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                DEPARTMENT OF HEALTH AND HUMAN SERVICES

 

                      FOOD AND DRUG ADMINISTRATION

 

                CENTER FOR DRUG EVALUATION AND RESEARCH

 

 

 

 

 

 

 

 

 

 

 

 

             ADVISORY COMMITTEE FOR PHARMACEUTICAL SCIENCE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

                       Tuesday, October 19, 2004

 

                               8:30 a.m.

 

 

 

 

 

 

 

 

 

                CDER Advisory Committee Conference Room

                           5630 Fishers Lane

                          Rockville, Maryland

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                              PARTICIPANTS

 

      Arthur H. Kibbe, Ph.D., Chair

      Hilda F. Scharen, M.S., Executive Secretary

 

      MEMBERS

      Patrick P. DeLuca, Ph.D.

      Paul H. Fackler, Ph.D.

      Meryl H. Karol, Ph.D.

      Melvin V. Koch, Ph.D.

      Michael S. Korczynski, Ph.D.

      Marvin C. Meyer, Ph.D.

      Gerald P. Migliaccio, Ph.D. (Industry

      Representative)

      Kenneth R. Morris, Ph.D.

      Cynthia R.D. Selassie, Ph.D.

      Nozer Singpurwalla, Ph.D.

      Marc Swadener, Ed.D. (Consumer Representative)

      Jurgen Venitz, M.D., Ph.D.

 

      SPECIAL GOVERNMENT EMPLOYEES SPEAKERS

      Judy Boehlert, Ph.D.

      Gordon Amidon, Ph.D., M.A.

      FDA Staff

      Gary Buehler, R.Ph.

      Lucinda Buhse, Ph.D.

      Jon Clark, M.S.

      Jerry Collins, Ph.D.

      Joseph Contrera, Ph.D.

      Ajaz Hussain, Ph.D.

      Monsoor Khan, R.Ph., Ph.D.

      Steven Kozlowski, M.D.

      Vincent Lee, Ph.D.

      Qian Li, Ph.D.

      Robert Lionberger, Ph.D.

      Robert O'Neill, Ph.D.

      Amy Rosenberg, M.D.

      John Simmons, Ph.D.

      Keith Webber, Ph.D.

      Helen Winkle

      Lawrence Yu, Ph.D.

                                                                 3

 

                            C O N T E N T S

 

                                                              PAGE

 

      Call to Order

        Arthur Kibbe, Ph.D.                                      5

 

      Conflict of Interest Statement

        Hilda Scharen                                            5

 

      Introduction to Meeting

        Helen Winkle                                             8

 

      Subcommittee Reports - Manufacturing Subcommittee

        Judy Boehlert, Ph.D.                                    26

 

      Parametric Tolerance Interval Test for Dose

         Content Uniformity                                     53

 

      Critical Path Initiative

 

        Topic Introduction and OPS Perspective

          Ajaz Hussain, Ph.D.,                                  64

 

        Research Opportunities and Strategic Direction

           Keith Webber, Ph.D.                                 105

 

        Informatics and Computational Safety

          Analysis Staff

          Joseph Contrera, Ph.D.                               117

 

        Office of New Drug Chemistry

          John Simmons, Ph.D.                                  165

 

      Open Public Hearing

        Saul Shiffman, Ph.D.                                   192

 

      Critical Path Initiative--Continued

 

        Office of Generic Drugs

          Lawrence Yu, Ph.D.                                   204

 

        Office of Biotechnology Products--Current

          Research and Future Plans

            Amy Rosenberg, M.D.                                248

            Steven Kozlowski, M.D.                             282

                                                                 4

 

                      C O N T E N T S (Continued)

 

                                                              PAGE

 

        Office of Testing and Research--Current

          Research and Future Plans

            Jerry Collins, Ph.D.                               316

            Lucinda Buhse, Ph.D.                               338

            Mansoor Khan, R.Ph., Ph.D.                         362

 

      Wrap-up and Integration

        Jerry Collins, Ph.D.                                   410

 

      Challenges and Implications

         Vincent Lee, Ph.D.                                    419

 

      Committee Discussion and Recommendations                 428

 

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                         P R O C E E D I N G S

 

                             Call to Order

 

                CHAIRMAN KIBBE:  Ladies and

 

      gentlemen--welcome.  I want to take a little page

 

      from the coach at the New York Times, who says that

 

      a meeting that starts that eight o'clock actually

 

      starts at five minutes before.  And to get us

 

      rolling in about 30 seconds, ahead of time.

 

                Do we know--

 

                [Comment off mike.]

 

                --he'll be here tomorrow.  All right.

 

      So--Dr. Amidon, my co-pilot here, will be here

 

      tomorrow.

 

                I'd like to call you all to order for my

 

      last go-round as Chairman of this August body.  And

 

      the first order of business, of course, is to read

 

      about all of our conflicts.

 

                     Conflict of Interest Statement

 

                MS. SCHAREN:  Good morning.

 

                The following announcement addresses the

 

      issue of conflict of interest with respect to this

 

      meeting, and is made a part of the record to

 

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      preclude even the appearance of such.

 

                Based on the agenda, it has been

 

      determined that the topics of today's meeting are

 

      issues of broad applicability, and there are no

 

      products being approved.  Unlike issues before a

 

      committee in which a particular product is

 

      discussed, issues of broader applicability involve

 

      many industrial sponsors and academic institutions.

 

      All special government employees have been screened

 

      for their financial interests as they may apply to

 

      the general topics at hand.

 

                To determine if any conflict of interest

 

      existed, the Agency has reviewed the agenda and all

 

      relevant financial interests reported by the

 

      meeting participants.  The Food and Drug

 

      Administration has granted general matters waivers

 

      to the special government employees participating

 

      in the meeting who require waiver under Title 18,

 

      United States Code Section 208.

 

                A copy of the waiver statements may be

 

      obtained by submitting a written request to the

 

      Agency's Freedom of Information Office, Room 12A30

 

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      of the Parklawn Building.

 

                Because general topics impact so many

 

      entities, it is not practical to recite all

 

      potential conflicts of interest as they may apply

 

      to each member, consultant and guest speaker.  FDA

 

      acknowledges that there may be potential conflicts

 

      of interest, but because of the general nature of

 

      the discussions before the committee, these

 

      potential conflicts are mitigated.

 

                With respect to FDA's invited industry

 

      representative, we would like to disclosed that

 

      Paul Fackler and Mr. Gerald Migliaccio are

 

      participating in this meeting as a non-voting

 

      industry representative, acting on behalf of

 

      regulated industry.

 

                Dr. Fackler's and Mr. Migliaccio's role on

 

      this committee is to represent industry interest in

 

      general, and not any one particular company.  Dr.

 

      Fackler is employed by Teva Pharmaceuticals,

 

      U.S.A., and Mr. Migliaccio is employed by Pfizer,

 

      Incorporated.

 

                In the event that the discussions involve

 

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      any other products or firms not already on the

 

      agenda for which FDA participants have a financial

 

      interest, the participants' involvement and their

 

      exclusion will be noted for the record.

 

                With respect to all other participants we

 

      ask, in the interest of fairness, that they address

 

      any current or previous financial involvement with

 

      any firm whose products they may wish to comment

 

      upon.

 

                Thank you.

 

                CHAIRMAN KIBBE:  Thank you.

 

                And now we'll hear from the Director of

 

      the Office of Pharmaceutical Sciences, Ms. Helen

 

      Winkler.

 

                        Introduction to Meeting

 

                MS. WINKLE:  Good morning, everyone.

 

                All right, I want to welcome everybody

 

      this morning to the Advisory Committee for

 

      Pharmaceutical Science.  This is, I think, a very

 

      important meeting, and I"m really looking forward

 

      to the discussion.  But before we get there, I want

 

      to welcome all of the members.  We have one new

 

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      prospective member, Carol Gloff--Dr. Gloff--has

 

      joined us.  And we have two other prospective

 

      members who we're having a little complication with

 

      in getting on board.  So we're working on that.

 

                We also will have a number of SGE's here

 

      today; Dr. Boehlert, Dr. Amidon and several others

 

      who are going to participate with us in a number of

 

      things.  So I want to welcome everybody.

 

                I also want to thank Dr. Kibbe.  This is

 

      his last time as Chair.  It will break all of our

 

      hearts to see Dr. Kibbe go out of this position.

 

      He has been very, very enthusiastic as the Chair of

 

      this committee, and I think all of us have enjoyed

 

      working with him.  But he's not to go very far.

 

      We've already told him that we anticipate him

 

      coming back to a number of meetings and helping us

 

      with some of the discussion in the future.  So we

 

      really want to, again, thank him for all he's done.

 

                Dr. Cooney--Charles Cooney--has agreed to

 

      be the chair of the committee for the next two

 

      years.  Unfortunately, Dr. Cooney couldn't be

 

      here--after he accepted, he couldn't be here today.

 

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      But he will be here at the next meeting.  So--he's

 

      been very gracious to accept this position.  He and

 

      I have talked at length about some of the issues we

 

      want to cover on the Advisory Committee, and he's

 

      very enthusiastic about moving ahead for the future

 

      of the committee.

 

                The agenda for the meeting today:  there's

 

      a number of things we want to take up.  I'm going

 

      to talk a little bit about next year--2005 being, I

 

      guess, this fiscal year--and some of the things

 

      that we plan to take up with the Advisory

 

      Committee, where we're going in OPS, just to give

 

      the committee a little feel about some of the

 

      things that we're looking at.

 

                I also want to give a quick--and I mean a

 

      quick--update of the cGMP Initiative for the 21                          

                                                                                

  st

 

      Century.  We're also going to have an update on a

 

      number of the subcommittee and working groups.  Dr.

 

      Boehlert is going to talk about the Manufacturing

 

      Subcommittee meeting that we had several months

 

      back.  It was a very, very--we accomplished a lot,

 

      I think.  It was a very good meeting.  And Judy can

 

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      fill us in on some of the highlights of that

 

      meeting.  Also Bob O'Neill is going to talk about

 

      the Working Group with IPAC RS, and some of the

 

      accomplishments--or the focus that we've had in

 

      that Working Group.

 

                We're also going to talk about the

 

      Critical Path Initiative.  And I think this is a

 

      really important discussion that we can have with

 

      the committee today.  Critical Path is, of course,

 

      one of the main initiatives in the agency now, and

 

      what we would like to talk about with the committee

 

      is give you some idea of our thoughts, as far as

 

      Critical Path; some of the things that we're doing

 

      in the Critical Path Initiative, in the office of

 

      Pharmaceutical Science in the various product

 

      areas, and get some input from you as to what

 

      direction we need to go; if there's other things we

 

      need to be thinking about; and if there's other

 

      types of topics that we need to be taking up, we'd

 

      like to do that.

 

                Dr. Woodcock talked about the Critical

 

      Path Initiative when she introduced it, saying that

 

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      FDA was really in the best position to identify

 

      those areas, or those gaps, in drug development,

 

      and to work with others--collaborate--on how we

 

      could get the data necessary to fill those gaps.

 

                So this is really what we're looking for

 

      doing under the Critical Path Initiative.  And we

 

      need to be certain that we are identifying the gaps

 

      correctly, and that we are able to do the types of

 

      research that needs to be done to fill those gaps.

 

      Of course we can't do everything, so I think some

 

      of what we want to talk about and think about, too,

 

      is how we can prioritize some of that research.

 

                Tomorrow, we're going to talk about

 

      manufacturing, and moving toward the desired state.

 

      As I said, we had a very productive meeting of the

 

      Manufacturing Subcommittee.  A number of things

 

      were identified at that meeting that we need to

 

      discuss further; that we needed to look at and

 

      determine how we're going to do it.  A number of

 

      questions that we need to answer--and we're looking

 

      at possibly having a subgroup to do some of that--a

 

      fact-finding group.  So Judy will talk to that.

 

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                But there are a number of things, too,

 

      that we want to talk about with the committee

 

      today; a number of--the gaps that we recognize that

 

      we have in OPS and the agency, in moving toward

 

      that desired state.

 

                So several of us are going to talk about

 

      those gaps.  We're going to talk about the

 

      organizational gaps, the science gaps, and the

 

      policy gaps--all of which are important if we in

 

      the agency are going to be prepared as the

 

      manufacturers and others move toward that desired

 

      state.

 

                So I think that will be a really

 

      interesting issue, and I think there are a number

 

      of things that the committee can help us with in

 

      identifying how best to address these answers and

 

      to address the gaps.

 

                We also have a number of bio-equivalence

 

      issues that we want to discuss.  We want to

 

      continue the conversation from the last Advisory

 

      Committee we had on bio-equivalence.  And Dr. Yu

 

      and some of his staff are going to talk about some

 

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      recommendations from that.  And we're also going to

 

      bring up a new topic on gastroenterology drugs.

 

                So--moving on to OPS in 2005.  I think

 

      2004, we had an extremely busy year, mainly focused

 

      on the GMP Initiative, and all of the aspects of

 

      that initiative--especially the areas concerning

 

      manufacturing science and how wee were going to

 

      really address those issues and concerns, and how

 

      we were going to incorporate those into the

 

      regulatory framework.

 

                As we move into 2005, I think we still

 

      have a lot of issues that we have to handle under

 

      Pharmaceutical Quality Initiative.  We've already

 

      said that that's going to be some of what we take

 

      up with the Advisory Committee today.  But we

 

      really need to pursue those next steps.  In doing

 

      that, though, we also need to be looking at

 

      continuing to streamline the review processes.  We

 

      continue to get more and more products in for

 

      review, and there's got to be some way to offset

 

      that increasing workload.  And streamlining the

 

      review processes seems to be--we're moving in that

 

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      direction, and it seems to be the answer to

 

      handling some of the enormous workloads that we

 

      have.

 

                Also, we need to incorporate best

 

      practices.  We've added the Office of Biotech

 

      Products in the last year.  They joined us in

 

      October of 2003, and they have a lot of practices

 

      in their review that I think can be very helpful as

 

      we move forward in looking at ways to improve--both

 

      in out office of New Drug Chemistry, and our Office

 

      of Generic Drugs.

 

                So we're going to be looking at

 

      incorporating best practices across the entire

 

      organization.

 

                Supporting the Critical Path

 

      Initiative--I've already brought this up.  It's a

 

      very important part of where we're going.  I think

 

      much of our research is going to be done there, and

 

      I think we're talking about much more than

 

      laboratory research. I think there's a number of

 

      activities that we hope to take on in 2005 where

 

      we're looking at improving on how we do the

 

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      regulation, and in actually working through the

 

      Critical Path Initiative to get some of this done.

 

      So we'll talk more about that as we get into

 

      Critical Path and some of those projects that we're

 

      looking at doing.

 

                We're looking at further integrating the

 

      whole Office of Biotech products.  There are still

 

      some things that need to be accomplished there.  I

 

      think there are still a number of questions that

 

      the Advisory Committee can be very helpful to in

 

      answering.  So you will hear more about this in the

 

      next fiscal year.

 

                And, last of all, I think there still

 

      continues to be a number of regulatory on follow-on

 

      proteins, as well as a number of general scientific

 

      issues that we'll want to discuss with the

 

      committee.

 

                So I think we have a lot on our plate

 

      during the year, and I look forward to working

 

      closely with the Advisory Committee in the next

 

      fiscal year to help us identify some of the--other

 

      things that we need to look at, as well as help us

 

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      with the issues that we already have identified

 

      ourselves.

 

                Okay.  As I said, I'm going to talk real

 

      quickly about the CGMP Initiative for the 21st

 

      Century.  I think most of you all have probably

 

      read the background material, which included the

 

      report.  We've actually come to the end of the

 

      first two years of the initiative.  And I"d like to

 

      emphasize:  I don't think that's the end of the

 

      initiative.  I think it's just the beginning.  I

 

      think that the initiative helped us identify a

 

      number of things that we need to be looking at in

 

      review, that we need to be looking at in

 

      inspection.  We still have a lot of changes to

 

      make.  I think we've made a lot of progress--and

 

      I'll talk a little bit about some of that progress.

 

      But I think we've got a lot more that we have to

 

      focus on.

 

                So that was only, in my mind, the first

 

      step.

 

                But I thought it would be helpful just to

 

      step back real quickly and look at what the goals

 

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      of the initiative were.  Because I think you can't

 

      really appreciate the accomplishments without

 

      really understanding what the goals were.

 

                So there were basically six major goals.

