ATDEPARTMENT OF HEALTH AND HUMAN SERVICES

> FOOD AND DRUG ADMINISTRATION
>
> CENTER FOR DRUG EVALUATION AND RESEARCH
>
> **ADVISORY COMMITTEE FOR PHARMACEUTICAL SCIENCE**
>
> Monday, October 21, 2002
>
> 8:30 a.m.
>
> CDER Advisors and Consultants Conference Room
>
> 5600 Fishers Lane
>
> Rockville, Maryland
>
> PARTICIPANTS
>
> Vincent H.L. Lee, Ph.D., Chairman
>
> Kathleen Reedy, R.D.H., M.S., Executive Secretary
>
> MEMBERS
>
> Gloria L. Anderson, Ph.D., Consumer Representative
>
> John Doull, M.D., Ph.D.
>
> Judy Boehlert, Ph.D.
>
> Joseph Bloom, Ph.D.
>
> Nair Rodriguez-Hornedo, Ph.D.
>
> Lemuel A. Moye, M.D., Ph.D.
>
> Marvin C. Meyer, Ph.D.
>
> Arthur H. Kibbe, Ph.D.
>
> Nair Rodriguez-Hornedo, Ph.D. (by telephone)
>
> SPECIAL GOVERNMENT EMPLOYEE CONSULTANT
>
> Thomas Layloff, Ph.D.
>
> INDUSTRY PARTICIPANT
>
> Tobias Massa, Ph.D.
>
> INDUSTRY GUESTS
>
> Leon Shargel, Ph.D., R.Ph.
>
> Efraim Shek, Ph.D.
>
> Leslie Z. Benet, Ph.D. (by tellephone)
>
> Kenneth R. Morris, Ph.D.
>
> Thomas Garcia, Ph.D (by telephone)
>
> FDA STAFF
>
> Ms. Helen N. Winkle
>
> Ajaz Hussain, Ph.D.
>
> Yuan-Yuan Chiu, Ph.D.
>
> Lawrence Yu, Ph.D.
>
> Vilayat Sayeed, Ph.D.
>
> Robert Osterberg, Ph.D.
>
> [C O N T E N T S]{.underline}
>
> [PAGE]{.underline}
>
> Call to Order, Vincent H.L. Lee, Ph.D. 4
>
> Conflict of Interest,
>
> Kathleen Reedy 6
>
> Introduction to Meeting, Ms. Helen Winkle 8
>
> Subcommittee Reports:
>
> Non-Clinical Studies:
>
> John Doull, M.D., Ph.D. 20
>
> Frank Osterberg, Ph.D. 27
>
> Frank D. Sistare, Ph.D. 33
>
> Process Analytical Technologies:
>
> Thomas Layloff, Ph.D. 41
>
> Ajaz Hussain, Ph.D. 53
>
> Other Updates:
>
> Risk-Based CMC Review:
>
> Yuan-yuan Chiu, Ph.D. 87
>
> Vilayat Sayeed, Ph.D. 91
>
> Blend Uniformity:
>
> Ajaz Hussain, Ph.D. 111
>
> Regulatory Issues Related to Crystal Habits-Polymorphism:
>
> Introduction, Gary Buehler, R.Ph. 142
>
> Scientific Considerations of Pharmaceutical
>
> Solid Polymorphism, Lawrence Yu, Ph.D. 153
>
> Expert Comments:
>
> Kenneth R. Morris, Ph.D. 184
>
> Leslie Z. Benet, Ph.D. 201
>
> Committee Discussion 208
>
> [P]{.underline} [R]{.underline} [O]{.underline} [C]{.underline}
> [E]{.underline} [E]{.underline} [D]{.underline} [I]{.underline}
> [N]{.underline} [G]{.underline} [S]{.underline}
>
> **Call to Order**
>
> DR. LEE: Good morning. I am the chair of the committee and I would
> like to call the meeting to order. Let me begin by asking everyone to
> introduce herself or himself, starting on my far right side.
>
> MS. WINKLE: Good morning. I am Helen Winkle. I am the acting director
> of the Office of Pharmaceutical Science.
>
> DR. HUSSAIN: Ajaz Hussain, deputy director of the Office of
> Pharmaceutical Science.
>
> DR. MOYE: Lem Moye, committee member and University of Texas
> Biostatistics.
>
> DR. DOULL: John Doull, clinical toxicologist, Kansas Medical Center.
>
> DR. MEYER: Marvin Meyer, emeritus professor, University of Tennessee,
> now living in Florida.
>
> DR. KIBBE: Art Kibbe, professor of pharmaceutics, Wilkes University
> Nesbitt School of Pharmacy.
>
> MS. REEDY: Kathleen Reedy, Food and Drug Administration.
>
> DR. LEE: Vincent Lee. I am professor and chair of pharmaceutical
> sciences at USC.
>
> DR. ANDERSON: Gloria Anderson, Callaway professor of chemistry, Morris
> Brown College, Atlanta.
>
> DR. BLOOM: Joseph Bloom, University of Puerto Rico.
>
> DR. BOEHLERT: Judy Boehlert, and I have my own pharmaceutical
> consulting business.
>
> DR. SHARGEL: Leon Shargel, vice president biopharmaceutics, Ianlabs, a
> generic manufacturer.
>
> DR. SHEK: Efraim Shek, vice president for pharmaceutical and
> analytical R&D, Abbott Laboratories.
>
> DR. MASSA: Tobias Massa, executive director of regulatory affairs, Eli
> Lilly & Co., and chair of their PQRI steering committee.
>
> DR. LAYLOFF: Tom Layloff, Management Sciences for Health and NGO
> working in less developed countries and acting chair of the PAT
> committee.
>
> DR. OSTERBERG: Bob Osterberg, acting associate director for
> pharmacology and toxicology for the Office of New Drugs.
>
> DR. LEE: Thank you very much. I would like to ask Kathleen Reedy to
> read the conflict of interest.
>
> **Conflict of Interest**
>
> MS. REEDY: Acknowledgement related to general matters waivers,
> Advisory Committee for Pharmaceutical Science, October 21, 2002:
>
> The following announcement addresses the issue of conflict of interest
> with respect to this meeting and is made a part of the record to
> preclude even the appearance of such at this meeting. The topics of
> today\'s meeting are issues of broad applicability. 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 and federal guests have
> been screened for their financial interests as they apply to the
> general topics at hand. Because they have reported interests in
> pharmaceutical companies, the Food and Drug Administration has granted
> waivers to the following special government employees, which permits
> them to participate in today\'s discussion, William Jusko and Judy
> Boehlert.
>
> A copy of the waiver statement may be obtained by submitting a written
> request to the agency\'s Freedom of Information Office, Room 12A-30 of
> the Parklawn Building.
>
> Because general topics impact so many institutions it is not prudent
> to recite all potential conflicts of interest as they apply to each
> member, consultant and guest. FDA acknowledges that there may be
> potential conflicts of interest but, because of the general nature of
> the discussion before the committee, these potential conflicts are
> mitigated.
>
> We would also like to note for the record that Dr. Efraim Shek of
> Abbott Laboratories, Dr. Leon Shargel of EON Labs are participating in
> this meeting as industry representatives, acting on behalf of
> regulated industry. As such, they have not been screened for any
> conflicts of interest.
>
> In the event that the discussions involve 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 product they may wish to comment upon.
>
> DR. LEE: Thank you very much. I now would like to invite Helen Winkle,
> the acting director of the Office of Pharmaceutical Science, to
> introduce the meeting.
>
> **Introduction to Meeting**
>
> MS. WINKLE: Good morning, everyone. Good morning to Dr. Lee, the
> chair, and to the committee members and to the audience. I really want
> to tell the committee how much I appreciate their participation today.
> I know that this is not the best part of the country to have to visit.
> So, I know it is almost a hardship to come into this area right now.
> As Dr. Kibbe was saying, just avoid the gas station and you are fine.
>
> \[Slide\]
>
> This morning I really want to step back a little bit and look at the
> accomplishments of the committee. There are a number of people that
> are going off the committee after this particular meeting and I felt
> like it was important that we look back on those accomplishments
> before we ended this particular group of people as the committee, and
> I think it is really important to stress some of the things that the
> committee has contributed to the Office of Pharmaceutical Science over
> the last several years and to emphasize how much the recommendations
> of the committee have assisted us in OPS in meeting our various
> missions and our goals and objectives. I want to highlight some of
> those accomplishments to start off with this morning.
>
> \[Slide\]
>
> First of all, many of the accomplishments have led to guidance
> development or to help us in the development process. The first one is
> to provide input on the food effect guidance. The second is to provide
> input on the biopharmaceutical classification system. There were a
> number of questions that came up after the draft guidance was issued
> and the committee has helped us a lot in actually addressing those
> questions; helping in establishing the process analytical technology
> subcommittee. This has been a really important subcommittee to us. The
> issues that have come up have been extremely important and the
> advisory committee was very influential in helping get this committee
> set up.
>
> \[Slide\]
>
> We have discussed DPK at an advisory committee meeting and this has
> helped us in making the decision to withdraw the draft guidance on DPK
> and to begin to focus on more general bioequivalence methodology for
> topical drugs. We have discussed the PQRI project on blend uniformity,
> and this has assisted OPS a lot in determining the acceptability of
> the recommendations from PQRI.
>
> \[Slide\]
>
> We have debated individual bioequivalence and replicate designs, and
> the committee has provided OPS with feedback that serves as background
> for making changes to the general BA and BE guidance. We have had
> several discussions on orally inhaled and nasal drug products, and the
> committee has made recommendations on BA and BE and chemistry
> guidances for these products.
>
> \[Slide\]
>
> Also, the committee has participated in a number of awareness sessions
> on the following topics that include lactation, polymorphism,
> liposomes and risk-based CMC review. That is a lot. Actually, when you
> look back, we haven\'t had that many meetings in the three years so
> that is a lot to have taken in. As I said to start with, the
> discussions have contributed significantly to a lot of the decisions
> that have been made in OPS. So, I really want to thank all of the
> committee for that.
>
> \[Slide\]
>
> Besides the advisory committee discussions, we also have a number of
> current subcommittees that have been active, and many of the advisory
> committee members participate on those subcommittees and a lot of
> issues have come out of the subcommittees for discussion here. They
> would include the process analytical technologies, the oral inhalation
> and nasal drug products committee, and the non-clinical studies
> subcommittee.
>
> \[Slide\]
>
> Looking ahead, I think we have already talked, as I said, about what
> we have accomplished in the last three years but there is a lot we
> still have to accomplish in a lot of areas that are kind of going to
> come up for discussion in the future.
>
> I wanted to start off a little bit by talking about what I see as the
> vision for the subcommittee structure in ACPS. We have talked a number
> of times at this committee about setting up some additional
> subcommittees and I think it is really important just to give that
> vision briefly to you all. It has been our decision in OPS that it
> would be very helpful to have discipline-specific subcommittees.
> Basically, we are looking at probably five subcommittees right now.
> They would be manufacturing, clinical pharmacology, pharm-tox,
> microbiology and biopharm.
>
> The clinical pharmacology is the only one of those five committees
> that is set up. It actually will have its first meeting tomorrow.
> Currently there are three other committees that are active, the PAT,
> the NCSS and the OINDP subcommittee. What we see is the PAT committee
> probably being dissolved and reconstituted under the manufacturing
> subcommittee. We will talk more today about the NCSS subcommittee. The
> committee as it is now will be moving to the National Center for
> Toxicology Research and we will set up a pharm-tox subcommittee under
> this advisory committee to handle issues that come up in this area.
> OINDP is still active. We still have some questions that need to be
> resolved before we finalize the guidances in this area but eventually
> this committee too will be dissolved and absorbed into the other
> areas.
>
> \[Slide\]
>
> Future focus\--the future has a lot, as I said. I think there are many
> issues that we are going to have to handle in the future. The first
> one basically I see as being really important, and really important in
> the reason why we want to set up the manufacturing subcommittee is the
> agency\'s GMP initiative. I think many of you have seen the press on
> the GMP initiative. This is GMP for the 21st century, a risk-based
> approach. It will include a lot of manufacturing practices and
> policies. We will be looking at those both from the review side as
> well as the investigational side. I think there are going to be a lot
> of scientific issues that come up when we start looking at the
> initiative in more depth. We have a number of working groups currently
> active in the Center. There are a lot of industry working groups that
> are set up, and I know there will be a lot of issues and questions
> that will come up so I am sure that we will be bringing those to the
> committee. Actually, tomorrow we are going to talk about some of
> those. The CBER-CDER consolidation\--obviously, as you know, there are
> certain products out of CBER that are now going to be consolidated in
> CDER. I am sure, as we go down the road, there will be some scientific
> issues that come up with that; some decisions that are going to have
> to be made about OPS and others on how to handle some of the questions
> especially in the review area. So, I see this as some of the
> challenges we have in the future.
>
> \[Slide\]
>
> Developing policies and practices to regulate new products. A number
> of new products are out there, new delivery systems, etc. Developing
> and revising new standards and guidances, we will continue to have
> more and those guidances all have to be revised. There are always
> changes being made; they are in constant flux. So, there will be
> issues there as well.
>
> We also plan to have in OPS a focus on generic products. There have
> been a lot of questions on bioequivalence methods for approving
> generic products. There are products that are out there currently and
> we do not have the methodology to be able to ensure the bioequivalence
> of these products, and there are a lot of things down the road that we
> will be talking about here, and the evaluation of future PQRI
> recommendations. We have talked about blend uniformity and there are
> still a number of other recommendations that are going to come out
> under PQRI in the near future and we would like to use this committee
> to help us in evaluating those recommendations in making final
> decisions.
>
> \[Slide\]
>
> One of the other things that is going to happen with this committee is
> that there is going to be a big change in membership. I don\'t know
> how this happened, that half the committee is leaving at this time but
> we are right now actively replacing the people on the committee,
> getting new membership and stuff, but I do want to mention up front
> how much we have appreciated working with the work of group that have
> been on this committee.
