of the letter.

14 As I mentioned yesterday, the goals of a

15 randomized, controlled trial are to allow causal

16 inference; to allow the conclusion that the drug is

17 the reason for the effect we observe.

18 I want to add to that that another major

19 reason for doing clinical trials is to get point

20 estimates of very important parameters which

21 characterize what the drug is all about. It is

22 instructive in trying to design clinical trials to

23 contemplate how one would use the information that

24 comes out of them; what kind of information one

25 really wants.

115

1 If one thinks about onset, duration and

2 dosing intervals as if you knew the entire story,

3 you know, the probability distribution of onset and

4 duration and response rates, you would see that it

5 is a complicated, multidimensional space that would

6 be very hard to characterize. And, what we are

7 looking to do in these clinical trials is to find

8 very, very minimally informative point estimates

9 which describe to some degree the amount of the

10 effect that we are talking about, median time to

11 onset and the like.

12 Too many measures, as Janet says, are not

13 necessarily useful, and for these trials for the

14 longest period of time we have collected data on

15 both relief, which refers to original time, and

16 current intensity. I am pleased to see the agency

17 moving to the notion of dropping redundancy at

18 least in the notion that it may be redundant in the

19 beginning but certainly long term. Good thinking.

20 The same thing is true about all of these

21 parameters. They are functions of pain intensity

22 levels. So, again, the hyper space in which these

23 characteristics are described is very, very high

24 dimensional.

25 \[Slide\]

116

1 Let me start by talking about stopwatch

2 and measure onset. I believe that it is important

3 to eliminate the two stopwatch theme that has been

4 used by many companies in the recent past and

5 return to the one stopwatch approach that measures

6 meaningful relief because I believe that that is

7 the most useful concept that can be measured, and

8 that the redundancy in having a second watch to try

9 to capture perceptible relief merely adds

10 complexity and does not really bring in enough new

11 information to warrant or justify its use. And, I

12 think that second stopwatch is a very useful tool,

13 which I will mention in a second, that cay be used

14 to look at duration.

15 \[Slide\]

16 Once one collects the data, I think it is

17 important to conceptualize the ideas associated

18 with onset as representing two subpopulations, one,

19 people who will not respond or who have not

20 responded; and the second, the group that has

21 responded. That is characterized statistically by

22 the top equation. It is called the cure model. We

23 won\'t talk about it today but it has been described

24 in the reference in the bottom of the slides. That

25 particular model conceptualizes the outcomes as

117

1 falling into two groups, the responders group and

2 the non-responders group.

3 I believe that the regulatory indications

4 of collecting data the way I have described and

5 breaking up the population into these two subgroups

6 flows very naturally. The clinical trial\'s

7 objective will be to estimate the proportion of

8 patients who respond, who get this meaningful pain

9 relief, and look at the survival distribution

10 including the median time to obtaining meaningful

11 relief.

12 \[Slide\]

13 The regulatory implications that flow from

14 that I believe fall in two camps. One is a

15 comparative camp and the other is a numerical

16 estimate camp which has to do with characterizing

17 the drug independent of another drug or placebo.

18 So, the first requirement would be that Pd

19 is bigger than Pp for the placebo group. The

20 proportion or response must be demonstrated to be

21 statistically superior on the drug than the

22 proportion who respond on placebo. Perhaps a

23 minimal difference in the proportions is called for

24 so that sample size doesn\'t dominate the decision

25 as to whether there is a proportion.

118

1 \[Slide\]

2 But then the issue of whether or not a

3 drug works within an hour or more generally within

4 T units is characterized by the second requirement

5 which only talks about absolutes, not comparators.

6 That is, the median time to onset among the

7 responders on this drug ought to be within some

8 period of time, perhaps an hour, perhaps an hour

9 and a half but more generically T. T, of course,

10 may depend on the pain intensity, the model setting

11 and a variety of other things relating to the

12 individual and the biological response that that

13 individual represents.

14 \[Slide\]

15 Perhaps more difficult to contemplate is

16 the question of duration.

17 \[Slide\]

18 Let me suggest to you that the FDA\'s

19 concerns about using the various interferences that

20 are introduced by the nurse or whoever is

21 collecting the data or deciding whether or not to

22 give that second dose is mitigated by putting that

23 second stopwatch that used to be used for something

24 else, so they are around and there is no extra

25 expense\--that second stopwatch can be used to

119

1 answer the question when is the patient no longer

2 getting pain relief.

3 The agency used to worry about what they

4 called back then the minute wars of the first

5 interview for onset at 15 minutes, demonstrating

6 efficacy, would provoke another drug company to

7 collect its first interview data at 14 minutes so

8 that they could claim faster onset. Well, the

9 stopwatch eliminates that problem and it does so

10 here as well. It removes the bias, the

11 interpersonal possible interference that the nurse

12 observer or the person who could give the next

13 medication introduces.

14 The estimating functions that would derive

15 from collecting data of that sort are exactly

16 analogous to what we would obtain in the onset

17 story. We would estimate the survival distribution

18 of time to rescue and the proportion who respond.

19 Very importantly, they do not impute a value for

20 those people who never got onset.

21 The question of how long a drug works

22 after it has worked is not informed by the

23 percentage of people or the time at which those

24 people rescue if they never got onset. it is a

25 different question. The answer to the question of

120

1 when shall I remedicate when a person is not doing

2 well on the drug I gave him is a very different

3 question from the one that asks when do I

4 remedicate after there has been a long period of

5 time where the patient has responded.

6 A number of the things that can be

7 reported along the way are the proportion who

8 respond at the various times that are convenient,

9 like 6, 12 and 24 hours; median time to rescue

10 among responders who do rescue.

11 Let me focus on that for a minute. It is

12 useful to say ten percent of the patients respond,

13 and among the ones who do\--sorry, median time to

14 rescue. Among the people who rescue, how long does

15 it take before they need rescue? That is going to

16 depend on severity and the like, but that informs

17 the notion of the time to rescue and is a

18 complement to the proportion who don\'t rescue.

19 Those different arms are the reason I described in

20 the beginning the hyper dimensionality of the

21 outcome space when you do a clinical trial of this

22 kind. To mix them up is to blur and lose

23 information about what is actually transpiring.

24 \[Slide\]

25 The regulatory implications of choosing a

121

1 dosing interval on this basis has to do with, in my

2 view, a compromise between the wide range of dosing

3 intervals that are absolutely necessary, that all

4 of the clinicians on this panel discussed in the

5 last hour but, nonetheless, if the agency chooses

6 to characterize with one number, I think that

7 number is the median despite the comment that I

8 don\'t want the other half of my patients to do

9 poorly because the dosing interval is honored in

10 the breach. So, if this is the one number you want

11 to produce, I think you are stuck with the median

12 and, therefore, the dosing interval is some number

13 less than or equal to the median time to rescue.

14 I believe the limitation that you place on

15 providing information in the label is a very

16 artificial one, and the notion of posting

17 information on the web doesn\'t need to be defended.

18 You don\'t need to hide behind the label to describe

19 what happened in the trials; put them out some

20 other way. Once they are out, clinicians will find

21 a way to use them if they care to find out the

22 information.

23 So, the regulatory implications are that

24 the percentage of patients, the second point, who

25 need rescue is significantly less than the

122

1 proportion of patients who need rescue on placebo

2 among the people who responded to placebo. That

3 would need to be demonstrated statistically.

4 The first point, the comparative one, the

5 absolute is that the proportion of responders is

6 less than some fixed time point, and that is less

7 than a half.

8 \[Slide\]

9 Just one comment quickly on Larry\'s

10 feeling that return to baseline is a flawed metric.

11 I think one can conceptualize this whole idea as

12 the complement, the counterpoint to the responders

13 analysis. If you like, this is the failures

14 analysis and patients will return to baseline

15 individually. The argument that the mean does not

16 return to baseline doesn\'t mitigate against the use

17 of return to baseline or no longer getting

18 meaningful relief on an individual basis, and it is

19 the counts of how many of those people there are as

20 well as the time to the event that makes the game

21 playable.

22 \[Slide\]

23 So, clearly informed by PK and informed by

24 the experience of the clinical trials in the acute

25 phase, one has to look at multiple days and the

123

1 question is what to do in that context and I had to

2 think about it. My view is that this is not the

3 place to be exploring dose response. In the very

4 mild pain circumstances where pain is almost gone

5 the next day, it makes no sense to me statistically

6 as a statistician to impute data from day one to

7 day two to show artificial differences which are

8 not real.

9 I believe that you can only sustain the

10 notion of what the effective dosing interval that

11 has been proposed and see if it makes patients

12 \"happy.\" So, at the end of day in these mild cases

13 there should be no need to demonstrate superiority

14 to placebo, but the proportion of patients who

15 require rescue ought to be smaller than some

16 absolute number that is credibly determined on a

17 judgment basis.

18 \[Slide\]

19 For more serious pain or perhaps severe

20 pain models were PRN narcotic is required, I see no

21 alternative to the idea of using the dose sparing

22 property of the drug.

23 \[Slide\]

24 There is an old rule that every animal

25 pharmacologist will ascribe to, I am sure, that

124

1 says if you fix dose, study outcome. If you fix

2 outcome, study doses. In the dosing sparing

3 setting where you use PRN narcotics you are fixing

4 an outcome. Patients titrate to adequate relief.

5 The only thing to study is the amount of narcotic

6 that is spared. It is sensible and there are

7 caveats raised by others in the group here about

8 interaction, about promoting side effects.

9 Remember, this drug has been studied in the acute

10 setting. It is known to be an analgesic. Now the

11 question is what does it do on day one, two or

12 three and that kind of sparing relationship, in

13 face of the knowledge from the earlier trials, is

14 pretty clearly evidence if you believe in the

15 hidden assumption\--as Jim pointed out, there is a

16 hidden assumption and in this case it is that there

17 is a dose response to the narcotic being used. So,

18 dose sparing makes sense to me as the way to

19 sustain that data.

20 \[Slide\]

21 One last situation then, we are in

22 long-term use, and I am anxious to hear the

23 objection. If chronic pain situations where

24 patients on placebo drop out at very high rates,

25 once again we are into the game of projecting

125

1 forward; we are making up data\--statisticians call

2 that imputation, to justify whether the drug still

3 works at week W where W is a big number like 12.

4 I think that makes no sense. It is a

5 circumstance, again, where we are only trying to

6 sustain the notion that this drug continues to work

7 after 12 weeks. We are not trying to prove

8 effective here; it is does the drug still work?

9 The best way to answer that question is not with

10 respect to placebo patients who drop out earlier;

11 it is with respect to patients in whom the drug is

12 working, it is withdrawn and superiority to placebo

13 in a randomized, controlled trial is demonstrated.

14 I believe that this kind of an approach is

15 a rational way of looking at onset and duration and

16 choosing dosing interval. And, I thank you for

17 listening.

18 DR. FIRESTEIN: Thank you. The next talk

19 will be from Dr. Babul, from TheraQuest.

20 DR. BABUL: Good morning.

21 \[Slide\]

22 I would like to address the committee and

23 the division on the issue of multi-dose analgesic

24 development. This is one of the questions that the

25 division has asked the committee to consider in

126

1 terms of evaluating analgesics in acute pain.

2 \[Slide\]

3 I have previously provided a conflict of

4 interest statement and that stays on record so I

5 won\'t repeat it here.

6 \[Slide\]

7 This slide shows the essential approach

8 that we have been taking for the last two decades

9 to evaluation and approval of analgesics in acute

10 pain. Certainly from an efficacy perspective, we

11 do some of those studies by screening a patient,

12 initiating some sort of an acute insult, having

13 some sort of a period of recovery when the pain

14 stimulus reaches a particular intensity, moderate

15 or severe usually. We will then dose the patient.

16 We evaluate the response over a single dose and

17 then we terminate assessments either after the

18 dosing interval is over, which is generally 8, 12

19 or 24 hours, or at the time that the patient

20 requests their first rescue analgesic.

21 \[Slide\]

22 There are compelling reasons why

23 pharmaceutical sponsors have not gone down the path

24 of efficacy evaluations in the multi-dose arena,

25 and I would like to address these and propose some

127

1 potential solutions.

2 \[Slide\]

3 There is no doubt that there is no growing

4 request for data. I recall that even at the Vioxx

5 advisory committee meeting there was discussion of

6 the availability or relative lack of multi-dose

7 data in the dossier. There have been increasing

8 requests from both Division 550 and 170 for such

9 data.

10 I think the challenge here is, if I can

11 just be frank and I guess this is for the record,

12 that our collective rhetoric perhaps outpaces the

13 actual science of drug development. In other

14 words, our methodologic ability, to echo what Dr.

15 Laska was saying, to actually tease out some of

16 those differences is not always there.

17 In order to address this issue of

18 multi-dose analgesic evaluation from an efficacy

19 perspective, we need to ask ourselves precisely

20 what our objectives are. Are they to establish

21 efficacy? Are they to demonstrate effectiveness?

22 Are we trying to establish dosing frequency? Are

23 we trying to prospectively test a draft package

24 insert? Or, are we merely trying to provide some

25 sort of supportive safety data in a perioperative

128

1 setting where perhaps patients might be critically

2 ill and otherwise compromised?

3 \[Slide\]

4 Here are some of the challenges to

5 evaluating these drugs in acute pain. The first

6 issue, and this has been alluded to earlier, is

7 that the natural trajectory of acute pain is such

8 that, whether treated or untreated, for the most

9 part it diminishes. To be sure, and Dr. Katz

10 referred earlier to thoracotomy patients or lumbar

11 laminectomy patients who may have somewhat

12 long-term pain. To be sure, some patients may have

13 a longer trajectory, but a majority of these

14 patients have a relatively short trajectory. So,

15 this introduces an issue that most analgesiologists

16 have called assay sensitivity.

17 We are also faced with a reduced duration

18 of hospitalization. A significant number of

19 patients after major surgery are home within four

20 days to a week\'s time.

21 There is also a growing trend towards

22 surgical techniques that reduce surgical pain. For

23 instance, hip arthroplasty, as is currently being

24 conducted, requires substantially less

25 postoperative opioids than perhaps 10 or 15 years

129

1 ago and this presents a bit of a challenge.

2 Furthermore, patients will sometimes

3 refuse to consent to multi-dose placebo controlled

4 studies. It is one thing to convince patients to

5 do a single-dose placebo controlled study, but to

6 tell them you are going to repeatedly be give

7 placebo over the next five or seven days presents a

8 bit of a challenge.

9 We also have this issue of data

10 contamination when you give rescue analgesia, and

11 we have a problem in terms of availability of

12 trained analgesic observers or nurse raters. This

13 is a very specific discipline requiring an

14 exceptionally well-trained individual who truly

15 understands analgesic methodology, and there is a

16 real shortage of such folks. Your most senior

17 study coordinator usually wants to work the day

18 shift so you have 72 hours more to go beyond that

19 to evaluate the patient.

20 \[Slide\]

21 I would like to suggest some proposed

22 approaches without getting too prescriptive. Some

23 of these have really been spurred through

24 discussions with Division 550 with Dr. Witter and

25 Dr. Simon and others. One option clearly is to use

130

1 active controls, with the Division\'s prior consent.

2 That is certainly one possibility to consider.

3 The other option is to use what I call

4 pseudo placebos. So, these would not be placebos

5 but would be perhaps ultra low dose of an approved

6 agent, to allow us to get some assay sensitivity.

7 Yet another option, and this was discussed

8 previously by Dr. Laska, is to use rescue analgesia

9 as an endpoint. This has been used successfully

10 but only with a modest degree of success in the

11 past.

12 We can also integrate rescue and pain

13 assessment data, and there are some techniques

14 available for that. Of course, because of the

15 shortage of trained study coordinators, we can

16 perhaps consider doing serial assessments long

17 term. We can use recall instruments to assess

18 pain.

19 \[Slide\]

20 The rationale for integrating rescue and

21 pain scores to come up with some composite scores

22 is given on this slide, and I am going to be brief

23 here. Traditional studies have tended to discard

24 rescue after the first dose. The issue is that

25 rescue tends to confound our analgesic evaluation.