 

      The first one was to incorporate the most

 

      up-to-date concepts of risk management and quality

 

      systems approaches; secondly, was to encourage the

 

      latest scientific advances in pharmaceutical

 

      manufacturing and technology, ensure submission

 

      review program and the inspection program operating

 

      in a coordinated in synergistic manner; apply

 

      regulation and manufacturing standards

 

      consistently; encourage innovation in the

 

      pharmaceutical manufacturing sector; and use FDA

 

      resources most effectively and efficiently to

 

      address the most significant health risks.

 

                And you can see, when you look back at

 

      these initiatives, the role OPS has had to play in

 

      all of these goals.  I think they're very

 

      important, not only to the agency, but important to

 

      us at OPS, and important to the industry and others

 

      involved in the manufacturing of pharmaceutical

 

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      goods.

 

                So, quickly, through the

 

      accomplishments--again, you can read the report.

 

      You'll get a lot more out of the report.  But I

 

      just want to emphasize that there was an awful lot

 

      done in the last two years; a lot that will affect

 

      how we move forward in the future, in the 21st

 

      century.  So I wanted to highlight those.

 

                The first thing was Part 11.  We did a

 

      last in the last two years to clarify the scope and

 

      application of Part 11.  There were quite a few

 

      questions; quite a bit of complication in

 

      implementing Part 11.  And I think we've moved

 

      forward in trying to eliminate some of that

 

      complexity and complication.  We issued two

 

      guidances during the two-year period that have

 

      helped in that clarification.

 

                Technical Dispute Resolution Process--this

 

      was also a very important part of the initiative.

 

      And it really has had a very positive effect, I

 

      think, on the industry, and a positive effect on

 

      how the field has dealt with inspections and has

 

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      increased the time and effort that the inspectors

 

      are putting into the inspections, and the time and

 

      effort that they're spending with industry when

 

      they go in and do these inspections.  And it has

 

      really been the basis of much discussion in the

 

      inspection process.  And the outcome--we have not

 

      had any technical disputes.  We have a very good

 

      process--as I said, the process has sort of set the

 

      framework for opening up the discussion.  And so I

 

      think that it has had a really positive effect.

 

      I'm actually a co-chair of that group. I kept

 

      waiting for disputes.  I thought we were just going

 

      to have tons of them.  We have a pilot program, and

 

      I thought in the 12 months of the pilot we'd be

 

      able to figure out how best to run the program.

 

      But not having any disputes, we haven't learned a

 

      whole lot of lessons.

 

                But, again, it's had its very positive

 

      effects.  So I think that it has really been useful

 

      under the initiative.

 

                The GMP warning letters--this was an issue

 

      that was handled very early on.  And we

 

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      accomplished the goals that we wanted under this

 

      particular working group of the initiative; and

 

      that's that warning letters now are reviewed by the

 

      Center to ensure--in the Center before they go out

 

      to the companies--to ensure that they have adequate

 

      scientific input.  Many of the warning letters that

 

      went out in the past were not reviewed to make sure

 

      that the issues were scientifically sound.  So that

 

      has changed now.  And I think that's had a very

 

      positive effect.

 

                International collaboration--I won't go

 

      into that, but we have spent a lot of effort in

 

      ICH, and Q8, Q9, and hope to do a lot in Q10.  And

 

      also one of the things we are planning on doing is

 

      getting more involved with PICS, which is looking

 

      at inspections on a worldwide basis.

 

                Facilitating innovation--including doing

 

      standards and policies--we were very fortunate to

 

      put out a number of different guidances under this

 

      part of the initiative; the aseptic processing

 

      guidance--which industry is very familiar with.

 

      They've been waiting for this guidance for a long

 

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      time.  And I think it addresses many of the

 

      questions that have been out there in industry's

 

      mind.  So I think it's a very, very positive part

 

      of the initiative that we were able to accomplish.

 

                The next guidance that was put out--I

 

      think many of the people--in fact, everyone on the

 

      Advisory Committee is very familiar with this

 

      guidance, because we did have a subcommittee on the

 

      PAT--the Process Analytical Technologies--under the

 

      subcommittee, and we were able to put, under Dr.

 

      Hussain and others in the group, we were able to

 

      put out a guidance to industry which has had an

 

      extreme effect, I think, on how industry and others

 

      are looking at manufacturing in the future.  I

 

      think it's been probably one of the best parts of

 

      the whole initiative.  It really has promoted the

 

      two--the team approach to doing work; working on

 

      standards.  We've worked with ASTM under E55.  And

 

      I think, all in all, this has been an extremely

 

      successful initiative under the GMP initiative.

 

                The last guidance that we've had, that was

 

      comparability protocol.  That guidance is still in

 

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      limbo.  We're trying to make sure that before we

 

      issue the guidance that we're not increasing the

 

      regulatory burden--which I think many of us felt

 

      when we read the original draft guidance.  So we're

 

      busily working on that to make sure that what we

 

      come out of is very beneficial to industry and to

 

      FDA, and that we don't put any additional resource

 

      requirements on either part of the regulatory

 

      system.

 

                Manufacturing science--the desired state

 

      under !8 of ICH has become a very important aspect

 

      of where we're driving to.  And, of course, we're

 

      going to talk to that tomorrow morning; continuous

 

      improvement and reduction of variability have been

 

      an important part of manufacturing science, and

 

      areas that we need to explore more in the future,

 

      and assure that we can accomplish that, especially

 

      being able to open up in the agency and allow more

 

      continuous improvement for manufacturers.

 

                Product specialists--this includes

 

      enhancing the interactions between the field and

 

      the review.  We're looking at a team approach, in

 

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      having our reviewers all out on inspections.  And

 

      we're looking at best practices from both the PAT

 

      team and Team Biologics.  I think there's a lot of

 

      best practices there that we can incorporate in out

 

      thinking in the future on how we handle review and

 

      inspection.

 

                Integration of approval and

 

      inspection--this is more of that.  We have

 

      developed the pharmaceutical inspectorate, and

 

      we're looking also at changes in pre-market

 

      approval program.

 

                Quality management systems--there's a

 

      number of things that we've worked on here.  They

 

      take a number of directions.  We've developed a

 

      standard quality systems framework; a quality

 

      systems guidance.  We've worked on GMP

 

      harmonization, analysis process validation, and

 

      good guidance practices--none of which are going to

 

      go into in detail, but I think all very beneficial

 

      to helping us in the future in the 21                                     

                                                        st century.

 

                Risk management--risk management, I had

 

      thought--we did introduce a site-selection model

 

                                                                25

 

      for inspection under this part of the initiative.

 

      I believe there's a number of other things that we,

 

      especially in Review, need to focus on as far as

 

      risk management, and have a much better idea of

 

      what the risk of products are, and how we're going

 

      to mitigate those risks.  And I think this is

 

      something that we will bring up in the future at

 

      the committee.

 

                Team Biologics was to look at a number of

 

      initiatives that were already underway, and adopt a

 

      quality systems approach.

 

                And last of all was the evaluation of the

 

      initiative, which hasn't been completed yet, but

 

      it's a very important part of what we've done.

 

                So that, in a nutshell--I mean, that's a

 

      lot of effort, obviously, that we've done.  And if

 

      you, again, will read the report I think you'll get

 

      a much better feel.  But I felt like, since we've

 

      talked about it so much during the last few years,

 

      that it was very important to sort of wrap up what

 

      has happened in the last two years with this

 

      committee.

 

                                                                26

 

                So that's all I have to talk today.  I'm

 

      going to give it back to Art, and I look forward to

 

      very lively discussion on a number of these issues,

 

      and look forward to working with you for the next

 

      two days.

 

                Thank you.

 

                CHAIRMAN KIBBE:  Thank you, Helen.

 

                We now have a report from the chair of one

 

      of the subcommittees--the Manufacturing

 

      Subcommittee.

 

                Judy?

 

                          Subcommittee Reports

 

                       Manufacturing Subcommittee

 

                DR. BOEHLERT:  Good morning, ladies and

 

      gentlemen.  Before I just get started here--I tried

 

      pressing down, and--aha.  I need an SOP for how to

 

      operate the slides.

 

                [Slide.]

 

                It's a pleasure for me to be here this

 

      morning to update you on the Manufacturing

 

      Subcommittee.  We met in July.  And I think you'll

 

      find that a lot of the topics we discussed tie in

 

                                                                27

 

      very well with what Helen was talking about this

 

      morning, and also with some of the topics that are

 

      going to be on your agenda.

 

                [Slide.]

 

                We met for two days in July.  Just a brief

 

      overview of the topics that we discussed:  quality

 

      by design--we've heard that this morning;

 

      introduction to Bayesian approaches--and we'll talk

 

      just a little bit about that; research and training

 

      needs--the industrialization dimension of the

 

      Critical Path Initiative--another topic we heard

 

      about this morning; manufacturing science and

 

      quality by design as a basis of risk-based CMC

 

      review; and risk-based CMC review paradigm.

 

                [Slide.]

 

                On the 21                                                      

       st:  introduction to

 

      pharmaceutical industry practices research study; a

 

      pilot model for prioritizing selection of

 

      manufacturing sites for GMP inspection; cGMPs for

 

      the production of Phase I INDs; and applying

 

      manufacturing science and knowledge, regulatory

 

      horizons.

 

                                                                28

 

                What I'm going to do is just go over,

 

      briefly, some of the topics that were discussed,

 

      and also the comments that were made by committee

 

      members.

 

                [Slide.]

 

                Quality by design:  topic updates.  This

 

      addressed three guidances that should be coming out

 

      of ICH.  The first of ICH Q8, which is a guidance

 

      on pharmaceutical development section of the Common

 

      Technical Document.  It's going to describe

 

      baseline expectations and optional information;

 

      requires FDA and industry to think differently.

 

      Industry needs to be more forthcoming with

 

      information in their submissions, and FDA needs to

 

      look at the review process; focuses on process

 

      understanding and predictive ability.  And if you

 

      really understand your process, you'll gain

 

      regulatory flexibility.  It's a framework for

 

      continuous improvement.  And Step 2 is expected in

 

      November this year.  That means it will be out for

 

      public review and comment.

 

                [Slide.]

 

                                                                29

 

                ICH Q9 is quality risk management.  It

 

      looks at risk identification--should link back to

 

      the potential risk to the patient, because, after

 

      all, that's what's important; risk assessment--what

 

      can go wrong?  What is the likelihood?  What are

 

      the consequences?

 

                Risk control--options for mitigating,

 

      reducing and controlling risks; risk

 

      communication--between decision makers and other

 

      shareholders.  And this may also reach step two in

 

      November of this year, although that was a bit

 

      questionable.

 

                [Slide.]

 

                And then we're going to talk about quality

 

      systems needed to recognize the potential of !8 and

 

      Q9.  And this is ICH Q10:  monitor and evaluate

 

      processes with feedback groups in a manner to

 

      identify trends and demonstrate control or the need

 

      for action; manage and rectify undesirable

 

      occurrences; handle improvements; management,

 

      implement and monitor change.

 

                This is currently on hold, not because

 

                                                                30

 

      it's not a good topic, but primarily because all

 

      the resources that would address Q10 are tied up

 

      with Q8 and Q9.

 

                [Slide.]

 

                We also talked about the ASTM E55

 

      Committee.  And Helen mentioned that this morning.

 

      Their involved in the development of standards for

 

      PAT.  And the important things here are consensus

 

      standards, with input from industry, academia and

 

      regulators.  There's an established process, with

 

      an umbrella set of rules.  And ASTM is recognized

 

      worldwide.

 

                They have three functional subcommittees

 

      on management, implementation and practices and

 

      terminology.  But one of the concerns expressed by

 

      the committees is are they going to duplicate other

 

      initiatives.  There area lot of people right now

 

      working on PAT initiatives, and are they going to

 

      duplicate some of that.  So we need to make sure

 

      that everybody gets on the same page.

 

                [Slide.]

 

                All right.  Now, this topic I'm going to

 

                                                                31

 

      be reluctant to say a whole lot about, but we had

 

      an introduction to Bayesian approaches.  Dr. Nozer

 

      Singpurwalla was kind enough to give us an

 

      introduction to the topic.  So, Nozer, I apologize

 

      if I mis-speak when I summarize--[laughs].

 

                You know--so it's with fear and

 

      trepidation--he's threatened us a quiz--

 

                DR. SINGPURWALLA:  You've already done it.

 

                DR. BOEHLERT:  Yes, I know. [Laughs.]

 

      That's what I was afraid of.  But I didn't think I

 

      could leave it out, or you'd get after me then,

 

      too.

 

                Okay--Reliability for the Analysis of

 

      Risk."  Reliability--the quantification of

 

      uncertainty.  And I'm just going to say a few words

 

      here:  utility--costs and rewards that occur as a

 

      consequence of any chosen decision.  These are the

 

      things that Nozer talked to us about--risk

 

      analysis--process assessing reliabilities and

 

      utilities, including an identification of

 

      consequences.  We talked about scales for measuring

 

      uncertainty--for example, probability.

 

                                                                32

 

                [Slide.]

 

                Now this is a quote, so I have to be

 

      careful here.  "When the quantification of

 

      uncertainty is solely based on probability and its

 

      calculous, the inference is said to be Bayesian."

 

      I am not a statistician, so I'm certainly not a

 

      Bayesian statistician.  And then there is

 

      discussion of use of Bayesian approaches for ICH

 

      Q8, Q9, Q10 and the use of prior information.

 

                [Slide.]

 

                Industrialization--dimension, the Critical

 

      Path Initiative.  We heard about that this morning.

 

      We'll hear about it in the next two days:

 

      examining innovational stagnation.  Everybody needs

 

      to take a look at what we've been doing in the past

 

      and get things moving forward in a new environment,

 

      with new technologies.

 

                Critical path--has been inadequate

 

      attention in areas of new or more efficient

 

      methodologies and development research.

 

                Industrialization--goes from the physical

 

      design of prototype up to commercial mass

 

                                                                33

 

      production.  And Education and research

 

      infrastructure needs improvement.  And this

 

      education and research applies to industry; the

 

      education also applies to the agency.  We all need

 

      to learn how to go forward in the new environment.

 

                [Slide.]

 

                FDA has a strong interest in computational

 

      methodologies to support chemistry and

 

      manufacturing control submissions.  They're putting

 

      together a chemometrics group.  There's a new FDA

 

      research program focusing on industrialization

 

      dimension.  And there's training needs.  AS I

 

      mentioned before, particularly with the

 

      pharmaceutical inspectorate.  That's started.

 

      There is an inspectorate now of trained

 

      investigators.  There need to be more.

 

                [Slide.]

 

                Manufacturing science and quality by

 

      design--it's a basis for risk-based CMC review.

 

      Companies share product-process understanding with

 

      regulators.  And this is a new paradigm, if you

 

      will, that companies will share more of the

 

                                                                34

 

      information that they have available than they have

 

      in the past.

 

                Specifications should be based on a

 

      mechanistic understanding of the process; there

 

      should be continuous improvement; and real time

 

      quality assurance.  You shouldn't have to wait

 

      until the end of the process to know that your

 

      product is okay.

 

                [Slide.]

 

                Science perspective on

 

      manufacturing--define current and the desired state

 

      and the steps to go from here to there; define

 

      terms--and this is going to be important going

 

      forward--things like "manufacturing science,"

 

      "manufacturing system," "manufacturing

 

      capability"--what do they really mean?

 

                Real case studies will help.  This came up

 

      time and again in the committee discussions.  It's

 

      nice to talk about all these theoretical concepts,

 

      but give me a real case study that I can look at

 

      and see what it really means.

 

                Testing is mostly non-value added. 

 

                                                                35

 

      Quality by design is the desired state.

 

                [Slide.]

 

                Risk-based CMC review--from the Office of

 

      New Drugs--should provide regulatory relief by

 

      incorporating science-based risk assessment; more

 

      product or process knowledge shared by the

 

      industry--and I've said this several times; more

 

      efficient science-based inspections; focus

 

      resources on critical issues; and specifications

 

      are based on a risk-based assessment.

 

                [Slide.]

 

                Quality assessment rather than a chemistry

 

      review--in the past it's been a strict chemistry

 

      review:  go down the list and check off the boxes;

 

      conducted by inter--and I see some smiles on the

 

      parts of agency folks--conducted by

 

      interdisciplinary scientists--so it could be a team

 

      approach.  It should be a risk-based assessment;

 

      focus on critical quality attributes and their

 

      relevance to safety and efficacy.  They have to

 

      rely on the knowledge provided by applicants.  If

 

      industry doesn't submit the information, the agency

 

                                                                36

 

      has nothing to make their decisions on.  And the

 

      comparability protocols are an important part of

 

      this review.