>
> This has been an excellent group to work with. The recommendations and
> the involvement of the committee have been really exceptional and I
> just want to tell you how much OPS has appreciated this. I especially
> want to thank Dr. Lee. He has been a really excellent chair. He has
> kept all of us in line, including me. I appreciate that considerably.
> I also want to mention that Dr. Venitz is on sabbatical. He will
> actually be at the subcommittee on clinical pharmacology on Wednesday
> but he will be there for FDA, not for the advisory committee. He is on
> sabbatical with us currently.
>
> \[Slide\]
>
> Last of all, I just want to go through the agenda for the next few
> days and talk quickly about some of the things that we are going to do
> and discuss. The first thing this morning is that we will give an
> update report on the noon-clinical studies subcommittee. Frank Sistare
> and Bob Osterberg are here to present that. Then Dr. Layloff, who is
> the chair of the process analytical technologies, will bring you all
> up to date on where we are with that subcommittee.
>
> Later in the morning we will talk about risk-based CMC review. If you
> will remember, in 2000 Dr. Chiu talked to you about this and gave you
> an awareness of what we are doing in this area. We will talk more
> about the progress with these initiatives and get your input as to the
> next steps that we need to take.
>
> Also this morning we will revisit blend uniformity. We have two
> invited guests, Dr. Massa who is the chair of the PQRI committee and
> Tom Garcia who was actually the chair of the working group for blend
> uniformity. We have made modifications to the proposals that were
> submitted to PQRI and we want to report on those modifications and the
> next steps so that we can continue to move forward with the
> recommendations from PQRI.
>
> After lunch and the public hearing we will talk about polymorphism. At
> the last meeting we did have an awareness discussion on polymorphism
> and since that time we have had a workshop to talk about some of the
> issues, an internal workshop in generic drugs to talk about some of
> these issues. We have given you all a chance to look at the concept
> paper on polymorphism. We still have some questions that we would like
> to address basically on what direction we need to go as far as the
> decision tree is concerned for bioavailability and stability. We will
> discuss that with you and then we hope to finally close out this topic
> and finish the guidance.
>
> Tomorrow we have another full day. As I mentioned, we are anxious to
> get started with the manufacturing subcommittee. We are going to
> introduce that subcommittee to you and talk about what we see this
> committee doing in the future. We will also talk about transitioning
> the PAT subcommittee into the manufacturing subcommittee. This
> committee will basically handle all CMC issues that come up. We have
> asked several members from industry to come and talk to us about their
> ideas as far as the subcommittee and give us their input as to how
> this committee will be beneficial to them.
>
> As part of that discussion in the morning and the rest of the
> afternoon, we are going to talk about manufacturing issues, sort of
> kick of the manufacturing subcommittee. The first issue we will
> discuss with the committee is aseptic processing. This is basically a
> guidance that has been drafted. You have all received the concept
> paper to review. This guidance has been drafted by the Office of
> Compliance. We have been working with them. The Office will present to
> the subcommittee what they feel are the questions around aseptic
> processing and we will get the committee\'s input on what the next
> steps are and where we need to go from here. It should be a fairly
> interesting discussion and we look forward to it. It is sort of a new
> way for us to handle it. We have not brought the Office of Compliance
> into the advisory committee before and we feel like this will be very
> beneficial. We have invited several guests to give their input so we
> can have a more vigorous technical debate.
>
> Basically that is the agenda for the next two days. It is a full
> agenda; we have a lot to cover. I look forward to the discussion on
> all of these issues and I look forward to continuing to work with many
> of you even though you are leaving the committee. Many of the rest of
> you I have already asked to participate in future subcommittees and we
> look forward to working with you in the future. So, thank you.
>
> DR. LEE: Thank you very much, Helen. You are very kind in commending
> the committee. In fact, I can say, since we are ahead of schedule, I
> would like to take the floor to acknowledge your contribution and
> Ajaz\'s contribution. It certainly has been a pleasure to work with
> the agency. I think the thing that has impressed me the most is making
> decisions on the basis of science. I think that is very important. I
> would like to stress, as we go through the deliberations today and
> making recommendations, let\'s focus on the science. I think that is
> very important. Also, when science is progressing, I see that the
> agency is very bold in reflecting about past decisions. Certainly, we
> will miss spending nights at the Ramada Inn\--
>
> \[Laughter\]
>
> MS. WINKLE: Vince, you can come any time you like. We would love to be
> able to have you come and we will put you right back up at the Ramada.
>
> DR. LEE: I think it is an inside joke! On that note, are we ready to
> begin with the subcommittee reports? The first subcommittee report
> will be the non-clinical studies.
>
> MS. WINKLE: Dr. Doull is going to give us an update on the
> subcommittee and then Frank and Bob will talk about the future.
>
> **Subcommittee Reports**
>
> **Non-Clinical Studies**
>
> DR. DOULL: Well, we are very pleased to have a chance to come to the
> committee and update you on the activities of your non-clinical
> studies subcommittee. As some here may recall, this committee was
> established in 1999 and the intent of this committee is to encourage
> the development of biomarkers which could be used to predict the
> adverse effects of drugs during the development phases. Actually, what
> we were hoping to find is biomarkers which could be used both in the
> preclinical and in the clinical phases of drug development. We felt
> the best way to accomplish this would be to have a cooperative effort
> between the pharmaceutical industry, between the Food and Drug
> Administration and between academia.
>
> During the first year that our committee functioned we spent a lot of
> time looking at all the different available biomarkers. We looked also
> at some that were imaging techniques, PET scan and MRI and so on, and
> eventually we focused on two areas. We focused on those areas
> primarily because we felt there was a strong need in both of those
> areas and because we felt that there was promise of or finding good
> biomarkers in those areas. As you know, the two areas we focused on
> were the biomarkers of cardiac toxicity and biomarkers of vascular
> injury.
>
> We appointed subcommittees in both of those areas and those
> subcommittees have been working now for about a year. During that
> period they have had lots of meetings; they have had workshops. It has
> been a very active year for both of those subcommittees and we are now
> at the stage where the subcommittees are about ready to bring reports
> containing their recommendations and conclusions to the committee. As
> a matter of fact, in the meeting that we held last September 8th and
> 9th, the working group on cardiovascular toxicity presented an outline
> of their report which the subcommittee approved, and the working group
> on vascular biomarkers presented a first draft of their report which
> the subcommittee also is working on. So, at the present stage then we
> are close to being ready to deal with reports from both of our working
> groups which we will, of course, bring eventually to this group.
>
> Dr. McGregor has put together a series of slides which kind of
> summarize the evolution of this process and I am not sure I can do
> those.
>
> MS. WINKLE: Dr. McGregor\'s slides have been passed out to each one of
> the members of the committee. If there are any questions, I think we
> could address those to Dr. Doull and Dr. McGregor at this time.
>
> DR. DOULL: Well, if you have copies of those I can run through them. I
> am just not sure how to operate this.
>
> \[Slide\]
>
> The first slide, as I have already mentioned, is the formation of the
> active expert working groups. It indicates on that sheet that the
> chair for the cardiotoxicity group was Dr. Ken Wallace, from the
> University of Minnesota. There is a co-chair for the vascular injury
> working group and that is Bill Kerns and Les Schwartz.
>
> \[Slide\]
>
> The next page or slide outlines a couple of issues which the working
> groups considered initially in their evaluation of this topic. The
> issue for the cardiotoxicity group, one of the main issues\--
>
> MS. WINKLE: While John works on this I just want to publicly thank
> John. He keeps us going as far as all the technology that goes behind
> putting this together. He leaves the room and we fall apart.
>
> DR. DOULL: Thank you. These are the two subgroups. As I indicated, Ken
> Wallace and Bill Kerns and Les Schwartz are the co-chairs of the
> groups. These are the two issues that the working groups focused on.
> Myocardial injury is being used in a lot of human studies but we
> don\'t have a lot of animal correlates for the human observations.
> Nevertheless, that gave us a start, a working place to go.
>
> In the vascular area it is much more complicated and much more in
> development than is the myocardial injury. There are a lot of common
> immune-mediated effects in animals, a lot of effects in animals which
> have been observed but these have not really been correlated with
> human biomarkers.
>
> \[Slide\]
>
> The mandate then for the group is to evaluate and develop
> understanding of cardiac and vascular injury in humans and animals and
> to identify opportunities for biomarkers based on these mechanisms, to
> figure out how to do validation and, finally, to define a plan to
> implement the utilization of new markers, which is fairly complicated
> and would, of course, involve this committee.
>
> \[Slide\]
>
> As I indicated, the subcommittee met on September 8 and 9, and we
> heard reports from both of our working groups. As I indicated also,
> both of these are under review now by the subcommittee. We have a
> first draft from the biomarkers for vascular injury and we have an
> outline, and the cardiac toxicity working group is working on their
> draft.
>
> \[Slide\]
>
> These are some of the major conclusions that we received at the
> September 9th and 10th meeting. There were a number of suggestions by
> members of the subcommittee for revisions to the draft that we had
> from the vascular group. One of the problems was that the vascular
> group has developed a plan whereby they would have storage for agents
> that would be used in these tests and these then would be provided to
> investigators to test various biomarkers. There are some procedural
> difficulties with establishing a storage place for the agents,
> dispensing them, and so on, and we spent a fair amount of time trying
> to figure out how best to do that, and I think we have some pretty
> good ideas.
>
> Both groups, as they went through their exercise, identified data gaps
> which really hinder the development of effective biomarkers in both
> areas. We talked a lot about those data gaps and how the subcommittee
> could facilitate filling in those data gaps.
>
> The vascular group particularly has moved extensively into the genomic
> area and is going to be doing some development, particularly in
> proteomics. So we reviewed that protocol with them.
>
> \[Slide\]
>
> These are the conclusions of the other group, the cardiotoxic group
> and they, of course, are focusing on troponins as biomarkers. As I
> indicated, they have some data gaps and we talked about filling those.
>
> One consideration that both groups have, particularly the cardiac
> group, is now that they have produced their report and made a
> recommendation, that recommendation, of course, will focus heavily on
> the use of troponins as a biomarker. The question then is what is the
> next step, and our subcommittee is encouraging them to go ahead and
> look at other biomarkers of cardiac toxicity in the hope that we will
> find additional ones worthy of consideration.
>
> \[Slide\]
>
> The report of the subcommittee in September is available at the Food
> and Drug web site. So, the outline for the cardiac toxicity and the
> first draft of the report from the vascular biomarkers group is
> available at that web site.
>
> I will be glad to answer any questions about the activities of your
> clinical sciences subcommittee.
>
> DR. LEE: Thank you, John. Any questions for John?
>
> \[No response\]
>
> Very clear. Thank you.
>
> DR. OSTERBERG: Good morning. I am Bob Osterberg, the acting associate
> director for pharmacology and toxicology, and I will lead off with a
> discussion of the pharmaceutical sciences subcommittee guidance which
> we have drafted. So, good morning to you all.
>
> \[Slide\]
>
> Let me give you a little history of how this came about. I was asked
> by Mrs. Winkle to attend a meeting with her and some of her staff
> several weeks ago to discuss this particular activity. In listening to
> it and participating in the discussion, I realized that it was
> something that would help the pharmacology and toxicology staff of the
> Center for Drugs, specifically the Office of New Drugs, and I was
> quite pleased to find out that my predecessor, Dr. Joseph DeGeorge,
> also had agreed that this was a good thing to occur. We spoke with Dr.
> John Jenkins, who was the director of the Office of New Drugs, and we
> got his concurrence also. So, he agreed that this was a worthwhile
> activity to pursue.
>
> Well, why do we need this particular subcommittee within pharmacology
> and toxicology at least to help us out? I would like to give you the
> general structure of the pharmacology/toxicology group within the
> Office of New Drugs and that may answer your question. As the acting
> associate director for pharm/tox I report to the medical director of
> the Office of New Drugs and within the Office of New Drugs we have
> five ODEs or offices of drug evaluation. Each of these five offices
> are staffed by a medical officer.
>
> Now, within these ODEs we have three divisions and, of course, they
> are staffed by a medical officer as the director. Within each division
> we have a supervisor. Sometimes we have two supervisors, depending
> upon what the size of the pharm/tox group is. In each ODE we have an
> associate office director for pharmacology and toxicology that reports
> to me, and they are responsible for some policy within that ODE, that
> office. They also constitute a policy group. Each of the supervisors
> in pharm/tox constitutes the pharmacology and toxicology subcommittee
> which I chair, and that committee also has a research subcommittee
> which Dr. Sistare and I co-chair. That means that we have a lot of
> discussion about the types of pharm/tox research or questions that we
> would like to have answered.
>
> The pharmacology and toxicology coordinating committee has many
> subcommittees attached to it, things like carcinogenicity assessment,
> genetic toxicology, reproductive toxicology and active ingredients and
> botanicals, and there are several other subcommittees which provide
> guidance to the pharmacology and toxicology coordinating committee.
>
> Therefore, I think you can see that pharm/tox, based upon its
> structure, has no specific ability to house its own advisory committee
> and, therefore, when we got the opportunity to participate with the
> Office of Pharmaceutical Science Advisory Committee we thought it was
> a very good idea to pursue. As a result of this, Dr. Sistare and I
> decided that it was probably a good idea to draft a guidance, which is
> what we are going to be discussing this morning. I will briefly
> discuss the purpose, the background, the objectives, responsibilities,
> procedures and communications contained within this guidance. Dr.
> Sistare, who is the director of the Division of Applied Pharmaceutical
> Research, will discuss the membership and other
> pharmacology/toxicology related subjects.