131

1 Furthermore, rescue differentially confounds the

2 analgesic response. David Silverman, for instance,

3 has suggested a rather elegant but simple approach

4 to integrating rescue and analgesia scores.

5 \[Slide\]

6 Alternative approaches that are available

7 involve the use of recall instruments. We know

8 that recall, at least among analgesiologists, is

9 viewed as somewhat suspect but we, and others, have

10 shown and have published data demonstrating that

11 recall is actually quite sensitive. We have done

12 studies where we have looked at recall in

13 orthopedic pain and other models, and we think that

14 this allows you perhaps to conserve on the

15 resources that are a problem in multi-dose studies.

16 \[Slide\]

17 The last potential option that one ought

18 to consider is rescue analgesia as an endpoint. I

19 believe it is a potential endpoint. It does have

20 some risks because the variability is not

21 insignificant.

22 \[Slide\]

23 These are data that were presented in 1998

24 at the Arthritis Advisory Committee in the review

25 of rofecoxib submission. As you can see in this

132

1 particular study, over day two to five there was a

2 difference between placebo and rofecoxib in terms

3 or rescue consumption. It was a one tablet per day

4 difference. Now, whether this is clinically

5 meaningful is a separate issue but it certainly

6 provided some assay sensitivity in an attempt to

7 look for differences.

8 In summary, the methodology for multi-dose

9 efficacy evaluation is not quite cooked; it is not

10 established. I think there are some possible

11 options that are available, but we need to

12 understand that there are some compelling reasons

13 why single-dose evidences have formed the primary

14 basis for efficacy evaluation. None of these

15 techniques can meaningfully, in my opinion, answer

16 questions related to the time course of effect and

17 dose response. Those questions, and they are

18 critical questions, need to be addressed in

19 single-dose efficacy evaluations. Thank you.

20 Further Discussion of Criteria for

21 Chronic Global Pain

22 DR. FIRESTEIN: Thank you very much. At

23 this point Lee has asked us to revisit our

24 discussion of the proposal for the criteria to

25 obtain a chronic global pain indication. Just to

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1 remind people, there are two essential issues. One

2 is that for such an indication the proposal was

3 that three separate models would need to be

4 explored, and in each of them there would be three

5 separate domains that would have to be all

6 positive.

7 So, what we are going to do now is

8 actually go around the table and get people\'s

9 opinions on those issues. I would ask that people

10 restrict their comments to two minutes or less.

11 Please don\'t feel obligated to use the entire time

12 because there are about twenty of us and it will

13 take quite some time if we wax poetic.

14 I will go ahead and start and then people

15 can take various and sundry pot shots at my

16 comments, either amplify or deny them.

17 DR. ELASHOFF: I am still unclear on the

18 question.

19 DR. FIRESTEIN: The question is what do

20 the individual members feel about, number one, what

21 the criteria should be for a chronic pain

22 indication, with the initial proposal that there be

23 three separate indications explored in order to get

24 labeling for chronic pain.

25 DR. SIMON: Global chronic pain indication

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1 with three areas of etiopathogenesis that would

2 have to be studied with three domains as

3 co-primaries in replicate trials.

4 DR. FIRESTEIN: So, those are the two

5 separate issues that we should comment on. Does

6 that clarify that?

7 DR. ANDERSON: But what are domains?

8 DR. SIMON: To remind you, they were

9 patient global, function and a pain score. It is

10 just in chronic pain. I know we have just talked

11 about acute pain but we didn\'t get enough clarity

12 yesterday for us to know exactly what you all felt

13 about our proposal.

14 DR. FIRESTEIN: We were appropriately

15 obtuse. So, I will start and then we will just go

16 around the table. For introductions we went to my

17 left and this time we will go to my right.

18 There were a number of other proposals

19 that were also made with regard to the number of

20 indications. First of all, I think that the bar

21 should necessarily be high for a global chronic

22 pain indication. The question whether it should be

23 two, three, four or five indications is really not

24 well defined by evidence-based medicine but, based

25 on opinion, three doesn\'t sound like a lot and four

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1 sounds okay and five sounds like a lot. So, by

2 process of elimination, four sounded reasonable to

3 me.

4 The other issue is whether or not you need

5 replicate trials for a global pain indication. It

6 seems to me that the indication is global pain, not

7 the individual models. So, for instance, a

8 confirmatory trial would not be a second OA trial

9 but a second trial in another indication,

10 preferably different mechanism, and I think there

11 needs to be considerable care with regard to

12 choosing how one selects the different models,

13 making sure that there is adequate representation

14 from multiple mechanisms\--neuropathic pain,

15 musculoskeletal pain, cancer pain, etc. So, from

16 my perspective, it seems to me that a single trial

17 with more indications makes sense.

18 With regard to the domains, the main issue

19 is that function may not necessarily be a

20 reasonable endpoint for some of these indications,

21 as was pointed out yesterday, and I think there

22 needs to be some flexibility in endpoint selection.

23 Pain is obviously going to be the more important

24 one and function may be less important in certain

25 patients where strictly comfort is all that

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1 matters.

2 So, why don\'t we move off to the right?

3 Dr. Brandt? Was that clear enough?

4 DR. BRANDT: Fundamentally, I think I

5 agree with Gary. The complexities in the science

6 that drives chronic pain, as we heard yesterday, I

7 think are very significant and it makes it hard to

8 reduce this in terms of a limited number of models

9 of disease states in which a drug shows efficacy to

10 be comfortable that that truly gives enough

11 information for a global pain indication. So, I am

12 more comfortable considering pragmatics. I think

13 it would be reasonable.

14 I think we regard to the outcome measures,

15 certainly pain, certainly patient global, and I

16 think that you have to look at function in terms of

17 the specific disease state that is more relative to

18 certain diseases than it is to others, as we heard.

19 But I think the greater breadth that would be

20 provided by demonstrated efficacy in four disease

21 states for chronic pain has appeal to me, and

22 perhaps more than looking at three times with the

23 six-pack.

24 \[Laughter\]

25 DR. KATONA: Looking at the issue from the

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1 pediatric point of view, for the chronic model it

2 will be very difficult to recruit enough patients

3 since out of the four proposed models really the

4 only one which could be found in children in great

5 numbers is the cancer pain. Children have no OA,

6 very rarely low back pain, a low incidence of

7 neuropathic pain. So, I think the study is going

8 to be limited. The acute model I think is very

9 important in children. So, those two will have to

10 be concentrated on.

11 As far as efficacy, I think we always rely

12 a lot on the adult trials and I think we definitely

13 will do the same. However, I think the PK studies,

14 the dosing schedule and especially the safety are

15 going to be extremely, extremely important in

16 children. So, I think those are going to have to

17 be conducted and these have to be long term. Thank

18 you.

19 DR. ABRAMSON: I would maybe take a

20 slightly different position at least from Ken and

21 Gary on this. I mean, chronic pain is a very broad

22 term. Although it is clinically a very important

23 issue, the name of the term itself is like the 1899

24 Merck Manual of Hepatology or lumbago and I think

25 we have to be careful in setting a bar for a

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1 broader indication that the elements within that

2 indication are robust in the way that they are

3 looked at from the term etiopathogenesis that Lee

4 used.

5 Therefore, whether a global pain

6 indication requires three, four or five individual

7 etiopathogenic syndromes, I think the bar for each

8 of those syndromes has to be as high as it would be

9 for anything else that a drug is getting approved

10 for, namely, two replicate pivotal studies for

11 example.

12 When you talk about domains in these

13 studies, the domains may vary within the syndrome

14 you are looking at, whether it is neuropathic pain,

15 low back pain, osteoarthritis pain, etc. So,

16 clinical outcomes, meaningful clinical responses,

17 things that you might tag on to look for mechanisms

18 of pain will vary within each of those.

19 So, I would make the argument for keeping

20 the bar very high for any individual entity of the

21 individual syndromes that need to be looked at,

22 recognizing that fibromyalgia is different from low

23 back pain and the musculoskeletal indication for

24 example.

25 Then, whether one gets for marketing

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1 purposes a more global indication will depend on

2 three, four or five very highly rigorous standard

3 replicate studies that would have been required for

4 independent registration.

5 DR. FIRESTEIN: Lee, would you just

6 comment on whether or not this would change the bar

7 for individual indications? In other words, that

8 is a separate issue I think.

9 DR. SIMON: No, in fact, the bar, as we

10 have described it in my earlier discussion, for any

11 one indication with two replicate trials with three

12 domains is obviously open to discussion based on

13 which domains, but we would like patient global

14 pain and a functional domain. It is particularly

15 applicable to osteoarthritis but it may not be

16 applicable to all of them. So, that would not

17 change an individual indication issue.

18 What we are really discussing here is, is

19 that high bar too high for the global chronic pain

20 indication? And, we each have our opinion and that

21 is what we are waiting to hear.

22 DR. WITTER: I just want to add a thought,

23 and I think Dr. Katz brought it up yesterday. As

24 you think about this, I mean, we are interested in

25 labeling that makes sense to you as clinicians and

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1 also to your patients. So, were we to construct

2 chronic pain, the big claim, you know, I think you

3 need to think through your current repertoire of

4 medicines and ask if they should be able to reach

5 that hurdle. If they do, then what implications

6 does that have for whatever claim structure we

7 might set up because would we be creating something

8 and everybody would get it and may not have what we

9 had hoped down the road. So, I think maybe you

10 want to think about that as well.

11 DR. MANZI: I think when I was thinking

12 about this the one assumption here that is probably

13 true is that the number one biggest problem

14 probably in the U.S. is that we under-treat chronic

15 pain, more than abuse of medications or

16 over-treatment. So, with that in mind, I said what

17 would the advantage be of having a global

18 indication more than industry incentive in some

19 way? What advantage to the patient?

20 I guess from that perspective, I actually

21 would presume that a global indication may open the

22 door for a broader application of some of the

23 potential medications in patients with chronic

24 pain.

25 With that in mind, I would say what are

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1 the downsides? The downsides may be that it is not

2 as effective in certain disease states or that

3 perhaps in certain subpopulations it may not be

4 safe. I think those are clear concerns.

5 With that in mind, I guess my perspective

6 is that I might actually consider lowering the bar

7 a bit and say is it really safety issues and

8 efficacy that we are worried about, or do we really

9 want to open up to our patients the availability of

10 a broad range of potentially helpful agents for

11 treating chronic pain?

12 With that said, this is arbitrary but I

13 would say I would go a little lower with perhaps

14 the three entities not having to capture every

15 pathophysiologic mechanism for pain because I am

16 not sure that is even possible, obviously, keeping

17 the individual rigor that the FDA does already with

18 each of those entities. So, I think I would favor

19 more a slightly lower overall bar to get a global

20 label for the reasons that I mentioned.

21 As far as the domains, I agree with the

22 previous speakers that I think you have to a priori

23 determine which domains are relevant to the disease

24 state that you are looking at and decide what the

25 success is in each of those and not make a standard

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1 requirement across the board for each population.

2 DR. KATZ: I feel more comfortable

3 articulating some general principles relevant to

4 this discussion, rather than just throwing out a

5 number of five, three or something like that. So,

6 I don\'t know if my comments will help you in any

7 way but I will go ahead and take my two minutes or

8 less anyway.

9 First of all, there has been a great

10 debate as to whether giving an overall

11 categorization for acute pain, chronic pain, or

12 what-have-you, is appropriate. My feeling is that

13 the opioids have taught us that it is possible to

14 have a class of drugs that are broad spectrum

15 analgesics for just about all kinds of pain. So, I

16 think that the notion of a broad spectrum analgesic

17 does have construct validity.

18 Number two, I think the opioids have also

19 taught us that just because a drug has broad

20 spectrum applicability in acute pain, chronic pain,

21 it doesn\'t mean that it is going to work for all

22 subcategories or all populations or all people. I

23 think that is fine and it should not dissuade us

24 from giving a broad sort of labeling, although it

25 would be nice if we had some way, through the label

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1 or otherwise, to educate physicians that just

2 because a drug has a broad label doesn\'t mean it

3 will work for everybody and it doesn\'t relieve them

4 of their responsibility to manage their individual

5 patient or different disorders.

6 I think acute pain as a category does have

7 construct validity and I think chronic pain as a

8 category does have construct validity too. It

9 seems to me that in order for something to be

10 called a medication for chronic pain, it needs to

11 work for neuropathic pain as a broad construct and

12 also for musculoskeletal pain because drugs that

13 work for musculoskeletal pain may not work for

14 neuropathic pain, and vice versa. So, it is

15 inconceivable to me that something could be called

16 a medication for chronic pain without working

17 robustly in both of those different categories.

18 So, I wouldn\'t see it possible to label a

19 drug for chronic pain unless one could also label

20 it for neuropathic pain broadly and one could also

21 label it for musculoskeletal pain broadly, with

22 whatever robustness of evidence one would need in

23 each of those individual subcategories.

24 We have just had a meeting for a whole day

25 and talked about neuropathic pain and what sort of

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1 trials would be necessary for that. People have

2 thought that you would need a six-pack or more just

3 for peripheral neuropathic pain, let alone chronic

4 pains. That is a big discussion and I am not going

5 to try to summarize it all here, but I think it is

6 important to just say that you have to be confident

7 of neuropathic pain before you get to the point of

8 chronic pain.

9 In terms of the issue of replicate trials,

10 personally I find it much more useful to see

11 different trials in different disease entities than

12 in the same entity. For example, two identical

13 replicate trials in osteoarthritis don\'t help me

14 nearly as much as one good trial in osteoarthritis

15 and one good trial in some other kind of

16 musculoskeletal pain like low back pain or

17 rheumatoid arthritis, or something like that. I

18 think that is where the information comes in. So,

19 personally I would discourage replicate trials and,

20 if you are looking for a broad categorization, then

21 try to get as broad an experience as possible of

22 disease entities within that category.

23 Lastly, in terms of the issue of the

24 requirement for the three co-primaries, my

25 experience suggests to me that that is an

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1 absolutely wrong approach. I think it is obvious

2 that if a drug reduces pain but does not

3 necessarily improve function, quality of life or

4 whatever, it is still an analgesic.

5 On the other hand, I think that those are

6 very, very fundamentally important secondary

7 outcome variables that will differ from disease to

8 disease and can also help us understand the meaning

9 of the primary and borderline cases or unusual

10 cases. I think the data should definitely be

11 collected. It should be required but not as

12 co-primaries for developing analgesics.

13 DR. ANDERSON: I actually agree with quite

14 a lot of what Dr. Katz said, although I disagree

15 about the domains. First, I didn\'t like the idea

16 of this global indication at all because I just

17 don\'t think a single drug can do it all and also

18 retain function. Also, it seems to me that it

19 would be abused in the sense of, you know, you had

20 all your three areas or even six areas where you

21 showed it worked it would be used in many more

22 where it might not work at all or might be unsafe.

23 So, I think that you should just stick

24 with what you have at the moment, which is for any

25 particular indication, pathogenesis area or

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1 whatever, you have to have two trials, perhaps with

2 a different disease.

3 I think that the three domains are all

4 important. Okay, this is an analgesic but it is

5 more than an analgesic. You know, for an analgesic

6 which is just for acute pain, then, okay, pain is

7 the only outcome that matters. But for an

8 analgesic that is for chronic pain or long-lasting

9 pain, then it is not much use unless the person can

10 have function unless you are talking about terminal

11 illness where there is no hope for that. But I

12 think that we would want to use these drugs in

13 cases where people want to retain and improve

14 function. So, function, patient global and pain

15 score I think are equally important and should all

16 be kept and be required.

17 DR. ASHBURN: I am an anesthesiologist who

18 has left the OR to take care of patients who have

19 chronic disease over long periods of time. So, as

20 a result, I am used to having conflict within

21 myself.

22 \[Laughter\]

23 I think that this is one of the areas

24 where I have mixed feelings. In a global area I

25 think it is really important to recognize that

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1 individuals who have complex chronic pain disorders

2 require more than one medication. They frequently

3 benefit from polypharmacy with medications targeted

4 towards specific issues and specific individual

5 patients. They frequently have depression; they

6 frequently have sleep disorders; frequently have

7 anxiety. They also have social issues that need to

8 be addressed by cognitive behavioral therapy. They

9 also have physical dysfunction and require

10 activating physical therapy. To a certain degree,

11 it is almost disingenuous to think that one

12 medication could be useful as a global indication

13 for chronic pain.