 

                [Slide.]

 

                Role of process capability in setting

 

      specifications will need to be addressed.  Very

 

      often, those kinds of process controls that you

 

      have may have no clinical relevance.  The knowledge

 

      base at the time of submission can be an issue,

 

      because very often you don't have that much

 

      information at the time you submit.  It's a

 

      learning process as you go through early

 

      marketability and commercial production.

 

                Specifications should not be used as a

 

      tool to control the manufacturing process.  And we

 

      might need to expand the Quality Overall Summary

 

      going forward.

 

                [Slide.]

 

                AS I said before, the extent of product

 

      knowledge is key.  Risk-based decisions should be

 

      based on supportive data.  Voluntary--all of these

 

      new initiatives are voluntary.  And that needs to

 

                                                                37

 

      be made very clear to the industry.  These are not

 

      requirements that everybody drop what they've been

 

      doing in the past and start over with new

 

      approaches--strictly voluntary.

 

                Supplement need is based on the knowledge

 

      of the risk of the change.  And there should be a

 

      clear rationale for the selection of

 

      specifications.

 

                [Slide.]

 

                Identify critical parameters for product

 

      manufacturing and stability; train FDA staff and

 

      regulated industry--this came up a number of times.

 

      We all need to learn what the other is doing;

 

      should give us--industry--greater flexibility in

 

      optimizing the process; should lessen the

 

      supplement burden, which is good for industry and

 

      good for the agency.  And, once again, real

 

      examples would be an asset.

 

                [Slide.]

 

                In the Office of Generic Drugs--generic

 

      industry's focus is on producing a bioequivalent

 

      product.  Often patent issues--to design around. 

 

                                                                38

 

      They may not have the flexibility as the new drug

 

      folks.  Workload in OGD is a significant issue, and

 

      committee members made a number of comments on this

 

      when they heard how many submissions there are, and

 

      how far behind they are.  We were impressed by the

 

      workload.

 

                Provide advice to industry on improving

 

      quality of DMFs--those are "drug master

 

      files"--very important to the generic

 

      industry--also to the new drugs, but to a lesser

 

      extent.

 

                [Slide.]

 

                Desired state--include needed data in a

 

      filing; process and product design; identify

 

      critical attributes; identify process critical

 

      control points.  And this is the difference from

 

      the past.  Analyze data to produce meaningful

 

      summaries and scientific rationales; and reviewers

 

      assess the adequacy of the submission by asking the

 

      right questions.

 

                [Slide.]

 

                Okay--some additional committee comments

 

                                                                39

 

      that came out of the Day One discussion:  ICH and

 

      ASTM appear to be synergistic, but ICH needs to be

 

      very aware of the ASTM focus.  There was some

 

      concern they might not be tied into what's going on

 

      there; some concern that FDA, internally,

 

      themselves, may be getting ahead of what's

 

      happening on an international basis. So they may be

 

      a little ahead of ICH Q8, Q9 and Q10.  That's not

 

      necessarily a bad thing, by the way.

 

                Need concrete examples--that came up time

 

      and time again; need to clearly demarcate "minimum"

 

      and optional information--you know, just what do

 

      you mean by "this is the minimum you need," and

 

      just what is "optional" information?  And

 

      "optional" information comes in degrees.  The more

 

      you make the more you know.  So you may not have as

 

      much information at submission as you will down the

 

      road after you've been in commercial product for a

 

      number of months or years.

 

                [Slide.]

 

                Need to avoid implying there are two

 

      different quality concepts.  We don't want to say

 

                                                                40

 

      that products made in the conventional way---the

 

      way we've always done it--are different than

 

      products that may be made according to some new

 

      paradigms.  Bring in new training programs--and

 

      Helen mentioned we're talking about forming a

 

      working group under the Manufacturing Subcommittee

 

      to address some of the issues, particularly case

 

      studies.

 

                We need to find better terms than

 

      "minimal" and "optional;" and focus on process

 

      first, and then the tools that we're going to need.

 

                [Slide.]

 

                We had some reports on an FDA research

 

      project that's being done by Georgetown University

 

      and Washington University, and their goal is to

 

      identify attributes that impact inspection

 

      outcomes.  They're compiling and linking FDA

 

      databases.  They're looking at variables for

 

      product-process, facility, firm and FDA.  Right now

 

      they're collecting data.  CDER is just about

 

      completed, and CBER is ongoing--although by now it

 

      may be even further down the road.  This was July.

 

                                                                41

 

                [Slide.]

 

                Focus--are cGMP violations related to

 

      managerial, organizational and technical practice?

 

      And then interviewing manufacturers.  They have an

 

      internet-based questionnaire that went out in the

 

      fall of 2003.  They're looking at U.S. and European

 

      manufacturers.  And their data collection is near

 

      completion.

 

                [Slide.]

 

                There's concern with just looking at

 

      numbers of deviations or field alerts, particularly

 

      when investigation may have shown little cause for

 

      concern.  You can put in a field alert and then

 

      find out later on that--oh--you know, we figured it

 

      out.  It really wasn't a problem.  So if you just

 

      look at numbers, you get those as well as the ones

 

      that are true issues.

 

                Also it was pointed out that if you're a

 

      company with a very detailed SOP you have a much

 

      bigger chance for deviating from it than your

 

      company with a really poor SOP that sort of allows

 

      you to do anything, where you're hardly ever going

 

                                                                42

 

      to deviate.  But who's to say which one is better?

 

                India and China are not include in the API

 

      manufacturers.  And we saw this as a downside to

 

      that survey, because they are major manufacturers

 

      of APIs.

 

                [Slide.]

 

                We talked then about risk ranking and

 

      filtering, where risk ranking is a series of

 

      decisions to start to rank within a class or across

 

      classes.  Tools may be customized for each

 

      application.  And filters may be used to reflect

 

      resource limitations and/or program goals.

 

                [Slide.]

 

                There's a pilot risk-ranking model to

 

      prioritize sites for GMP inspections, using ICH Q9

 

      concepts to define risk; Site Risk Potential--a new

 

      term for us--SRP--includes product, process and

 

      facility components.

 

                Look at probability and severity

 

      components that make up harm; and look at other

 

      risk-ranking models, for example those used by EPA

 

      and USDA; and then using the CDER Recall database.

 

                                                                43

 

                [Slide.]

 

                Comments--from the committee--focusing on

 

      volume at a site may be misleading because, in

 

      fact, when you have a high volume your process may

 

      be better controlled than if you have small volume.

 

                We need to also consider the risk of the

 

      loss of availability.  If you're a single-source

 

      drug for a life-threatening condition perhaps that

 

      needs to come into the equation.

 

                Look at "hard to fabricate" products, or

 

      products with difficulty controlling uniformity.

 

      Investigator consistency will be--and has been--an

 

      issue, but with the pharmaceutical inspectorate

 

      that should be better.  And it was suggested by at

 

      least one member that maybe they should look at

 

      high personnel turnover in a plant, because that

 

      might be indicative of problems--although it was

 

      recognized that that might be hard information to

 

      come by.

 

                [Slide.]

 

                Committee members wanted to know if the

 

      sites are going to know how they are ranked.  That

 

                                                                44

 

      would be very useful information for management to

 

      know about.  Right now self-inspections are a

 

      critical part of the quality system but the value

 

      of these would be diminished if that information

 

      were to become available to FDA.  This has been a

 

      longstanding concern of industry.  You know, you

 

      don't want to share your self-inspections because

 

      then they lose their value to you.

 

                [Slide.]

 

                Next talked about GMP guidance that's

 

      proposed for the production of Phase I drugs.  CMC

 

      review to ensure the identify, strength, quality

 

      and purity of the investigational drugs as they

 

      relate to safety.  This draft guidance is in

 

      process.  It's a risk-based approach.  No regular

 

      inspection program, but these Phase I drugs are

 

      looked at on a "for cause" basis.

 

                I want to point out that it was noted

 

      during that discussion that for Phase 2 and Phase

 

      3, those drugs still fall under the GMP

 

      regulations--21 C.F.R. 210 and 211.

 

                [Slide.]

 

                                                                45

 

                Also had an update on the PAT initiative.

 

      As Helen indicated, that guidance was recently

 

      finalized, in September.  It should be expanded to

 

      cover biotech products.  And, of course, it

 

      requires continued training of FDA staff.

 

                [Slide.]

 

                We also talked about--we had a full

 

      agenda--comparability protocol.  We had an update

 

      on guidances, The goal is to provide regulatory

 

      relief for post approval changes.  It requires a

 

      detailed plan describing a proposed change with

 

      tests and studies to be performed, analytical

 

      procedures to be used, and acceptance criteria to

 

      demonstrate the lack of adverse effect on product.

 

      Many comments have been received from the public.

 

      That was FDA's comment on this.  We did not see

 

      those.

 

                But the committee had comments, as well.

 

                [Slide.]

 

                Single use protocol has limited utility.

 

      It's more utility if you're going to have

 

      repetitive changes--if you're only going to do it

 

                                                                46

 

      once it may not help.  Specificity of the protocol

 

      may limit repetitive use.  Just how much

 

      specificity is needed?  And for a well-defined

 

      protocol, an annual report should be sufficient.

 

      That really will lessen the regulatory burden.

 

                [Slide.]

 

                Some general conclusions from our two

 

      days--and we've heard the first one several

 

      times--general principles are good, but case

 

      studies are needed to facilitate understanding.

 

      That came up time and time again.  Case studies

 

      should cover all industries; for example, dosage

 

      form, API, pioneer and generic.

 

                The committee expressed concern on what

 

      appears to be understaffing in OGD.

 

                [Slide.]

 

                Failure Mode &Effect Analysis can be

 

      linked with risk-based decision-making wherein the

 

      results feed into decision trees; training and

 

      education of both regulators and the industry in

 

      the new approaches is going to be key; historical

 

      inconsistency in regulator findings may limit the

 

                                                                47

 

      utility of surveys.  In the past, you know, not all

 

      investigators have investigated in the same manner,

 

      so it's difficult to compare results.

 

                And that's the end of my presentation.  I

 

      thank you for your attention, and would be happy to

 

      address any comments, now or later.

 

                CHAIRMAN KIBBE:  Are there any questions

 

      for Judy?

 

                DR. SINGPURWALLA:  I have some comments,

 

      but I probably would wait until all the

 

      presentations are over, and then make comments.

 

      Would that be acceptable?

 

                CHAIRMAN KIBBE:  Whichever way you want to

 

      do it, as long as it's within one of the two tails

 

      of the Bayesian distribution we're all right.

 

                [Laughter.]

 

                DR. SINGPURWALLA:  You are confused, Mr.

 

      Chairman. [Laughs.]

 

                CHAIRMAN KIBBE:  On a regular basis.

 

                [Laughter.]

 

                You had a question?

 

                DR. MORRIS:  Actually, just one comment to

 

                                                                48

 

      add to what you'd said, Judy, about the Georgetown

 

      study.

 

                I think they had made sort of a plea that

 

      the reason that they hadn't been able to go to the

 

      Indian and Chinese manufacturers was strictly a

 

      resource issue.  It wasn't that they had ignored

 

      that as an area of concern.

 

                DR. BOEHLERT:  Ken, thank you for that

 

      clarification.

 

                CHAIRMAN KIBBE:  Go ahead.

 

                DR. KOCH:  I guess, looking around on the

 

      schedule, I'm not sure if we're going to talk any

 

      about training.  You mentioned it in several

 

      different ways:  the continuation, the inclusion of

 

      industry, etcetera.  But will that come up as a

 

      discussion topic at some point?

 

                DR. HUSSAIN:  Not in this meeting.  I

 

      think we will eventually bring that back at some

 

      other meetings, though.

 

                MS. WINKLE:  Actually, when I talk about

 

      some of the organizational gaps I'm going to bring

 

      up training as part of that gap.  So if you want to

 

                                                                49

 

      comment then, it would be fine.

 

                CHAIRMAN KIBBE:  Anybody else?

 

                DR. SINGPURWALLA:  Well, maybe I'll speak

 

      now.  I just--we--this is a question more to

 

      Ajaz--about case studies and specifics.

 

                We've been through many sessions of the

 

      Manufacturing Subcommittee meetings.  Has there

 

      been any concrete plan made to start seriously

 

      undertaking some case studies?  And, if so, would

 

      you be kind enough to let me know?

 

                DR. HUSSAIN:  Yes.  Dr. Boehlert's

 

      presentation to this committee--she's the chair of

 

      the subcommittee--and the decision was made to form

 

      a working group under that.  And after this meeting

 

      we'll start populating that working group and

 

      create a working group under that committee to

 

      start addressing that.

 

                In addition to that, I think we're also

 

      looking at other parallel tracks to create case

 

      studies.  One such case study has just started to

 

      take shape, with Ken Morris, and then Purdue is

 

      working with our reviewers to actually develop a

 

                                                                50

 

      case study also.

 

                So we hope in the next several months we

 

      will have examples and case studies to outline the

 

      framework.

 

                CHAIRMAN KIBBE:  Anything else?

 

                DR. SINGPURWALLA:  Yeah.  One other

 

      matter.  After the subcommittee meeting, some

 

      minutes were released, and I had made some comments

 

      about the minutes.  I did not receive an update of

 

      the minutes--update of the revision.

 

                Has--is there any reason for that?

 

      Because the normal protocol--the normal protocol is

 

      you put out the minutes, people give comments on

 

      the minutes.  You either incorporate those

 

      comments--and if you don't, you let us know why.

 

      And then you issue a final document of the minutes.

 

      And then the entire committee, or whoever it is,

 

      says "Yes, we go along with these minutes."  And

 

      they should become a part of the record.

 

                I was wondering if this was done, because

 

      I did not have access to that.

 

                                                                51

 

                CHAIRMAN KIBBE:  I think the final draft,

 

      or the final copy of the minutes is posted on the

 

      web page--FDA website--so that after the draft goes

 

      out to the members of the committee and the

 

      corrections come back in, they update to reflect

 

      the suggestions from each of the members, and then

 

      they post it.

 

                So if you wanted to check the website you

 

      could see whether--you know, how well your

 

      suggestions were incorporated in the final minutes.

 

                DR. BOEHLERT:  I would just add, also,

 

      that I reviewed comments that were made to the

 

      minutes before I made this presentation, and I

 

      tried to make sure that they were all incorporated

 

      in what I said today.

 

                DR. SINGPURWALLA:  I thought so.

 

                DR. BOEHLERT:  If they were not well

 

      reflected in the minutes, they should have been

 

      reflected in my comments today.  So--

 

                DR. SINGPURWALLA:  I thought so, but I

 

      wanted to see what the protocol was.

 

                DR. BOEHLERT:  Okay.  Thank you.  That's

 

                                                                52

 

      fair.

 

                CHAIRMAN KIBBE:  Okay?

 

                DR. WEBBER:  One quick question.

 

                CHAIRMAN KIBBE:  Go ahead.

 

                DR. WEBBER:  That will be okay?

 

                You mentioned the pharmaceutical

 

      manufacture and research study, and I'm looking at

 

      the dates there. It seemed like it was fall of

 

      2003.  And I just wanted to confirm whether or

 

      not--that was during the period of transition of

 

      products from CBER to CDER.  Were our products in

 

      OBP--the biotech products that transitioned

 

      over--were they--are they completed now within

 

      CDER?  Or are they considered part of the CBER.

 

                DR. BOEHLERT:  Yes, I think Ajaz

 

                DR. HUSSAIN:  No, Keith, that's

 

      not--that's an external study that's focusing on

 

      all of manufacturing.  So all products--CDER and

 

      CBER--products are under.  It doesn't matter

 

      where--

 

                DR. WEBBER:  Where they were--just all

 

      products--okay.  Thank you.

 

                                                                53

 

                CHAIRMAN KIBBE:  Anybody else?  Good, that

 

      will keep us pretty well on schedule.

 

                I have now a "Parametric Tolerance

 

      Interval Test for Dose-content Uniformity"--Robert

 

      O'Neill.

 

                 Parametric Tolerance Interval Test for

 

                        Dose-content Uniformity

 

                DR. O'NEILL:  Magic button.  There we go.