>
> \[Slide\]
>
> Let me give you the general background of this committee. In general,
> the CDER advisory committees provide the Center for Drugs with
> non-binding but highly valuable expert external advice. However, the
> advice is usually very product specific. The pharm/tox subcommittee of
> this advisory committee is expected to provide feedback not only to
> the pharm/tox coordinating committee but also to facilitate NCTRs
> non-clinical studies subcommittee in meeting CDER\'s
> pharmacology/toxicology research needs.
>
> \[Slide\]
>
> The objectives and responsibilities of this subcommittee would be to
> provide expert advisory feedback to the pharmacology and toxicology
> coordinating committee in areas of cross-cutting research where
> integration of new scientific knowledge and methodology can be helpful
> in not only drug development but also in helping to identify
> laboratory-based research priorities to address data gaps identified
> by the pharm/tox coordinating committee.
>
> Some of these areas, as Dr. Doull mentioned, would be
> pharmacogenomics, proteomics, metabonomics. As you know, some parts of
> the Center for Biologics will be transferred into the Center for Drugs
> probably within a year, maybe sooner, and we will have a whole list of
> questions in biotechnology that this subcommittee could help us in
> answering. We are also concerned with biomarkers, as Dr. Doull pointed
> out before. We are concerned about alternatives to the two-year
> carcinogenicity bioassays, specifically things like the TGAC mouse
> model, the p-53 and others. Of course, we are concerned about genetics
> and mutagenicity.
>
> \[Slide\]
>
> As you know, the ICH or the International Committee on Harmonization
> has identified a battery of genetic toxicology studies to help all the
> regulatory agencies make decisions, and that battery can be updated
> depending upon innovations and the science, and this subcommittee
> could help us in that regard. Also, the subcommittee could provide
> input to the National Center for Toxicology Research, the NCSS, to
> address the Center for Drugs identified data gaps. Also, the
> subcommittee could advise the PTCC in the evaluation of research data
> derived from the non-clinical studies subcommittee related to
> pharmacology and toxicology activities.
>
> \[Slide\]
>
> The procedures that the subcommittee standard deviation follow would
> be that the meetings of the subcommittee would occur on an as needed
> basis and we would anticipate two meetings per year. Regarding
> communication, agendas and topics for the subcommittee would be
> proposed by the pharm/tox coordinating committee. So, in essence, the
> pharmacology group would help direct traffic for the subcommittee.
>
> \[Slide\]
>
> The activities and recommendations of this particular advisory
> committee would be given to the Advisory Committee for Pharmaceutical
> Science, to CDER\'s PTCC and, as needed, to NCTR\'s non-clinical
> studies subcommittee. A member of the pharm/tox coordinating committee
> research subcommittee which I mentioned will serve on NCTR\'s NCSS,
> and that member is Dr. Frank Sistare and I would like to turn the rest
> of the discussion over to him to talk about membership and other
> things.
>
> DR. SISTARE: At the conclusion of my presentation Dr. Osterberg and I
> will entertain any questions if everything is not perfectly and
> crystal clear with all the connections that will need to be made to
> make this successful.
>
> \[Slide\]
>
> To summarize essentially the process that Bob went over, the PTCC
> research subcommittee played a pivotal role in helping to identify
> topical scientific areas and recommend these to CDER\'s pharm/tox
> coordinating committee. This research subcommittee will not be
> involved just in research that will be the subject of this
> subcommittee; it is also involved in helping us prioritize our own
> internal research. It is helpful in terms of giving feedback to NCTR
> individual investigator initiated protocols where they want various
> centers to give them feedback. It is also involved in identifying, for
> example, chemicals through our chemical selection working group
> mechanism that may ask for funding through NTP directly. Those kind of
> activities will not come to this subcommittee; a certain subset will.
> So, the PTCC research subcommittee serves as sort of a triage role in
> terms of identifying those things to the PRCC with its recommendations
> as to how these things can be addressed.
>
> As Bob pointed out, that PTCC, that coordinating committee within
> CDER, will serve to coordinate the input to this specific committee
> and will present those issues to the subcommittee. When the decision
> is made for noon-clinical studies subcommittee under NCTR to
> coordinate external collaborative research, the concept is as well
> that when that data comes back from that effort and, as pointed out by
> Dr. Doull, we have two pretty mature efforts right now, the vision is
> that some very helpful final data will come back from there with some
> recommendations. The dialogue that needs to take place will be
> directly with our PTCC and that dialogue will occur also with the
> Advisory Committee for Pharmaceutical Science\'s P-T subcommittee
> regarding the concept or the vision of the impact of the final data
> conclusions and its impact on regulatory practice and potential
> modifications to existing policy.
>
> We discussed at some length the generation of the Advisory Committee
> of the Pharmaceutical Science\'s pharm/tox subcommittee membership,
> and this is really a proposal; this isn\'t written in stone yet but we
> need to work out the last element. There is clearly going to be a
> chair person and that person will be a member of this committee. There
> will need to be a consumer representative as well that will sit on
> both committees. In order to ensure communications, the feeling is
> that one of the members of the pharm/tox subcommittee should also sit
> on the NCTR NCSS as well to make sure that there is continued dialogue
> and shared communication between those groups.
>
> The last point that we really need to make a firm decision on is
> should the rest of the membership be a permanent membership of this
> subcommittee, or should we establish ad hoc members, maybe have a
> mixture of some permanent members and some ad hoc members because we
> envision that much of the focus will be in very specific targeted
> areas. As Bob pointed out, there may be one or two meetings a year so
> there will be time to prepare and make up the committee to make sure
> if we are going to be asking questions about modifications to
> alternative carcinogenicity testing, for example, we may have members
> with special expertise there. If we are going to ask for advice on how
> to integrate microarray into pharm/tox data generation and validation
> we may have people with specialties in those areas. So, that needs to
> be worked out.
>
> \[Slide\]
>
> Now I am going to try to walk you through this maze and this network
> or process and how key linkages and interactions really need to occur
> to make sure this takes place.
>
> As I mentioned, the PTCC research subcommittee really serves as sort
> of a conduit to bringing advice from a lot of areas within CDER. There
> is representation on that committee from both research components
> within CDER and also from all of the offices, the pharm/tox divisions
> within the major five offices within CDER are responsible for bringing
> to the PTCC areas where we feel there is new technology; there are new
> questions; there are issues which may or may not be research but at
> least ought to be on the radar screen that we need to think about in
> terms of modifying our current practice.
>
> So, essentially this subcommittee is responsible for identifying and
> prioritizing internal needs and capabilities. As I mentioned, we have
> direct contact with NCTR and this committee also is involved in
> oversight of research activities within CDER. We have the Office of
> Women\'s Health Initiatives that may come here when we need some
> feedback that may be pharm/tox based. We have regulatory science
> research initiatives that are more data-mining based that this
> committee will also get involved in. As I mentioned, NTP nominations
> will also be involved in here.
>
> But there is another category of research that we have become aware
> of, and that is research which is not necessarily focused on one
> particular chemical but broad-ranging issues, issues that are not
> going to be handled by one small laboratory but issues that are going
> to need external collaboration in order for them to really achieve the
> impact that we expect. This is the subject of what we want this
> pharm/tox subcommittee of the ACPS to participate in. We would like
> this subcommittee to advise on the likelihood of the impact on drug
> development of research that should be carried out in these
> broad-ranging areas. So, this research will be coordinated with the
> non-clinical studies subcommittee which will sit under the National
> Center for Toxicological Research. Again, the research product, the
> research that will be coordinated there will be a target for external
> collaborative programs. So, it is going to be broad-based in nature.
>
> With this color scheme I have sort of indicated here that the makeup
> of the Advisory Committee for Pharmaceutical Science is going to be
> very broad-based. One of the components will be pharm/tox and, as
> Helen mentioned, there will be manufacturing; clinical pharm
> microbiology. I don\'t have biopharmaceutics; that is my oversight.
>
> Now, to give a clear picture of the predecessor here, the non-clinical
> studies subcommittee, part of my goal is also to explain what is going
> to happen to that committee. That committee is going to be under the
> auspices of NCTR. How that is going to be administered will be decided
> soon. Whether it will report to their scientific advisory board or
> whether it will report directly to NCTR, those kinds of details will
> need to be worked out and there is going to be a meeting next week to
> get into some of the details of that. But the vision is that this
> non-clinical studies subcommittee will, as it is doing now, coordinate
> external collaborative research initiatives that are focused in the
> area of safety and toxicology research. They will establish expert
> working groups as they are doing now. The makeup of this non-clinical
> studies subcommittee is envisioned to include membership from CBER and
> CDRH, members of the academic community, members of industry and also
> a consumer rep as well.
>
> I think that pretty much covers everything. Are there questions for
> Bob or me?
>
> DR. LEE: Thank you. Are there questions? I think there is one question
> about how the membership ought to be constituted. Will it be ad hoc or
> kind of semi-permanent?
>
> DR. SISTARE: Or a mixture of the two?
>
> DR. LEE: Any strong feelings? Dr. Doull, would you like to offer some
> advice?
>
> DR. DOULL: We did discuss this reorganization, of course, in the
> meeting of the subcommittee and although, as you can see, it is not
> clearly outlined, the subcommittee by and large was very enthusiastic
> about it. We see this as kind of a win-win situation for the
> activities that our subcommittee is attempting to do.
>
> The main concern I think our subcommittee has is that we need to
> ensure that there is a conduit by which we can bring our
> recommendations and advice to the agency, and the mechanism that is
> suggested here seems to us to be a reasonable one, one that we feel
> will be workable in the subcommittee and for this committee.
>
> DR. LEE: Thank you. Other points of opinion?
>
> \[No response\]
>
> Folks are pretty quiet this morning. Well, I think the subcommittee
> structure is excellent. First of all, my personal experience is that
> being a member of this committee is a very scary experience because,
> you know, you have to expose yourself to diverse aspects of science,
> and in the end if you apply pharmaceutical common sense you are okay.
> So, my personal preference is actually to have a panel constituted
> depending on the issues. That is pharmaceutical common sense.
>
> Thank you. Hopefully, we are saving energy for this afternoon\'s
> discussion. Thank you very much. The next one on the agenda is the PAT
> and Tom Layloff\--I am sure that Tom is going to stir something up.
>
> **Process Analytical Technologies**
>
> DR. LAYLOFF: The first surprise is which set of slides am I going to
> be using? You have two sets in front of you. We are using the one that
> was handed out recently.
>
> \[Slide\]
>
> Serving as the acting chair on the PAT committee has been a very
> exciting thing for me. I was fascinated with pharmaceutical
> manufacture because, I am not sure but I think, it originated with
> pharmacology compounding rather than chemical engineering. Because it
> is housed in a conservative industry, pharmacology manufacture sort of
> stays in the background and the information age and the technology
> associated with other industries, like the petroleum industry, the
> chemical industry, has left the pharmaceutical industry unscathed. So,
> Ajaz took this initiative to look and see if the FDA could encourage
> the adoption of new technologies and the information age to try and
> improve the quality and control of pharmaceutical manufacture.
>
> \[Slide\]
>
> So, it has been a pretty exciting time, and we will go on and look at
> it. We had a meeting on February 25 and 26 looking at applications and
> benefits, and there were some really striking benefits, mostly in
> turn-around time and quality issues. We looked at process and
> analytical validation and chemometrics.
>
> At our second meeting we continued to look at product and process
> development; process analytical validation and the proposed PAT
> certification program which is, to me, probably the most exciting part
> of the PAT activity.
>
> \[Slide\]
>
> Going through the areas that we considered, we looked at R&D efforts
> in pilot plants, and the R&D efforts in a pilot plant could help
> develop better understanding of processes and then identify PAT areas
> where they could be employed. The PAT technologies would have to be
> shown to be suitable for intended use and they would have to be
> validatable. We would have to be able to validate that those
> technologies were, in fact, performing correctly.
>
> \[Slide\]
>
> The R&D efforts in manufacturing would have to verify the validation
> from the pilot plant; investigate transferability, scale-up issues and
> so forth. The committee also looked at model refinement that might be
> necessary and process signature; process signature used
> interchangeably with fingerprint where you actually do not unravel the
> chemical but look at broad aspects of the process stream. As you know,
> in pharmaceutical manufacture the components are weighed into the
> process stream so, actually, the only issue in going from weighing in
> components to final products is how you average those components in a
> blending area. So, it is looking at uniformity and consistency in the
> process stream and you can use other technologies apart from chemical
> analysis, such as fingerprints or process signatures then for FDA
> submission of a protocol and the original application or it could come
> in as a supplement.
>
> \[Slide\]
>
> For routine manufacturing using PAT, the PAT information should have
> equivalent or better informing power than the corresponding
> conventional approved or end-product testing. Conventional testing is
> looking at the active pharmaceutical ingredient as it moves through
> the process stream and treating the whole process stream as a
> univariate activity. One dimension is looked at. PAT should look more
> broadly at the polyvariate aspects of manufacturing so it should be
> much richer information.
>
> It is recommended that they show a table showing the relationship
> between PAT testing and the current testing methodology so you
> constantly validate against the two. And, parallel PAT testing and
> conventional testing, in-process and/or release, should be performed
> for a sufficient number of batches, which is basically establishing
> confidence in the technology.
>
> There is a level of redundancy which is a business decision, but I
> think it probably will be a critical factor in PAT technology that
> will be more than one technology or parallel technologies to give
> better control.
>
> \[Slide\]
>
> Steps for resolving OOS observations, because the PAT is moving into a
> continuous monitoring of a stream, it is possible to say if there is
> non-uniformity which occurs in the stream and it occurs near the end
> of the process of the stream that you could discard the last 10
> percent of a production run and clear 90 percent of it. So, the PAT
> could be used for selective rejection or partial batch release of the
> process stream itself.
>
> Within batch trend information should facilitate resolution of out of
> specs. Because you are requiring so much more data on the process
> stream, so much more knowledge of the process stream, you are in a
> better position to deal with out of specs.