14 The other thing that even makes it more

15 difficult in that area is that pain management

16 physicians and physicians in general tend to be

17 enamored with the use of unproven techniques in

18 this patient population. I think that that poses

19 some concern with regard to safety.

20 On the other hand, six well-controlled

21 trials for the indication seems to be an extremely

22 high bar. Drilling down to the specifics, I am a

23 little bit worried about the specific definitions

24 of group as far as how you define, how you group

25 patients. One concern that was already brought up

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1 is how would you study children, and for

2 essentially orphan children who have chronic pain

3 in these areas. Clearly, designing six

4 well-controlled clinical trials that include

5 adequate numbers in children would be extremely

6 difficult. Do you do it by mechanism? Do you do

7 it by cancer? We have already heard discussions

8 that patients who have metastatic cancer don\'t

9 necessarily have one etiology of their pain but

10 frequently have multiple ones that are working

11 simultaneously, and is that a meaningful patient

12 population to study? Or, do you do it by body

13 location, which also is fraught with all sorts of

14 problems?

15 My concern is that if you set the bar too

16 high companies will go for a narrow indication,

17 which may be appropriate but, on the other hand, a

18 narrow indication will lead towards less data on

19 safety in different patient populations, which I

20 think would be very helpful in guiding use.

21 With regard to a patient global

22 indication, I think that this is something that

23 probably ought to be required but I have a concern

24 about it being used as a primary endpoint to

25 determine approval. I think having six positives

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1 is very, very difficult. Also, I don\'t know that

2 the patient global assessment is well defined in

3 the literature, and whether or not that assessment

4 tool, which has become very common, has been

5 validated in a meaningful and appropriate way and

6 is used in a uniform and consistent manner.

7 Lastly, most of the function scales have

8 multiple different measurement tools and they have

9 to be well defined with regard to how you would

10 affect function. The usefulness of a tool will

11 vary by patient populations. So, it is possible

12 that you will be offered different function

13 assessment tools for different patient populations

14 and you will not be able to combine that in a

15 meaningful way. Again, with pediatrics there is

16 very little data on validated disease-specific

17 measures of health in children with pain, and even

18 less data on children at the end of life. As a

19 result, children are again going to be orphaned.

20 An alternative is to require the use of

21 validated, as best one can, disease-specific

22 measures of health specific for the population to

23 be studied in each individual trial and use that

24 data, not necessarily solely for determination of

25 approvability, but use that to inform the label.

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1 Thank you.

2 DR. ELASHOFF: I don\'t feel well enough

3 informed to comment on the issue of how many

4 separate indications one might make or what they

5 would be. However, I do feel that each one going

6 into that should have sufficient information. So,

7 I feel very strongly that you should have replicate

8 studies.

9 In terms of the outcome domains, probably

10 each indication is going to need somewhat different

11 ones, but the whole issue that I am concerned about

12 is that all this needs to be extremely carefully

13 defined before the study is started or, perhaps

14 even before you talk about an indication for a

15 specific area which things ought to be measured.

16 the whole issue of exactly how one is going to deal

17 with multiple co-primaries on a statistical basis,

18 what you are going to do about alpha levels what

19 the implications of this are for power, you will

20 probably need to look very closely for each

21 indication at how correlated these things are

22 because that is going to have a great deal of

23 influence on the powering of the study. If they

24 are very highly correlated you are in essence only

25 asking for one of them. If they have very low

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1 correlation, then you may well need bigger sample

2 sizes.

3 The other thing that wasn\'t put into the

4 question, although some people have mentioned it,

5 is that I think the safety requirements, the safety

6 information that you would need if you are going to

7 have a global indication should be far greater than

8 for any single indication.

9 DR. FIRESTEIN: Dr. Farrar, you are up.

10 DR. FARRAR: I guess from my perspective,

11 understanding that no drug is going to be perfect

12 and that every drug is going to fail at something

13 and that FDA approval is being used more and more

14 to limit payment for therapies by insurance

15 companies, I am in favor of a global indication to

16 allow me to use medications in patients for which

17 there is good clinical trial evidence that they

18 work but which may not have been submitted to the

19 FDA for formal approval, which is really very often

20 driven by costs and marketing considerations.

21 As such, I think it is reasonable to think

22 of a global indication. In fact, I would favor two

23 trials in syndromes which are clearly neuropathic

24 and would also request that those be in separate

25 entities but clearly neuropathic, and two trials in

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1 what are clearly somatic pain, also two separate

2 entities as being the bar for efficacy.

3 In addition, since patients really are the

4 defining factor in terms of whether a medication

5 works or not, I think that the global outcome is

6 exactly the right measure provided it is done

7 correctly, and I think it can clearly be done

8 incorrectly. By correctly, what I mean is that it

9 is supported by several other outcomes that are all

10 going in the same direction. To have a global

11 outcome that is by itself I think would be

12 incorrect.

13 In this setting, however, the most

14 important issue and the thing for which the bar

15 needs to be set the highest is safety. If the drug

16 is going to be used or potentially used in a wide

17 variety of patients, it needs to be shown to be

18 safe in those populations, in specific, the elderly

19 and children. It may be hard to find enough

20 children to demonstrate efficacy in all of these

21 areas, but if I know that it is going to be safe I

22 would be willing to try it, and maybe clinical

23 trials that are done outside of FDA approval will

24 help to guide my therapy.

25 Lastly, I would like to suggest that

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1 perhaps there needs to be a different study that is

2 called perhaps a labeling study. We look at dose

3 in a Phase II trial, but maybe we need to look at

4 dose in Phase III(c) or perhaps even in Phase IV to

5 help us answer some of these questions that have

6 been raised in terms of whether a 50 percent

7 response time is the appropriate dosing schedule if

8 it, in fact, limits our use of the medication. In

9 actual fact what we are talking about is limiting

10 the use as opposed to providing real benefit in

11 terms of the guidance for use. So, those would be

12 my suggestions.

13 DR. BORENSTEIN: My thoughts on the

14 subject have to do with trying to follow the

15 clinical situation with the clinical setting. If

16 we are going to have a chronic pain indication on a

17 general basis, those situations for an individual

18 neuropathic pain versus low back pain versus even

19 osteoarthritis may not be quite the same. My hope

20 would be that the FDA would allow studies to be

21 done that could show potential efficacy that would

22 mirror the clinical situation. Now, it may make it

23 a little bit more difficult because the trials may

24 have a different look to the patients that would be

25 admitted and things of that sort. But it would

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1 have greater applicability to what the clinical

2 situation is.

3 So, whether that would be three or four

4 settings where it would follow what would be

5 happening in the clinical situation, that would

6 make it much more applicable. So, this idea of

7 either having multiple drugs and adding or

8 withdrawing would then be allowed so that a trial

9 for osteoarthritis might look different than one

10 with neuropathic pain versus one with low back

11 pain, but would still be accepted and how many

12 would be needed, whether that would be two of each

13 in neuropathic and somatic versus three, I think

14 would still need to be decided.

15 I think also very important is the idea of

16 safety and that the studies be done at least long

17 enough for us to get a handle on how these agents

18 would be used in these clinical situations. I

19 think that is very important because it is all well

20 and good to have a single drug and see whether it

21 is safe but in the real world many patients are on

22 three, four or five different drugs. They are

23 hypertension drugs; diabetes drugs. And, it is the

24 interaction of the new agent with the other ones

25 which makes it, once again, clinically applicable.

155

1 So, I think the closer we can get to the real world

2 and still do good science would certainly be quite

3 useful.

4 The last point I would make regards the

5 domains. I think a global assessment is clearly

6 very important, but I think as an analgesic, we

7 want to be sure that patients are achieving pain

8 relief and that should be the primary outcome of

9 studies. But every study should look at patient

10 satisfaction and global outlook. So, I think those

11 two at least. Then, in the appropriate setting how

12 that is affecting their daily function and using

13 the appropriate outcome measure to measure that

14 would once again be important. But, once again, I

15 think it is the clinical situation, as close as we

16 can get to it, the greater will the impact will be

17 of the information which is actually observed from

18 these studies.

19 DR. STRAND: Well, I would like to perhaps

20 give a little bit of a preview to what I was going

21 to say this afternoon, after lunch. The group that

22 I led at the NIH breakout meeting finally decided

23 on five domains that they felt were essential as a

24 minimum number of domains to be assessed in

25 clinical trials of chronic pain. They were pain;

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1 patient global; some type of measure of physical

2 function or health-related quality of life, a

3 generic measure of health-related quality of life

4 and adverse events.

5 So, what we are really talking about here

6 I think is that these need not necessarily be

7 co-primaries. As has been done in other diseases,

8 and I am not trying to shove this into the

9 rheumatoid arthritis model, one could ask for any

10 number of these five domains assessed by different

11 instruments to show improvement without the others

12 showing deterioration.

13 We could perhaps elevate patient global to

14 something like a health utilities measure, which is

15 more like the way the patient would weigh all risks

16 and benefits from the intervention in terms of

17 their pain and assess what they think of it.

18 Certainly, we talked about physical

19 function and belabored the point that it doesn\'t

20 work in metastatic cancer pain. I would simply

21 argue that what we need to be doing is looking at

22 the instrument. There are plenty of different

23 instruments that would assess domain of some type

24 of function\--the ability to perform activities of

25 daily living, the ability to even get out of bed,

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1 whatever. They can be disease specific even down

2 to the type of cancer that there is. So, I think

3 there always is some instrument that would help in

4 the clinical setting that we are looking at the

5 pain.

6 Clearly, we have to ask about pain. A

7 reason to look at a generic measure of

8 health-related quality of life, besides economic

9 assessments which might be important in

10 noon-malignant types of pain, would also allow us

11 to compare interventions across different kinds of

12 pain. If we are talking about doing, say, three

13 different models or four different models of

14 chronic pain, somatic, musculoskeletal, or

15 inflammatory as I would like to think of it, versus

16 neuropathic.

17 Adverse events are obviously quite

18 important and that was, of course, the fifth

19 domain. In terms of the fact that these domains

20 would not be closely related, if they are combined

21 in some type of a responder analysis that should

22 decrease the sample size quite significantly. It

23 certainly is true with rheumatoid arthritis. In

24 terms of saying that perhaps both the global and

25 the pain measures, whatever they might be, have to

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1 be required as improved and then the others must

2 not show deterioration, or whatever, that is

3 another way to make sure that the domains that

4 everyone thinks are most important are specified.

5 But it also makes it a lot easier than requiring

6 that any three domains be co-primaries which is

7 very difficult.

8 Finally, not to do any of this that isn\'t

9 evidence based. I have been a part of predefining

10 responder analyses on the basis of consensus with

11 there being no data, and those are fraught with

12 very much of a likelihood of failure, as Jane

13 Elashoff has mentioned. But it could be done based

14 on looking at data in Phase II with the product and

15 then defining a responder analysis based on the

16 data dredging from the Phase II studies.

17 DR. MCLESKEY: I would like to reiterate

18 what I said basically yesterday, that I think we

19 are all in this together. Our purpose, as I

20 believe I mentioned yesterday, is to advance the

21 practice of medicine and how might we best go about

22 doing that

23 The concern that I expressed yesterday, I

24 will reiterate today, and that is to study a new

25 agent in three different models of disease, each

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1 studied in a replicate fashion; each having three

2 co-primary requirements that all have to hit in

3 order to obtain a claim is, in fact, a high hurdle,

4 perhaps too high a hurdle, perhaps a hurdle that

5 you simple cannot get over. I am just concerned

6 that if industry feels that it is such a high

7 hurdle that it can\'t be achieved then that might,

8 in fact, stifle innovation, which is the antithesis

9 of what we are all about.

10 So, I just restate that again. I hope

11 that I am reflecting adequately what industry in

12 general feels, but it seems to me that the hurdle

13 that has been proposed as a possibility seems a bit

14 high and potentially challenging to a degree we

15 can\'t meet.

16 Another issue, and it has been raised by

17 previous panelists around the room, is that some of

18 those co-primaries may actually be inappropriate in

19 certain models of disease and, therefore, maybe

20 those co-primaries need to be reexamined and

21 reduced a little bit in their importance in certain

22 circumstances. Also as was previously mentioned,

23 the question of validation of some of the tools

24 also potentially deserves a closer look.

25 The discussion yesterday regarding

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1 multiple alternatives that has been reiterated

2 today reminded me of a an advisory meeting that was

3 held a couple of months ago, which Gary had

4 mentioned earlier. It was a discussion of

5 neuropathic pain and there were multiple

6 possibilities mentioned at the time, one of which I

7 will just reiterate for this group today, those who

8 were not in attendance, because I haven\'t heard

9 this particular possibility alluded to yet. As a

10 suggestion, it was that one method or one model

11 disease could be studied in replicate and then

12 other models of disease studied not in replicate

13 but in single form, sort of a combination or merge

14 of the two different proposals. At that meeting, I

15 heard mentioned that we might do a replicate

16 analysis of one model and then look at maybe two

17 other models of disease in a single study format to

18 justify a broader claim.

19 Just as an aside, Lee, I would like to

20 compliment you for mentioning yesterday and then

21 highlighting again today the fact that you are

22 proposing a subsequent meeting to examine these

23 kinds of issues more closely, more carefully,

24 perhaps in a more focused way in the presence of

25 the academic community, the presence of the

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1 regulatory community and perhaps a more meaningful

2 presence from the industrial community as well,

3 with representatives with a more substantial

4 presence at that occasion. That is reassuring

5 certainly to the industry members in the audience

6 today.

7 As an aside also, I think some of the

8 industry people would also like to be reassured, if

9 that were possible, that the arrangements that are

10 already under way and the commitments that have

11 already been made will, in fact, be honored as

12 these new guidance proposals are development and in

13 process, some reassurance there would be

14 appreciated, I know, by some in the room.

15 Also, just as an aside or perhaps as a

16 commentary, some of the industry people have come

17 up to me during the breaks and they are reflecting

18 on the following, and that is the issue of idealism

19 versus realism. There are many physicians and

20 healthcare providers at this table in practice;

21 there are many in the regulatory agency; there are

22 many in the industrial organizations and sponsors

23 that are in the room today and all of us know, as

24 has been mentioned by many of the clinicians at the

25 table, the variability in patients and the

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1 variability in their circumstances. It is that

2 variability that makes some of these trials so

3 difficult to accomplish and complete in a fashion

4 that would satisfy the proposal that is before us

5 today.

6 That is why I am concerned that the hurdle

7 might be set too high. We just must not lose

8 perspective of the variability in patients and in

9 their situations and in their circumstances which

10 would make it very difficult to hit on all of the

11 targets that have been proposed.

12 DR. FIRESTEIN: Before we move on, I would

13 just like to remind people to please keep their

14 comments to about two minutes, and let\'s try to

15 answer the specific questions that have been

16 raised. Dr. Max?

17 DR. MAX: Regarding the models, I agree

18 with Dr. McLeskey that people are going to want to

19 do replicate trials in one condition anyway to get

20 the drug on the market. It would make sense to me.

21 I would rather have a broader representation of

22 diseases and I don\'t need any more replication.

23 So, whether the number would be two and one, plus

24 two additional conditions or three additional

25 conditions, I would recommend that the FDA do a

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1 careful economic analysis, and if you could get

2 more conditions without killing the wonderful

3 engine of industry, I would make it five trials, if

4 not four trials, and you can figure that out.

5 I think in each condition you should try

6 to either make it relatively homogeneous

7 mechanistically for clinical criteria, or at least

8 allow the information to be there. For instance,

9 if you study cancer pain, mixed cancer pain means

10 very little mechanistically. We should be able to

11 look at bone pain separately and, similarly in back

12 pain, the people with root injury are different

13 from those with central back pain. So, try to use

14 the clinical criteria to allow some mechanistic

15 inferences.