 

                Good morning.  I'm Bob O'Neill.  I came

 

      before at the last meeting--I was asked to be the

 

      chair of a working group that you all blessed, and

 

      I'm here to give you an update on where we are on

 

      this issue of addressing the specifications for the

 

      delivered dose--uniformity of inhaled nasal drug

 

      products.

 

                [Slide.]

 

                Just to refresh your memory, the folks on

 

      the left-hand side are the FDA folks who are part

 

      of this working group, and some are more active

 

      than others--some of them, in blue, are part of a

 

      sub-group that has been put together that is

 

      working on more specific issues that I'll address

 

                                                                54

 

      in a moment; and the folks on the right--Michael

 

      Golden, in particular, who is a colleague on the

 

      industry side, who is coordinating our efforts in

 

      that area.

 

                [Slide.]

 

                The objective of this working group--as

 

      you probably know--is to develop a mutually

 

      acceptable standard delivered dose uniformity

 

      specification--that's both the test and the

 

      acceptance criteria--for the orally inhaled nasal

 

      drug products, with a proposal to come back to you

 

      all.  And that's the time frame that I'm talking

 

      about right now.

 

                So there's been a lot of work going on in

 

      the past few months, and that's what I just wanted

 

      to bring you up on.

 

                [Slide.]

 

                There have been three full working group

 

      meetings, where the folks on that previous

 

      slide--and some others--have come together at FDA

 

      for two, three hour sessions, and to go through

 

      information that has been presented to--primarily

 

                                                                55

 

      by the industry--to us to chew on.  And we have

 

      spent a lot of time internally talking to

 

      ourselves, and coming up with some additional

 

      issues and proposals, and we met the last time with

 

      the working group, and FDA had a proposal that we

 

      felt was moving in the direction of what everybody

 

      wanted.

 

                Subsequently, there's been a working group

 

      that will now be chewing on what was presented to

 

      the last joint meeting, and they're meeting

 

      November 4                                                th.  And

there's a lot of statistical

 

      issues; there's data analysis issues.  But I think

 

      what we're all on the same page with regard to is

 

      that the need to reassess the FDA--the past FDA

 

      recommendations, and I think there's--as we

 

      indicated the last time we briefed you--that the

 

      parametric tolerance interval approach is an

 

      improvement in a value-added type of testing

 

      strategy, over and above the zero tolerance

 

      interval strategy that's been used for awhile.

 

                So the next steps are the following.

 

                [Slide.]

 

                                                                56

 

                This working group is meeting--the

 

      sub-group is meeting in November, and we hope that

 

      they will then come back to the full working group

 

      by the end of the year, and we will evaluated the

 

      iteration between the FDA modification to the

 

      proposals that have been made by IPAC--and this has

 

      a lot to do with the placement of the operating

 

      characteristic curve for the acceptance criteria.

 

      Essentially, there have been many operating

 

      characteristic curves that have been shown to you,

 

      some of which are more steep, some of which are

 

      more shallow.  But where the proposal is being

 

      evaluated right now is:  how good is it at getting

 

      from an acceptance or rejection perspective, those

 

      assays that essentially are off target mean.  You

 

      can look at the performance characteristic, or an

 

      operating characteristic curve of a testing

 

      strategy if you assume that it's 100 percent on

 

      target. But the more you move away from 100 percent

 

      on target, the more you look at how well does it

 

      grab that, and how robust is it to allowing you to

 

      be a little off 100 percent?

 

                                                                57

 

                [Slide.]

 

                And so we're in the stages of looking at

 

      the statistical performance characteristics of

 

      that, and we hope that the working group will

 

      evaluate this proposal in more detail, and come

 

      back to you in the spring of 2005, with a final

 

      recommendation to discuss with you.  So that's sort

 

      of the game plan.

 

                And Michael Golden is here.  He's my

 

      colleague on the working group from the industry

 

      side, and we'd both be willing to take any

 

      questions if you have them.

 

                CHAIRMAN KIBBE:  Questions?

 

                Nozer?

 

                DR. SINGPURWALLA:  Well, I guess Jurgen's

 

      hand went up before mine.  So--

 

                DR. VENITZ:  Okay, let me go first.

 

                DR. SINGPURWALLA:  He may ask the same

 

      question.

 

                DR. VENITZ:  Maybe.

 

                In your draft proposal--or what you're

 

      considering so far to be a draft proposal--

 

                                                                58

 

                DR. O'NEILL:  Yes.

 

                DR. VENITZ:  --are you considering the

 

      intended use when you look at statistical

 

      characteristics of your operating curve, for

 

      example?

 

                DR. O'NEILL:  Well, certainly that has

 

      been discussed, both from an emergency--a

 

      one-time-only, a chronic use, a medical risk

 

      involved--

 

                DR. VENITZ:  Right.

 

                DR. O'NEILL:  --so, certainly, Dr.

 

      Chowdhury is involved, and others are involved, in

 

      considering this issue.  So--

 

                DR. VENITZ:   And I would encourage you to

 

      do that because, obviously, in my mind, it is

 

      different whether you're looking at inhaled

 

      insulin--

 

                DR. O'NEILL:  Right.

 

                DR. VENITZ:   --and you're looking at the

 

      performance of a drug product, versus a beta

 

      agonist, for example.

 

                DR. O'NEILL:  Yes.

 

                                                                59

 

                CHAIRMAN KIBBE:  Go ahead.

 

                DR. SINGPURWALLA:  Dr. O'Neill, we had

 

      this discussion when you made the first

 

      presentation, so I'm going to back--

 

                DR. O'NEILL:  Right.

 

                DR. SINGPURWALLA:   --to the same point

 

      again.

 

                I agree with you that tolerance interval

 

      approach is to be preferred to the zero tolerance,

 

      or something to that effect.

 

                DR. O'NEILL:  Right.

 

                DR. SINGPURWALLA:  But in your description

 

      of the next steps, you have talked about operating

 

      characteristic curves, and performance

 

      characteristic curves.  Of course those are not

 

      indicative of any Bayesian thinking towards this

 

      particular area.  And while you're in the process

 

      of formulating your plans, I strongly encourage you

 

      to incorporate that into your thinking.  You may

 

      not want to adopt towards the end, but at least it

 

      should be evaluated.

 

                And the second comment I'd like to make is

 

                                                                60

 

      that--and I'm certainly not volunteering and, if

 

      asked, I would refuse--the working group members

 

      consists of individuals from the FDA and from the

 

      pharmaceutical industry.  It would be good to have

 

      some neutral people on the working group--people

 

      from industry or people from government agencies

 

      that are not connected with the FDA, so that you

 

      get some sense of balance.  Otherwise, it seems to

 

      be--you know, it seems to be a self-serving group.

 

                So I would like to encourage you to expand

 

      your membership.

 

                DR. O'NEILL:  Yeah.

 

                DR. SINGPURWALLA:  And I want to

 

      emphasize:  I'm not available.

 

                DR. O'NEILL:  Well--no, the last point--I

 

      mean, this is hard work.  The people who are doing

 

      this work are spending a lot of time, and there's a

 

      lot of evaluation--a lot of data evaluation going

 

      on.  We were presented with information from the

 

      IPAC group that consisted of a huge database.

 

                And one could look at, well, how much time

 

      do you want to spend on evaluating a huge database?

 

                                                                61

 

      I mean, it's an electronic database, and lots of

 

      different--and where I'm going to on this is the

 

      Bayesian argument.  The Bayesian argument is very

 

      much a sensible argument--or a sensible framework

 

      when you can look at empirical data that allows you

 

      to feel pretty comfortable about what your priors

 

      are, and what the distribution of information is.

 

      That is not always accessible to the agency.  It

 

      may be accessible to a sponsor.

 

                So the strategy of being in-process and

 

      out-of-process, and being in control, and what's

 

      acceptable variability is very much--very much--a

 

      Bayesian framework, and very much within the

 

      context of how you may want to be looking at this,

 

      in terms of looking at in-process validation, as

 

      well as acceptance criteria.

 

                The extent to which that carries over into

 

      the type of testing we have to be very clear about.

 

      And it's--at the point we're at right now, we're

 

      essentially most interesting, or most concerned

 

      about how far out can you push the acceptance curve

 

      so that it has a proper balance between accepting

 

                                                                62

 

      and rejecting--particularly when we don't have, or

 

      no one can show us empirically, what the

 

      distribution of off-target means are, for example.

 

      How far away from 100 percent does the mean have to

 

      be before you want to maybe ratchet in this

 

      operating characteristic curve?

 

                So, I certainly could see the value to

 

      external folks' helping us out.  The more the

 

      better.  And I believe that this is a

 

      time-intensive effort.  And just as, you know, you

 

      would not like to volunteer, we would have to go

 

      and find folks who could invest the amount of time

 

      that is necessary, in the time frame that we're

 

      talking about, so we can get where we want to be.

 

                That's not to say that more brains are

 

      not--and independent brains--are--but this is--I

 

      would say we're pretty much trying to meet in the

 

      middle of this whole thing with resources that

 

      we've thrown out it that we feel are fair and

 

      objective.

 

                DR. SINGPURWALLA:  Let me clarify.

 

                I'm not volunteering because I'm making

 

                                                                63

 

      the suggestion.

 

                DR. O'NEILL:  Yes.  Yes.

 

                DR. SINGPURWALLA:  And that's the proper

 

      thing to do.

 

                What I would like to encourage you is to

 

      involve at least two Bayesian's on your group--two,

 

      because they need support--

 

                [Laughter.]

 

                --from the point of view of simply guiding

 

      a framework, or guiding the concept, and things

 

      like that, rather than get involved with the

 

      nitty-gritty.

 

                And the two individuals--or perhaps

 

      more--need not come from two stratified groups.

 

      They should come from somewhere else.

 

                So I'm making two suggestions:  one is to

 

      have people with expertise in Bayesian statistics

 

      involved, and to have people from outside these two

 

      communities also involved--perhaps in a limited

 

      way.  This will give you a broader perspective and

 

      will not subject you to criticism two years down

 

      the line.

 

                                                                64

 

                And that's the suggestion.

 

                DR. O'NEILL:  Okay.

 

                CHAIRMAN KIBBE:  Anybody else?

 

                Ajaz, do you have something to say?

 

      Reaching for your mike?

 

                DR. HUSSAIN:  I think the point I was

 

      going to make was, I think, at this point in time

 

      it's going to be difficult to add more people to

 

      the working group.  But the point is well taken

 

      that I think you do need to bring that perspective.

 

      And I'm hoping this Advisory Committee, and some

 

      other format, could be sufficient to sort of bring

 

      that framework for that--that perspective to bear

 

      on the progress of this working group.

 

                CHAIRMAN KIBBE:  No one else?

 

                Thank you Dr. O'Neill.  Appreciated your

 

      presentation.

 

                Dr. Ajaz, perhaps you could begin our next

 

      topic, and then we can take a break, because we're

 

      running slightly ahead, and it will give us a

 

      little flexibility as we move on.

 

                And so we're going to talk about Critical

 

                                                                65

 

      Path Initiative.

 

                The Critical Path Initiative--Challenges

 

                           and Opportunities

 

                 Topic Introduction and OPS Perspective

 

                DR. HUSSAIN:  Yes, I think I'm pleased

 

      that we have more time, because many of the

 

      presentations here are very lengthy

 

      presentations--[laughs]--including mine.

 

                I'd like to sort of introduce the topic of

 

      Critical Path Initiative--the challenges and

 

      opportunities.

 

                [Slide.]

 

                The goals that we have for the fiscal year

 

      2005--and the initiatives, and the strategic goals

 

      at FDA level and the Department level are shown on

 

      this slide.  And the slide is from the "State of

 

      CDER" address by Steve Galson and Doug

 

      Throckmorton.

 

                Today, our discussions will primarily

 

      focus on the Critical Path, the cGMP initiative,

 

      focused on risk management and innovation.  And the

 

      goal at the Department level is to increase science

 

                                                                66

 

      enterprise research.  But also, I think the follow

 

      on biologics, follow-on proteins, I think is

 

      interconnected to all of these discussions.

 

                [Slide.]

 

                My focus today is to introduce you to the

 

      topic of Critical Path, and also outline a proposal

 

      that we are contemplating at the OPS immediate

 

      office level as an umbrella proposal for all the

 

      discussions you'll hear today by scientists from

 

      different parts of the Office of Pharmaceutical

 

      Science.

 

                But at the same time, some of the

 

      discussions in here also impact, say,

 

      counter-terrorism effort and other efforts that are

 

      ongoing.  And not all projects that we'll discuss

 

      are Critical Path projects today.

 

                [Slide.]

 

                What is Critical Path?  It's a serious

 

      attempt to examine and improve the techniques and

 

      methods used to evaluate the safety, efficacy and

 

      quality of medical products as they move from

 

      product selection and design to mass manufacture.

 

                                                                67

 

                [Slide.]

 

                In the continuum of drug discovery and

 

      development, you really go from basic research to

 

      prototype design or discovery, to preclinical

 

      development, clinical development, to an FDA filing

 

      and approval.  You have a focused attempt, say, for

 

      example, at the National Institutes of Health on

 

      translational research.  The Critical Path research

 

      does overlap with some of the aspects of the NIH

 

      translational research, but it covers predominantly

 

      the drug development aspects of the entire

 

      sequence.

 

                In our White Paper, we identified some of

 

      the challenges for Critical Path.  The drug

 

      development process--the "Critical Path" is

 

      becoming a serious bottleneck to delivery of new

 

      medical products.

 

                [Slide.]

 

                Our research and development spending has

 

      been exponentially increasing.  And as an index of

 

      1993, you can see the exponential increase from

 

      1993 to the current 10 years--increase in both

 

                                                                68

 

      private and public spending on research.

 

                [Slide.]

 

                However, new product submissions have

 

      remained flat--or, some would argue, are on the

 

      decline.

 

                [Slide.]

 

                Why is FDA concerned?  FDA's mission is

 

      not only to protect but also to advance public

 

      health by improving availability of safe and

 

      effective new medical products.

 

                [Slide.]

 

                FDA has a unique role in addressing the

 

      problem.  FDA scientists are involved in reviewing

 

      during product development--they see the successes,

 

      failures and missed opportunities.  FDA is not a

 

      competitor, and can serve as a crucial convening

 

      and coordinating role for consensus development

 

      between industry, academia and government.  FDA

 

      sets standards that innovators must meet.  New

 

      knowledge and applied science tools needed not only

 

      by the innovators must also be incorporated into

 

      the agency's review process and policy.

 

                                                                69

 

                [Slide.]

 

                The challenge is how do we proceed?  It

 

      should be a science-driven and shared effort,

 

      drawing on available data, need to target specific,

 

      deliverable projects that will improve drug

 

      development efficiency.  It cannot just be an FDA

 

      effort.  We can identify problems and propose

 

      solutions.  Solutions themselves require efforts of

 

      all stakeholders.  We have issued a Federal

 

      Register notice requesting input from broad

 

      stakeholders, and we have received a number of

 

      suggestions, and we are working through those

 

      suggestions as we formulate our strategy for a

 

      Critical Path research program.

 

                [Slide.]

 

                This is a significant initiative, and the

 

      Department of Health and Human Services' Medical

 

      Technologies Innovation Taskforce is providing

 

      broad leadership.  Dr. Lester Crawford is chair of

 

      this Medical Technologies Innovation Taskforce, and

 

      it includes CDC, CMS, NIH and FDA.

 

                This taskforce is working on finding

 

                                                                70

 

      additional funding to meet the needs of the

 

      Critical Path program.  It is meeting with external

 

      stakeholders to identify opportunities, enlist

 

      allies, and so forth.

 

                [Slide.]

 

                In summary, I think from a Critical Path

 

      perspective, the present state of drug development

 

      is not sustainable.  We believe FDA must lead

 

      efforts to question any assumptions that limit or

 

      slow new product development:  are these

 

      assumptions justified?  Are there more efficient

 

      alternatives?  If so, why are the alternatives not

 

      being utilized?

 

                [Slide.]

 

                As we sort of focus on the discussions

 

      today, I'll remind you that the Office of

 

      Pharmaceutical Science is predominantly focused on

 

      one aspect:  Chemistry Manufacturing Control--or

 

      the initialization dimension.  But the Office of

 

      Pharmaceutical Science also supports many other

 

      aspects, from pharmacology, toxicology to clinical

 

      pharmacology research and so forth.  So, although

 

                                                                71

 

      our review responsibilities predominantly are on

 

      the quality side, our research programs are

 

      interconnected to every aspect of the drug

 

      development process.