>
> Until the PATs are approved for regulatory purposes, the conventional
> test results supersede the PAT results. That is, you stay with a
> conventional platform while you develop your PAT, and the PAT is a
> research vision which is not considered to be an integral part of the
> process until it has been approved.
>
> If an out of spec result is traced to an instrument failure, then
> traditional approved methods can be utilized for batch release in lieu
> of PAT. So you just have a backup of your conventional procedures and
> that, of course, is why there probably will be redundancies in PAT.
> The PAT technologies are relatively inexpensive.
>
> \[Slide\]
>
> Product development and process again\--identification of relevant
> critical formulation and process variables, looking at product
> performance and process control for assurance of quality is looking at
> critical variables in the process stream and controlling those.
>
> Use of indirect or inferential measurements, process signature or
> correlation\--a link between the statistical and causal issues between
> the PAT parameter and product characteristics. That is a logical
> fallout from continuous stream measurements. Then, establish
> acceptable variability. That is a very interesting point in the
> process stream, to define how the PAT will fit into it and what is
> acceptable variability on the process measurements, the PAT
> measurements.
>
> \[Slide\]
>
> The definition of the process and analytical validation: Systems for
> the analysis and control of manufacturing processes based on timely
> measurement during procession of critical quality parameter and
> performance attributes of the raw and in-process materials and
> processes to assure acceptable end-product quality at the completion
> of the process, basically a paradigm shift from where we are now,
> which is product-based testing, to process-based testing where, during
> the process stream itself, large quantities of data are acquired which
> are then moved into information streams and then finally knowledge of
> what the processes are doing. So, it is a better understanding of your
> processes and better control of them.
>
> \[Slide\]
>
> The existing validated measurements invariably correlate poorly with
> process performance. Validation issues, again, are univariate and are
> used to infer compliance of these multivariate dynamic systems. There
> are lots of examples where the uniformity of the drug substance is
> there but an excipient might not be, which will change the behavior
> characteristics of the product.
>
> Measurement has not been seen as process related. Measurement needs to
> respond to process need over the product life cycle. And, you need to
> understand the process. You need to recognize also that the
> conventional approach to validation is limiting\--might be limiting;
> probably limiting.
>
> \[Slide\]
>
> Further background, it is essential to understand the process, look at
> the unit operations and assess the risk potential for each unit
> individually, so basically moving to a risk-based assessment of the
> process stream; design systems to manage the risk and make univariate
> measurements and multivariate systems; to develop systems; to
> establish proof of concept; challenge validation. The objective, of
> course, is to confirm the processes and measurement validity in real
> time across the life cycle.
>
> \[Slide\]
>
> Process analytical validation continuing, validation protocols will be
> different for new products associated with well-designed, understood
> manufacturing processes and existing products where PAT is applied
> retrospectively. So, you can come to an existing process where you can
> apply retrospectively.
>
> The validation plan will reflect the total system design concept since
> a real-time QC/QA manufacturing process, statistically based,
> essentially revalidates itself on every manufacturing batch. So you
> can make adjustments on the acceptability of the stream.
>
> The rationale for model validation incorporating the pass/fail
> criteria must be clearly defined, thereby, establishing the
> authenticity of predictions in routine manufacturing and ensuring
> compliance.
>
> \[Slide\]
>
> There are three distinct ways of analyzing unit operations and
> releasing products. Current operating scenario, which is basically
> according to the fixed process conditions set during the development
> and confirmed during the initial process and product validation.
> Release is conducted by physical and chemical testing subsequent to
> manufacture.
>
> Another way, product is manufactured according to process conditions
> that have been shown during development and manufacturing to infer
> product performance and is confirmed during the initial process and
> product validation. Relationships are developed and confirmed with
> physical and chemical testing subsequent to manufacturing runs.
> Release is conducted by review of process conditions during each batch
> manufacture\--a paradigm shift.
>
> \[Slide\]
>
> Product is manufactured according to process conditions that are
> responding to direct measurements of in-process product quality or
> unit dosage forms as they are being manufactured. Relationships are
> developed between process and product performance that are optimized
> and bounded by data obtained in development and manufacturing runs.
> Release is conducted by data collected from in-process product or each
> dosage form during manufacture. Release specification form and
> validation criteria can be defined for each condition based on the
> nature of their release.
>
> \[Slide\]
>
> Going on to recommendations for a guidance, for the FDA guidance, the
> PAT should be suitable for the intended purpose. There should be
> general validation criteria, as discussed. It should be anchored in
> the ICH documents, Q2:a and b; 6a and 6b, and the FDA analytical
> procedures and methods validation procedures.
>
> There should be in the guidance a research exemption as a safe harbor
> so you can investigate the use of PAT without having to deal with a
> lot of problems. There has to be a discussion or treatment of out of
> spec and out of trend. Trend, of course, mostly comes from the PAT
> technology to stream continuously. Out of spec generally refers to
> what you are analyzing. The guidance should encourage use of PAT and
> the FDA should have a mechanism to institute these new technologies
> and methods. Ajaz will address that in his presentation following this
> one.
>
> \[Slide\]
>
> I think one of the most exciting parts of the recommendations from our
> committee was the training and certification program and defining the
> course content for that program. The proposed process analytical
> technology certification program for FDA investigators and reviewers,
> hopefully, will bring reviewers and inspectors to a common page on
> performing the inspections and review of the submitted documents.
>
> On completion of the certification program, participants should be
> able to evaluate the adequacy and performance of current and emerging
> PATs. This certification will require a demonstrated understanding of
> the fundamentals, importance and impact of PATs.
>
> \[Slide\]
>
> Participants will be able to demonstrate an understanding of the
> distinguishing characteristics of a PAT; the identification and use of
> process critical control points; suitability and validity of the
> statistics, chemometric and instrumental approaches applied to PAT;
> typical PAT applications and the associated capabilities and
> limitations of the methodology; data handling, analytical, control and
> engineering tools and vocabulary relevant to PAT\--a lot!
>
> \[Slide\]
>
> Our last meeting will be later this week, on Wednesday, and we will
> deal with computer software validation, security, electronic batch
> records and signatures as they apply to PAT. There will be a breakout
> session with a mock PAT submission, and there will be a session on
> rapid microbial testing. At the end of this meeting information needed
> to develop a general guidance should be available to the FDA.
>
> That first issue, discuss issues related to computer validation
> issues, is Part 11 which will have a big impact on PAT because PAT is
> very information rich.
>
> Now I will turn to Ajaz.
>
> DR. HUSSAIN: I seek your permission to share with you what we have
> learned from the subcommittee so far.
>
> DR. LEE: Please proceed, and are you going to take all the difficult
> questions?
>
> DR. HUSSAIN: Yes. Tom just got back from Africa and I met with him
> yesterday to walk through some of the progress.
>
> \[Slide\]
>
> Since we have some time, thank you for permitting me to share some
> more thoughts on the PAT and give an FDA progress report on what we
> have been able to do so far.
>
> I am very pleased to share with you that the PAT inspection team has
> been assembled. This includes participation from Office of Regulatory
> Affairs, Center for Drugs and Center for Veterinary Medicine, and I
> see my colleagues in the audience. The Center for Veterinary Medicine
> is part of the PAT initiative itself.
>
> We held quite a successful meeting a couple of weeks back and this
> brought us talking together and getting them ready for the extensive
> training and certification program that starts in December.
>
> The curriculum developed by the PAT subcommittee was the basis for
> developing training contracts with three schools, three universities,
> University of Washington, the Center for Process and Analytical
> Chemistry; University of Tennessee, the Measurement Control
> Engineering Center; and the University of Purdue. What we have been
> able to do is bring the chemistry, process analytical chemistry,
> clinical engineering and industrial pharmacy together to bear upon the
> training needs of the PAT review and inspection team.
>
> They have also put together a PAT policy development team and have
> been successfully recruiting engineers and industrial pharmacists for
> this team. We have been making significant progress with the PAT
> research and there have already been publications and several
> presentations planned for a meeting.
>
> \[Slide\]
>
> To share with you the PAT team, in a sense we have a PAT steering
> committee that includes Doug Ellsworth, Dennis Bensley, Mike Olson,
> Joe Famulare, Yuan-yuan Chiu, Frank Holcomb, Moheb Nasr and myself.
> So, you can see from this membership that we have brought in
> individuals from every organization within FDA which has an impact and
> has responsibility for manufacturing and from review to inspection and
> from human drugs to veterinary drugs.
>
> The PAT review and inspection team members were nominated by each of
> their organizations, and investigators were selected to represent
> different districts. You have Atlanta, San Juan, New Jersey and
> Philadelphia districts represented. Then compliance officers, as
> identified, will be part of the program and reviewers from both new
> drug chemistry, generic drugs and Center for Veterinary Medicine. So,
> essentially, this will be the review and inspection team that will be
> responsible for submissions and issues related to PAT that come in.
> This team will undergo an extensive training program starting in
> December.
>
> We also have a PAT policy development team which essentially is
> working under the PAT steering committee. Here you look at Raj Uppoor,
> a review chemist with industrial pharmacy background; Chris Watts,
> from the University of Tennessee, an industrial pharmacist with a
> biomedical engineering degree; and Hiquan Wu, a chemical engineer, who
> all have very broad experience. We are still waiting for one more
> member to come in with process analytical chemistry expertise. When he
> is on board I think the team will be essentially complete.
>
> We have PAT training coordinators. John Simmons and Karen Bernard are
> sort of managing the training program with the help of Kathy Jordan.
> So, this essentially has evolved into a full-fledged team with
> organized efforts leading to facilitating implementation of a PAT
> program within FDA.
>
> \[Slide\]
>
> To share with you, the input from the advisory committee\'s
> subcommittee on PAT has been extremely valuable to setting up a
> conception framework for PAT, actually not only to develop that
> conceptual framework but also to help establish consensus with an
> outside agency and even in the international arena. I recently
> received a copy of a publication from EFPIA, which is the European
> version of PhARMA which essentially has incorporated some of these
> concepts, and in many ways I think harmonization is occurring without
> any effort or without any designed efforts. So, that is a very good
> sign.
>
> As we move forward, I think we have started to look at PAT as a part
> of an example of the new FDA-wide initiative of cGMPs for the 21st
> century. You can see why once we have all the information relevant for
> the general guidance the activities of the PAT subcommittee could sort
> of be under the manufacturing subcommittee, and that would sort of
> evolve to that step.
>
> \[Slide\]
>
> Just to share with you the key elements that formed the conceptual
> framework for the PAT, I could talk for three hours on this but I will
> not, it sort of addresses every aspect of the manufacturing from
> incoming raw materials and using that information of attributes of
> incoming raw materials to adjust your process parameters, and to
> measure the processing on-line, and focusing on process critical
> control points and moving towards endpoints, process endpoints and
> making decisions in real time using chemometrics and information
> technology tools to have indirect or inferential assessment of quality
> and performance.
>
> It also sort of brings into focus the continuous improvement. How do
> you develop this; how do you use the design of experiments and how can
> you benefit from that. Optimization of continuous improvements sort of
> evolves from this. It also opens up the possibility of evolutionary
> optimization. Management of change, formulation process change has
> always been a challenge and will continue to be a challenge in
> pharmaceuticals but having measurement tools that can relate to
> product performance or predict performance actually offers many new
> opportunities which have not existed before. We can even start
> thinking about the concept of evolutionary optimization which has been
> sort of not a practical process in pharmaceuticals but is a very
> valuable tool outside the pharmaceutical industry.
>
> Really the PAT framework not only sort of enhances our ability to
> improve quality but also improve efficiency, and what we also have to
> do is to start thinking in terms of a multivariate systems approach,
> not just focus on univariate assessment technologies that we have been
> used to. It also brings in risk classification and mitigation
> strategies that takes us to the next step.
>
> \[Slide\]
>
> I will sort of spend a few minutes on that very topic. One aspect
> which sort of summarizes Dr. Kibbe\'s working group\'s concept at the
> last meeting was that quality has to be based on knowledge, and that
> is an important concept and that relates to science and risk-based
> cGMPs in one of these fashions.
>
> Let me explain this. Data information knowledge, I think everybody
> understands that. Today, to a large degree, FDA\'s responsibility is
> to assess whether the quality of a product is acceptable or not. In
> many ways we address the question was quality built in or was quality
> designed into the product or not in the review and the inspection
> site.
>
> The information that is generally available to the review staff when
> they set specifications is limited, and in the U.S. particularly
> development reports and development history is not available to the
> reviewers, which is different from Europe. So, they are blind in many
> ways and often we criticize the CMC processes as very conservative.
> The reason for the conservativeness is because of lack of information.
>
> So, today it is often difficult from an FDA perspective to assess
> whether the quality was built in by design or not. The reason for that
> is that our decisions tend to be based on data derived from trial and
> error experiments and decisions based on a univariate approach. As a
> result, our systems are very conservative and we have to monitor and
> inspect every step of the way. So, that is one perspective on what the
> current situation is. I know of many companies which do extensive
> process development optimization and a lot of things, but that
> information is often not shared with the FDA for reasons of mistrust
> in many ways\--how will the agency use this information.
>
> With PAT what we have tried to do is to sort of shift that paradigm
> and say all right, in a sense, when we have information that allows us
> to have causal links established within critical variables and product
> performance, and also our ability to improve or predict product
> performance is visible and can be utilized we can move up in this
> knowledge pyramid whereby quality by design is easier to determine. It
> will be limited to the experimental design phase but it will be much
> better than what we have today. Then we can start focusing on a
> risk-based approach to GMP and CMC we now focus more on critical
> process control points rather than every step of the way.
>
> Clearly, as you move up on this knowledge pyramid, when you build more
> mechanistic understanding of processes that relate to performance and
> move towards first principles things change. But that is a major
> challenge. Our systems are often very complex in a physical and
> chemical sense so it is highly unlikely that we will reach first
> principles in most dosage forms. In some cases, like gases, yes, we
> could probably utilize thermodynamic principles directly but PAT sort
> of sets up a framework for improving knowledge in pharmaceutical
> manufacturing and improving regulatory decisions. So, that is one sort
> of learning that we have from the PAT subcommittee discussions.