16 Regarding the issue of the three proposed

17 co-primaries, I again disagree with that. I think

18 that pain should be the primary outcome. I agree

19 that a global outcome and function are important

20 things to measure but they should be secondary

21 outcomes and, obviously, if over the pattern of

22 studies globals deteriorate and function

23 deteriorates there is something wrong with the drug

24 and it won\'t be approved. But I would make pain

25 the only primary. And, I think general chronic

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1 pain is a great idea as it will drive the science

2 forward.

3 DR. DIONNE: Well, I have very little

4 experience with chronic pain so, presumably, I

5 don\'t have the basis for an intelligent opinion but

6 that hasn\'t stopped me before.

7 I just wanted to reiterate the concept of

8 some sort of a data-driven regulatory practice for

9 analgesic drug development in this particular

10 question that might take the form of a

11 meta-analysis of the existing drug classes that are

12 generally accepted for chronic pain, be it

13 tricyclics and NSAIDs, and look back and see if

14 there is enough evidence to support the application

15 of these criteria that are being considered

16 prospectively when we look at the evidence that

17 exists for drugs that have been studied for 50 to

18 100 years. Then, on the basis of that we might

19 determine that the standard is too high, too low,

20 if it doesn\'t actually apply to drugs that have

21 already been approved, and then make the subjective

22 evaluations that have to be made about the

23 prospective criteria at least on the basis of the

24 data for the drugs that are already out there.

25 DR. WOOLF: I must admit, I am concerned

165

1 about this notion of there being a global chronic

2 pain analgesic in the absence of evidence that such

3 a drug exists. I think that is the key issue.

4 This needs to be evidence based. I am worried that

5 we don\'t know which trials, whether they be three

6 or five, in which conditions are going to be

7 predictive of whether any drug is going to be

8 effective across a wide range of different chronic

9 pains.

10 So, the issue to me is how happy are we

11 going to be living with an analgesic that has a

12 global pain indication and, yet, is not effective

13 in subcategories or different diseases? If we

14 don\'t have a basis yet for predicting which of the

15 suitable trials, whether it be low back pain or

16 fibromyalgia or age-related neuropathy, it is pure

17 guess work as to which of these we can select and

18 how many to try to come to an assessment of whether

19 any individual treatment is going to be effective

20 across a wide range of conditions.

21 The other issue that hasn\'t been discussed

22 yet is in these trials are we looking for

23 placebo-controlled trials or active comparators?

24 If so, since they are going to be so different what

25 would the active comparator be if you are going to

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1 compare fibromyalgia versus neuropathic pain in the

2 conduct of these trials?

3 MS. MCBRAIR: I too am concerned about a

4 global assessment. It seems early on and what I

5 would really like to see us do is a really good job

6 with each one of the indications or diseases or

7 health problems and be able to give the very best

8 guidance to the practitioners that are using these

9 medications and to the patients. I think we need

10 to focus on that first before we go towards a

11 global assessment.

12 As far as the domains, I think they are

13 all important based on the individual health

14 problem. I do think patients need to be able to

15 function if they are supposed to, and that is the

16 goal of the medication in part. Certainly in

17 rheumatoid arthritis, if we are just covering the

18 pain we may not be addressing the inflammatory

19 process and that needs to be paid attention to as

20 we are looking at these individual situations. But

21 I think the domains are very important to the

22 people that we are trying to serve.

23 DR. WOOD: It is getting late. I agree

24 with much of what has been said before,

25 particularly by Dr. Abramson. I also agree with

167

1 what Dr. McLeskey said, that there are worries

2 about having multiple primary endpoints and merging

3 these into a composite endpoint rather than just

4 having your primary endpoint being the reduction in

5 pain which is, after all, the indication we are

6 looking for.

7 On the other hand, a global indication

8 seems to me to go beyond the science. If you think

9 of other areas, we don\'t give global indications to

10 improvement in cardiovascular health. We say

11 cholesterol agents do one thing; beta blockers to

12 something else; ACE inhibitors do something else.

13 All of these drugs, in fact, produce mortality but

14 we have a recognition about the specific

15 indications for their use to reduce that mortality

16 and that seems appropriate here; it is just that

17 the science isn\'t as far advanced.

18 The one thing that has not been discussed

19 that I would want to put on the table is that it

20 seems to me there is an underlying assumption being

21 made up till now that all our studies are going to

22 come out positive in a global indication. What are

23 we going to do with studies that come out

24 negatively? Never mind how many positive studies

25 you need, how many negative studies do you need?

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1 Does one negative study immediately knock you out

2 of the park? I mean is that it? That you can no

3 longer get a global indication?

4 I would be particularly concerned that

5 that is going to give rise to gaming of the system.

6 You know, I think we can reliably expect that we

7 will hear about all the positive studies. The

8 negative studies may not be presented in this room.

9 So, I think the idea that somehow all the studies

10 will come out positive and really all we are

11 arguing about, as Bernard Shaw said, is the number

12 is unrealistic. Some are going to come out

13 negative. And, I think there is a big danger for

14 industry in going for a global indication because,

15 clearly, if you go for a global indication and one

16 of your studies comes out negative you are dead in

17 terms of a global indication. There is a

18 possibility that one of your competitors may come

19 out with a study that is negative and that is then

20 used to undercut your global indication.

21 So, I think there is a risk in that and I

22 think we should be cautious about extending to

23 indications for which we don\'t have obvious data to

24 support them.

25 DR. CALLAHAN: Well, I think Dr. Woods

169

1 made a very good point about if there is a negative

2 indication. So, based on that, I would like to say

3 I would like to see two replications of whatever

4 indications, and the numbers I think would depend

5 on sort of the feasibility within the company in

6 terms of how many indications they could look at.

7 Clearly, you need to look at different types of

8 mechanisms within that.

9 In terms of the domains, I think pain

10 should be a primary outcome, not have the

11 co-primary, but I would like to see some sort of

12 disease specific function included, as well as

13 patient global. Then, I very much like the idea of

14 a general health-related quality of life so that

15 they can be compared across conditions.

16 DR. CUSH: There is a benefit to going

17 late; you get to listen to everybody else\'s ideas

18 and be swayed by them. I will back off. I was

19 very much in favor of this when it was first

20 presented and I would say I am against it.

21 \[Laughter\]

22 DR. FIRESTEIN: I am going to have to go

23 around the table again now, so be careful!

24 {Laughter\]

25 DR. CUSH: I think that there is an issue

170

1 regarding under-treatment of pain, but I think that

2 doesn\'t rest with the lack of available options or

3 drugs that could be labeled as globally effective

4 therapies. I think that rests more with poor

5 education and poor understanding of pain and pain

6 control. I think if you look at drugs that we

7 might call sort of global drugs, widely used drugs,

8 broad-spectrum antibiotics, while they may have

9 been helpful there has also been a certain degree

10 of misuse, and the problems that that may have

11 arisen from that I don\'t think were anticipated.

12 When we look at our arthritis drugs, we

13 have drugs like methotrexate and disease-modifying

14 drugs. They tend to be used globally, sometimes

15 outside of indications because we don\'t have

16 options. Sometimes that is done because we

17 understand the mechanism of disease. Sometimes it

18 is done quite blindly and quite stupidly, and with

19 no apparent effect and maybe with great expense or

20 maybe toxicity. I think that there are drugs that

21 are out there that are being used in this manner

22 currently, drugs such as the COX-2\'s and narcotics,

23 are basic globally used pain medicines. Currently

24 they are used in a way that basically forces the

25 physician to be intelligent and understand the

171

1 mechanisms of disease and what is going on with the

2 patient, and also act as an advocate on behalf of

3 the patient to go for those indications and write

4 letters to explain why this is indicated.

5 So, you know, would a global indication

6 actually help a payer, an approver of drugs that

7 they may not be indicated for? So, would they

8 actually approve the use of a new, novel pain

9 medicine for phantom limb pain, acute gout or

10 visceral pain associated with losing to the

11 Yankees? I don\'t know.

12 \[Laughter\]

13 I still think it forces me to have to

14 still write those letters to get these drugs

15 approved, and for this reason I would say that we

16 should not have this indication.

17 I will close by just saying I think we

18 have an issue of nomenclature here that was raised

19 yesterday by Dr. Ashburn. The whole use of words

20 \"acute\" and \"chronic\" are a little bit

21 disconcerting and I think we should try to maybe

22 redefine the terms we use and maybe go for things

23 such as short-term therapy or long-term therapy.

24 In this instance, general global pain indication is

25 a bit too obtuse clinically and unrestrictive to be

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1 useful. Thank you.

2 DR. SHERRER: I am last but I didn\'t

3 change my mind. So, some of us can stay steady.

4 While it is true that we do, in fact, use

5 medications that are on the market with restrictive

6 indications broadly, nevertheless, as a clinician,

7 I think it would be very useful to me in

8 prescribing to know that a drug has utility across

9 different types of pain. If the studies were

10 useful and really are showing me that, for

11 instance, if you do osteoarthritis and low back as

12 two of your models I am not so sure that you are

13 looking at different pain. On the other hand, if

14 you look at cancer bone pain and you look at

15 diabetic neuropathy and you look at OA, you

16 probably are looking at different pains and it

17 would be very useful for me to know that that has

18 been demonstrated.

19 In terms of looking at the domains, I am

20 one of those who believes that we need to look at

21 the total impact of the drug as an outcome. So, I

22 would favor looking at least at three, if not four

23 of them. I think pain is useful but the total

24 impact of a drug is even more useful to my

25 patients. In fact, that is why some won\'t take

173

1 certain pain medications, because of the side

2 effects, because of their effect on quality of

3 life. So, I would use several of those, and most

4 important to me would be pain, would be patient

5 global and some appropriate assessment for the

6 particular disease of function or quality of life.

7 One thing I haven\'t heard that I would

8 like to bring up, and maybe it would be a

9 secondary, is steroid sparing because I think that

10 in certain chronic pain disorders where steroids

11 are an important part\--I said steroid sparing,

12 opioid sparing\--many patients are very concerned

13 about opioids and so are we, and if a drug spares

14 opioids, that would be very important to me.

15 DR. FIRESTEIN: We are done. We have gone

16 all the way around the table. So, we will break

17 for lunch and we will reconvene at 12:55, which

18 means we will start at 1:00.

19 \[Whereupon, at 12:05 p.m., the proceedings

20 were recessed for lunch, to reconvene at 1:00 p.m.\]

174

1 A F T E R N O O N P R O C E E D I N G S

2 DR. FIRESTEIN: I am happy to introduce

3 Dr. Vibeke Strand, who is going to talk about

4 responder index, a model.

5 Responder Index, a Model

6 DR. STRAND: Thank you, Gary. We have

7 been more or less talking around this topic for the

8 last day and a half, and perhaps we should have

9 started sooner with this discussion.

10 \[Slide\]

11 What I would like to do is basically

12 present to you a discussion that was started at the

13 last NIH-FDA meeting on pain. Just to point out

14 something that we have talked about before,

15 responder analyses have face and content validity.

16 They do allow the assessment of multiple domains.

17 They probably could better help us categorize

18 analgesics.

19 They should also help facilitate

20 comparison of efficacy across products and disease

21 populations and indications. I think in analgesia,

22 as in rheumatology, most of our patient populations

23 are quite heterogeneous and this would help

24 considerably.

25 This might or might not lead to a tiered

175

1 approach in label indications as has been done in

2 rheumatoid arthritis but really has not yet been

3 done otherwise. The precedent, as we have talked

4 about previously, is the ACR responder criteria in

5 rheumatoid arthritis.

6 \[Slide\]

7 Jim Witter pointed this out to you this

8 morning. it is a model for other responder

9 analyses. One could say that the two criteria

10 here, which are tender and swollen joint count,

11 could be required in a responder analysis in pain,

12 for instance, whatever assessment of pain could be

13 required and perhaps also the patient global

14 assessment could be required. The others could be

15 included.

16 One of the things we do know is that it is

17 probably too stringent to require all components of

18 a responder analysis to be improved. It is

19 possible to choose the majority of them to be

20 improved. It is also possible to indicate that the

21 remaining ones should not be deteriorated.

22 If we want to talk about a definition of

23 no deterioration, however, we have to allow that

24 statistical definition to account for test/retest

25 variability, which we have alluded to before in our

176

1 discussions around changes in visual analog scales.

2 \[Slide\]

3 The strength of the rheumatoid arthritis

4 guidance document is that it has had a proven track

5 record and since its inception we now have six

6 products approved for the treatment of rheumatoid

7 arthritis, some of them just for the signs and

8 symptoms, as in the COX-2 products, but many of

9 them now for improvement in signs and symptoms in

10 either 6 or 12 months and then inhibition of

11 radiographic progression at 12 months, and

12 subsequently improvement in physical function

13 without deterioration in health-related quality of

14 life over 2 to 5 years. In this case it has been

15 over 24 months.

16 These outcomes have all been achieved in

17 single protocols using prespecified outcome

18 criteria, whereby the first outcome criterion must

19 be satisfied statistically significantly, p less

20 than 0.05. Then one may look at the subsequent, in

21 sequence, criteria, provided each one remains

22 statistically significant without taking a p value

23 correction. That is a very valuable way to look at

24 multiple different aspects of a disease and how it

25 affects the disease population.

177

1 \[Slide\]

2 When we had this breakout session at the

3 workshop, in May, the definition for the

4 workshop\--and I am not saying that is a definition

5 we have been working on today, but the definition

6 for chronic pain was randomized, controlled trials

7 of at least three months duration in pain of at

8 least three months duration, regardless of the

9 underlying cause. That was simply taken as a

10 definition so we could have the discussion we were

11 going to have.

12 We agreed in that discussion that we would

13 not specify specifically different diseases. We

14 agreed that maybe there might be some differences

15 specifically for chronic cancer pain, but for the

16 purposes of the discussion we would not

17 distinguish.

18 \[Slide\]

19 We were considering musculoskeletal

20 indications such as rheumatoid arthritis,

21 osteoarthritis and low back pain, as we have talked

22 about in the last two days, also fibromyalgia,

23 neuropathic pain, the examples being diabetic

24 neuropathy, post herpetic neuralgia, trigeminal

25 neuropathy. For cancer pain, we agreed that it

178

1 wouldn\'t necessarily be for a three-month duration

2 in terms of trial and that we would be thinking

3 about rapidly progressive disease and adjust

4 intervention as the disease progresses which is, of

5 course, a very important thing around cancer pain.

6 \[Slide\]

7 We agreed to select the domains regardless

8 of the clinical indication; that we would consider

9 the available instruments and whether or not they

10 were validated and whether or not they had been

11 validated in pain trials; just that they had been

12 used in previous randomized, controlled trials but

13 not necessarily in pain; and whether they were

14 disease specific or generic was sufficient.

15 The point really was that the outcome

16 measures in rheumatology clinical trials, the

17 OMERACT international consensus process has

18 actually helped to define the ACR responder

19 criteria, and is helping to define responder

20 criteria in osteoarthritis, but the first decision

21 is around the domains to be used, not the specific

22 instruments, and that there is some flexibility

23 around which instruments might be utilized to

24 satisfy each of the domains.

25 \[Slide\]

179

1 We did believe, however, that the strength

2 of choices in terms of domains was based on

3 multiple available instruments and our own prior

4 clinical experience. So, the choices, as they were

5 thrown out and written up, were pain and we talked

6 a lot about the multiple different measures of pain

7 that probably should be important to be included in

8 a given trial under a single domain, including the

9 patient global assessment; including the assessment

10 of rescue medications; and time to treatment

11 failure\--all of these which we talked about this

12 morning.

13 Suffering was suggested as a domain, as

14 was pain relief, a disease specific measure of

15 improvement and/or physical function and/or

16 health-related quality of life was proposed. So

17 was health-related quality of life, and we have

18 been throwing around the term quality of life. I

19 think it is important that we specifically mention

20 that it should be health-related quality of life in

21 all the way health affects you. Because,

22 certainly, political circumstances, economic

23 circumstances and the presence or absence of food

24 and money are not part of health-related quality of

25 life but certainly are part of quality of life.