 

                So you will hear presentations coming from

 

      all aspects--all three dimensions of the Critical

 

      Path.

 

                [Slide.]

 

                The three dimensions are:  assessment of

 

      safety; how to predict if a potential product will

 

      be harmful; assessing efficacy; how to determine if

 

      a potential product will have medical benefit; and,

 

      finally, industrialization--how to manufacture a

 

      product at commercial scale with consistently high

 

      quality.

 

                [Slide.]

 

                Our discussions, to a large degree, have

 

      focused on the third dimension.  And I think you

 

      will see, today, many of the projects within OPS

 

      that also impact the other two dimensions.

 

                [Slide.]

 

                In our White Paper, we defined the three

 

                                                                72

 

      dimensions and the connections to the Critical Path

 

      as follows:  safety, medical utility, and

 

      industrialization.  An every aspect--every box that

 

      is there has a need for improvement and research to

 

      support that improvement.

 

                Applied science is needed to better

 

      evaluate and predict the three key dimensions on

 

      the Critical Path development.

 

                I just returned from Europe--spending a

 

      week there last week--and with respect to the

 

      industrialization dimension, I came back somewhat

 

      depressed.  The amazing work I saw coming out of

 

      the University of Cambridge in the area of

 

      industrialization of pharmaceuticals--the approach

 

      to new technology, in terms of manufacturing, novel

 

      drug delivery systems and manufacturing processes

 

      itself, was astounding.  I don't see any of that in

 

      the U.S.

 

                So my concern is, much of the R&D and

 

      innovation is going to come from Europe and Japan,

 

      probably.  And unless we really improve our

 

      infrastructure, we are going to be lagging behind

 

                                                                73

 

      in a very significant way.  And I think that

 

      concern keeps growing on me, and I think I do want

 

      to sort of emphasize that.

 

                [Slide.]

 

                Office of Pharmaceutical Science programs

 

      and Critical Path Initiative--the discussion today

 

      is to seek input from you and advice, on aligning

 

      and prioritizing current OPS regulatory assessment

 

      and research programs, with the goals and objects

 

      of the Critical Path Initiative.  Please note that

 

      not all research programs and laboratory programs

 

      are intended to focus on "Critical Path."  There

 

      are equally important other aspects--bio-terrorism

 

      and so forth--which may not be considered as part

 

      of the Critical Path Initiative, but they're

 

      equally important.  So all of our programs and

 

      projects are not likely--or should not be part of

 

      the Critical Path.  There are aspects.  So you have

 

      to distinguish that.

 

                We hope that you'll help us identify gaps

 

      in our current program; identify opportunities for

 

      addressing the needs identified by the Critical

 

                                                                74

 

      Path Initiative.

 

                [Slide.]

 

                What I'd like to do today is--before I

 

      introduce Keith Webber--he took the lead on putting

 

      this program together--I'll share with you an OPS

 

      immediate office project that Helen and I have been

 

      developing.  These are our initial thoughts of how

 

      an umbrella project, within the OPS office, will

 

      help to sort of bring all of this together.

 

                So let me share some of our thoughts on a

 

      Critical Path project that OPS--Helen and I are

 

      sort of developing right now.

 

                An immediate need in OPS is to ensure

 

      appropriate support of general drugs--the growing

 

      volume and complexity of applications.  That's the

 

      challenge.  You saw the numbers increasing.

 

                In the New Drug Chemistry, the new

 

      paradigm for review assessment and efforts to

 

      support innovation and continuous improvement goals

 

      of the cGMP initiative--Office of New Drug

 

      Chemistry has taken the lead to be the first office

 

      to sort of implement all of this.  So they have

 

                                                                75

 

      significant need for support.

 

                Biotechnology products--complete

 

      integration into OPS, and the evolving concept of

 

      "follow-on protein products"--although I have put

 

      follow-on protein products under this, we don't

 

      know exactly how the regulatory process will

 

      evolve.  It could be--let's say, a work in

 

      progress.

 

                And, clearly, alignment of research

 

      programs in OPS to meet our goals and objectives.

 

                [Slide.]

 

                So what are our thought processes, from

 

      our immediate office perspective?  To develop a

 

      common regulatory decision framework for addressing

 

      scientific uncertainty in the context of complexity

 

      of products and manufacturing processes in the

 

      Offices of New Drug Chemistry, Biotechnology

 

      Products, and General Drugs.

 

                Regardless of the regulatory process,

 

      regardless of regulatory submission strategies and

 

      so forth, we believe we need a common regulatory

 

      decision framework--a scientific framework--for

 

                                                                76

 

      addressing the challenges.

 

                [Slide.]

 

                What are the motivations here?

 

      Uncertainty--whether it's variability or knowledge

 

      uncertainty--and complexity are two important

 

      elements of risk-based regulatory decisions.  A

 

      common scientific framework, irrespective of the

 

      regulatory path or process for these products, will

 

      provide a basis for efficient and effective policy

 

      development and regulatory assessment to ensure

 

      timely availability of these products.

 

                That's the overreaching OPS goal, is to

 

      provide the common framework.  Although the

 

      submission strategies might be different, the

 

      science should not be different.

 

                [Slide.]

 

                How are we trying to approach this

 

      challenge?  We know that there are no good methods

 

      available for developing a standard approach for

 

      addressing uncertainty.  That means you need

 

      different approaches for different assessment

 

      situations. [Laughs.] All right, let me complete my

 

                                                                77

 

      thoughts.

 

                So what we are thinking about--a decision

 

      framework for selecting an approach for addressing

 

      uncertainty over the life cycle of products is what

 

      is needed.  So you may have different approaches

 

      and so forth, but a common decision framework will

 

      help us identify the right approach.

 

                [Slide.]

 

                Project 1 is to create an "As Is"

 

      regulatory decision process map for the Office of

 

      New Drug Chemistry, Office of Biotechnology

 

      Products, and Office of Generic Drugs.  Much of

 

      this work will be done through a contract--we plan

 

      to have a contractor come in and work with us on

 

      some of these things.

 

                We think a representative sample of

 

      product applications could be selected for mapping

 

      the scientific decision process in the three

 

      offices.

 

                [Slide.]

 

                Determine regulatory processes efficiency

 

      and effectiveness, using metrics similar to that

 

                                                                78

 

      what we have learned from the manufacturing

 

      initiative; and identify and compare critical

 

      regulatory review decision points and criteria in

 

      the three different offices; evaluate, correlate

 

      and/or establish causal links between review

 

      process efficiency metrics and critical decisions

 

      criteria, and available information in the

 

      submission--that's the mapping process; and, also,

 

      evaluate the role of reviewer training and

 

      experience, and how it bears on some of these

 

      decisions.

 

                [Slide.]

 

      Summarize available information on selected

 

      products; collect and describe product and

 

      manufacturing process complexity, post-approval

 

      change history, and compliance history--including,

 

      when possible, adverse event reports that come

 

      through MedWatch and other databases; describe

 

      product and process complexity and uncertainty with

 

      respect to current scientific knowledge;

 

      information available in submissions; reviewer

 

      expert opinions and perceptions; and, if feasible

 

                                                                79

 

      or possible, seek similar information from the

 

      sponsors or company scientists on these same

 

      products that we might select.

 

                [Slide.]

 

                What we hope to do is aim for the

 

      following deliverables:  organize Science Rounds

 

      within our office to discuss and debate the "As Is"

 

      process map, and the knowledge gained from the

 

      study; identify "best regulatory practices" and

 

      opportunities for improvement--these may include

 

      opportunities for improvement of filling the

 

      knowledge gap, develop a research agenda for all

 

      OPS laboratories based on what we learn.

 

                What is, I think, missing today is a

 

      common scientific vocabulary.  There's a need to

 

      develop a common scientific vocabulary to describe

 

      uncertainty and complexity.  There can be--each

 

      come from a very different perspective right now.

 

                Develop an ideal scientific process map

 

      for addressing uncertainty and complexity; adapt an

 

      ideal scientific process map to meet the different

 

      regulatory processes.

 

                                                                80

 

                In the following--I think the three

 

      projects that we're thinking about are not actually

 

      fully independent.  They're all connected together.

 

                [Slide.]

 

                Project 2 is to sort of focus on a systems

 

      approach.  We believe that without a systems

 

      approach to the entire regulatory process--that is

 

      from IND to NDA--Phase IV commitments and cGMP

 

      inspection, the broad FDA goals under the cGMP and

 

      the Critical Path Initiatives will not really be

 

      realized.

 

                [Slide.]

 

                So the team approach and the systems

 

      perspective that evolved under the cGMP Initiative

 

      only addressed a part of the pharmaceutical quality

 

      system.  Quality by design and process

 

      understanding to a large extent is achieved in the

 

      research and development organization.

 

      Pharmaceutical product development is a complex and

 

      a creative design process that involves many

 

      factors, many unknowns, many disciplines, many

 

      decision-makers, and has multiple iterations in the

 

                                                                81

 

      long life-cycle time.

 

                So we have to treat it as a complex system

 

      optimization problem.

 

                [Slide.]

 

                Significant uncertainty is created when a

 

      particular disciplinary design team must try to

 

      connect their subsystem to another disciplinary

 

      subsystem--for example, clinical versus chemistry,

 

      or CMC to GMP.  When you bring those connections,

 

      there's significant uncertainty.

 

                Each subsystem can have its own goals and

 

      constraints that must be satisfied along with the

 

      system-level goals and constraints.  It is possible

 

      that goals of one subsystem may not necessarily be

 

      satisfactory from the view of other subsystem and

 

      design variables in one subsystem may be controlled

 

      by another disciplinary subsystem.  Impurities is a

 

      good example.  Pharmtox, CMC, and how you bring

 

      that together.

 

                [Slide.]

 

                So the Project 2 proposal that we're

 

      developing is to use ICH Q8 as the bridge between

 

                                                                82

 

      the cGMP Initiative and the rest of the regulatory

 

      system, and to develop a knowledge management

 

      system to ensure appropriate connectivity and

 

      synergy between all regulatory disciplines.  Can

 

      that be done?  I mean, that's the feasibility

 

      project that we are trying to develop.  So--connect

 

      Pharm/Tox, Clinical, Clinical Pharmacology,

 

      Biopharmaceutics, CMC, Compliance all together.

 

                [Slide.]

 

                The current thinking is to approach this

 

      problem as connecting every section within the ICH

 

      Q8 CTD-Q, within the same document, but to all

 

      other sections in an NDA, in some way or form.  For

 

      example, each section within the P2 can have an

 

      impact on the other P2 sections and, similarly,

 

      other sections of a submission and to cGMP.

 

                By recognizing this as a complex design

 

      system that involves multiple attributes, goals,

 

      constraints, multidisciplinary design teams,

 

      different levels of uncertainty, risk tolerances,

 

      etcetera, we wish to find opportunities to identify

 

      robust designs and design space that provides a

 

                                                                83

 

      sound basis for risk assessment and mitigation.

 

                So this would be a scientific framework.

 

      It was a regulatory tool that could come out of

 

      this.  And with the case studies and everything

 

      coming together, this might be a way to bring and

 

      connect all the dots.

 

                [Slide.]

 

                What we have been looking out is outside

 

      pharmaceuticals.  We believe that a significant

 

      body of knowledge exists.  Example, in mechanical

 

      engineering, as it applies to the design of

 

      aircrafts, that addresses some of these challenging

 

      points that we have discussed.  These are three

 

      examples that I have selected as just illustrative

 

      examples of how multidisciplinary optimization

 

      methods and system-level problem solving tools can

 

      be thought about in the drug context.

 

                [Slide.]

 

                Just to illustrate this point, let me

 

      create an example here.  The applicability of

 

      multidisciplinary optimization methods for solving

 

      system-level problems and decision trade-offs will

 

                                                                84

 

      be explored in an NDA review process.  That's what

 

      we're proposing.

 

                For example, in the Common Technical

 

      Document for Quality--the P2 section, which is what

 

      ICH Q8 will define--critical drug substance

 

      variables that need to be considered in section

 

      2.2.1, which is "Formulation Development" are

 

      described in section 2.1.1.  So there's a drug

 

      substance, and there's a formulation.  They're two

 

      different sections.

 

                Information for "Drug Substance," has a

 

      bearing on that of the "Formulation Development."

 

      So how do you connect the two together?

 

                For example, the current language in ICH

 

      Q8 for "Drug Substance," states:  "Key

 

      physicochemical and biological characteristics of

 

      the drug substance that can influence the

 

      performance of the drug product and its

 

      manufacturability should be identified and

 

      discussed."

 

                So that's describing the information

 

      content in section 2.1.1. that we will hopefully

 

                                                                85

 

      receive whene ICH Q8 is done.  So how does this

 

      have a bearing on the "Formulation Development"

 

      section?

 

                [Slide.]

 

                I'll skip this and just show you a figure.

 

                [Slide.]

 

                You have the API--or drug substance

 

      manufacturing process.  The X(1.1) is the design

 

      variable; the f(1.1) is the objective function to

 

      be addressed; and the g(1.1) is the constraint for

 

      that manufacturing process that delivers the drug

 

      substance.  Okay?

 

                Since this is not part of ICH Q8, what

 

      will be part of ICH Q8 is section 2.1.1., which

 

      will identify what are the critical variables for

 

      the drug substance, as they relate to the

 

      formulation aspect.  But that becomes the input for

 

      what--how it connects to the "Formulation

 

      Development" aspect.  And that link is through a

 

      linking variable.

 

                Since my means and standard deviations

 

      have become finger-pointing and so

 

                                                                86

 

      forth--[laughs]--so you know--you have a design

 

      variable, you have a linking variable, you have an

 

      objective function, you have constraints around

 

      which you define your design space.  You have mean

 

      objective function--that's your target.  You have a

 

      standard deveiation that you sort of bring to bear

 

      on that.  And deviation range of the design

 

      solution, or the design space.

 

                So all of this sort of has to come

 

      together for this to be meaningfully connected.

 

      And, for example, if you start with a simple design

 

      of experiment, you may have mathematical models,

 

      which are empirical, but then they provide that

 

      connectivity.  So it's a start of a very formal,

 

      rigorous approach to dealing with uncertainty,

 

      knowledge gaps and complexity.

 

                So this might be a useful concept.  So

 

      that's the process right now, to see whether this

 

      could be a feasibility project that we could do.

 

                [Slide.]

 

                So the potential deliverables of using

 

      this approach could be significant. Since we are

 

                                                                87

 

      moving towards electronic submissions, in

 

      conjunction with electronic submissions, this

 

      project can potentially provide a means to link

 

      multidisciplinary information to imporve regulatory

 

      decision--that is, clinical relevance to CMC

 

      specifications.  We may not all have all that

 

      information, but the links--the structure--will be

 

      there as we grow, as we improve our knowledge base,

 

      or will it be refined, the links could get

 

      populated, and this might be an approach for

 

      knowledge management within the agency.

 

                Creating a means for electronic review

 

      template and collaboration with many different

 

      disciplines; provide a ocmmon vocabulary for

 

      interdisciplinary collaboration; create an

 

      objective institutional memory and knowledge base;

 

      a tool for new reviewer training; a tool for FDA's

 

      quality system--and, clearly, it can help us

 

      connect cGMP Initiative to the Critical Path

 

      Initiative.

 

                So that's the project that we hope to

 

      develop.  We really want to get some feedback from

 

                                                                88

 

      you, and develop this as a project under the

 

      Critical Path Initiative.

 

                [Slide.]

 

                But the third aspect of this--it all could

 

      happen in parallel--explore the feasibility of a

 

      quantitative Bayesian approach for addressing

 

      uncertainty over the life cycle of a product.  The

 

      most common tool for quantifying uncertainty is

 

      probability.  The frequentists--the classical

 

      statisticians--define probability as "limiting

 

      frequency, which applies only if one can identify a

 

      sample of independent, identically distributed

 

      observation of the phenomenon of interest."

 

                The Bayesian approach looks upon the

 

      concept of probability as a degree of belief, and

 

      includes statistical data, physical models and

 

      expert opinions, and it also provides a method for

 

      updating probabilities when new data are

 

      introduced.

 

                The Bayesian approach may proivde a more

 

      comprehensive approach for regulatory decision

 

      process in dealing with CMC uncertainty over the

 

                                                                89

 

      life cycle of a product.  It may also provide a

 

      means to accommodate expert opinions.