>
> \[Slide\]
>
> Let me sort of spend a few minutes on risk and how does the agency
> address risk and how the agency can address risk under the PAT
> scenario. I have used the SUPAC classification of risk, level 1, 2 3,
> level 3 being the most severe risk. A concept that is prevalent in
> many different systems but I have used the GMP, which is an ISPE
> document on good automated manufacturing practices, version 4.
>
> Let me explain this. Impact on quality of a change or of a critical
> variable, if we judge that to be high, in the SUPAC guidance we sort
> of came up with general consensus on what impacts quality more. The
> SUPAC guidance says if you change magnesium stearate by more than
> such-and-such a percent then it is a major change. If you change
> lactose at that percent, it may not be a major change. So, we
> essentially have that in there. But what we do not have is a refined
> method of assessing risk likelihood.
>
> Keep in mind that the possibility of this likelihood or probability is
> the discussion here. Is it possible that a change or a manufacturing
> variable can impact quality and performance? Yes. Is it probable? We
> don\'t know unless we have better understanding. With PAT, as you move
> towards quality by design and systems based thinking, you can actually
> get a better handle on risk likelihood and, in fact, reduce that risk
> likelihood. What that can do is actually lower your risk
> classification under the SUPAC concept. So, something that is a level
> 3 change, if you reduce the risk likelihood to low you could move
> towards a level 2 change sort of a scenario.
>
> \[Slide\]
>
> Once you have reduced the risk classification, you can further have a
> better understanding if your risk priorities about where to put your
> resources and focus on by asking the question how does quality by
> design and systems approach improve the probability of detection of a
> deviation or a risky situation, with multivariate technologies we are
> talking about we can actually increase or enhance the probability of
> detection of a problem and, therefore, I think the PAT concept not
> only brings a higher level of sophistication to our risk assessment
> which is science based, by reducing risk classification we are also
> improving, increasing or enhancing the probability of detection. As a
> result, the risk priority where the agency could focus their risk
> situations would be lower. So, that is how I feel.
>
> I think the PAT subcommittee has been very valuable in sort of
> formulating this conception framework. As we move forward, the third
> meeting will give us the key aspects of computer system validation and
> some of the Part 11 issues that we need to address as we facilitate
> PAT introduction.
>
> One of the thought processes right now, and what we have done is to
> provide the subcommittee with all our current guidances on software
> validation which have been developed by the Center for Devices. I
> personally like those guidances because they are very straightforward
> and pragmatic approaches to software validation. My proposal to the
> subcommittee would be to take a look at those and see whether we can
> simply refer to that or adopt some of those so we don\'t have to
> reinvent the wheel.
>
> There are definitely issues related to software security, electronic
> signature, electronic batch records. We hope to get that information
> from companies and from the members of the committee on Wednesday.
>
> I am also very excited to share with you that two companies have
> submitted mock submissions for discussion on Wednesday. One is by the
> Bristol-Myer\'s PAT team. It is a wonderful example of
> crystallization, controlling crystallization on-line and sort of how
> does that relate to product quality. So, I am excited and look forward
> to discussing that case study with the subcommittee on Wednesday.
> Thank you.
>
> DR. LEE: Thank you. Ajaz, would you like to take some questions, if
> any? Are there any questions for Ajaz? Yes, Lem Moye?
>
> DR. MOYE: I was trying to think through this process and how
> biostatistics is involved in this. I guess I was plagued by something
> and plagues are probably at their most effective when they are shared
> so I am going to share it with you. That is, at least from my point of
> view, we are trying to administer a process we don\'t really
> understand, and we are trying to encourage the evolution of a process
> we don\'t really understand,1 and that is to say how a compound is
> manufactured from the beginning to the end, the ingredients, the
> quality of the ingredients, the blend of the ingredients. And, from a
> macro point of view I think we all understand how this is done, but in
> order to completely elucidate what the critical decision points
> are\--you mentioned the word optimization, that we ought to optimize
> this. I think we can\'t do it without understanding it. I think that
> is one of the points you made in one of the latter slides that you
> provided.
>
> I guess it is a curiosity to me, and I don\'t expect anybody to answer
> it for me, how the pharmaceutical companies have managed to escape
> full elucidation of this. If you look at the petrochemical industry,
> that is clearly understood, what they do and also to some extent the
> nuclear industry is clearly understood. Yet, the circumstances we are
> in now are different. So, this is a question that was too hard for me
> to answer so what I usually do is speak to some people who are smarter
> than I am.
>
> So, I spoke to some people in chemical engineering and engineering in
> general and they made the following recommendation that I just want to
> pass along. That is, why not begin a process that has been very useful
> for these alternative fields, and that is one of simulation?
> Simulation techniques now are far superior than they were twenty-five
> or thirty years ago and I think we would get two things from that.
> Number one, we would understand the process. You cannot accurately
> simulate something that you don\'t understand, and the process of
> simulation would require us to begin or to continue to ask the
> questions that we need to ask to understand this. What information are
> we missing to full1y understand this, number one?
>
> Number two, the output from simulation allows you to identify new
> critical points that perhaps weren\'t so obvious from the macro view,
> and also allows the opportunity for further optimization of the
> process.
>
> You talk about you can\'t use a univariate approach, it has to be
> multifactorial and another that I heard is polyfactorial, that all
> suggests to me that the parametric approach\--we are a little too
> immature in our understanding of this entire manufacturing process to
> be able to come to grips with it from a parametric approach. So, given
> simulation tools are becoming increasingly useful from petrochemicals
> right up to NASA, why don\'t we consider using those here?
>
> DR. HUSSAIN: I have a slightly different perspective. I think you
> mentioned that systems are not well understood and so forth. There are
> two aspects to that. One is what is available from a regulatory
> perspective and decision-making? Companies, when they develop their
> formulations and processes do validation. They do extensive
> optimization. But often that information is not fully shared by the
> agency. So, the agency view of that is in absence of all that
> available information. So, I am not sure I fully agree with the
> concept that the systems are not understood because we have been
> manufacturing and establishing this for years.
>
> What is missing is the ability to communicate the optimization
> strategies to the regulatory authorities, more so than anything else.
> As we sort of move forward I think we are opening up channels for
> further communication and bringing more of these data into a
> decision-making process which will sort of help the agency conclude
> the optimization aspects that industry itself has done.
>
> The other aspect I think is that in many ways the pharmaceutical
> dosage forms are far more complex. When you deal with solids, physical
> chemical systems, understanding and using simulation tactics for that
> is far more difficult. I think petroleum would be a very simple system
> to simulate compared to pharmaceuticals. So, I think we have to, in a
> step by step fashion, sort of proceed and sort of bring some of this
> knowledge in.
>
> DR. MOYE: Well, let me ask you directly. Do you think simulation is an
> admissible procedure even though it is more complicated than in the
> petrochemical field? And, I will accept your representation of that.
> Do you think it is an admissible strategy?
>
> DR. HUSSAIN: In fact, I have been looking at that very question with
> respect to fluid dynamics and how some of that can come in. At some
> point, I think as we make progress eventually there will be a role for
> that. I am looking at Ken Morris who has recently published in two
> publications in this area. One was sort of modeling the blending
> operations and predicting what the blending conditions should be for a
> higher scale, and so forth. So, there is already a lot of progress.
> When will that become valuable from a regulatory perspective? In due
> course of time I think we will move in that direction.
>
> DR. LAYLOFF: I would like to reinforce that. You are dealing with a
> very heterogeneous system and in the process stream you have particle
> size ranges; differences in density of the various particle portions
> of the stream. When you start talking about moving to fingerprints and
> signatures it means that you really can\'t identify all those
> dimensions when you try and move back statistically to a more
> behavioral type approach to it rather than a quantitative simulation.
>
> DR. MOYE: Again, I don\'t deny it is complicated. I mean, it is one of
> the reasons we are here talking about it. I just think that simulation
> procedures and algorithms have evolved far beyond what they were even
> fifteen or twenty years ago and that there may be an aspect of that
> that would be worth including in a simulation. Also, simulations are
> evolving. The first models are going to be clumsy and cumbersome but
> as experience grows, as expertise grows, as the modeling tools get
> more sophisticated you will get some useful output if sincere effort
> is put into the model.
>
> DR. LEE: Yes, I do agree that simulation has a role. I think it would
> really put how much you know to the test. If it doesn\'t fit, that
> means that we don\'t understand. As little as I understand the
> process, I think PAT appears to make the entire process more
> transparent; that you have lots of information. In fact, I don\'t know
> why can\'t you shut down the process if you are willing to set some
> specifications along the way? I guess for PAT, as I understand it, you
> collect information as you go along and you can anticipate the range
> which you can tolerate. Can\'t you just say, okay, this is how much I
> can tolerate and then if there is any venture outside these boundaries
> then the process should shut down.
>
> DR. HUSSAIN: It is possible, yes.
>
> DR. KIBBE: Let me inject. I think in the evolution of any technology,
> and our industry is relatively old in a lot of respects and, quite
> honestly, I was pleased to see that we recognize that manufacturing
> came out of compounding and didn\'t come out of direct application of,
> say, the petrochemical industry\'s way of processing. We are in the
> process of moving incrementally forward. I think the application of
> models to the system is useful, but I think the original models that
> we come up with will be oversimplifications and will gradually
> iterate.
>
> We are looking at PAT now, whereas the next iteration in our ability
> to control very complex systems\--and we don\'t need to know every
> aspect of the complex system well to be able to get to an endpoint
> that is useful and viable. It is almost evolutionary in that we are
> going from end-stage testing to in-process testing which is the
> direction of practically every industry over the years. Quite
> honestly, a lot of what we have done in the past has been almost
> superstitious in the way we have done it. We have made a good tablet
> this way; we are not going to make it any other way because that is
> the way we made a good tablet.
>
> There is a wonderful example from Samurai sword-making which is made
> under an extremely ritualistic method because they didn\'t understand
> metallurgy but they knew if they followed every single one of these
> steps they ended up with a wonderful sword. Well, as we get more and
> more in depth either through direct measurement with some of these
> more sophisticated in-process tools or the application of more
> sophisticated modeling, I think we are going to be improving
> continuously.
>
> What I see here, which is more important than all of the science and
> all the technology, is an opening of a window and a reduction in
> suspicion between the regulatory agency and the regulated industry on
> making improvements in process control and in end-product quality. In
> the past I think we have seen real reticence to improve products at
> all and you see some wonderful examples in the industry of products
> that are being made today the way they were made in 1932 because no
> one wants to come forward and improve the product for fear of what
> that means in terms of the marketplace and the regulation of the
> product. I think what we have done here and what I think Ajaz and
> Helen have tried to do and what the industry has responded positively
> with is moving away from that old \"heels dug in\" process that we had
> into this.
>
> First, I agree with your concept of putting models to it. I think it
> is going to be iterative. We are going to have information. We are
> going to put models to it. Those models will work in some cases;
> won\'t work in others. We will get more information out of the models.
> We will get more information out of what we call fingerprinting and
> together the whole process will move forward. As long as we maintain
> the open dialogue between the regulators and the regulates, I think we
> have a good shot at it.
>
> DR. LEE: Judy, would you like to say a few words?
>
> DR. BOEHLERT: I would just like to make a comment. Another area where
> I think we are going to improve the way we look at processes is
> improving the way we look at the input to those processes which are
> the raw materials. Right now we look at the active ingredient and we
> do a pretty good job there but not perfect because we are looking at
> polymorphism at this meeting. But excipients is a very big issue where
> there hasn\'t been a lot of attention, particularly to physical
> properties. We do the testing that is in the Pharmacopeia and say,
> okay, we are done. I think the PAT approach is going to force us to
> take a much closer look at those raw materials and control them better
> than we have in the past, and that is an evolving area and many people
> are looking at it but we are not there yet.
>
> DR. LEE: Leon?
>
> DR. SHARGEL: Yes, I have a couple of comments, perhaps related but
> looking at it a little differently. I think the PAT is quite
> interesting. However, from the point of view of older or previously
> approved drug products, when we have new technology we often have new
> standards and new tests for things that might not have been noticed in
> the original manufacturing process.
>
> So, the first question is how will these PAT effects or new standards
> be affecting older products that are already manufactured? The second
> is that we often have some products that are probably low volume. By
> that, I mean only a few batches per year are manufactured and the cost
> of PAT is going to be high for those small manufacturers who are
> making smaller volume product. If the cost is very high and regulatory
> impact is high, then there will be a loss of these products to the
> marketplace. So, I am wondering if the agency or anyone has considered
> these issues.
>
> DR. HUSSAIN: Well, I think with respect to the PAT we were very, very
> clear that this is not a requirement for anybody. This is simply for
> companies that have the know-how, that have the technology but are
> hesitant to apply and utilize, this would benefit that. Eventually, I
> think in the short-run or in the very near future what we hope is that
> maybe a few handfuls of companies will move in this direction because
> we are not planning for everybody to do this. As the knowledge and
> information grows, I think if this makes business sense everybody will
> move in that direction automatically if it makes business sense.
>
> There are two incentives that we are trying to sort of provide. One is
> what we are calling a safe harbor concept. The term safe harbor may
> not be in the guidance but a research exemption type of a term will be
> there. What it simply means is that the current products, as being
> manufactured and released, are fit for intended use. We have approved
> those. So if you identify problems when you use the new technology,
> that is not going to negate those products anyway. And, we have
> learned with any new technology, like HPLC and so forth, how to manage
> that. So, that is not a major challenge from one perspective.