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1 Patient global assessment, adverse events and

2 specifically how they are perceived by the patient

3 which is something we are not very good at in

4 clinical trials; we usually trust the physician to

5 report those adverse events and often not with very

6 much input from the patient, other than that the

7 complaint has been offered. Damage, whether it is

8 due to the disease or its treatment, and

9 specifically indicating that it is irreversible,

10 and economics.

11 \[Slide\]

12 After a relatively brief series of

13 discussions, we came up with the final vote the

14 first time when everyone was allowed to vote on

15 basically three parameters: Unanimous decision for

16 pain; an almost unanimous decision for a disease

17 specific or a disease relevant measure. We have

18 been talking a lot about physical function but, as

19 I said to you before, I think it can be basically

20 perceived as a disease relevant or specific measure

21 of either function or health-related question.

22 Health-related quality of life as a generic measure

23 was an almost unanimous decision. Patient global

24 and adverse events followed.

25 So, this was felt to recommend a minimum

181

1 core set of required domains, and that other ones

2 could certainly be added but if we were to speak

3 about trying to do a responder analysis, these

4 should be the components to be considered at a

5 minimum.

6 \[Slide\]

7 We have talked a lot about defining

8 improvement in pain, but I think the point we are

9 all trying to get at is defining improvement

10 multidimensionally. We know that patients

11 experience pain and they report pain, but they

12 report it specifically as they feel on the day they

13 are reporting it. So, if they are forward filling

14 their diaries, it is based on how they are feeling

15 that day. If they are back filling, it is also

16 based on how they are feeling that day.

17 One of the important things too is that

18 their expectations of what they can do and what

19 they should be able to day change according to how

20 their pain is. So, if they have already had

21 significant pain relief their expectations have

22 changed and become even greater than they were when

23 they, for instance, first entered the study and

24 were suffering considerable pain.

25 What we are trying to do, obviously, is

182

1 separate the experience of pain from functional

2 impairment and disability which may or may not

3 occur because of the pain or follow the pain. We

4 want to separate physical impairment from

5 disability. It is important, I think, to use

6 individual responder analyses because it allows us

7 to define responder, non-responder. We don\'t have

8 to impute data. All cause dropouts before the

9 endpoint are then considered non-responders.

10 Therefore, from a statistical analysis it can be a

11 more robust analysis. I think it is important that

12 we use both disease specific or disease relevant

13 measures as well as generic measures.

14 \[Slide\]

15 Something to quickly point out is that

16 disability is really in the eyes of the beholder.

17 It is, of course, age and gender appropriate. It

18 is important and pertinent to the work, the family

19 and the social setting. But, in fact, someone who

20 has had cerebral palsy since birth and is

21 wheelchair-bound may not perceive themselves as

22 being disabled even though we would certainly

23 consider them to be far more than just physically

24 impaired.

25 The other part of it is that impairment

183

1 may be due to pain or it may be due to structural

2 alterations, and functional limitations are

3 certainly something that we can measure. There are

4 arguments about disease specific or disease

5 relevant measures of physical function and how

6 accurate they are in that those of us who are

7 rheumatologists often note that our fibromyalgia

8 patients are far more severely impaired than our

9 rheumatoid arthritis patients. But, by and large,

10 if we can choose the right types of instruments we

11 can usually find some type of a valid report that

12 is consistent with the other self-reports that the

13 patient may offer.

14 \[Slide\]

15 One of the other things about a global

16 assessment is that it is probably much more

17 important to ask the patient in all the ways that

18 your pain is affecting you, including its

19 treatment\--how are you doing today? When we talk

20 about visual analog scales for patient global

21 assessments, we always talk about how are you doing

22 today, this moment? The other part of it here is

23 to make it a global assessment and to include sort

24 of the risk as well as the benefit as an important

25 thing in terms of the patient assessment of the

184

1 pain treatment.

2 Now, a transition question can probably be

3 equally sensitive, in other words, how are you

4 compared to when you first started taking this

5 medication? That may well get to the same point.

6 The other point that is quite useful is

7 that health utilities which are used for economic

8 measures are single reports sometimes, questions or

9 several questions around how patients are doing in

10 terms of what their perception of perfect health

11 would be. A health utilities index or the EQ5D can

12 be given. It is a simple questionnaire that the

13 patients can fill out. Or, one can ask the patient

14 to report, by a feeling thermometer, how they are

15 doing in terms of perfect health and death. That

16 looks very much like a visual analog scale

17 vertically.

18 \[Slide\]

19 We have talked a lot about minimum

20 clinically important differences. We consider them

21 to represent changes which are perceptible to

22 patients and are considered clinically important

23 and meaningful. When they were first started in

24 the OMERACT process we used patient query as well

25 as a delphi technique. Then they were demonstrated

185

1 to be consistent with patient global assessments of

2 improvement or patient global assessments of how

3 they were doing.

4 In fact, when we determined the proportion

5 of patients with clinically meaningful improvement

6 or clinically important improvement, this gives us

7 a much more interpretable result than, in fact,

8 trying to say, okay, this many patients had 50

9 percent improvement in pain or this many patients

10 had 30 percent improvement in pain.

11 \[Slide\]

12 If we think about this, we have now

13 noticed that changes in disease specific or

14 relevant measures of function and health-related

15 quality of life that have been statistically

16 related to much or very much improvement in patient

17 global assessments, either by visual analog scale

18 or Likert have given us very consistent values

19 across OA, RA and fibromyalgia, and I will show you

20 that briefly.

21 \[Slide\]

22 Briefly, measures of chronic pain include

23 a lot of different things. There is the brief pain

24 inventory, the McGill pain questionnaire, all of

25 these others. Perhaps one of the more important

186

1 new ones is the treatment outcomes and pain survey

2 which was developed as an add-on to the SF-36 and

3 has been shown to be very useful in cancer pain, as

4 well as some other non-malignant settings of pain,

5 chronic pain with multidimensional therapy.

6 \[Slide\]

7 The faces rating scale we have talked

8 about before. We talked about using a visual

9 analog scale that is not anchored. This one

10 actually combines a Likert scale of more or less 7

11 with a visual analog scale of 10 and is sort of the

12 example of what not to do at the same time to get

13 sensitivity and specificity, which is why I chose

14 to show this slide because I, myself, would be very

15 confused about which face to combine with which

16 number.

17 \[Slide\]

18 Talking about MCID, one of the nice papers

19 published by Dr. Farrar, sitting at the table, is

20 looking at the pain intensity numerical rating

21 scale and comparing that to very much improved in

22 patient global assessment.

23 These are 10 placebo, randomized control

24 trials of Pregabalin, which is not yet approved,

25 but this has been published in Pain 2000 for

187

1 diabetic neuropathy, low back pain, fibromyalgia

2 and OA. So trials across different indications of

3 chronic pain have shown that the relationship of

4 much and very much improved in PGIC and pain

5 intensity by numerical rating scale is very

6 consistent with reduction of 30 percent or two

7 points in the pain intensity scale.

8 This is really interesting given the wide

9 variety of disease states here, and this is

10 regardless of the baseline pain scores in these

11 patients. So, a robust MCID definition.

12 \[Slide\]

13 If we look at other measures of physical

14 function and health-related quality of life in

15 chronic pain, I just want to remind you again that

16 the top survey here is meant to look at changes in

17 health-related quality of life in individuals over

18 time, which is different from the generic measure

19 of health-related quality of life, the SF-36, which

20 I will come back to in a minute, and one other

21 measure that is an HRQOL measure in pain is the MPI

22 which specifically looks at psychosocial role

23 functioning but omits work-related activity.

24 Finally, cancer-related health-related quality of

25 life has been looked at a lot on the BPI, the brief

188

1 pain inventory, but that has not been validated in

2 non-malignant pain.

3 \[Slide\]

4 Generic health-related quality of life

5 measures go back as far as the sickness impact

6 profile which is, in fact, considered not to be a

7 very popular instrument because it implies to the

8 patient that they are sick.

9 The Nottingham health profile is also an

10 older measure of HRQOL and not particularly

11 popular. A very popular one is the SF-36 which is

12 expanded over the SF-12. It is designed to measure

13 health-related quality of life in large groups and

14 across different disease states. It has problems

15 if it is being used as a single measure of HRQOL in

16 pain states or in arthritis states because there is

17 a limited assessment of upper extremity function,

18 as well as upper extremity pain and facial pain,

19 and does not differentiate well between low back

20 pain and upper body pain.

21 The WHOQOL is a new instrument, but with

22 100 questions it has fallen out of favor. There

23 are some shorter version. The EQ5D is widely used

24 in Europe.

25 \[Slide\]

189

1 Disease specific measures of physical

2 function and/or health-related quality of life

3 include all of these. We have called them disease

4 specific. People like Jim Freis, who developed the

5 health assessment questionnaire, prefers not to

6 call it disease specific because he believes it can

7 be used across many disease states as well as

8 aging, which is not a state of disease, as he wants

9 to remind me. So, I have chosen to also call these

10 disease relevant measures.

11 Clearly, the WOMAC is something that is a

12 very good one for osteoarthritis of a knee or a

13 hip. There are others, as well as some for the

14 hand which are being developed. We talked about

15 Roland-Morris and Oswestry. There are some for

16 geriatrics and, of course, a variety of ones for

17 cancer.

18 \[Slide\]

19 What I would like to do very quickly is

20 just show you some examples of how these measures

21 interrelate in rheumatoid arthritis, osteoarthritis

22 and fibromyalgia.

23 \[Slide\]

24 So, if we look at rheumatoid arthritis, we

25 talk about the health assessment questionnaire

190

1 which has now become widely used in randomized

2 controlled trials in rheumatoid arthritis. It is a

3 measure of physical function with 20 questions. It

4 also accounts for when patients use aids or devices

5 to perform these activities.

6 \[Slide\]

7 The SF-36, as I mentioned to you, is

8 validated and widely used. It has been validated

9 across multiple cultures, many disease states.

10 There exist gender and age specific norms for

11 multiple populations, both in the U.S., Canada and

12 northern Europe and other countries. Then, it has

13 eight domains as well as a physical component score

14 and a mental component score. It has been shown in

15 RCTs to show change in as short a time as four

16 weeks, probably sooner than that.

17 \[Slide\]

18 The physical domains are physical function

19 role, physical body pain, general health. They are

20 combined positively into the physical component

21 score which then negatively also weights the mental

22 domains of vitality, social function, emotional and

23 mental health. So, positive changes here are

24 weighted positively here against the positive

25 changes in these domains, which are negatively

191

1 weighted for the mental component score. The

2 mental and physical component scores are based on

3 normative data only to a total of 50. Therefore,

4 they can show less change. And, if you are looking

5 at a disease like rheumatoid arthritis where the

6 predominant change is in the physical component

7 domains, then one is not going to be seeing much

8 improvement in mental domains because they are

9 weighed against by the improvements in these.

10 \[Slide\]

11 What we have learned from the various

12 trials is MCID for the HAQ disability index is a

13 score 0.22 improvement. For the SF-36 it is about

14 5 to 10 points in domains. For the physical and

15 mental component scores, 2.5 to 5 points.

16 \[Slide\]

17 So, if I look very quickly across some

18 clinical trials in rheumatoid arthritis you can

19 see, with the leflunomide Phase III trials across

20 all three studies, with methotrexate and

21 sulfasalazine the mean improvement over two years

22 exceeds MCID almost to twice in all treatment

23 groups.

24 \[Slide\]

25 If we look at the ATTRACT study, and this

192

1 is HAQ disability index over two years, again we

2 see that in the placebo group it does not quite

3 reach MCID and is about twice that in all of the

4 active treatment groups.

5 \[Slide\]

6 Similar types of improvements in the ERA

7 trials with Etanercept versus methotrexate.

8 \[Slide\]

9 If we go back to look at the U.S. study

10 with leflunomide and methotrexate, which was the

11 first to show that the SF-36 was sensitive to

12 change in rheumatoid arthritis, you can see that

13 based against age and gender matched U.S. norms the

14 patient population had significant decrements in

15 all domains of healthcare quality of life, but

16 particularly physical function, role physical,

17 bodily pain and vitality. As we know, patients

18 perceive their health-related quality of life

19 differently, and one can see the changes here in

20 the active groups actually are within MCID for

21 almost every domain, with some deterioration in

22 placebo.

23 \[Slide\]

24 If one then goes forward, we see that

25 these are the baselines for the treatment groups

193

1 and these are the age and gender matched norms,

2 then treatment with leflunomide and methotrexate,

3 in fact, just about bring health-related quality of

4 life up to a normative population level. That is

5 probably a very meaningful change and it certainly

6 does equal MCID in many of these eight domains.

7 \[Slide\]

8 There is similar improvement infliximab in

9 the ATTRACT trial. These are the two of the

10 physical domains. If we look at the PCS and the

11 MCS we see that there is very significant decrement

12 in the physical component score at baseline, almost

13 two standard deviations from the U.S. norm, and

14 treatment over one and two years brings it to

15 within one standard deviation of the U.S. norm. As

16 we might expect, the MCS was not that different

17 from expected, and it could not show a great deal

18 of improvement based on the large amount of

19 improvement in the physical domains. Nonetheless,

20 improvement is shown.

21 \[Slide\]

22 This is the median improvement in PCS

23 score with the ATTRACT trial showing the same type

24 of a picture, with placebo showing not much

25 improvement.

194

1 \[Slide\]

2 This is the early RA trial, again showing

3 baseline for the PCS, about two standard deviations

4 below the U.S. norm, and improvement to

5 approximately one standard deviation from the U.S.

6 norm with treatment.

7 \[Slide\]

8 So, I think you can see from this that

9 basically improvements in HAQ disability index, in

10 other words the disease relevant measure of

11 physical function and the generic measure of

12 health-related quality of life appear to be very

13 clinically meaningful, and that there are

14 consistent values for MCID across these

15 instruments. We are showing that improvement in a

16 disease relevant measure is highly correlated with

17 a generic instrument, and the generic instrument is

18 useful because we can compare it across different

19 disease states for an economic basis, but also to

20 try and understand improvement, for instance as we

21 might when we are looking at chronic pain

22 indications.

23 \[Slide\]

24 Quickly, lets look at osteoarthritis. The

25 WOMAC is the disease specific measure in OA of the

195

1 knee and hip. It reflects physical activities that

2 are most affected by the osteoarthritis. It is

3 composed of pain, five questions on joint

4 stiffness; two questions on physical function which

5 dominates the instrument of 17 questions out of a

6 total of 24, and is scored either by a zero to 4

7 Likert or a zero to 10 VAS scale for each question.

8 \[Slide\]

9 So, what we have found out looking at the

10 COX-2 trials with both celecoxib and roficoxib is

11 that basically, using a Likert scale for the

12 composite total WOMAC score, MCID was about 10

13 points and was different according to the domains

14 because they had more or less questions. If one

15 uses the VAS scale for all of the questions, then

16 we see very consistent MCID for each of the domains

17 of about approximately 10.

18 \[Slide\]

19 This is what this looks like in the

20 composite scores of WOMAC in clinical trials of

21 celecoxib versus placebo and the active comparator,

22 naproxen. Here is MCID.

23 \[Slide\]

24 If we look at it for rofecoxib using the

25 primary outcome question in the physical function

196

1 subscale we see again that improvement is evident

2 and exceeds MCID considerably.

3 \[Slide\]

4 If we look at the improvement in the SF-36

5 with rofecoxib and we compare it to age differences

6 in the U.S. population, we can see that there is

7 considerable improvement in the mental domains as

8 well as the physical domains, but the largest

9 improvement is in role physical.

10 \[Slide\]

11 Similarly, if we look at the changes with

12 celecoxib in the SF-36 in the trials that I showed

13 you previously, you can again see that MCID is

14 reached in many of the domains, particularly the

15 physical ones.

16 \[Slide\]

17 This actually translates again towards

18 improvement that approaches the U.S. norm. This is

19 the U.S. normative population and these are the

20 final scores with the different doses of celecoxib

21 and naproxen and placebo.

22 \[Slide\]

23 So, again, we see clinically meaningful

24 improvements. We see that the MCIDs are consistent

25 across agents and patient populations in this

197

1 disease, and that improvement in the WOMAC

2 correlates with the generic HRQOL SF-36 measure.