 

                And I think there's a connection here.

 

      The evolving CMC review process may be a means to

 

      incorporate expert opinions.  And I think that is a

 

      significant opportunity.

 

                Using the information collected in Project

 

      1--that I described--you would seek to develop a

 

      quantitative Bayesian approach for risk-based

 

      regulatory CMC decision in OPS.

 

                So that would be a project that will run

 

      in parallel to the other two approaches that we are

 

      moving forward.

 

                [Slide.]

 

                So, I'll stop my presentation here with

 

      sort of summarizing, in the sense--I think OPS,

 

      from its goals and objectives, has to have an

 

      overreaching project that sort of connects all the

 

      dots together.  And the proposal--the first one

 

      clearly is a process map--"As Is" and so forth.

 

      But the two others are feasibility projects that we

 

      want to look at the Bayesian approach and a complex

 

                                                                90

 

      system optimization problem.

 

                The knowledge exists outside.  It's simply

 

      adapting and adopting it in our context.

 

                What you'll hear--after the break, I

 

      think.  Or--unless you want to start earlier--after

 

      the break, is other immediate office projects;

 

      Office of Biotechnology projects, Office of New

 

      Drug Chemistry project, Office of Generic Drug

 

      projects on Critical Path, and Office of Testing

 

      and Research.

 

                What we have done is Keith Webber will

 

      introduce the reset of the talks.  You will hear

 

      each group's perspective.  And we have requested

 

      Jerry Collins to come back and sort of

 

      summarize--after his talk on the Critical Path--the

 

      entire Critical Path Initiative from an OPS

 

      perspective and pose questions to you.

 

                And we have also invited Professor Vince

 

      Lee, who is now part of FDA--who used to be the

 

      chair of this committee--who has been with agency

 

      for almost a year now, to come with his perspective

 

      on how--what are challenges he sees.  So you will

 

                                                                91

 

      hear sort of presentations and some opinions from

 

      people who have been at the agency and been looking

 

      at this challenge for some time.

 

                So, again, the discussion today is to seek

 

      input and advice on ACPS; on how to align, identify

 

      gaps, and identify opportunities.

 

                I'll stop here and entertain questions on

 

      my part of the presentation.

 

                CHAIRMAN KIBBE:  Are there any questions?

 

                DR. SINGPURWALLA:  I have comments.

 

                CHAIRMAN KIBBE:  Okay.  Thank you.

 

                DR. SINGPURWALLA:  I just--what you say is

 

      music to my ears.  You have good vision about some

 

      of the things you want to do.  But I think it's now

 

      time that the dance should begin.

 

                We should get back--take concrete problems

 

      and address them.  I've said this before.

 

                But let me just make some specific

 

      comments on some of the things you've said.  And,

 

      of course, I'm going to question some of the things

 

      you said.

 

                The first argumetn I want to make on your

 

                                                                92

 

      slide on page 7, about efficacy and safety:

 

      generally, those tend to be adversarial.  Drugs

 

      that give you benefit may have side effects.  So

 

      the important issue is to do a trade-off.  For that

 

      you need to talk about assessing utilities:  what

 

      is the utility of the benefit, and what is the

 

      dis-utility of the harm?  That's a part of the

 

      whole package of thinking about these problems, and

 

      I encourage you to look into it.

 

                Now, I take strong objection to some of

 

      the things you have said.  You have distinguished

 

      uncertainty into stochastic and epistemic.  I have

 

      seen that distinction before.  I claim it's totally

 

      unnecessary.  Uncertainty is uncertainty, and one

 

      doesn't--one should not pay much attention to the

 

      source of the uncertainty--

 

                DR. HUSSAIN:  Right.

 

                DR. SINGPURWALLA:   --whether it is

 

      regulated allatoire uncertainty, or epistemic, does

 

      not matter.

 

                CHAIRMAN KIBBE:  Right.

 

                DR. SINGPURWALLA:  The Bayesian approach

 

                                                                93

 

      does not distinguish between the two.  And since

 

      you've been talking about it, I think--

 

                You also say that there are no good

 

      methods for devleoping standard approach for

 

      addresing uncertainty.  I think that's the wrong

 

      slide to put up.  That's liable to do more harm

 

      than good.

 

                DR. HUSSAIN:  Okay.

 

                DR. SINGPURWALLA:  There are methods

 

      available.  So I would not encourage you to put it.

 

                And the other thing is:  I don't like your

 

      linking uncertainty and complexity.  They're two

 

      different issues.

 

                And you also say that there is no common

 

      scientific vocabulary.  Well, I claim there is a

 

      common scientific vocabulary, and that is

 

      probability.

 

                Now, as far as recommendations are

 

      concerned:  I'd like to suggest--and, again, I'm

 

      not volunteering since I'm making the

 

      suggestion--that you have your people exposed to a

 

      tutorial on Bayesian methods and Bayesian ideas, so

 

                                                                94

 

      that you get a better appreciation of what it's all

 

      about.  And the best way to do this is to take a

 

      simple example and work through it; work through

 

      your expert opinion notions that you're saying.

 

                Go through an example, and you'll get a

 

      better appreciation of what it's all about.  And

 

      once you get that appreciation, you'll be tempted

 

      to remove some of the other things you've said.

 

                Those are just comments.  Thank you.

 

                DR. HUSSAIN:  No--the point's well taken.

 

      And we actually have a project right now with the

 

      University of Iowa, looking at our stability data

 

      from a Bayesian perspective.  So we're just

 

      starting to put a real-life example on that.  So

 

      that's--

 

                With regard to the utility, Jurgen and the

 

      Clinical Pharmacology Subcommittee has been sort of

 

      bringing that up.  So we will connect to the

 

      Clinical Pharmacology group.

 

                Jurgen, do you want to say anything about

 

      that?

 

                DR. VENITZ:  [Off mike.] Well, other than

 

                                                                95

 

      the fact that--other than the fact that we're

 

      discussing it.  It is a controversial issue,

 

      because you're really trying to map, then, a lot of

 

      different things into a uniform scale.  Personally,

 

      I don't see an alternative, and I think it's

 

      already done.  We're just doing it intuitively, as

 

      opposed to expressedly.

 

                So it is being discussed.  We have to see

 

      where it goes.

 

                DR. HUSSAIN:  And, regarding, I think, the

 

      common vocabulary, I think it's a common vocabulary

 

      in the context of when we speak from a pharmacist

 

      to a chemist to an engineer--we have very different

 

      interpretation--that's what was referred to.

 

                DR. SINGPURWALLA:  That's why you need a

 

      tutorial.

 

                DR. HUSSAIN:  That's exactly--

 

                DR. SINGPURWALLA:  Put people together.

 

      Because about 15, 20 years ago, the Nuclear

 

      Regulatory Commission was facing similar problems.

 

      And one of the things they did is they had lots of

 

      tutorials to get everyone on board, talking the

 

                                                                96

 

      same language.  Otherwise, you'll have a doctor

 

      talk to an engineer, and those two talking to a

 

      lawyer--and you know what can happen.

 

                [Laughter.]

 

                VOICE:  [Off mike.] Lawsuits.

 

                CHAIRMAN KIBBE:  Another question?

 

                DR. KOCH:  I guess, just to build on the

 

      last comment--when you get into all those

 

      multidisciplinary functions--and particular when

 

      the ICH Q8 is going to serve as a group, together

 

      with the implementing the cGMPs--there's a couple

 

      of organizations out there I think could serve as

 

      very valuable resources.  One we've heard about a

 

      couple times today in the ASTM 55, as a body to

 

      help at least standardize the terminology.  And the

 

      other one is the ISPE, which could serve as a

 

      multidisciplinary conduit that, working together

 

      with ICH, could probably facilitate some of the

 

      multidisciplinary issues.

 

                DR. HUSSAIN:  I think we do plan on

 

      extensive training and team building and coming on

 

      the same page.  If you look at the PAT and the

 

                                                                97

 

      manufacturing signs White Paper that we issued, we

 

      actually laid out a lot of these things in there,

 

      including the role of ISPE, ASTM, PQRI, and so

 

      forth.

 

                So we have been thinking about this in

 

      that context, and at the ICS meeting in

 

      Yokahama--on Wednesday, I think, the date is

 

      set--we will be updating on that.  So I'll get a

 

      chance to talk about ASTM to ICH in Yokahama,

 

      Japan, also.

 

                So, we're aligning everything together.

 

      So that's happening.

 

                There was one point that I wanted to

 

      respond to:  the reason for keeping uncertainty, in

 

      terms of variability in knowledge--keeping the

 

      distinction, at least as we think about this,

 

      was--and the link to complexity, also--clearly,

 

      complexity and uncertainty are two independent

 

      things.  But, unfortunately--well, the challenge we

 

      face is this--in the sense we have a very complex

 

      product.  We have simple products--within the same

 

      office, in OPS and different regions.  Yet today, I

 

                                                                98

 

      think, from a variability perspective, we're not

 

      very sophisticated in how do we deal with

 

      variability.

 

                And, for example, in our manufacturing

 

      science White Paper, we don't even deal with

 

      variability of our dissolution test method.  We

 

      don't even know how to handle it.  So we have

 

      challenges today where simple variability--we don't

 

      have a good handle on.

 

                So that was the reason for keeping

 

      variability and knowledge-based uncertainty on the

 

      table.

 

                CHAIRMAN KIBBE:  Ken?

 

                DR. MORRIS:  Just a quick question:  on

 

      your identification of the gaps in the current

 

      programs, are you thinking more in terms of

 

      technical gaps--as in science that needs to be

 

      done?  As opposed to logistical gaps within--

 

                DR. HUSSAIN:  Both.  Both.

 

                DR. MORRIS:  So, with respect to the

 

      scientific gaps, are thinking, then, to take it one

 

      level more--basically, are you talking more about

 

                                                                99

 

      new science that needs to be created?  Or science

 

      that needs to be communicated more

 

      effectively--within the agency?

 

                DR. HUSSAIN:  Well, I think the immediate

 

      need would be to communicate the existing science

 

      and bring all the existing knowledge to bear on

 

      that.  And, clearly, in the long term there are

 

      fundamental issues--and most of the new science

 

      would be needed.  So I think it's an issue of

 

      timing.

 

                DR. MORRIS:  Thank you.

 

                CHAIRMAN KIBBE:  Anybody else?  Nozer, you

 

      wanted to--

 

                DR. SINGPURWALLA:  No, I just wanted to

 

      say that this distinction between allatoire and

 

      epistemic has been artifically created by

 

      frequentist statisticians.  And Bayesians don't buy

 

      it.

 

                DR. SELASSIE:  I have a question.

 

                CHAIRMAN KIBBE:   Yes, please.

 

                DR. SELASSIE:  You know, in your graph on

 

      R&D spending--has there ever been a breakdown in

 

                                                               100

 

      how much of that spending can be attributed to the

 

      "R" and how much to the "D?"

 

                DR. HUSSAIN:  I don't have that--I'm sure

 

      that information's--I don't have it.  So I'm not

 

      aware of it.

 

                DR. SELASSIE:  Because would one parallel,

 

      you know, the flatness?

 

                DR. HUSSAIN:  One was the public funding;

 

      one was more private funding, so--

 

                DR. SELASSIE:  Yes, but they're both going

 

      up.

 

                DR. HUSSAIN:  Yes.

 

                DR. SELASSIE:  But I'm wonder if, you

 

      know--because you look at your product submissions

 

      are flat.  Now, is that because there's not been an

 

      increase in development funding?  Or--

 

                DR. HUSSAIN:  I don't think so.  But I

 

      don't have an answer.

 

                DR. SELASSIE:  Yes.

 

                DR. HUSSAIN:  So let me say that.

 

                CHAIRMAN KIBBE:  Marvin?

 

                DR. MEYER:  Ajaz, you don't seem like a

 

                                                               101

 

      depressive kind of guy--

 

                DR. HUSSAIN:  [Laughs.]

 

                DR. MEYER:   --but you said you were

 

      depressed last week.

 

                DR. HUSSAIN:  Yes.

 

                DR. MEYER:  Can you give us just a real

 

      short synopsis of where you see Europe doing things

 

      right, and us doing things wrong?

 

                DR. HUSSAIN:  [Sighs.] [Laughs.]

 

                No, I mean, again, I'll focus on what I

 

      see happening in Europe--especially in the

 

      U.K.--and how they're translating academic

 

      research--academic finding research--into

 

      entrepreneurial business--in particular in

 

      manufacturing, in particular in dosage form

 

      design--the pharmacy-related ones.

 

                Look at Bradford, particle engineering.

 

      And the one I saw--I saw a beautiful manufacturing

 

      system for coating.  Forget coating pans.  This is

 

      electrostatic coating; precise, automated, complete

 

      on line, and so forth.

 

                Nothing of that sort is happening

 

                                                               102

 

      here--within my domain.

 

                CHAIRMAN KIBBE:  We have a couple more

 

      comments, and then we're going to have to take a

 

      break.

 

                Go ahead.

 

                DR. MORRIS:   Yes, just to follow up on

 

      that.  I think there's--I just came back from

 

      Europe depressed, as well, but I was in

 

      Scandinavia.  So maybe that had something to do

 

      with it.

 

                [Laughter.]

 

                Yeah, it's pretty dark up there.

 

                But, in any case, I agree with Ajaz in

 

      that there are a couple of caveats and, in fact, if

 

      you look at our latest hires, they're one from--via

 

      Bradford, another one via Bath.  My post-doc is

 

      from Nijmwegin, another post-doc from Roger Davies

 

      Group in the U.K.

 

                And we're not training people--number one.

 

      So, aside from not transferring the technology

 

      effectively we're not training people to do it very

 

      much any more.  There are few places--represented

 

                                                               103

 

      at the table--that still do it to some degree.

 

                But that stems back to one of your earlier

 

      slides, which is trying to muster NIH and NSF to

 

      fund this sort of research.  Because some of you

 

      have been a lot closer to deanships than I.  If

 

      there's no overhead money, it doesn't get a very

 

      kind reception.  And the fact of the matter is is

 

      we haven't had it.

 

                So, this is--I'll stop here, because this

 

      is my old soapbox.  But I lay this at the door, in

 

      part, of NIH and NSF for not recognizing, in the

 

      face of overwhelming data, that there is a crisis

 

      that needs to be address.

 

                On the upside, there are some people in

 

      Europe doing some things--and Japan, as well.

 

                CHAIRMAN KIBBE:  Pat, go ahead.

 

                DR. DeLUCA:  Just a quick follow up on

 

      that, too.  I know from my trips to Europe, too, if

 

      you just look at the colleges--the pharmacy schools

 

      in Europe--I mean, they all have departments of

 

      pharmaceutical technology.  I mean you'll be

 

      hard-pressed to find pharmaceutical technology as

 

                                                               104

 

      an area of focus in an American college of pharmacy

 

      now.  Certainly you won't see any departments of

 

      pharmaceutical technology.

 

                So I think it's been--and it wasn't that

 

      way 20 years ago.  But, I mean, it certainly has

 

      changed, though.

 

                CHAIRMAN KIBBE:  Anybody else?

 

                Good--I think we're at a nice break point.

 

      And if we could take perhaps a 10 minute

 

      break--because Ajaz has managed to get us--use up

 

      all of our lead time.

 

                [Laughter.]

 

                And we can get Keith to start his talk at

 

      about 10:22, that would be great.

 

                [Off the record.]

 

                CHAIRMAN KIBBE:  22 minutes after 10 has

 

      arrived, and one way or another we're going to get

 

      back on process.

 

                Dr. Webber, are you prepared to get on

 

      process?

 

                He's on the way to the podium.

 

                Those of you walking around with cakes in

 

                                                               105

 

      your hands, and sodas, you want to sit down.

 

      Nozer.  Here we go.  Good luck.  We gave you 10

 

      minutes to do that.

 

               [Pause.]

 

                You snooze, you lose, as the old saying

 

      goes.

 

                So, Dr. Webber, shall we start our

 

      Strategic Critical Path?

 

             Research Opportunities and Strategic Direction

 

                DR. WEBBER:  Okay.  I guess we're about

 

      ready to get started on this session, regarding

 

      research activities and our strategic goals for the

 

      Office of Pharmaceutical Science.

 

      I'm Keith Webber, with the Office of Biotechnology

 

      Products.  And let me--

 

                [Slide.]

 

                --there we go.