>
> The other aspect was that in many ways we are sort of changing the
> paradigm here. In fact, the argument you posed was for some slow
> volume products and that this may be a problem. You don\'t have to do
> it for the low volume products to start with, but I think a better
> answer to that is that I think we can actually move to miniaturization
> of the manufacturing process in a continuous mode. There are some
> wonderful experiments being sort of proposed. I can\'t mention the
> company but it actually goes to a continuous manufacturing mode and
> the entire manufacturing unit would be on a desk top sort of thing.
> So, I think the paradigm will shift and the shift will keep occurring
> in all aspects. Tom?
>
> DR. LAYLOFF: I was going to say that when we looked at the PAT
> technology there was always the question as to whether it was tied to
> a process step or a product step because the signature is a product
> step but the technology itself is a process step. You link it to a
> process rather than a product. So, if you start looking at a process
> you can put the PAT technology in and then, of course, it doesn\'t
> care what product it is looking at because you establish signatures
> for the range that you are doing. It has nothing to do with volume. It
> is concerned with how you monitor a process step rather than a
> product.
>
> DR. SHARGEL: I understand the idea of the process. The thing is if you
> have a product that is not large and you want to now use a new
> technique to look at the process, that becomes a business decision
> whether you want to move to the new approach or continue with what has
> been useful. However, as we have new processes we often have new
> standards and then, again as you are saying, whether you are phasing
> in new and older standards, as sometimes happens, that impact then the
> versatility of the new process whether it is dedicated to a large
> volume product may not be as easily done where you are using a tablet
> press for two or three different products every six months, or
> something. So, these are some of the issues to look at.
>
> DR. MOYE: Can I respond to that? I take your point but it doesn\'t
> have to be a total loss for a small company to assume this new process
> paradigm. For example, there may be some identification of a new
> optimization procedure that would allow for more cost efficiency, and
> a low volume producing agent could take advantage of that and also the
> product might be safer. So, there may be some definite advantages to
> the switch even though there might be increased cost in the short
> term.
>
> DR. LEE: Efraim?
>
> DR. SHEK: I want to address my comments to what Judy was talking
> about, the excipients. They are very, very critical, you know, and
> today I don\'t think we have a good way to handle it. Some of the
> aspect is basically getting a partnership with the excipient
> manufacturers. Basically, I think our business as a pharmaceutical is
> a small part of it and that is an economical fact and reality, and
> changes in those excipients are really affecting any optimization or
> even simulation that, you know, we have done before.
>
> I am intrigued by the simulation aspect. I talked with chemical
> engineers, and looking at, let\'s say, the most economical process to
> make solid doses or tablets, I don\'t think today, as far as I know,
> there are good models to even do a scale-up. So, you can optimize it
> in a small scale and then you start all over as you increase. There
> has to be a way to model and predict basically what you expect to be
> happening.
>
> The other aspect which we have to take into account is that today the
> investment over the years for equipment and unit operating processes
> is extremely expensive. I believe there are better ways to make
> tablets with other forms which will be predictable as well as you
> predict for making liquids, where I think we have models today. But
> this is a tremendous not only product shift but an economical shift to
> replace the equipment that we have today. So, at least I look at the
> PAT as a way to collect a significantly huge amount of data and maybe
> with this data you can go to the next step and understand the process
> better and take the next step.
>
> DR. LEE: Well, now you hit on a very important point. You said you
> have lots of data, lots of information. Can you share it? I hope it
> can be shared.
>
> DR. HUSSAIN: I think there are sort of three points that I wanted to
> respond to, if I may. One, I think the simulation aspect is a
> wonderful sort of step towards, you know, the first principle of
> getting into that and I think that will be the goal of sort of
> bringing the knowledge of pharmaceutical manufacturing to such
> quantifiable and predictable model. Essentially, I think that is all
> of our dream anyway. I think I fully support that. I just want to make
> sure that my comment did not come across as not supporting that.
>
> Efraim raised several issues. One was the issue of excipients and he
> pointed out that the pharmaceutical volume is a fairly small volume,
> and the suppliers of these excipients apply to a much larger volume
> and if we start, you know, sort of making more requirements on these
> excipients, then either they won\'t sell it to us or the prices will
> sort of go up. So, that definitely is sort of one concern.
>
> But in the PAT concept, if you really look at it, in a sense it allows
> you to handle the variability associated with the incoming raw
> materials in a different way. You have two options. One option is to
> apply stringent incoming raw materials specifications and not use
> materials that do not meet all the physical attributes. That would
> sort of add to the cost but, at the same time, you could actually say
> I will simply use USP NF sort of criteria and the physical attributes
> that are different lot to lot, I will manage that with a process which
> will be flexible enough to adopt that. So, that is the concept the PAT
> sort of brings in, that is, you will blend until it is uniform rather
> than blend to ten minutes because blend to ten minutes assumes that
> your raw materials are similar all the time. So, if you blend until it
> is homogeneous you can accommodate certain variabilities that are
> inherent in your starting raw material.
>
> That is the reason I felt that, instead of moving towards a
> functionality test and requiring those in the USP, you may just manage
> the variability in more intelligent ways with the processing
> technologies that are currently available. So, that was sort of one
> aspect.
>
> DR. LAYLOFF: I don\'t think the excipient industry is going to create
> a standard for the pharmaceutical industry, but I think that you can
> establish robustness on the signature or fingerprint to have a control
> which allows that variability because you define a certain fingerprint
> and you could have robustness on the critical control points.
>
> DR. LEE: Toby?
>
> DR. MASSA: Ajaz, you and I have talked about this many, many times. I
> think for PAT to have acceptability within the industry\--I still
> don\'t think it is clear to a lot of us in industry how this will
> impact development and validation. It is being discussed with a
> smaller group of people and I think for this to have universal
> acceptance, since it has been discussed that PAT will change our
> concept of validation as we know it today, and I truly believe that
> based on everything I have heard, I think we have to be broader in the
> message that we are sending to industry. It is not clear to industry
> as a whole how this will impact validation as we know it today.
> Validation really has two meanings depending on whether or not you are
> talking about the European concept of validation or the U.S. concept
> of validation. So, I think that is the first thing that really needs
> to be addressed.
>
> The other thing, and it is tied to that, is that we need to make it
> clear how all of the data will be handled under Part 11. Part 11 is an
> extremely burdensome regulation on industry and there is a study that
> PhARMA will be releasing in the not too distant future that shows that
> the cost impact of Part 11 to every company is over 100 million
> dollars to make their systems to be totally Part 11 compliant. We have
> to make it clear what the safe harbor is going to be for all the data
> that the computer systems that are going to handle all of the data
> that will be generated on Part 11.
>
> So, I think those two things really need to be made clear. I know that
> is still evolving but before PAT is going to get the acceptance that
> we want it to have and the impact that we want it to have those two
> things really do need to be delineated for industry.
>
> DR. HUSSAIN: Well, in terms of the first comment, the message not
> reaching a wider audience, we hope that the future workshop that we
> are planning as well as the GMP initiative could be an example would
> sort of start highlighting some of the advantages and how this will
> impact on validation, the review and so forth.
>
> The second point you made with respect to Part 11, I think we
> understand the challenge ahead and we are starting to sort of focus
> our discussion on those very topics on Wednesday. At the same time,
> what the GMP initiative has done is move responsibility of Part 11 to
> CDER now. So, that gives us a better handle on looking at the PAT and
> those issues and coming to something more rational that is conducive
> to innovation and new technology. So, that is a significant challenge
> and we hope to start addressing that soon. I don\'t have an answer
> today for you.
>
> DR. KIBBE: A couple of things that came out of some of the other
> comments\--I don\'t want to drag on this discussion interminably but,
> first, PAT is going to give us, I believe, a much tighter
> understanding of the variability of the system. I think some people
> worry that that will mean a higher cost to control those variables,
> and we need to keep clear that if there is variation but if it is
> livable, even though it is statistically significant it isn\'t
> clinically significant we can still live with it. I mean, the cost
> benefit of cleaning it up or not cleaning it up has to be worked out.
>
> I think PAT is going to give us an opportunity to go to almost
> batchless manufacturing. With batchless manufacturing validation of
> the process can be measured in terms of how many days does the process
> run smoothly rather than how many batches do I have to manufacture.
> Then, if we go to batchless manufacture, if we go to a complete flow
> process manufacture, then perhaps we can validate on the same
> equipment that we are going to use continuously because the amount of
> output is going to be 24 hours a day, 7 days a week and, instead of
> having to scale up from a batch of a 200,000 tablets to a batch of 10
> million, we just turn the process on and let it keep rolling and when
> it starts to vary outside of the parameters we have set for it, then
> we make corrections to it. I think it is going to save companies a lot
> of money, and I think companies can look at smaller, more efficient
> production lines, smaller, more efficient continuous processing from
> beginning to end.
>
> Also, I don\'t necessarily agree with Tom on our excipient suppliers.
> We might not be their largest buyers but we are a significant
> purchaser and if there is going to be an improvement in what we can
> do, if they will improve what they do then the negotiated cost back
> and forth between what it costs us to get it and what it costs them to
> do it we might actually get some tighter controls on some of the
> excipients. I am thinking in terms of compressible excipients and
> things like that.
>
> So, I see this down the road as a real win-win situation not only for
> the manufacturers but the end users and even for the suppliers who
> have an even better idea of what they need to supply and how to do it.
>
> DR. LEE: And I think certainly for the American public. Well, I think
> it is a very interesting subject. We can go on forever and certainly
> this is a concept like the early days of software, and I hope that we
> see wonderful things happening with that. Anybody else want to say a
> few words about the PAT before we take a break? We are way ahead of
> schedule but I am kind of worried about the afternoon. I propose that
> we take a break and reconvene at about 10:35. Thank you.
>
> \[Brief recess\]
>
> DR. LEE: So far we have had a very good discussion and now we will
> introduce the section on other updates, risk-based CMC review. Is Dr.
> Chiu available?
>
> **Other Updates**
>
> **Risk-Based CMC Review**
>
> DR. CHIU: I will need technical support. Good morning.
>
> \[Slide\]
>
> Dr. Vilayat Sayeed and I will give you an update to the CMC risk-based
> review. This is a project initiated in the year of 2000.
>
> \[Slide\]
>
> As you recall, the project is actually looking at performing CMC
> reviews based on risk of the product, based on product quality risk.
> At the time we proposed this we were looking at the products and tried
> to find out the attributes and also the acceptance criteria to define
> a product as low risk. Then, if we compiled a list of drugs which
> should be considered low risk, then we will have reduced CMC oversight
> with respect to information submitted to the agency. Perhaps we will
> eliminate most of the supplements to the NDA and the ANDA. What would
> be left would be mainly the changes described in the law. We will
> reduce the CMC information needed to be submitted to an original ANDA
> and to the annual report of an approved NDA and ANDA.
>
> \[Slide\]
>
> Over the years, since the year 2000, we have had a number of internal
> discussions. We brought the topic to the CMC, to the components
> coordinating committee meetings. We had internal scientific rounds. We
> had many meetings among the reviewers. We also brought this topic to
> this committee twice, once in November, 2000 and in July 2001. There
> was an AAPS workshop. Through those meetings we received many useful,
> constructive comments.
>
> \[Slide\]
>
> This project is a three-tier process, as you know. The first tier
> includes two steps and we are in the first tier. The first one, step
> A, is to establish attributes and acceptance criteria which we can
> used to define a low risk drug. We are going to issue a draft
> guidance, hopefully early next year, to define the attributes and
> acceptance criteria. We will then have public comments. After that, we
> will finalize the guidance and based on the attributes and criteria we
> will propose a drug list which will be considered low risk with
> respect to quality. We will publish that list as a draft. Then we will
> have comments from the public on whether that list is realistic,
> whether other products should be on the list, whether some products
> should not be on the list.
>
> After receiving the comments, then we will finalize the drug list
> after internal medical consultation. That is tier two, which is the
> medical safety evaluation. Once we finalize the list, then
> applications for those drugs considered low risk will have less FDA
> oversight. However, whether a company will be eligible for that
> privilege will be based also on their GMP compliance history. So, that
> is tier three.
>
> \[Slide\]
>
> We talked among ourselves about the general principle for the final
> list drugs. In this diagram, on the Y axis is the probability of
> detecting product defects or criteria attributes. When you have a high
> probability of detection, then the risk is low. When you have a lot
> probability of detection the risk is high. On the X axis is the
> complexity of the drug substance, drug product characterization. So,
> simple molecules would be considered low risk and macromolecules,
> complex molecules or complex dosage forms would be considered high
> risk. It also depends on the complexity of the mechanism of product
> performance. If it is simple immediate release, it would be low
> dosage, low risk. If it is targeted release, then it could be high
> risk. It also depends on manufacturing technology. So, a simple
> synthesis would be considered low risk. However, maybe formation of
> recombinant cells, formation of liposomal products would be considered
> high risk.
>
> We are actually looking right now at this high probability of
> detecting and low complexity as low risk products. I believe, you
> know, in the future when we gain experience with this project and also
> ways for implementation of on-line or in-line testing we will be able
> to expand this area. The medium and low risk area could be shrunk. So,
> this is what we are working on.
>
> \[Slide\]
>
> We formed two working groups to look at the drug substance
> characteristics with respect to attributes and acceptance criteria,
> and we have another subgroup working on drug product. Now, you know,
> we are more or less in the stage of finalizing the draft guidance and
> soon it will be out for internal comment. Dr. Sayeed will describe to
> you our current thinking. So, without further ado, Vilayat.
>
> DR. SAYEED: Good morning, everybody.
>
> \[Slide\]
>
> Yuan-yuan has basically explained the objectives and other aspects of
> this initiative so I am going to go right into what we have done for
> to how to achieve this objective.
>
> \[Slide\]
>
> What I am going to do, I am going to present the drug substance and
> drug product decision trees which we have developed for identifying
> low risk candidates. These trees were developed by the general
> principle which was discussed as to the probability of detection and
> the complexity, and I am not going to go into the details of this
> chart. The focus of the working group was to find or identify drug
> substances and drug products which would fit into this box, here,
> where the failure for the probability of detection is high and the
> complexity is low.