3 \[Slide\]

4 I don\'t have outcomes for fibromyalgia,

5 but I do have interesting consistent relationship

6 at baseline between pain, sleep disturbance and

7 fatigue. These are all patient reported and they

8 are highly correlated either by a pain diary or a

9 sleep quality diary or multidimensional assessment

10 of fatigue, a well-known fatigue instrument. And,

11 this is whether it is done by a numerical rating

12 scale that is ostensibly recorded daily in the

13 diary or a visual analog scale that is done at the

14 office visit weekly. It has been shown that the

15 high baseline scores indicate impaired sleep.

16 Significant fatigue, we know that our fibromyalgia

17 patients think of themselves as being very

18 physically impaired, and these correlate with low

19 scores in SF-36, particularly role physical, bodily

20 pain and vitality domains; poor sleep quality by

21 the MOSA sleep, high fatigue and also more anxiety

22 than really depression.

23 \[Slide\]

24 In terms of cancer, there are a lot of

25 different instruments that would be useful in

198

1 trials of cancer pain, and they can be the FACT-G

2 or FACT that is a P for prostate or any one of the

3 cancers that you want to look at. The same for

4 LASAs which can also be done for symptoms of

5 chemotherapy as well as for symptoms for cancer or

6 pain. The same kind of thing for the FLIC.

7 Basically, there are all these different

8 instruments that can be used and, again as I

9 mentioned to you before, the TOPS has been

10 developed and validated in cancer pain, among

11 others.

12 \[Slide\]

13 Since the TOPS was defined as an extension

14 of the SF-36 it has been a very useful instrument

15 and it really does show change in individual

16 patients over time.

17 \[Slide\]

18 So, the appropriate domains, based on what

19 we discussed at that particular breakout session

20 and as a recommendation to this group, would be

21 that pain would be included as a domain. There are

22 many instruments. We have talked about looking at

23 different ways of assessing pain. Perhaps we can

24 get away from some of our old visual analog scales

25 and Face scales.

199

1 A disease specific or disease relevant

2 measure of health-related quality of life and the

3 ways that the disease affects you in your day to

4 day activities could be used, or one could use the

5 TOPS which is much more generic. When it is

6 relevant to whatever the disease is, other measures

7 could be looked at. They do not necessarily have

8 to be included in the responder analysis.

9 I think you can see that the

10 health-related quality of life measure SF-36 as a

11 generic measure has turned out to be very useful

12 and sensitive to change across a large number of

13 types of diseases; and some way of asking the

14 patient how they are doing in terms of risk/benefit

15 in terms of the treatment as well as the pain; and

16 finally adverse events, which we haven\'t talked

17 about, might be subsumed under this global

18 assessment if it does include the treatment as well

19 as the pain.

20 \[Slide\]

21 Certainly for acute pain we probably don\'t

22 need a measure of health-related quality of life,

23 as we have discussed, and certainly we can talk

24 about all of these. We do want to remember time to

25 treatment failure and rescue medications as being

200

1 part of something that needs to be assessed in the

2 pain domain.

3 \[Slide\]

4 When we go to subacute pain or pain of two

5 to five days, or whatever the definition is that is

6 less than chronic pain but more than one day of

7 pain, it would appear that these different domains

8 would be equally relevant. We can show changes in

9 SF-36 over a very short period of time. Again, it

10 might be useful to use the TOPS or to use a disease

11 relevant measure.

12 \[Slide\]

13 In fact, again Dr. Farrar has published a

14 very nice paper on cancer-related breakthrough

15 pain, acute pain. This was in a study of oral

16 transmucosal fentanyl citrate, which ultimately was

17 not approved. But these were 130 patients who were

18 naive to the study drug, many episodes of pain, and

19 the differences in pain scores between the episodes

20 which did and did not yield adequate pain relief.

21 Again we see MCIDs for pain intensity difference

22 and maximum total pain relief of about 33 percent.

23 Again, the same kinds of changes in terms of

24 absolute pain relief and sum of pain intensity

25 differences of 205 points in a Likert scale, which

201

1 are then consistent with what we were looking at in

2 the other measures of chronic pain.

3 \[Slide\]

4 So, in my conclusions, a responder

5 analysis for pain randomized controlled trials

6 would make sense. I would never suggest that we do

7 it in the absence of data. I would never suggest

8 that we prospectively put it together and then set

9 out to validate it but that, instead, it be

10 developed over time using perhaps a particular

11 product and validating it from Phase II data into

12 Phase III final randomized, controlled trials. Or,

13 perhaps we would be able to work on it as a

14 concerted effort with a bit of help from

15 meta-analyses. Unfortunately, most of these

16 domains have not actually been assessed even in

17 recent clinical trials of pain relievers and that

18 will limit a lot of what we can do post hoc. I

19 think this represents minimum number of required

20 domains. We certainly want to use validated

21 instruments. As I have mentioned before, several

22 different components have to be included.

23 As with other responder analyses, it could

24 be required that the majority of them showed

25 improvement but not that all would be required to

202

1 show improvement in the domains we are talking

2 about here. As Dr. Simon had proposed, three of

3 those five would be improved. It could be added

4 that there should not be deterioration in the other

5 two, or that could be omitted. The degree of

6 improvement proposed could be based on MCID values

7 at least for those instruments that we have.

8 When we know that these different domains

9 are not closely correlated in responses, then we

10 know that we have both a very robust clinical

11 response when we get a responder analysis that is

12 positive, and that we have additive statistical

13 power which allows our sample sizes to decrease

14 considerably. That certainly has been true in

15 rheumatoid arthritis and, hopefully, it will be

16 true in some of these chronic pain studies.

17 \[Slide\]

18 At any rate, I would just say that there

19 is a rating scale in the \"San Francisco Chronicle\"

20 for movies, and so on, which has to do with the

21 little man and whether he is falling out of his

22 chair or whether he is asleep. If he likes the

23 movie he is jumping up and down, and if he hates

24 the movie he is asleep. Perhaps some day, after we

25 make all these evidence-based decisions, we can

203

1 develop a universal quality of life scale. Thank

2 you very much.

3 DR. FIRESTEIN: Thank you very much,

4 Vibeke. Does anybody have any specific questions

5 about the instruments? Steve?

6 DR. ABRAMSON: Vibeke, a question that I

7 guess that you have dealt with and the FDA has

8 begun to think about, but have you lumped together

9 diseases like RA and OA and these other pain

10 syndromes, particularly in RA where we have

11 mechanism-based therapies? So, if you treat with

12 steroids or anti-TNF blockers you get a very nice

13 response on pain. Obviously, we are going to need

14 to sort out when we look at diseases like RA what

15 it is that we are measuring.

16 I guess the related question to be

17 grappled with is that we will have pain indications

18 for OA that are separate from indications for the

19 treatment of OA. I think those are two separate

20 questions, but I guess I am mostly curious about

21 how rheumatoid arthritis would be included in these

22 kinds of studies.

23 DR. STRAND: Well, for brevity I did not

24 include the COX-2 data in rheumatoid arthritis but,

25 in fact, you can show very nice improvements by

204

1 ACR-20 responder analyses and also by SF-36 and HAQ

2 even with a medication that we would consider to be

3 largely a pain reliever.

4 Now, the magnitude of those improvements

5 is not as great as we see with our DMARDs or our

6 biologics but, in fact, most of the time patients

7 are on background therapy with those agents. So,

8 there is still some incremental improvement when

9 those patients have been taken off whatever

10 anti-inflammatory they were taking and they flared,

11 and then they would go into these trials.

12 I think the other part of that is that

13 when you see some of the improvement with the

14 COX-2s in terms of morning stiffness, which we

15 consider to be not a good component of responder

16 analysis because it wasn\'t sensitive to change, and

17 you see that the morning stiffness can be

18 completely abrogated in some of these clinical

19 trials you realize that we are again still looking

20 at multiple dimensions of a multidimensional

21 disease, and that the treatment of the

22 inflammation, either by an ostensibly mild agent or

23 even a much more significant agent, really impacts

24 many of these domains. So, there is a lot of

25 physical function and there is a lot of

205

1 health-related quality of life that is clearly

2 impacted by pain. Does that get at the question

3 you were asking?

4 DR. ABRAMSON: Yes, I think that is part

5 of it. I guess the other is if a drug has an

6 indication for OA, is it possible then to mine the

7 data on the pain aspects of the studies that allow

8 approval for OA and have a separate pain

9 indication? We need to cross over what we are

10 looking at in some of these clinical trials.

11 DR. STRAND: Well, I would certainly think

12 that we could try that. I mean, I think that it

13 has to do with the risk/benefit profile of the

14 product as to whether you would even argue that a

15 DMARD might be a pain reliever or might be usable

16 just in RA but, say, OA. I think we could consider

17 this the same type of thing and, clearly, when you

18 look at the data in OA that I showed and the data

19 that we just talked about in RA with the COX-2s and

20 the data with the COX-2s in various other pain

21 models, that is true.

22 The other side of it is I can\'t imagine

23 that if we affect structure significantly either in

24 OA or RA without a lot of other symptom

25 modification that we won\'t ultimately still see

206

1 improvement by patient-reported measures.

2 DR. FIRESTEIN: One of the questions that

3 comes up, and you addressed here to an extent, is

4 whether these domains must not be closely

5 correlated if they are going to be useful. This

6 has come up again and again with regard to

7 especially the arthritis clinical trials where the

8 ACR-20 or even pain measurements are very

9 closely\--you are going to say no? Well, in early

10 RA the HAQ scores do correlate reasonably well with

11 pain. In late RA it is primarily with erosions and

12 joint damage.

13 So, the issue is whether or not these are

14 independent variables or whether they are dependent

15 variables, and how one takes that into account when

16 trying to set up an instrument for measuring this.

17 DR. STRAND: Our definition is different

18 around close correlations. The ACR criteria, with

19 the exception of tender and swollen joint counts,

20 correlate with each other no better than an 0.4.

21 In all of the x-ray trials physical function HAQ,

22 sed rate, CRP, ACR-20 have not correlated with

23 x-ray any better than an 0.4 and usually less.

24 Even the tender and swollen joint counts that are

25 considered to be obviously appropriately changing

207

1 together have a correlation of no better than

2 around 0.7. So, I will defer to the statisticians

3 around that, but that is one of the reasons why we

4 have been able to decrease the sample sizes.

5 In terms of x-ray, we don\'t actually see

6 correlations with HAQ scores until we are looking

7 at very long disease duration, and although HAQ

8 scores correlate very high in early disease

9 patients, they go down very, very quickly when they

10 get their first DMARD. So, I think we are just

11 differing about the correlation coefficients.

12 DR. FARRAR: I want to address Dr.

13 Abramson\'s question from the following perspective,

14 which is that I think that one of our statistician

15 colleagues indicated that looking at the outliers

16 can be very informative. From that perspective,

17 for a broken femur and intramedullary rod is a pain

18 medicine with a very slow onset but a very

19 long-acting action.

20 I think your point though is well taken in

21 that when we are treating a disease as a primary

22 disease we clearly affect all of the symptoms

23 associated with that disease and, hopefully, with

24 Clifford\'s help and Mitchell\'s and others, we will

25 be able to look at it from a mechanistic

208

1 perspective and know whether we are treating the

2 disease or the pain process primarily. However, I

3 think it would be very reasonable to say that a

4 treatment for RA that improves the disease could

5 say in its labeling that it treats pain. However,

6 it would not then end up meeting the criteria for

7 treatment of a broken bone or treatment of other

8 things where we would also want to be able to use

9 it.

10 So, I think as long as we restrict and are

11 careful about how we label what the drug is

12 treating and, to the extent that we know, how it

13 improves the overall symptomatology, then we won\'t

14 have that problem.

15 Discussion of Point \# 4

16 DR. FIRESTEIN: One of the items that we

17 were asked to comment on is item number 4, to

18 discuss the domains and responder indices, and

19 address whether they adequately address the issues

20 of efficacy or safety. I would open that up for

21 the discussion. Obviously, Vibeke covered quite a

22 bit of this already. Are there other comments?

23 DR. KATZ: Just a question. I wonder what

24 people think the best way is to measure side

25 effects in these trials and how important that is.

209

1 DR. FIRESTEIN: Any comments? Yes,

2 Vibeke?

3 DR. STRAND: Well, we have our adverse

4 event reporting system which I do not want to

5 change, other than to improve it. But I think we

6 really do need to have some type of a patient

7 assessment, reported assessment of both the

8 positives and negatives of whatever intervention

9 they have undergone and they can weigh that.

10 Perhaps we do it best with a utility measure, but I

11 certainly see subsuming adverse events into that

12 because then it is in the eye of the beholder or

13 the experiencer how these adverse events truly

14 impact and should be weighed in their therapy.

15 DR. FARRAR: I think there are a couple of

16 things I would like to say about that. One is that

17 one person\'s side effect is another person\'s

18 effect. Just to make the point, if a drug is very

19 sedating it may be a very good sleeping medicine

20 and, you know, one can even look at nausea and

21 vomiting and say for ipecac that is the effect that

22 we are looking for.

23 So, the point is that the really isn\'t a

24 difference in looking at side effects and effects.

25 The measures are very often the same. I think

210

1 though that the point was just made by Dr. Strand,

2 which is that we need to allow patients to tell us

3 what is important to them, and that asking merely

4 how much of this do you have, or how frequently do

5 you have it doesn\'t get at the issue.

6 In a nice scale that was designed by Russ

7 Portnoid to look at systems, he asks how often, how

8 bad is it, and then how much does it bother you?

9 This is brought out by examples of patients that I

10 have treated for pain for whom the pain is a 10

11 and, yet, as soon as they develop a little bit of

12 constipation they go off the medicine because the

13 constipation is worse to them than the pain was. I

14 think it is important that we give patients the

15 opportunity to indicate whether or not they think

16 that side effect is important to them.

17 At the end of the day, I would have to

18 argue that you need to allow the patients to

19 integrate that information. I think it was said

20 before that we can come up with lots of models, but

21 none of those apply to every patient. A suggestion

22 might be the following, which is that I certainly

23 would want patients to think about all the various

24 pieces that go into how are you doing, like you

25 might ask them in SF-36, and at the end of the

211

1 SF-36, so you collect all that data and you have

2 all that for subanalysis, but at the end of the

3 SF-36 you say considering all of the above, are you

4 better, the same or worse than before I started the

5 medicine? That allows the patient to integrate all

6 of those different answers. We have assigned

7 values to each of them; we have dictated that pain

8 is a zero to 10 single measure in the SF-36 and

9 that there are three measures of being able to

10 move. So, we have said movement is three times as

11 important as pain by the way we analyze that study.

12 If we allow the patient simply to integrate that

13 for us by saying overall, in terms of your pain,

14 considering all of the above, are you better, worse

15 or the same we are certainly gaining a sense of

16 information that we don\'t get in any other way.

17 DR. FIRESTEIN: Isn\'t that essentially

18 what a visual analog scale would provide in

19 addition to these other instruments?

20 DR. FARRAR: You can ask the question any

21 way you like, and a visual analog scale would

22 certainly do it. From a global perspective, there

23 is evidence that a balanced scale is better so you

24 want to allow as many down steps as up steps to

25 really get a balanced view. People tend to look at

212

1 the middle of a scale and then go one way or the

2 other.

3 The other thing is you don\'t need to ask

4 globally how are you with regards to the world. I

5 think the issue was brought up before that your

6 food status, your money status and your children

7 status and all those things certainly play into it.

8 You can ask globally is your pain better, much

9 better, very much better or worse, a little worse

10 or much worse and get a global response integrating

11 the things you want.

12 DR. FIRESTEIN: Would that not be the gold

13 standard for an approvable agent? If the other

14 items were all very positive, if you were trying to

15 assess whether something is an analgesic, isn\'t in

16 the end whether their pain has improved the most

17 important measure?