 

                Ajaz went through a very good

 

      presentation, I think, on the Critical Path.  And

 

      I'm not going to really address very much about the

 

      Critical Path Initiative itself.  But, in my view,

 

      this--I've sort of summarized things into the Drug

 

                                                               106

 

      Development Path, which begins with discovery of

 

      potential targets--or potential new drugs; and then

 

      you have to have a period where one evaluates the

 

      candidates and makes a selection of what candidate

 

      you should carry forward into the pre-clinical

 

      study, where one looks for potential toxicities and

 

      potential efficacies in an indication of interest.

 

                If all goes wlel, one moves into clincal

 

      studies, and if all goes even better, into

 

      commercialization.  And then, once you're on the

 

      market, there's always the period of post-approval

 

      manufacturing optimization--or we would like to see

 

      that, from the FDA's perspective, anyway.

 

                And then, often, we get new

 

      indications--we see new indications being developed

 

      for drugs that are on the market.  And that

 

      essentially starts the process back up again--often

 

      at the clinical studies stage.

 

                [Slide.]

 

                The--I didn't bring a pointer.  Is there a

 

      pointer here?

 

                VOICE:  [Off mike.]  Just use the mouse.

 

                                                               107

 

                DR. WEBBER:  Just use the mouse.  Okay.

 

      That will work.  Right there is the mouse.  Okay.

 

                I guess, historically, FDA interactions;

 

      have occurred primarily ion this area here, from

 

      clinical studies on.  Prior to that, we have had

 

      very little influence, I think, until we receive a

 

      submission which contains information regarding the

 

      pre-clinical studies.

 

                But I believe we have opportunities to

 

      have an impact on this entire process in the

 

      future.

 

                Let's see.

 

                Essentially, I guess, sort of the essence

 

      of the Critical Path is the--in my mind--is the

 

      view from empirical versus guided drug development.

 

      And drug development has to be a learning process

 

      in order to make intelligent decisions regarding

 

      such issues such as your candidate selection; what

 

      dosage form you're going to have and what the

 

      formulation should be; in choosing clinical

 

      indications, you need to know what patient

 

      population is going to be the best selection for

 

                                                               108

 

      your product.  And then when you're evaluating

 

      clinical endpoints, one needs to know which are the

 

      most appropriate endpoints to evaluate in the

 

      clinical studies, and are there surrogate endpoints

 

      that are more appropriate than others, if you can't

 

      look at an endpoint which is directly related to

 

      survival or efficacy in the more normal manner.

 

                And, of course, with adverse event

 

      monitoring, any clinical trial is going to monitor

 

      particular parameters, and you need to have a good

 

      knowledge base in order to understand which adverse

 

      events we should be looking for, and the best way

 

      to evaluate those.

 

                And then, finally, the manufacturing

 

      method certainly is a major concern because that

 

      has to do with the ability to improve the

 

      manufacturing process post-approval and

 

      pre-approval, as well as avoiding issues that can

 

      come up with regard to safety and efficacy of your

 

      product.

 

                [Slide.]

 

                The goal of industry, as well as the

 

                                                               109

 

      agency, I believe, is to establish a knowlege base

 

      and the tools that are necessary to predict the

 

      probable success of any given product, and the

 

      manufacturing methods that are appropriate to it,

 

      and then to foster the development of products that

 

      are going to have a high likelihood of success,

 

      throughout clinical development and on the market.

 

                [Slide.]

 

                Now, for this late morning's presentations

 

      and this afternoon's presentations, we'll be

 

      hearing from a number of groups within OPS.  One is

 

      the Informatics and Computational Safety Analysis

 

      staff, which is in--essentially in the immediate

 

      office of the OPS; and then Office of New Drug

 

      Chemistry, Office of Generic Drugs.  And the first

 

      three here are the groups that do a lot of

 

      relational and database analyses as part of their

 

      research activities.  There are, in some cases,

 

      collaborative research going on with laboratories,

 

      per se.  But it's the groups on this--the last two,

 

      the Office of Testing and Research, and Office of

 

      Biotechnology Products, that have actual

 

                                                               110

 

      laboratories where research at the bench is going

 

      on.

 

                [Slide.]

 

                Let's see--within OPS's Critical Path

 

      Research, I think we can address--or can address

 

      the issues regarding candidate selection, based

 

      upon an understanding of the structure and activity

 

      of the relationships that we see, and the products

 

      that ocme down the line, as well as what's reported

 

      in the literature.

 

                Dosage form development and evlauation I

 

      think is an important area that we're working in.

 

      Toxicity predictions for products is--we're

 

      amenable to that, so our research can address that

 

      through, again, structure activity-type

 

      relationships and structure-function issues, as

 

      well as knowledge of the impacts that a particular

 

      disease state might have on physiological function

 

      that may lead to toxicities that wouldn't be

 

      present in all populations.

 

                Bioavailability and bioequivalence

 

      predictions are certainly important for all of our

 

                                                               111

 

      products, but particularly for the Office of

 

      General Drugs, they're quite critical.  And I think

 

      with regard to the follow-on products as well, it's

 

      a major area of concern.

 

                Metabolism prediction is something that

 

      is, I think, crucial because products, once they

 

      enter the body, as you know, they don't remain in

 

      their initial state.  And the metabolism can impact

 

      toxicity, it can impact efficacy, it can impact the

 

      bioavailability and biofluence of the products

 

      themselves.

 

                Immunogenicity is another area that is of

 

      large concern, particularly for protein products.

 

      And there we need to evaluate and understand, not

 

      only the caues of immunogenicity, or the impacts of

 

      various structures in the proteins on

 

      immunogenicity, but also the impact that the

 

      patient population has on immunogenicity; what

 

      impact the indication that's selected can have on

 

      impacts of immunogenicity as a safety concern.

 

                Often, as I mentioned earlier, you have

 

      biomarkers that you're looking at for

 

                                                               112

 

      pharmacodynamic parameters, or for surrogate

 

      endpoints.  And a good knowledge of the validity of

 

      a particular biomarker, and our ability to evaluate

 

      those, as well as industry's ability to select

 

      those, is dependent upon the knowledge that they

 

      have of the biology of the disease that they're

 

      studying, or that they're trying to cure or that

 

      they're trying to treat.

 

                The mechanism of action of the drug is

 

      certainly critical when you're looking at the

 

      potential.  One area is with regard to drug-drug

 

      interactions.  Oftentimes we've been looking

 

      primarily at metabolism for drug reactions, but

 

      certainly there's a concern that I think is

 

      building for utilization of multiple drugs that

 

      impact on the same metabolic--not metabolic

 

      pathways, but the signaling pathways, let's say, at

 

      the cell surface, which are getting the

 

      treatments--you know, getting a treatment into the

 

      cell, or that are resulting in the clinical

 

      effect--is what I'm trying to say, in a very poor

 

      way.

 

                                                               113

 

                Let's see--the pharmacogenomics is a new

 

      area that we're getting involved in, but it's very

 

      important with regard to patient selection, as well

 

      as the potential for certain populations to be

 

      impacted by drugs in a unique way, that can impact

 

      not just efficacy, but also the safety.

 

                And manufacturing methodologies are an

 

      area that we have research programs in within the

 

      office, and those are important for developing and

 

      understanding of the robustness of various

 

      manufacturing processes, and the ability to

 

      implement new paradigms, such as process

 

      technologies in the manufacturing process of

 

      pharmaceuticals

 

                [Slide.]

 

                Out strategy here is to coordinate

 

      cooperative research activities.  And, as I

 

      mentioned, we have predictive modeling programs.

 

      And these are generally based upon information from

 

      regulatory submissions that we receive, as well as

 

      from laboratory research that's going on within the

 

      agency, as well as outside and in the published

 

                                                               114

 

      literature.

 

                One area which, I think, we need to build

 

      is our abilities to get information from industry

 

      that we don't get in a our regulatory submissions,

 

      and that they don't publish, and finding a means to

 

      have them help us to gain knowledge of that

 

      information so that we can implement it into the

 

      decisions we make and share that--basically the

 

      conclusions that come out of that with industry as

 

      a whole, to address the Critical Path.

 

                [Slide.]

 

                There's also laboratory research going

 

      on--you'll hear from the Offices of Testing and

 

      Research, Applied Pharmacology Researhc, and

 

      Product Quality Research, and Pharmaceutical

 

      Analysis--and also from my office, Biotech

 

      Products, from our divisions of Monoclonal

 

      Antibodies and Therapeutic Products--it should be

 

      Therapeutic Proteins.  Sorry.  Typo there.

 

                There's also research going on in other

 

      FDA centers that we can collaborate with, and do

 

      collaborate with, as well as outside, to gain

 

                                                               115

 

      information from academia, industry and other

 

      egoernment agencies, as well.

 

                [Slide.]

 

                Now, I think we can gather all this

 

      information, but it's critical with regard to how

 

      we're going to use it, and how we're going to

 

      disseminate it, such that we can have an impact on

 

      the Critical Path.

 

                There are a number of avenues to get to

 

      academia and manufacturers, and those include the

 

      public forums, where we can present the conclusions

 

      and recommendations.  We certainly write guidance

 

      documetns that can help in this manner, as well.

 

      And then, when industry comes to meet with us at

 

      the regulatory meetings, such as pre-IND, and

 

      pre-NDA meetings--pre-BLA meetings--we can interact

 

      with them at those points, as well.

 

                But we also need to change, to some

 

      extent, our review processes within the agency,

 

      and--so the information has to go to the reviewers,

 

      as well.  And we can do that via training programs,

 

      as well as the guidance documents that we do write.

 

                                                               116

 

      They're used a great deal by the reviewers.

 

                Then, again, mentoring programs, to bring

 

      up the new reviewers in an understanding of the new

 

      paradigms and new concerns, or lessen their

 

      concerns for particular issues that relate to

 

      pharmaceutical manufacturing, or clinical issues.

 

                And then all of this together should help

 

      to enhance the application of your process from the

 

      reviewer's standpoint, and with regard to the

 

      manufacturers should help to remove some of the

 

      hurdles and obstacles we see in the Critical Path.

 

                [Slide.]

 

                You'll hear the coming presentations.  So

 

      there are some questions we'd like you to keep in

 

      mind, that we'll be bringing up later for

 

      discussion.

 

                And first is:  are we focusing, within the

 

      office, on the appropriate Critical Path topics?

 

      And are there other topics that we should be

 

      addressing through our research programs?  And it's

 

      both the database relational type information or

 

      research programs as well as the laboratory

 

                                                               117

 

      programs.

 

                And then, in the future, Critical Path

 

      issues may change.  So how should we identify

 

      Critical Path issues in the future.  And we'd like

 

      recommendations on how we should prioritize those.

 

      Because we're really--at this point, we can't do

 

      everything that needs to be done with the current

 

      resources, and so we're going to have to prioritize

 

      now, and in the future we'll need to prioritize, as

 

      well, and we'll need some guidance on that.

 

                That ends my presentation.  We'll move

 

      into the first talk--to stay on time--which is

 

      going to be--let's see, I'll bring it up here--Joe

 

      Contrera.

 

             Informatics and Computational Safety Analysis

 

                             Staff (ICSAS)

 

                DR. CONTRERA:  Okay.  I'm the director of

 

      the Informatics and Computational Safety Analysis

 

      group.  Our main mission, really, is to make better

 

      use of what we already know; material or safety

 

      information, toxicology information that's buried

 

      in our archives; and also in the scientific

 

                                                               118

 

      literature and in industry files.

 

                Our group develops databases and also

 

      predictive models.  You can't develop models

 

      without the databases.  So they go together.

 

                We have develop our own paradigms for

 

      transforming data, because traditional toxicology

 

      data is textual, and converting into a weighted

 

      numerical kind of a scale that is amenable to be

 

      processed by computers, and also to be modeled.

 

                And we encourage, promote and also work

 

      with outside entities to develop QSAR--qualitative

 

      structure activity relationship software--and data

 

      mining software, for use in safety analysis.

 

                We don't work alone.  And you'll hear more

 

      about this in my talk.  We leverage, very much, and

 

      cooperate, and collaborate very much with

 

      outside--with academia, with software companies and

 

      with other agencies.  And we do this through

 

      mechanisms such as the CRADA--the Cooperative

 

      Research and Development Agrement--which is really

 

      a buisness agreement--and also we do it with

 

      Material Transfer Agreements, for an exchange, quid

 

                                                               119

 

      pro quo exchange, with software and other

 

      scientific entities outside the center.

 

                [Slide.]

 

                The Critical Path Initiative--you've all

 

      been, and you're going to be hearing more about it,

 

      and you've heard a lot about it.  I'm focusing on

 

      what is relevant to my group, and that is:  the

 

      problem is that we have not created sufficient

 

      tools to better assess safety and efficacy.  We're

 

      still relying on toxicology study designs that were

 

      designed 50 or sometimes 100 years ago.  And it

 

      doesn't mean that they're inferior, but maybe there

 

      are better ways of doing this now.

 

                So we need a process to develop better

 

      regulatory tools.  And it was really a controversy,

 

      to some extent:  whose misison is this?  And in the

 

      past, the agency didn't consider it as the agency

 

      mission to develop these tools--necesarily.  It was

 

      academia.  And academia said, "No, it's the

 

      industry."  It wasn't--it was vague as to who was

 

      actually responsible for developing new analytic

 

      tools that can be used for regulatory

 

                                                               120

 

      enpoints--especially in safety endpoints.

 

                [Slide.]

 

                So now how d we connect with the citical

 

      path?  I think we were doing Critical Path research

 

      well before there was a Critical Path Initiative.

 

      I mean, we've been in operation, in one form

 

      another, for over a decade in the Center, at a time

 

      when people were questioning whether this was the

 

      mission of the agency in the beginning.

 

                We developed databases and then predictive

 

      tools that are used by the industry--by the

 

      pharmaceutical industry--more and more to improve

 

      the lead candidate selection.  And the question

 

      was:  why should the agency supply industry with

 

      better tools to select lead candidates?  Well, it's

 

      in our interest that they develop lead candidates

 

      that have fewer toxicology or safety problems.

 

      Because when they come to us, in the review process

 

      and submissions, they can said right through with

 

      very few issues.  Otherwise, they'd bog down the

 

      system.  And we have multiple review cycles, and

 

      there are issues to be addressed.  And it would be

 

                                                               121

 

      wonderful if they could just slide through.

 

                And so also to facilitate the reiew

 

      process internally, by having reviewers having a

 

      rapid access to information that is usable for

 

      "decision support," we call information; that they

 

      can use to make judgments on a day-to-day basis.

 

      And we hope that also this could reduce testing;

 

      reduce the use of animals.  And also encourage

 

      industry--software companies--to get into the

 

      business of developing predictive modeling tools.

 

                [Slide.]

 

                And we see this three-dimensional diagram

 

      for the Critical Path.  Well, the computational

 

      predictive approaches are identified in two of the

 

      three pathways.  And so we feel we're right in step

 

      with what the future goals of the agency are.

 

                [Slide.]

 

                What have we accomplished already?  Well,

 

      again, we do two things:  databases and predictive

 

      modeling.  And this sort of summarizes some of the

 

      accomplishments; the first being we've developed

 

      predictive software for predicting rodent

 

                                                               122

 

      carcinogenicity, for example, based on the compound

 

      structure.  It's being used by the pharmaceutical

 

      companies.  It's distributed by small software

 

      vendors.

 

                We are also--obviously, we cannot screen

 

      industry's compounds in the agency.  That would be

 

      a conflict of interest.  But our software is being

 

      used.  We have an Interagency Agreement with

 

      NIH--NIH has a drug development program--we have a

 

      contract with NIH.  NIH sends us compounds that

 

      they're screening in their drug development program

 

      for treating addiction.  And so we are, in our own

 

      way, practicing what we preach, in terms of using

 

      our software in lead selection in drug development.

 

                We also--software is being used--and we

 

      lay a consulting role, within the Center, for

 

      evaluating contaminants and degradants in new drug

 

      products and general drugs, to determine--to

 

      qualify them, and determine limits.  So we feel

 

      that our software could have much more application

 

      in that realm.

 

                And decision support for review divisions.

 

                                                               123

 

      We collaborate very closely with the Center for

 

      Food Safety.  And, in fact, we're training their

 

      scientists, and have shared our software with them,

 

      and they're using our carcinogenicity predictive

 

      software to screen food contact substances. Because

 

      they're working under the new FDAMA rules that

 

      place the burden on the agency; in other words, the

 

      agency has to, within 120 days, decide whether

 

      there is a risk.  The agency has to give cause why

 

      a substance is a risk.  It's a reverse of sort of

 

      what drugs are.