>
> Having this principle in mind, the first question which was raised for
> the drug substance was what drug substance would actually fit into
> these criteria. The general consensus in the working group was that a
> synthetic drug substance and simple inorganic salts would actually
> meet these criteria.
>
> \[Slide\]
>
> So, the first question on the slide on the drug substance decision
> tree is, is the drug substance of synthetic origin or a simple
> inorganic salt? If the answer for this is no, then this drug substance
> is not suitable for low risk consideration. If it is, then you move on
> to the next level.
>
> At this level there are certain exclusions. The question was raised
> can all synthetic drug substances fit into this concept? The answer by
> the working group was no, not every drug substance would meet this.
>
> \[Slide\]
>
> On this slide certain exclusions are included. Here are the
> exclusions. If a drug substance happens to be a radiopharmaceutical, a
> peptide or an oligonucleotide, then if the answer for this is yes,
> this drug substance cannot be considered for low risk; and if it
> isn\'t, then you move on to the next level.
>
> For the next level we have addressed issues relating to the drug
> substance characterization, its specifications and its stability
> issues. The question here, at this level is, is the drug substance
> well characterized, and are the specifications used to control the
> drug substance contemporary, and is the drug substance stable at
> ambient conditions? If the answer for this is no, it is not, then the
> consensus in the working group was that the drug substance is not
> suitable for low risk consideration. If the answer is yes, then the
> drug substance is a suitable candidate for the low risk assessment.
>
> \[Slide\]
>
> Here you see a little box. What we have done here, we have identified
> that if there are any physical characterization issues with regard to
> the drug substance. These issues will not be considered at this level,
> whereas these issues will be moved on and considered at the drug
> product level. So, if there are any physical property issues with the
> drug substance, those issues need to be identified in the drug
> substance and will be considered in the assessment of the drug
> product.
>
> \[Slide\]
>
> With the baseline established, the first question asked for the drug
> product is, is the drug substance assigned as a low risk? If the
> answer is no, if it is not there, then the drug product is not a
> suitable candidate for low risk consideration. If the answer is yes,
> then you move on to the next level.
>
> \[Slide\]
>
> At this level what we have done is we have identified certain dosage
> forms which the working group thinks will fit into that general
> principle where the probability of detecting a failure is high and the
> complexity of the product is low.
>
> \[Slide\]
>
> These drug products were identified as IR oral solids or topical
> liquids or sterile solutions of simple solids. So, this is what we
> think are drug products or dosage forms which would fit into this
> general principle concept. If the answer for this is no, then the drug
> product is not a suitable candidate for low risk consideration. If the
> answer is yes, then you move on.
>
> The same question was raised in the working group whether all IR
> solids and liquids will fit into these criteria. Obviously, the answer
> was no. So, we have included some qualifiers on the next slide.
>
> \[Slide\]
>
> The qualifiers are for the solids. We are saying is the strength per
> unit at least one milligram or one percent by weight? If it is
> anything less than that, we think it is not a suitable candidate. For
> the liquids we are not using the strength; we are using the solubility
> ratio, the intrinsic solubility ratio. We are saying if it is not less
> than 1:30, then it may not be a suitable candidate. If the answer for
> this is no, then the drug product is not a suitable candidate for low
> risk consideration. If the answer is yes, then you move on and look
> into other aspects of the drug product.
>
> \[Slide\]
>
> On this slide what we have done is we have looked into the interaction
> of the drug with the excipient. What we are saying is if there are any
> known interactions reported, if there are reported interactions
> between the drug and the excipients, then this product may not be a
> suitable candidate for this CMC low risk assessment. If the answer for
> this is yes, then the drug product is not a suitable candidate for the
> risk assessment. If the answer is no, then you can move on to the next
> level.
>
> \[Slide\]
>
> At this level what we have done is we have looked into the physical
> property of the drug substance, which we have left open on the drug
> substance tree and this is where we are capturing that part. We are
> saying if there is a reported impact, like if the physical properties
> of the drug substance are known to have some impact on the product
> performance, then this drug product may not be a suitable candidate
> for this low risk. Are the differences in the physical state of the
> drug substance reported to have an impact on the performance of the
> product? If the answer for this is yes, then you are saying the drug
> product is not a suitable candidate for low risk consideration. If the
> answer is no, then you move on to the next level.
>
> In the following few levels, what we have done is we have captured the
> aspect of the product specifications, product stability, product
> degradation and packaging and storage, and all of those things are
> covered in the next few levels.
>
> Here we are saying if the drug product meets the contemporary
> standards, you know, if the answer for this is no, then the drug
> product is not a suitable candidate for low risk consideration. If it
> is yes, that you do have product specifications which conform to the
> contemporary standards, then you move on to the next level.
>
> \[Slide\]
>
> At this level we are capturing the stability and the degradation of
> the product. We are saying do you know if the degradation of this
> product is predictable and if the degradants are controlled? So, the
> question is, is the drug product degradation profile predictable and
> are the degradants controlled? If the answer for this is no, then the
> drug product is not a suitable candidate for low risk consideration.
> If the answer is yes, then you go on to the next level.
>
> At this level we are capturing the product storage and packaging. What
> we are telling here is that for now we will only consider products
> which are stored at controlled room temperature and which do not
> require any special packaging. If the answer for this is no, then the
> drug product is not a suitable candidate for low risk consideration.
> If the answer is that, yes, it doesn\'t have those, then you move on.
>
> \[Slide\]
>
> At this level we are capturing a little bit of product history. We
> think we need to know at least a couple of years of real-time
> stability of the product on a minimum of three commercial batches for
> the product to be placed in this program. So, if the answer for this
> is no, then the drug product is not a suitable candidate for low risk
> consideration. If the answer is yes, then you do have a product which
> qualifies as a candidate for low risk assessment.
>
> \[Slide\]
>
> In conclusion, I would like to acknowledge the individuals who have
> spent a lot of time and effort in developing these trees. Thank you.
>
> DR. LEE: Thank you. Gloria?
>
> DR. ANDERSON: Would you comment on your definition of complexity?
> Based on what you said about single synthetic components, something to
> that effect, I am trying to get a picture of how big a molecule would
> be, if that is how you define complexity as opposed to some smaller
> molecule with a really horrible function group on it.
>
> DR. SAYEED: We are not going to functional groups. Did you want to
> comment on that?
>
> DR. CHIU: Yes, we are not going to base on molecular weight of the
> molecule. What we are going to base on is how easy it is to
> characterize the molecule. If one can use appropriate standard
> methodologies such as IR, UV and MR, and element analysis, then it is
> considered well characterized. When we talk about macro protein
> molecules, even with those tools you cannot characterize them. When we
> talk about single molecules, because sometimes you have combination
> products; you have two or three drugs at the same time and you may
> have multiple active ingredients, we will not consider that, you know,
> simple.
>
> DR. ANDERSON: I understand that but is it possible you could have a
> compound, a molecule that is easy to characterize, that can be well
> characterized and have a really bad functional group on there that
> could put it in another category? That is really what I am talking
> about.
>
> DR. CHIU: That would be caught by the other criteria in terms of
> stability, if you have degradation products whether you would detect
> that. So, the specifications and the stability will catch your
> concern.
>
> DR. ANDERSON: So this is the first step here.
>
> DR. CHIU: Right.
>
> DR. ANDERSON: Okay, thank you.
>
> DR. CHIU: Yes, the first step.
>
> DR. LEE: So, I guess everything is relative.
>
> DR. CHIU: Because there are three elements you have to fit all three
> elements together to be considered low risk.
>
> DR. LEE: I see.
>
> DR. CHIU: So, it is not either/or.
>
> DR. SHEK: A couple of quick questions. I will start from the end. The
> last one says are there at least two years real-time stability data.
> My question is does that apply to NDAs as well as ANDAs, this decision
> tree?
>
> DR. SAYEED: Yes, this decision tree applies to all applications
> basically.
>
> DR. SHEK: So, by definition, two years data wouldn\'t apply for NDAs?
>
> DR. CHIU: No, the idea of three years data does not mean the specific
> product from a single company. It means whether you ever have two
> years data for that drug, regardless who makes that.
>
> DR. SHEK: Right, but if it is a new chemical entity and an NDA is
> being filed, by definition it wouldn\'t fit into this category. Right?
> So, a new chemical entity will never be able to through this decision
> tree.
>
> DR. CHIU: Well, not necessarily because some NDAs do have more than
> two years stability data in the file.
>
> DR. SHEK: On commercial batches?
>
> DR. CHIU: Yes, because not necessarily are all NDAs first time around
> in this country. You know, occasionally we get NDAs with batches from
> Europe but those will be rare. So, I think you are right, most of the
> time a molecular entity may not fit as a low risk, but occasionally
> will. Most ANDAs will be qualified so that is why we proposed this
> truncated ANDA.
>
> DR. SHEK: If we go up the tree will we come out with a definition of
> what are contemporary standards?
>
> DR. CHIU: Yes. Yes, in the draft guidance we will explain what is
> contemporary standards. We propose mainly following ICH or FDA
> guidance.
>
> DR. SHEK: And if we go to the top of the tree, I think this is just
> the CMC aspect, and maybe it was there and I just missed it, but will
> there be any evaluation even before that of whether there is a
> therapeutic index?
>
> DR. CHIU: Yes. That would be the second tier, the medical
> consultation. Yes, there we would look at the safety and the medical
> risk.
>
> DR. SHEK: And that will happen first?
>
> DR. CHIU: That will happen after we propose the list of drugs. Then
> the medical people can look at those drugs and decide.
>
> DR. SHEK: Thank you.
>
> DR. LEE: Art?
>
> DR. KIBBE: Just a couple of questions. The question I have is about
> drug excipient compatibility issues. If there are known excipient
> compatibility issues but the product in question doesn\'t contain that
> excipient, and most good manufacturers would try to avoid excipients
> where there is a problem, then it would still be no? Even though there
> was a known issue with a different excipient, the product would not
> pass?
>
> DR. CHIU: No, no, that is not the case. We are talking about the
> excipients used in the product.
>
> DR. KIBBE: Right, not just that there is an issue.
>
> DR. CHIU: No.
>
> DR. KIBBE: I noticed that if they have a milligram or less than one
> percent they are not considered low risk, which means that all
> homeopathic remedies are high risk and we should start to evaluate
> those!
>
> \[Laughter\]
>
> I just throw that out. The question I also have is would you accept a
> petition from a manufacturer for exception based on data they have
> that would answer the issue on any one of these decisions?
>
> DR. CHIU: We will issue a draft guidance to explain all those
> criteria, and we will get input from manufacturers and from the public
> and then we will finalize that. I also said we will propose a drug
> list and then we will seek comments from outside. At that time the
> pharmaceutical companies can propose drugs which are not on our
> proposed list. In the future, when this is finalized, we will continue
> to accept petitions from companies if they have, for example, improved
> their specifications; they now have contemporary specifications so
> they should be included in the list. We will continue to revise our
> list of drugs.
>
> DR. KIBBE: Thank you.
>
> DR. LEE: Judy?
>
> DR. BOEHLERT: I have a few questions. In the drug substance decision
> tree you say that the drug has to be stable under ambient conditions.
> I am wondering if you are going to define what you mean by that
> because stable is in the eye of the beholder, and what do you mean by
> ambient? ICH conditions?
>
> DR. CHIU: Yes, ICH conditions. We really mean ICH conditions. If you
> store under ICH conditions and it shows that it is stable.
>
> DR. BOEHLERT: Stable means meets requirements?
>
> DR. CHIU: It means it meets the specifications.
>
> DR. BOEHLERT: Right now it doesn\'t really say that. The other issue
> that you talk about are physical properties. The way it sounds now is
> that if you need to set a specification for a physical property, such
> as particle size or maybe even polymorph, then it would automatically
> not qualify for this treatment and I am wondering why\--
>
> DR. CHIU: No, no. I don\'t think that is the case.
>
> DR. BOEHLERT: That is what I heard.
>
> DR. SAYEED: What we are trying to say is you identify those
> characteristics in the drug substance but those characteristics will
> not be used in saying whether this drug substance is high risk or low
> risk. What we are going to do is what kind of impact those
> characteristics they will have on the drug product performance.
>
> DR. BOEHLERT: Well, say they do have an impact on drug product
> performance but you have contemporary specifications; they are
> controlled; you know what they are and they are controlled in every
> batch, why would that change things?
>
> DR. CHIU: I see.
>
> DR. SAYEED: That is a good thing because again we go back to the level
> of controls we have. I mean, at least for now we want to deal with
> things that are just straightforward and simple. We don\'t want to get
> into how much control we can have on each company and each product.
> So, for now we want to keep it simple and maybe as time goes on and we
> learn more about it we can move into that area of you have the control
> so you can go ahead and use it.
>
> DR. BOEHLERT: If you don\'t want to use the term contemporary
> specifications because I have applied some of these newer controls
> such as\--
>
> DR. SAYEED: I mean, most of these things may have the controls but we
> are saying even if these controls happen to have any effect on the
> performance, then we will not use it. That doesn\'t mean that you are
> not going to control it; you control it but you can\'t use that drug
> substance.
>
> DR. CHIU: The proposal right now is that we would like to be rather
> more conservative at the beginning so we will take comments. If people
> strongly believe this is well controlled and they should be on the low
> risk drug list we will consider that. But at this time, you know, we
> just want to be rather more conservative.
>
> DR. LEE: We will take two more questions, so Marv and then John.
>
> DR. MEYER: The one milligram as a cut-off point, how was that selected
> and what will you do with multiple strengths, say half a milligram and
> a one milligram tablet? Where will it fall?
>
> DR. CHIU: The reason we picked one milligram is because we thought
> that for blend uniformity there may be issues so we thought it may not
> be considered a risk. I see your point about multiple doses and we
> haven\'t discussed that. Maybe we will go back to think about when
> there are multiple doses.