18 DR. FARRAR: I would agree, and I think

19 you have stated the two important features, which

20 is if you got the full measure of all of these

21 subcomponents and at the end of the day you said,

22 you know, are you better and they said I am

23 spectacularly better but all of their others were

24 saying they were worse, you would have to wonder

25 about whether the questions were constructed

213

1 correctly. But as long as everything is at least

2 consistent, I think that the gold standard is then

3 overall are you better, worse or the same.

4 DR. STRAND: I would simply second that

5 because we are looking for a robust response,

6 therefore, we want to see it along a variety of

7 components. It could be made so this was the

8 primary outcome provided the others showed

9 improvement or no deterioration.

10 DR. MAX: Vibeke, there is some indirect

11 evidence from pain scores from large groups of

12 patients in pain clinics from Jenssen and MrFarlan,

13 in Seattle, that because of fluctuation in pain

14 from day to day a mean of at least seven

15 measurements over a week is more robust and may, in

16 a clinical trial, theoretically allow half the

17 sample size as a single measurement on the last

18 day. But I haven\'t seen any such data in clinical

19 trials. Do you want to comment on whether a single

20 pain measurement on the last day or an average is

21 more robust?

22 DR. STRAND: I will actually let Dr.

23 Farrar comment on that in one minute because my

24 experience is very limited with pain trials. But

25 in terms of looking at area under the curve

214

1 analyses, for instance, in RA trials there are a

2 lot of baseline disease activity changes over time,

3 and that is why we typically get two pretreatment

4 values to give us a baseline, both an over time

5 analysis area under the curve or a landmark

6 analysis where you are looking at responders versus

7 non-responders at the last visit, where all-cause

8 dropouts are considered non-responders, show very

9 robust findings and actually reflect what we are

10 looking at. So, I agree it could be done either

11 way provided there is a value being given to

12 keeping the patient in the trial.

13 DR. FARRAR: I think that there are sort

14 of three ways of looking at that. Mark Jenssen has

15 done some spectacular work looking at the

16 robustness of different measures he looked at. I

17 think that, clearly, if you can reduce the sample

18 size that may be seen as being of importance.

19 Obviously, the talk we had yesterday about how

20 valid the measures are on a day to day basis would

21 be important in that evaluation.

22 But I think the question really gets back

23 to something that Dr. Simon said before, which is

24 that with a sufficient number of patients you can

25 prove anything is statistically significant. I

215

1 would raise the question of if you find that you

2 can get a smaller difference to be statistically

3 significant, which is really what we are talking

4 about\--when you say cut the sample size, what you

5 mean is I can use less patients to find the

6 difference, which is what they have shown. The

7 argument has been made that the VAS is more

8 sensitive than the ten-point scale. There is no

9 question that it is; no question.

10 However, in studies that have been done,

11 as you know, the variance is something like 21 mm.

12 So, if your variance is already 21 mm, who cares if

13 you can find a difference of 5 mm on a 100 mm

14 scale? Because a 5 mm scale, at least in pain

15 management, I would argue is not clinically

16 important difference. If it was in sepsis and you

17 are providing benefit in terms of mortality,

18 improvement in mortality, I would argue five

19 percent is of tremendous importance. But in terms

20 of symptom management, I wonder whether being able

21 to detect a 5 mm change versus a 10 mm is of any

22 particular use.

23 DR. MAX: Let me respond to that. We

24 pointed out that there is essentially no data

25 looking in pain clinical trials chronically to

216

1 compare the sensitivity of what we are saying is

2 the most important value, reduction in pain. The

3 only data that I have ever seen\--thank goodness for

4 the rheumatologists\--a couple of years ago Nicholas

5 Belamy published two studies in rheumatoid and

6 osteoarthritis where he gave people 11 different

7 scales and he found that the most sensitive were

8 the VAS, the zero to ten point scale, and scales

9 that had only four points were cruder and had less

10 power.

11 So, I think we are crying out for

12 methodological studies to see if just averaging an

13 area under the curve or taking a single last day

14 measurement is important. John, I would agree with

15 you that to just take a few patients could be

16 misleading, but I think a more efficient, reliable

17 scale is always better because you can take the

18 same number of patients and get more subtle

19 differences, and perhaps prove that mechanistic

20 subsets exist. So, this is the question that I

21 would suggest to you needs to be answered,

22 particularly if it is our first outcome.

23 DR. FIRESTEIN: Dr. Anderson, and then Dr.

24 Goldkind and then Dr. Elashoff.

25 DR. ANDERSON: On this issue of seven

217

1 measurements allowing you to have the sample size,

2 I think that is likely in most cases to be an

3 exaggeration because area under the curve analyses

4 have been done in rheumatoid arthritis and compared

5 with change during the trial, just looking at the

6 beginning and the end. Although you get some

7 improvement in power, it is not that dramatic. You

8 know, you always want to have, of course, the most

9 precise measure of the outcome that you can, but I

10 wouldn\'t count on it to halve the sample size.

11 DR. GOLDKIND: I just wanted to note that

12 the term robustness and sensitivity are different

13 terms. I think that we have seen examples in the

14 agency where using end of study, just a landmark

15 analysis in chronic pain, created a p value that

16 wasn\'t there\--I am sorry, that an area under the

17 curve did where a landmark did not.

18 The issue still remains though whether

19 something is overly sensitive, or sensitive to

20 irrelevant changes, or whether they are meaningful.

21 When you are looking at how to best identify a

22 metric that will help mechanistically, I don\'t

23 think that the kind of data that we are talking

24 about now will help in that regard. You need to

25 see how the model or the endpoint that you are

218

1 using to assess the mechanism is affected by time.

2 Dr. Lu\'s presentation yesterday I think pointed out

3 that, in a sense, the two metrics, a landmark

4 versus an area under the curve, give you different

5 ways of looking at the same picture and it really

6 depends on what you are interested in. I think one

7 of her points was that both of them add value. In

8 a chronic condition you want the landmark to show a

9 difference. On the other hand, if it asymptotes

10 out at three months and there is very little up

11 front, it is important to know that as well.

12 DR. ELASHOFF: I wanted to make comments

13 in two different areas. One is that in terms of

14 planning your studies, it is generally better to

15 have a more sensitive measure. The drug works as

16 it is going to work. If you can do more studies

17 because you can do each in a smaller sample size to

18 demonstrate that that drug works, that is a better

19 thing to have from an economic point of and for

20 more science.

21 If you are concerned about the issue of

22 finding statistical significance when you don\'t

23 believe it is real important, then you have to

24 address that issue in terms of clinically

25 meaningful. It isn\'t an argument for using a less

219

1 sensitive measure so you won\'t find out what is

2 going on.

3 The second point I wanted to make is that

4 it has been stated that responder analyses don\'t

5 require imputation. That is not true. If somebody

6 quits early you still have to impute something. It

7 is just that people are more ready to agree that

8 you should impute the answer non-responder. It is

9 not that no imputation is required.

10 DR. FIRESTEIN: Any additional comments in

11 this area? Dr. Katz?

12 DR. KATZ: Just one quick comment to just

13 again shore up what I hear as a few people\'s

14 recommendation of prospectively looking at symptoms

15 and the distress associated with the symptoms from

16 the patient perspective. There are few papers, one

17 written by a guy called Richard Anderson and also

18 Marcia Testa at the Harvard School of Public

19 Health, in Boston, looking at differences between

20 antihypertensive therapy and another set of papers

21 looking at differences between oral hypoglycemics.

22 Where the efficacy of the drugs was the same, the

23 side effects captured in a typical side effects

24 capture way in pharmaceutically sponsored trials

25 were equal between groups. A battery of typical

220

1 quality of life tests showed no differences between

2 groups but a prospectively administered symptom

3 distress inventory of something like 80 items

4 showed significant differences between groups that

5 then was able to predict dropouts from the trial

6 where none of the other measures predicted

7 dropouts.

8 So, there is evidence from that literature

9 anyway that sensitive methods to detect differences

10 in symptoms distress can actually more readily

11 discriminate outcomes between groups than either

12 primary efficacy AEs captured the usual way or

13 traditionally done quality of life batteries.

14 Maybe we should look at the same thing.

15 DR. STRAND: I think what we were trying

16 to say about domains and all that, and whether it

17 is a responder analysis or whether it is, in fact,

18 what you are suggesting, by indicating there is not

19 deterioration by some of these other instruments

20 would be a very fine way of looking at the

21 responder analysis. I think all we are trying to

22 argue for here is that we assess multiple different

23 aspects of the pain condition in these chronic pain

24 studies.

25 DR. FARRAR: Just a very brief comment,

221

1 which is that in every academic trial that I know

2 of we tend to prospectively collect side effect

3 data. We ask them at every visit. We give them,

4 you know, a 20-question scale to collect the data.

5 In the pharmaceutical industry the adage is to

6 basically report things that are self-reported.

7 I think that the concern was that in the

8 ask mode you are going to get a lot more side

9 effects, and that is certainly true. However, as

10 has been demonstrated in all of the last labels

11 that I have seen, if you display the side effect

12 rate within your treatment group and your placebo

13 group you can overcome that issue of having an

14 additional number of side effects and get at this

15 issue that Nat Katz was just remarking on, which is

16 that it begins to help us explain why patients

17 respond the way they do, and perhaps even get at

18 some mechanisms that Mitchell was referring to

19 before.

20 DR. FIRESTEIN: In item four it says

21 discuss how the selection of the measurement

22 instruments of metrics may impact the assessment of

23 efficacy. I don\'t think we can specifically answer

24 that, obviously, without knowing what the metrics

25 are. But I think that has been adequately covered.

222

1 There are a number of additional optional

2 points, some of which we have actually covered in

3 some detail, including patient global issues,

4 opioid sparing, as well as the time of onset of

5 effect.

6 One of the areas that we haven\'t talked

7 about, which probably we should touch on very

8 briefly, is the placebo issue and the relative

9 merits of active comparator versus placebo

10 controlled studies. This is a problem that comes

11 up frequently, and with greater frequency in

12 rheumatoid arthritis trials where the ability to do

13 prolonged placebo controlled trials has been

14 markedly attenuated by the fact that we now have

15 effective agents, and the ethics of having placebo

16 controlled studies for longer than, say, three

17 months now has become a significant issue.

18 I was wondering if we could touch on that.

19 We talked a little bit about open-label extensions

20 earlier, but are there any comments on the use of

21 active comparators versus placebo controls for

22 either acute or chronic indications?

23 MS. MCBRAIR: I, for one, would very much

24 like to see reduction in placebo, or maybe not at

25 all, especially in acute surgical pain, also with

223

1 children, and really all people. I think if we

2 didn\'t have good comparators, then we would have to

3 look at that differently, but we do. In that case,

4 I think we shouldn\'t lean toward placebo unless it

5 is absolutely necessary for some reason.

6 DR. FIRESTEIN: Yes, if there are rescue

7 methods when it is clear that placebo\--excluding

8 children for obvious reasons, does that still fit\--

9 MS. MCBRAIR: I think rescue methods

10 certainly help but if I have waited an hour for any

11 kind of pain medication and now I am being given

12 something that is going to take an hour, those two

13 hours following a surgical case, that is a long

14 time. Two hours is a very long time.

15 DR. FIRESTEIN: I would agree with that,

16 except in rheumatoid arthritis the issues are that

17 delay of therapy can have long-term implications.

18 Whether or not an additional hour of discomfort,

19 and when there is appropriate consent, is a

20 separate issue.

21 MS. MCBRAIR: I agree with rheumatoid

22 arthritis. I was really leaning towards the

23 postsurgical pain.

24 DR. ELASHOFF: I think the biggest issue,

25 as a statistician, to the question of whether you

224

1 use a placebo or an active comparator is whether

2 you are able, when you are using an active

3 comparator, to do a superiority trial or not

4 because as soon as you get into the non-inferiority

5 trial issues there are some very significant

6 statistical problems with interpreting the results

7 of the study and it may make it very, very

8 difficult to know what is going on, especially

9 since the definitions of what is equivalent or not

10 equivalent tend to be very problematic and you

11 could easily get a situation where, from one study

12 to another to another, you are creeping toward less

13 and less efficacy for what you are approving.

14 Although people worry a lot about not giving the

15 people placebo, it is good to remember that you

16 also are giving them something that is very likely

17 to have fewer side effects when you give them

18 placebo.

19 DR. FIRESTEIN: Go ahead, Dr. Anderson.

20 DR. ANDERSON: I agree with that, and I

21 would also like to say something about post surgery

22 trials because earlier this morning Dr. Babul, from

23 TheraQuest presented some data from a post surgical

24 trial which I scribbled down, I don\'t know if I got

25 it all correct but it looked as though in the

225

1 placebo group\--you know, it was active versus

2 placebo, and there was a 55 percent response rate

3 in the placebo group and 75 percent in the active

4 group. There was more rescue medication needed in

5 the placebo group. But I would contend that even

6 in a post surgery trial, of course in the two to

7 five days not the first day, there is room for

8 placebo I think.

9 DR. FIRESTEIN: It is important to

10 remember that one of the main issues we have

11 discussed is safety, and for a compound that is in

12 early development we don\'t know whether we are

13 doing more harm than good and it may be that the

14 placebo is the preferred arm of the study under

15 certain circumstances, but who knows?

16 DR. MAX: First regarding placebo, I think

17 analgesic experts would unanimously agree with

18 Temple and Ellenburg\'s article defending the

19 importance of placebo in early drug development.

20 And, nowhere is it more important than in fields

21 like analgesia. In my 20 years at NIH we have had

22 thousands of people participate in trials and

23 receive placebos, and they have complained about

24 some things that have occurred during their care

25 but I don\'t remember anyone complaining about

226

1 having received placebo given their chance for

2 rescue and their consent process.

3 Regarding active comparators, for the

4 reasons that Temple makes very well, comparisons of

5 the new drug to an old drug without a placebo can

6 be very misleading if you don\'t establish assay

7 sensitivity. So, it is important in most cases to

8 include a placebo or vary doses of one drug as

9 well.

10 So far, in chronic pain studies it is

11 remarkable that there are almost no published

12 studies comparing within the same population drugs

13 of two different classes. So, when we have sat

14 down, a number of us around the table, to try and

15 write up consensus documents on how to treat

16 patients we have nothing to inform us. We have to

17 go to different trials where one drug is compared

18 to a placebo and then, in a different year and a

19 different group of patients in a different place,

20 another drug is compared to placebo, and because of

21 the conditions of the study there is such a wide

22 confidence interval that you really can\'t draw any

23 conclusions.

24 So, I would urge the FDA to try to

25 encourage more comparisons of a new drug to a

227

1 standard. These are hard because some people don\'t

2 want to be on a standard and it may reduce

3 enrollment. There are a lot of complex issues but

4 it would do an awful lot for prescribing practice

5 to have that information.

6 DR. WOOD: I agree with that. I think it

7 is very important that as far as we possibly can

8 ethically we include placebo. Bob and Susan in

9 their article very eloquently point out that

10 everything that we know about placebo-controlled

11 trials has stood on its head almost statistically

12 when we try to use active comparators. More

13 carelessness in the trial, all the kinds of things

14 that normally discipline us are overturned. So, I

15 think we use active comparators at our peril in

16 particular in an area like this. So, I think we

17 should certainly be using placebo as much as we can

18 with appropriate ethical and safety issues, like

19 using escapements and so on.

20 DR. FIRESTEIN: Yes, Dr. Borenstein?

21 DR. BORENSTEIN: I just want to point out

22 that the difficulty we have is that placebo works

23 so well, and if it didn\'t work so well life would

24 be much easier for us. The difficulty is placebo,

25 as pointed out, is not necessarily a bad choice,

228

1 unfortunately. When that happens we have to just

2 wonder what is happening in those individuals. So,

3 I have no trouble when asking patients to be in my

4 trials. It may not be the largest group but I do

5 think placebo is something that should be in these

6 trials, and people are willing to participate in

7 those circumstances.

8 DR. FARRAR: We aren\'t here to discuss the

9 pros and cons of the placebo effect, which

10 obviously could take a whole day in and of itself.