 

                So in order to meet those kinds of

 

      deadlines, they had to go to predictive modeling to

 

      ascertain whether there's a potential risk of a

 

      food contact substance--within 120 days.

 

                EPA is looking at our--and we work with

 

      them.  And the software also can be used in

 

      deciding whether we have a data set that is

 

      adequate; whether there are research gaps that need

 

      to be filled.

 

                [Slide.]

 

                So we talk about the FDA information.  We

 

                                                               124

 

      get submissions, we review them.  There's an

 

      approval process, and then the post-approval

 

      process.  We extract information from this process.

 

      We extract proprietary toxicology data,

 

      non-proprietary toxicology and clinical data.  And

 

      we build proprietary and non-proprietary databases,

 

      so we can keep information that can be shared with

 

      the public through Freedom of Information and

 

      information that will not be shared--or cannot be

 

      shared legally--into two different databases.

 

                And we use these databases for a variety

 

      of functions:  for guidance development, for

 

      modeling.  And also for decision support fo the

 

      review; and also it feeds back on industry, because

 

      much of this information can be shared with the

 

      public, because it's under the Freedom of

 

      Information Act.

 

                [Slide.]

 

                We have leveraging initiatives in both

 

      realms.  We leverage to get support from outside to

 

      help us develop databases, so that we don't rely

 

      entirely just on FDA funding.

 

                                                               125

 

                And the objectives are to creat specific

 

      databases--endpoint specific.  They could be mouse

 

      studies, three month, 90-day studies, one year

 

      studies; the toxicology databases that people are

 

      interested in.

 

                These database initiatives are funded and

 

      supported through CRADAs and other mechanisms.  We

 

      have a CRADA with MDL Information Systems, which is

 

      a part of Reed Elsevier publishing company.  They

 

      are interesting in building a large information

 

      system, and so they're helping, supporting, our

 

      effort.  We have CRADAs in the works with Leadscope

 

      that has a wonderful platform for searching

 

      toxicology data.  And also we have a CRADA in

 

      process with LHASA Limited, in England--University

 

      of Leeds in England--that has a system also--an

 

      interest in these kinds of databases.

 

                What we--our databases are

 

      constructed--the center of our database is the

 

      chemical structure.  It is a chemical-structure

 

      based database.  And the structure is in digital

 

      form so that it can be teased--it's a

 

                                                               126

 

      chemoinformatic database.  And the digital form is

 

      called the .mol-file structure, and it's a common

 

      structure used in industry for over a decade.  So

 

      the chemical structure, as well as the name is the

 

      center search point.

 

                And then once you have a structure that's

 

      in digital form, you can not only ask a simple

 

      question about, "Can I find substance x," but you

 

      can also query and ask whether--"I'd like to know

 

      everything--all the compounds that are like it."

 

      And that's such a powerful tool--regulatory

 

      tool--that I think is another--puts us in another

 

      dimension.

 

                It's not that I want--"Tell me about

 

      acetaminophen," but I want to know compounds that

 

      are 90 percent like acetaminophen in a data set.

 

      And we're able to do that now--really easily--with

 

      the system.

 

                So once we have this system, then we tie

 

      in--the databases are linked to this search engine.

 

      We have our clinical databases that we

 

      model--post-marketing adverse event reporting

 

                                                               127

 

      system, and also the tox databases.  And we use all

 

      this--what we're really interested in is modeling;

 

      computational predictive toxicology.

 

                And the sources of that data on these

 

      databases come from reviews.  We extract

 

      information from the regulatory reviews and from

 

      other databases.

 

                [Slide.]

 

                So, now, getting into our modeling

 

      operation, we transform the data.  We supply the

 

      chemical structure data, and our collaborators and

 

      software companies supply the software.  And we

 

      work with them on an iterative basis to improve and

 

      make these things work, and develop software for

 

      these endpoints.

 

                We've also, I think, are probably the

 

      first group that have developed a way of using

 

      chemical structure to predict dose.  And so we have

 

      a paradigm for predicting what the maximum daily

 

      dose of a compound might be in humans, within a

 

      statistical, obviously, error bar, in humans.

 

                So, currently, in our prediction

 

                                                               128

 

      department, you might say, we have access to five

 

      or six different platforms.  And they represent

 

      very different algorithms.  And this is the

 

      point we want to have interactions with software

 

      companies that have approaches that are different

 

      from one another.  And then we evaluate and work

 

      with them to try to develop models, using our data

 

      sets.

 

                So we have two CRADAs on board right now,

 

      with multi-case and MD/QSAR, and we have others in

 

      the works.  And we also have interactions with

 

      other prediction approaches from the statistical.

 

                [Slide.]

 

                In terms of the models that we're working

 

      on now, the objective is to model every single test

 

      that's required for drug approval.  And so we

 

      started with carcinogenicity, because that was the

 

      most--the highest profile, in terms of preclinical

 

      requirement; and teratology would be next.  These

 

      are endpoints that cannot be simulated in clinical

 

      trials; mutagenicity, gene tox--all these are

 

      models, either have been created or are in the

 

                                                               129

 

      process of being created and being worked on.

 

                We're also attempting to model human

 

      data--the adverse event reporting system;

 

      post-marketing human data.  This is an enormously

 

      difficult data set; very dirty data set, but it's

 

      enormous, in terms of its size.

 

                [Slide.]

 

                And we have had some success, preliminary

 

      modeling, of hepatic effects, cardiac effects,

 

      renal and bladder, and immunological effects in

 

      humans.  These are still works in progress, but we

 

      have made progress.

 

                And in terms of the dose related

 

      endpoints, we have made really good progress.  We

 

      were surprised, ourselves, because we didn't really

 

      think this would work.  We've been able to

 

      successfully model the human Maximum Recommended

 

      Daily Dose--you know, that's the dose on the bottle

 

      when you get your drug.  It says "Don't take more

 

      than 10 milligrams a day for an adult.  Well, we

 

      modeled that, because that comes from clinical

 

      trial data.  That is really human data.  And it

 

                                                               130

 

      represents an enormous scale--I don't want to get

 

      into it--but it's like an eight-block scale of

 

      doses, and we have 1,300 pharmaceuticals that are

 

      either--that we've modeled, in our database.  And

 

      we were able to successfully model this--and I'll

 

      get back to that in a moment.

 

                [Slide.]

 

                The other question that came up was

 

      proprietary data and sharing industry data.  It

 

      would be nice to get their data, especially in

 

      areas that we know the industry has a great deal of

 

      experience in, like gene tox data.  Right now we

 

      can't have access to data that was not in

 

      submissions.  And so we need a way of doing this.

 

      Chemoinformatics gives you a way of at least

 

      getting there partially.  We're able to share the

 

      results by not disclosing the structure and name of

 

      a compound.  You can disclose the results, but you

 

      say "What good is disclosing results, or using the

 

      results, without knowing where they came from?"

 

      Well, you can use descriptors--chemical

 

      descriptors--that can be used in modeling, but

 

                                                               131

 

      cannot be used to unambiguously reconstruct the

 

      molecular structure.  But they contain enough

 

      information to model.

 

                And so you're sort of at least halfway

 

      there.  You can share some information that can be

 

      used in modeling.  And so this is a feasible

 

      approach and, in fact, it's already being

 

      accomplished--legally.  It's gone through our

 

      legal--our staff at the agency and it's

 

      incorporated in some of these softwares.

 

                [Slide.]

 

                And this is an example.  This is 74 MDL

 

      QSAR descriptors for the compound methylthiouracil.

 

      Now, these descriptors are used in modeling, and

 

      ocntain a great deal of scientific information, in

 

      terms of modeling.  But all of these descriptors

 

      will not unambiguously recreate the structure of

 

      methylthiouracil, because there's a lot missing.

 

      It's like a pixel pictures.  You know, you have a

 

      photograph--a digital photograph--if you've only

 

      got 70 pixels, you'll get a rough picture of what

 

      it is, but you won't know it's your uncle.  It's

 

                                                               132

 

      just a person--you know.  But if you had 10,000

 

      pixels, you'd know exactly who it is.  It's the

 

      same idea.  So you can share this crude image.

 

                [Slide.]

 

                Getting back to modeling the human maximum

 

      daily dose--at present, we have to go through many

 

      steps to arrive at a starting, Phase I clinical

 

      starting dose, in a drug that's never been into man

 

      for the first time.  We start with animal

 

      studies--multiple dose studies in multiple species.

 

      So already that's a lot of cost.  Then you estimate

 

      the no-effect level--has to be estimated from this.

 

      Then you have to decide which species is closed to

 

      man by looking at the ADME and, you know,

 

      metabolism and everything.  And then you have to

 

      convert that to a human equivalent dose using

 

      allometric scaling.  And then, on top of that, you

 

      use a little--the uncertainty factors, dealing for

 

      inter-species extrapolations--finally come up with

 

      a dose that you might try for your first dose in

 

      human--in clinical trials.

 

                Well, if you could model, on the basis of

 

                                                               133

 

      structure, the maximum recommended daily dose, you

 

      get a predicted dose in humans--because that's

 

      human data.  You take one-tenth, or one-hundredth

 

      of that, just to be on the safe side, and you have

 

      a dose.

 

                And what's the benefit?  There's no

 

      testing in animals.  There's no lab studies.

 

      There's no inter-species extrapolation, because

 

      you're using human data.  And we think it's more

 

      accurate, because animal studies don't predict

 

      whether a drug is going to cause nausea, dizziness,

 

      cognitive dysfunction.  Animals can't tell you

 

      that.  But yet that appears in labeling for old

 

      drugs all the time.

 

                So we feel that this is a good approach.

 

      Everyone acknowledges that the estimation of the

 

      first dose in clinical trials is a bad--but it's

 

      the only thing we know how to do.  So this has got

 

      to be better, because it's better than nothing.

 

      You know, because right now what we're doing is a

 

      very crude approximation.

 

                [Slide.]

 

                                                               134

 

                What's another application?  And--in

 

      conclusion--the two-year rodent carcinogenicity

 

      study--in mouse and rat.  It costs $2 million. It

 

      takes at least three years to do.  And there's

 

      always controversy about the outcomes of these.

 

      Yet it has an enormous effect on the drug's

 

      marketability.

 

                Is it necessary to do these studies for

 

      all drugs now?  Can computational methods replace

 

      some of them?  I'm not saying we're getting rid of

 

      all testing.  But if we know a lot about a

 

      particular compound, based on the experience of the

 

      past, perhaps with predictive modeling there may be

 

      a subset of compounds in which we don't have to

 

      test as vigorously.  And those which we know very

 

      little about--and the computer can tell you that;

 

      that the compound is not covered in the learning

 

      set, and therefore you better do all the studies.

 

                But if a compound is another--you know,

 

      antihistamine, maybe there's a lesser path because

 

      a structure that's so well represented in the data

 

      set, that it's sort of silly to keep testing it

 

                                                               135

 

      over again, just to meet a regulatory requirement.

 

                So we're hoping that this would reduce

 

      unnecessary testing and put the resources where

 

      they're needed; testing things that we really don't

 

      know anything about, and that are new--that are

 

      really new compounds.

 

                [Slide.]

 

                So the challenges for accepting predictive

 

      modeling:  we need accurate, validated--and that's

 

      always--you know, what we mean by "validation" is

 

      always arguable.  But we need to develop that.

 

      That's part of our mission.

 

                Standardization of software; experience

 

      and training--it's not something that's going to go

 

      on a reviewer's desktop ever, because it requires

 

      interpretation.  It's a really special skill.

 

                We need more databases; adequate sharing

 

      of proprietary information; the bigger the

 

      database, the better.  But we need, also,

 

      regulatory mangers and scientists that are willing

 

      to consider new ideas--consider; don't have to

 

      adopt--consider.  That makes a big--you know, opens

 

                                                               136

 

      the door for innovation.

 

                And then the ned for an objective

 

      appraisal of current methods.  It's the emperor's

 

      clothes.  How good, really, is what we're doing

 

      now?  And that is something that's painful, but

 

      it's something that needs to be done.  Compared to

 

      what?  Is it better, worse--compared to what?

 

                [Slide.]

 

                In PhRMA 2005 meeting that occurred

 

      several years ago--and I think it was very

 

      farsighted--Price Waterhouse Coopers had a

 

      paradigm.  And they said, "Right now you have

 

      primary sciences:  the lab-based, patients--you

 

      know, clinical trials; and the secondary is the

 

      computational--what the call "e-R&D"--that there

 

      will be a transition where they'll reverse from

 

      primary to secondary.  And the primary science

 

      maybe in the next generation, will be the modeling

 

      and predictive science, and the lab and clinical

 

      will be the confirmatory science.

 

                So, with that, I'll end my talk.  We've

 

      published much of what we've done.  A lot of it is

 

                                                               137

 

      in press right now.  We have a web site:  our

 

      maximum recommended daily dose database is on our

 

      website, and a lot of people are working with it,

 

      and we're happy to say that they're getting the

 

      same results--which was nice.

 

                And I'll end my talk here.

 

                CHAIRMAN KIBBE:  i'll take the prerogative

 

      of the Chair and ask the first question.  And then

 

      we'll get rolling.

 

                Your database looks wonderful when you're

 

      dealing with toxicity.  Have you also done a

 

      similar thing with clinical effectiveness, or

 

      utility, of compounds?  Some way of looking at the

 

      structure, and then looking at the effect, and

 

      being able to predict how effective one structure

 

      is relative to another?

 

                And then follow up with that--if that's

 

      true, can we plug into the opposite end of your

 

      program and go back the other way, and just bypass

 

      drug discovery?

 

                [Laughter.]

 

                DR. CONTRERA:  [Laughs.] Well--no fair. 

 

                                                               138

 

      I'll start with the last one--but you'll be only

 

      discovering what we already know.  There may be--

 

                CHAIRMAN KIBBE:  But I was thinking of

 

      plugging in different parameters--

 

                DR. CONTRERA:  Yeah.

 

                CHAIRMAN KIBBE:   --in the toxicity and

 

      outcome:  lower toxicity, higher efficacy--

 

                DR. CONTRERA:  Oh, yes.  Yes.

 

                CHAIRMAN KIBBE:   --and then go backwards.

 

                DR. CONTRERA:  Yes, that's possible.

 

                CHAIRMAN KIBBE:  Thank you.

 

                DR. CONTRERA:  But getting back to

 

      efficacy--yes.  In fact--I mean, industry is using

 

      it as an efficacy tool all the time.  That wasn't

 

      our mission.  But potentially--certainly

 

      applicable.  And sometimes we stumble on those

 

      things.  But that isn't our mission.

 

                And you know where research--we've got

 

      four people in this unit.  And then we have

 

      contractors.  And then we get students.  So we're a

 

      small, tight unit.  And you have to be very

 

      focused, in terms of your priorities, and doing

 

                                                               139

 

      what is feasible first, and less--and so we didn't

 

      get into efficacy.  No.

 

                CHAIRMAN KIBBE:  Who have I got down here?

 

      I've got everybody on the right side.

 

                So we'll start it at the end, and work our

 

      way down.

 

                Go ahead.

 

                DR. SELASSIE:  Okay.  I have a couple of

 

      questions for you.

 

                First of all, with your database, you have

 

      in-house data that you're generating for your

 

      toxicology?

 

                DR. CONTRERA:  Yes.

 

                DR. SELASSIE:  Do you ever go to the

 

      literature and get information from it?

 

                DR. CONTRERA:  Yes.  Actually, that could

 

      be a much more complicated slide.  But we mine

 

      everything.  We mine other databases; the NIH

 

      databases; literature.  And, in fact, we're

 

      using--we're using our CRADA with MDL--because MDL

 

      owns almost every journal in the world

 

      now--practically.  Elsevier owns almost everything.

 

                                                               140

 

      And so--and they have access to data that's

 

      enormous.

 

                So, using the leverage with a publishing

 

      company, we have a pipeline now to the literature.

 

      Yes.

 

                DR. SELASSIE:  Okay.  I have another

 

      question.

 

                DR. CONTRERA:  Yes.

 

                DR. SELASSIE:  When you're inputting the

 

      structures, do you all ever use the SMILES

 

      notation?

 

                DR. CONTRERA:  Yes, we use SMILES.  There