11 However, just a comment which is that every person

12 every day of their lives uses the \"placebo effect\"

13 to affect how they feel about what they are doing

14 and whether they go to work because they bumped

15 their leg or not. So, I think that the issue of

16 whether it exists or not and what it means is

17 important to take into consideration. As was just

18 commented, it can work really well in certain kinds

19 of syndromes, not so well in other ones. And, I

20 think that the primary issue is what Mitchell was

21 saying and what Dr. Wood was saying in terms of the

22 need to have a comparison against something that is

23 the least active, and that would be placebo with

24 the appropriate controls. It is rare that you

25 cannot come up with an ethical way to do it. Even

229

1 in a postop trial, if you are giving somebody a

2 pain medication that is supposed to work and you

3 give half of them a placebo, at the time of the

4 maximum pharmacologic dose you ask them is this

5 enough, and if it is not you give them a rescue.

6 Most patients, as I think was said, are willing to

7 participate in a study where they may have to put

8 up with some pain for a period of an hour or maybe

9 a little bit longer.

10 I think the second thing to mention is

11 that I have heard today or yesterday perhaps a

12 couple of times when people said placebo corrected

13 trials. I don\'t know what a placebo correction is

14 because the placebo effect is for free. You get

15 the placebo effect. When you give an active drug

16 you get the placebo effect. What we are really

17 looking at, and the advantage of a responder

18 analysis, is whether people reach a level where

19 they are satisfied with the relief in pain, or

20 whatever, and it doesn\'t matter what the response

21 rate is in the placebo group in terms of trying to

22 ascertain whether or not people are better. Right?

23 The question is better or not better. What then

24 matters is to decide whether the difference in the

25 response in the placebo group is sufficiently

230

1 different than the response in the active treatment

2 group. The one place where the placebo effect can

3 be problematic is if you have a population where

4 you end up at the top of a scale. If you end up

5 with the placebo effect working in 90 percent of

6 your population, then you are going to have a lot

7 of difficulty showing that last 10 percent where

8 you got a clinically important difference.

9 So, I think there are some issues but it

10 is not really related to subtracting out the

11 placebo effect. I think that doesn\'t get us

12 anywhere.

13 DR. FIRESTEIN: At this point, Lee, would

14 you like to summarize? Good luck!

15 Summary

16 DR. SIMON: Thank you, Gary and thanks

17 again to all the members of the committee for such

18 interesting discussions over the last day and a

19 half. I actually come up here with some humility,

20 being able to actually attempt to summarize what we

21 talked about and I hope that you will find it

22 useful.

23 There are a couple of statements that have

24 been made throughout from people on the committee

25 that I would like to be clear about. You know, we

231

1 are very open and we would like to believe that

2 this kind of meeting reflects how open the division

3 is to discuss with the sponsors and other

4 interested parties the way drugs are developed.

5 So, I think that is the first thing that needs to

6 be said, and can\'t be said enough.

7 \[Slide\]

8 We reviewed chronic and acute pain, and we

9 reviewed the concepts of the clinical approaches

10 and the concepts of the mechanistic approaches,

11 recognizing, of course, that the mechanistic

12 approaches are rather nascent in development. We

13 are not yet there and we still have to grapple with

14 those drugs that are presently in front of us and

15 to be soon in front of us, and have clear messages

16 about how these drugs can be approved for their

17 various different indications. Although we would

18 like to believe that the mechanistic approaches are

19 just around the corner, they are not yet there and

20 I don\'t think any of the protocols, drugs and

21 designs that we have in front of us right now are

22 actually dealing with mechanistic issues.

23 \[Slide\]

24 I think this sign really summarizes what I

25 mean by being clear. I don\'t want anybody to feel

232

1 like our division is giving you mixed messages. I

2 really would like you to believe that we are giving

3 you the real arrow to the right when it really

4 needs to be to the right.

5 \[Slide\]

6 So, we discussed temporal descriptions of

7 acute versus chronic for example, or intensity

8 differences such as mild, moderate to severe, and

9 we decided I think that they weren\'t enough to

10 really inform us about where we wanted to go. Some

11 of that is because of the issue of is chronic as

12 broad as it should be, or is it too broad, and

13 those kinds of issues.

14 So, we clearly need further clinical

15 trials to define mechanisms because we can handle

16 mechanisms better, but that is for the future, and

17 it is unknown whether there can be a global

18 analgesic right now for we know there are quite

19 different mechanisms driving the sensation of pain.

20 \[Slide\]

21 There is clear concern that we need, as an

22 agency, to design claims and consider proposed

23 trial designs fostering new development, new drug

24 development for pain. I actually think that is

25 very true. For the chronic pain proposal, I heard

233

1 some people thought it had merit. That was again,

2 just to remind everybody in case you have

3 forgotten, three models, three co-primary outcomes

4 of pain function and patient global, and it would

5 be replicated in nature with disparate

6 etiopathogenesis mechanisms or disease states.

7 They were replicated, necessary, when you were

8 doing studies in models with simpler mechanisms or

9 not. We weren\'t sure whether or not it was going

10 to need to be replicated in that particular

11 circumstance.

12 And, it seemed that in the vote we took,

13 although there was no vote but consensus building

14 that we took, although I am happy to say I

15 understand the camps, I am not entirely sure we got

16 consensus. Most people said yes to pain as a

17 measure; yes to patient global and that is a

18 measure of clinical relevance of the response; and

19 there was a qualified yes to function. We would

20 need to take that into consideration of the model

21 or mechanism or disease state that we were talking

22 about. Obviously, cancer function or a patient

23 with cancer who is functioning, that would be a

24 different issue than some other diseases.

25 There was debate of how many different

234

1 models are required to get any type of specific

2 claim for chronic pain. Are three different models

3 required? Dr. Verburg suggested four models of one

4 trial in each. Maybe Dr. Firestein resonated with

5 that a little bit. We were suggesting three models

6 with two replicate trials. Dr. Farrar suggested

7 two neuropathic models and two somatic pain models.

8 So, clearly, we will be taking back this

9 information to think more about what we should do.

10 \[Slide\]

11 In that context, the lumping and splitting

12 context is very important. We had thought we were

13 doing both lumping and splitting because we gave

14 the opportunity to split or lump. Dr. Abramson

15 kind of resonated with the rigor that would be

16 associated with that kind of approval, and it

17 really raised issues about whether it would be

18 iterative. You would get one indication and then

19 perhaps a much broader organ-based indication, and

20 then perhaps a whole disease indication, fully

21 recognizing, however, that the daunting nature of

22 the full, whole thing, the whole kit and caboodle

23 may be just too much and, in fact, companies would

24 opt for something easier, perhaps cheaper, and then

25 off-label use would drive that and that would not

235

1 be an ideal situation. I think it is really

2 critical for us to remember that we were providing

3 in our proposal that opportunity, for better or for

4 worse.

5 \[Slide\]

6 We also recognized and heard clearly that

7 acute pain is not similar to thinking about the

8 drugs that would be used to treat it. Thus,

9 actually we are thinking about short-term

10 analgesics rather than drugs for acute pain. The

11 same thing in obverse is true for chronic pain. We

12 are really thinking about drugs to be used for a

13 long period of time and that has issues regarding

14 safety and durability of response in trial design.

15 \[Slide\]

16 We learned something that I think we have

17 consensus on, that chronic low back pain, if

18 handled correctly, might be an indication to go for

19 independently, or actually may be part and parcel

20 of a much larger package. Although heterogeneous,

21 it consists of many different processes but they

22 can be delineated, and we could select a specific

23 patient population with some similarity in the

24 natural history, perhaps ignoring or removing those

25 patients with reticulopathy or neuropathy, and

236

1 perhaps we would have a model that we could use or

2 pain disease state that we could use for a clear

3 indication, as well as performance of a broader

4 label. It seemed that there was good consensus

5 about that if we made sure that we subtracted out

6 patients with neuropathic disease and systemic

7 disease.

8 I think we heard clearly that there are

9 two really broad patient populations that we have

10 not dealt with very well. One is the elderly and

11 one is the pediatric population, and we have to

12 recognize that the elderly are quite unique.

13 Polypharmacy is a significant issue with them.

14 Safety issues are particularly important, and some

15 of the elderly who are suffering chronic pain are

16 in unusual care-giving environments. Perhaps as

17 the baby-boomer population gets older it will be a

18 usual care-giving environment, but we have to learn

19 how to use nursing homes for actual study designs

20 and carrying out studies in those areas as the

21 patient population in them grows larger.

22 \[Slide\]

23 The issue of flair design was debated.

24 Some of us had problems with flair design. It

25 actually has been tried and true but, on the other

237

1 hand, it preselects those patients who both

2 tolerate the drug as well as respond. A priori

3 they have been on the drug for a period of time so

4 there are issues about that particular problem.

5 We heard about possible ways to do a

6 run-in phase and withdrawal studies, both of which

7 have problems. The run-in phase really doesn\'t do

8 anything differently than does the flare design.

9 It suggests that you are only taking patients who

10 are having a response and getting rid of all those

11 patients who can\'t tolerate the drug. So, you have

12 a true bias in the evaluation.

13 The other concept of the withdrawal phase

14 which Dr. Laska asked me to comment on was, in

15 fact, some concern about are the patients who get

16 withdrawn unblinded or not based on the symptoms

17 that emerge? So, that is an issue that I think we

18 are going to have to think about.

19 \[Slide\]

20 Many of us talked about the issue of

21 opioid sparing, although it is not dissimilar from

22 glucocorticoid sparing, and how important it is for

23 the assessment of outcome. It might be a good

24 response to measure. Would it be a primary

25 measure? Probably not. It might be a useful

238

1 secondary measure but we would have to debate that,

2 demonstrating that the study drug works and

3 decreases the need for opioids and, presumably, the

4 study drug in the circumstance would have less side

5 effects than the opioids so there would be a

6 warranted reason for the study. The problem, of

7 course, is that the study drug might enhance the

8 effects of the concomitant opioid therapy, thus

9 decreasing the use of opioids or, alternatively,

10 decreasing use of the opioids may be due to the

11 emergence of increasing toxic effects.

12 What I am constantly daunted by, and I am

13 not really that far off in glucocorticoid sparing

14 either, is that I don\'t know what it means to be

15 sparing because I don\'t know if 3 mg is better or

16 30 mg is really sparing, and I think we have to

17 debate what that really means. As mentioned by Dr.

18 Wood, there is the issue of the PK change and what

19 that would imply to the whole process.

20 \[Slide\]

21 We then moved on to the ABCs of acute

22 pain, and there seemed to be\--perhaps you could

23 show me with smiles on your faces\--less debate

24 about this. This seemed to be something that you

25 all bought into faster for good things.

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1 \[Slide\]

2 Clearly, we want to improve the

3 information in the label by turning from inferences

4 evidence by PK modeling to data derived from

5 clinical trials. That would be the multi-dose

6 assessments. That was informed by the B of the

7 ABCs.

8 We want to improve safety analysis of

9 short-term use by analyzing long-term exposures

10 even for drugs approved only for short-term use.

11 There seemed to be some confusion as to whether or

12 not, if we were going to require some chronic

13 exposure, and maybe even efficacy trials, that that

14 actually might mean two replicate trials or three

15 co-primary outcomes, maybe even three different

16 disease states. That is not really what we were

17 suggesting. It probably would be just one trial,

18 perhaps even just very robust and perhaps just one

19 outcome measure but we would have to debate that

20 and talk about it in an open fashion to determine

21 exactly what we would want. But this was then

22 informed by proposal C of the ABCs.

23 \[Slide\]

24 We clearly heard that generalizing to

25 postop pain and efficacy from a dysmenorrhea trial

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1 or dental pain trials really was a problem and we

2 have been very uncomfortable with that. So, we

3 needed to think about requiring or suggesting that

4 not only does one do an outpatient trial in such a

5 circumstance, but one might want to choose an

6 inpatient model which would give a broader aspect

7 of pain relief, thus, a bunionectomy model as well

8 as a dental pain model.

9 Additional info regarding the dosing

10 interval was needed, and that was clearly defined

11 by B of the ABCs; more optimizing of the dosing

12 schedule in responder versus non-responder

13 inclusion, which I actually found to be a

14 fascinating discussion.

15 \[Slide\]

16 Dose creep was brought up, and I think

17 that it is very important. and it came up several

18 times from the committee that we need to construct

19 our clinical trials in a real-world way to ensure

20 that we understand how the drugs are going to be

21 used in the real world, and that doesn\'t imply

22 open-label analysis; that just implies different

23 ways of thinking about trial design than we have

24 done before. Issues of longer time of use requires

25 the chronic studies, as we talked about.

241

1 \[Slide\]

2 The discussion went on after the

3 presentations regarding the matrix of clinical

4 trials. Again, I think everybody around the table

5 believed that they should inform us about

6 real-world use and should be labeled as such.

7 Time to rescue should include the

8 non-responders and that implies an

9 intention-to-treat analysis, not just a responder

10 analysis.

11 New designs with preemptive anesthesia

12 raises the question of whether or not we should be

13 thinking about that differently than acute pain,

14 and maybe that is a whole other world of trial

15 design, and all the consultants out there can start

16 to think about that and create new business for

17 yourselves, which is a good thing. Improved GDP

18 and all of that.

19 Short-term studies, pain relief, patient

20 global in terms of level of response for how long

21 and when is the onset; when it separates from

22 placebo; drugs not with onset within an hour but a

23 very good analgesic, do they inform about some

24 acute use? In fact, that came up several times,

25 this idea that there is the acute; there is the

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1 chronic; but what about kind of the middle ground?

2 We need to start to think about this subacute use

3 and what that really means.

4 \[Slide\]

5 Also, going through dose descriptions and

6 minimum time to the next dose is informed by the

7 time to onset. It needs also to be limited by

8 total dose and dose ranges may be better described

9 by quartiles of response. I really like that idea.

10 I think that really gives us a much better handle

11 on what this all means.

12 \[Slide\]

13 Lastly, but not leastly, we heard about a

14 tiered responder analysis, informing patients and

15 clinicians much more so than present analyses do

16 for pain. One could see that in acute pain you

17 could define a level of pain relief, along with the

18 duration of pain effect within the same construct

19 of explanation or description. And, in chronic

20 pain it would develop an information database

21 including efficacy, kind of encompassing pain and

22 suffering relief; durability of response; time to

23 retreatment or time to treatment failure; as well

24 as function and HRQOL measures; and then also

25 safety. So, this would be a remarkably robust data

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1 set to inform patients about what really is going

2 to go on with the therapy.

3 \[Slide\]

4 I want to close with this, and I don\'t

5 really show this entirely in jest\--entirely. This

6 was actually a real traffic sign in England where

7 they actually advertised and demonstrated the

8 directions to the secret nuclear bunker. We don\'t

9 really hold any secrets in the agency. People have

10 come over to me and said, well, would you really

11 talk to us? Or, can we come talk to you? Or, we

12 have our stuff already in and we are talking about

13 changing, are we going to be held to a different

14 standard when we have already done all of our

15 trials?

16 Well, one, you need to talk to us. Make

17 an appointment and come in for a meeting. Call

18 your project manager and see what the status is. I

19 would prefer not to hear any complaints that we are

20 not willing to talk to you. I am being very public

21 about this. We are willing to talk to you. There

22 are no secrets here.

23 Number two, we are willing to debate with

24 you as to what might be happening in this

25 particular turbulent time of change because, in

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1 fact, we are trying to do, and I think you all are

2 too, what is best for patients and to derive the

3 most information in the most open way. So, I

4 invite you to give us a call. Those of you that

5 have not been in for a while and have been busy

6 developing drugs, I really urge you to take

7 advantage of all the opportunities to have guidance

8 discussions because, in fact, it is much better to

9 come in and talk to us before you come in for your

10 pre-NDA meeting and be surprised.

11 So, in that context, let me suggest that

12 we show you the way to our secret nuclear bunker

13 and give you all the directions up front, and I

14 think everybody will be happy.

15 So, thank you again very much for coming.

16 Thank you to the committee for working so hard in

17 helping us and informing us about your ideas. I

18 don\'t know what will happen next but we will

19 certainly have another meeting about it.

20 DR. FIRESTEIN: Thank you very much. The

21 meeting is closed.

22 \[Whereupon, at 2:30 p.m., the proceedings

23 were adjourned.\]

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