>
> DR. MEYER: Any idea how many drug products will fall into the low risk
> category?
>
> DR. CHIU: Actually, it is very difficult to come up with physical
> attributes or chemical attributes so we asked our reviewers, based on
> their review experience, which drugs they consider to be really,
> really low risk, and we actually obtained something like 60 drugs.
> Then we went back to look at more than 300 applications and based on
> that data mining we came up with those criteria. So, I believe we
> will, you know, have many more than just 60 drugs.
>
> DR. MEYER: I would caution you that the reviewer system didn\'t work
> very well in picking up drugs with a high risk for therapeutic
> problems in the generic field. You had some very strange drugs on that
> list.
>
> DR. CHIU: That will be the next tier. The second tier will look at the
> medical safety. So, right now we are just looking at the physical
> characteristics, chemical characteristics. But we will take into
> account the medical safety.
>
> DR. LEE: John?
>
> DR. DOULL: I would like to go back to the excipient issue. You said
> that the yes/no question for excipients was whether they interacted
> with the active ingredient, drug. How about the inherent toxicity of
> the excipient? That is not part of the consideration? In other words,
> you could put a drug in a low risk category even though it had a
> highly toxic excipient. Is that true?
>
> DR. CHIU: Well, the toxic excipients will be studied during your NDA
> stage and the safety data to assure that the excipients used are not
> toxic. When you have an ANDA the review process will also catch toxic
> excipients. So, I think that probably will not be an issue.
>
> DR. DOULL: I was just concerned that if that is the criteria, then it
> omits the toxicity, inherent toxicity of these.
>
> DR. CHIU: You know, there is no difference from active ingredient,
> toxic or not. The agency evaluation includes the toxicity evaluation.
>
> DR. LEE: Maybe I should ask a question to close it. It may be a silly
> question. What is the motivation behind this?
>
> DR. CHIU: The motivation behind this, we have a multiple motivation
> because we are looking at everything. When we do an evaluation we look
> at the risk. Even the CMC review is to identify what are the risk
> factors; what are not risk factors so you can determine what is the
> critical process control and what are the release specifications. This
> is just an additional part of the risk assessment and risk management.
>
> The second reason is because the agency always has limited resources.
> We want to put our resources in places where more extensive review and
> evaluation is needed rather than giving every drug the same intense
> evaluation. For those low risk drugs, you know, we do not need such an
> oversight as high risk drugs. So, those are the reasons.
>
> DR. LEE: So, this is some kind of a triage.
>
> DR. CHIU: Yes.
>
> DR. LEE: Thank you.
>
> DR. MEYER: Can I ask a real quick question?
>
> DR. LEE: Me?
>
> DR. MEYER: No, no, I want to ask someone who knows!
>
> \[Laughter\]
>
> Would recall history play a role in this? Would you look at that also?
>
> DR. CHIU: I think in the GMP compliance part of the history we will
> look at recalls; we will look at deviations such as a warning and all
> those factors involved in GMP.
>
> DR. LEE: Toby, one last question?
>
> DR. MASSA: On August 8 of \'01, industry provided a readout from the
> workshop that Dr. Chiu and I co-chaired on this topic. I would suggest
> for the committee could get insight on over 500 participants both from
> industry and FDA, that the AAPS has a web site containing those
> comments and many of the comments that Dr. Chiu mentioned are
> contained in that document.
>
> To the point that you raised, the key thing that industry felt is the
> ability to control and characterize; complexity, not as big an issue;
> dosage form, not as big an issue as long as it is characterizable and
> controllable. Those are the things that industry really felt very
> strongly about. There is an extensive amount of information on the
> feed-out from that workshop for the committee\'s consideration.
>
> DR. LEE: Do you have to be a member to access those sites?
>
> DR. MASSA: No, I think that is available to the public.
>
> DR. CHIU: Yes, the report is on the web site of AAPS.
>
> DR. LEE: Thank you very much. Well, I think that we are getting back
> on schedule and we come to a very interesting topic, blend uniformity.
> Ajaz Hussain will tell us about what is going on.
>
> **Blend Uniformity**
>
> DR. HUSSAIN: This is an update since we had an extensive discussion on
> the PQRI proposal.
>
> \[Slide\]
>
> Let me sort of walk through the background history here. The issue
> that we are talking about is assuring and documenting adequacy of
> mixing operations. I think it is equally an issue of documentation as
> the assurance because sampling has been identified as a challenge.
>
> PQRI\'s proposal essentially is a proposal of using stratified
> sampling of dosage units during routine production to document
> adequacy of mix. As an awareness topic, we brought this issue to the
> advisory committee on November 28, 2001, and with an extensive
> discussion of the proposal on May 8, 2002. Tom Garcia presented this
> proposal and we discussed it and there was a general endorsement of
> the proposal.
>
> There were two recommendations. One was from the chair person, saying
> that you essentially need some additional peer review for that. Dr.
> DeLuca had that document peer reviewed and you have those reviews in
> your handout. But FDA had started a panel peer review process and we
> provided our comments to the PQRI on August 14, and PQRI essentially
> came back with a further analysis and addressed the comments we had
> raised and we met for about three hours on October 17. So, it happened
> late last week. I am just going to report on that and some next steps.
>
> \[Slide\]
>
> Let me talk to you about the FDA peer review process. This peer review
> process was set to have an additional peer review which did not
> include members of FDA staff who participated in the PQRI proposal
> itself. So, Dr. Chiu, Joe Famulare, Frank Holcomb, myself, Stella
> Machado Yi Tsong and Shen Meyiu, who is in the audience, sort of
> looked at this proposal. Stella and Meyiu Shen are from the
> biostatistics department and Dr. Chiu you already know. Joe Famulare
> is from the Office of Compliance; Frank Holcomb, from the Office of
> Generic Drugs.
>
> We found that the concept of stratified sampling was acceptable to us,
> but we arrived at that conclusion from a very different perspective.
> We focused our attention on the science and engineering of blending,
> compaction and capsulation operations, and we felt that based on our
> understanding and the publication by Tom Garcia and Jim Prescott of
> PQRI, which was published on the root cause analysis of blending
> problem, that became the basis for accepting this proposal.
>
> Further, examples of stratified sampling data that were made available
> to us by individuals sort of supported this further. Then, the PQRI
> decision trees and scientific justifications clearly outlined the
> whole process. So, those are the three-pronged aspects that we looked
> at.
>
> \[Slide\]
>
> The type of examples that we received which, unfortunately, were not
> submitted to PQRI, which helped us move toward stratified sampling
> were this. I actually shared this example with you on July 19, 2001 as
> part of the PAT discussion. The question of a representative sample
> was raised.
>
> This is a wonderful example that make a case, a scientific engineering
> case for stratified sampling. This is a commercial product where the
> blend sample analysis passes without any problem and USP content
> uniformity passes without any problem. But when you do a stratified
> sampling you tend to pick up segregation towards the end of the
> product run.
>
> Similarly, Pfizer had shared with us an example of when they had put
> near-infrared at line and they were doing 300 table analysis or more
> you could see some of the problems similar to that in their
> production.
>
> There was another case study which I did not get a chance to plot of
> about 18 manufacturing lots. It came from a generic firm which
> essentially showed the same thing, that you can pass USP and you can
> pass the blend testing, yet, you can have a segregation problem. So,
> in a sense today we may be having a problem so the stratified sampling
> may make better sense, to move in that direction.
>
> \[Slide\]
>
> The PQRI data mining statistical effort\--FDA sort of had a different
> perspective on this. We looked at this information as supporting data
> and the statistical simulation and assumption of normality was the
> primary focus, is it normally distributed? Our interpretation, which
> is outlined in the report we sent to PQRI, was that deviation from
> normality suggests potential content uniformity problems. I think that
> is how we interpret that issue. Normality itself I think sort of
> suggests a problem.
>
> We asked for additional justification based on what we heard from you
> and our analysis\--sample size, issues with respect to routine
> production; how does it relate to batch size; how does it relate under
> different conditions. We raised some questions about categorization of
> blends to readily and marginally complying based on an RSD value of
> four percent, and what the implications of this categorization would
> be on routine production. The sample size is small. It is in tablets
> and you are basing an estimate, or estimating variance on a small
> sample size which is less robust now compared to what you had when you
> had large number of samples in the validation run. So, what will that
> do?
>
> \[Slide\]
>
> The PQRI response\--you have a handout of the PQRI proposal but I do
> not plan to go through it point by point, but just to summarize for
> you the highlights of the discussion we had with PQRI.
>
> The points PQRI came back with I think made sense to us and sort of
> helped us make a decision to accept the proposal. These included that
> in general PQRI agreed that normality includes lack of homogeneity.
> That is in quotations because that is from their slide presentation.
>
> The type of segregation that is during start-up or run-out will not be
> found by testing powder in the blender. I think that was obvious to us
> but I think sort of points to why stratified sampling is a better
> reflection of a manufacturing process or system. Stratified sampling
> specifically targets locations which have a higher risk of producing
> failing content uniformity results. I think we could see some of the
> examples from information that we have.
>
> The issue that we struggled with most was the sample size. Dr. Kibbe
> had raised that issue at the advisory committee last time and we had
> discussed that. We deliberated on this quite a bit and the question
> came out to be is this a representative sample. I think that became
> the question. In validation, for example, you are looking at 20
> locations and essentially you are representing five percent of the
> batch every time you take a sample. More sampling locations would not
> change this substantially. The number of locations, 20 for validation
> seemed appropriate. Essentially, the argument PQRI proposed was that
> sampling here is dependent on sampling representative of the
> population. That, we felt, is a good starting point for that.
>
> \[Slide\]
>
> One issue which we are still struggling a bit with, at least in my
> mind I am struggling with this because although this looks simple on
> paper this could pose potential problems during routine production for
> the operators and for how companies will manage this, is the
> implication of finding a high RSD value during routine production is
> the issue.
>
> Remember, the proposal is to classify or categorize blends as readily
> meeting or marginally meeting the criteria based on an RSD, relative
> standard deviation, value of four percent or less. If the relative
> standard deviation estimated is less than four percent, it is
> classified as readily complying. If it is not, it is marginally
> complying. For readily complying products standard testing is
> proposed, and the standard testing is USP type, stage 1, where you
> look at 10 tablets and the mean has to be between 90-110 percent and
> the relative standard deviation is less than or equal to five percent.
> You could go to stage 2 where N equals 30 and when the RSD is not met.
> There the RSD value for stage 2 is less than or equal to six percent.
>
> The potential dichotomy of classifying this as readily complying based
> on four percent and routinely seeing a high RDS poses a
> question\--what happened? So, that had to be addressed, and what do
> you do in those circumstances.
>
> Just to sort of complete the thought process, tightened specifications
> or tightened testing was recommended by PQRI for products that are
> classified as marginally passing. That means you are looking at 30
> tablets and the mean between 90-110 percent and an RSD less than six
> percent. The proposal also went on to say that when five each of
> consecutive batches meet an RSD of less than or equal to five percent,
> then you revert to standard testing.
>
> \[Slide\]
>
> In response to sort of our question, PQRI came back with an additional
> comment saying that they proposed to add that when performing standard
> testing\--I am at the bottom part of the slide\--when performing
> standard testing, when the RSD of one batch following stage 12 testing
> is greater than five percent, then you will switch to tightened
> testing. So, that is what the new PQRI proposes.
>
> I think it sounds logical, but in terms of actually doing this,
> switching back and forth from testing and so forth at the operator
> level, I am not sure how much of a challenge this will pose. I think
> it is acceptable but I think we have some questions on the logistics.
>
> \[Slide\]
>
> The next steps are that we will have an internal FDA meeting. We met
> on October 17th and we did not meet after that. We will bring together
> all the thoughts to define an outline for a new draft guidance based
> on the PQRI proposal, defining both review and compliance roles;
> assess and plan for training needs; assign the responsibility to a
> small group of individuals to draft the guidance. We will publish the
> draft guidance to seek public comments. Formal training of FDA staff,
> especially investigators who will be dealing with these I think is
> necessary but I think we will have to see what sort of training will
> be needed, and then proceed to a final guidance.
>
> \[Slide\]
>
> I do want to sort of say a few things about the other peer review
> comments that you have in your handout. Ken Morris was one of the
> reviewers also. For our review we did not have those comments that you
> have in your handout. I went back to look at those comments from the
> outside peer review process. There was a range of comments.
>
> All the concerns that were expressed in this, I was happy to note that
> we captured those in our review, except for certain aspects.
> Implications and perceptions resulting from continued recommendation
> of blend testing during validation was raised, especially by the
> European folks\--in a sense, doesn\'t it contradict what you are
> trying to do? Also, some of the criticism was increased focus on
> end-product testing to db quality, that is, moving away from building
> quality in the paradigm; and new technological solutions ignored.
> Those are sort of the comments.
>
> I just want to sort of address that. Keep in mind that the PQRI
> working group was asked to focus on the existing problem within the
> confines of the draft ANDA guidance. So, since they did not cover
> that, they were not asked to cover that and, therefore, we did not
> want to bring those comments into our evaluation.
>
> \[Slide\]
>
> But I do want to address a potential perception of a dichotomy between
> what we are trying to do here with the stratified sampling and the
> PAT. I do not see that as a dichotomy. So, let me explain that.
>
> We are in the current situation of univariate testing to document the
> quality approach. That is reality; that is today. We are using
> traditional methods and the current PQRI proposal and draft guidance
> will be in line with that. At the same time, I think we will offer in
> the draft guidance some opportunities to bring in at-line methods
> which could be very rapid and the draft guidance may include
> information on the use of NIR methods itself.
>
> But under the PAT scenario where we will move towards a different
> paradigm, where you have multivariate quality by design approach,
> where somebody could have on- and/or at-line testing methods for all
> critical components and processes, where you are looking at
> homogeneity with respect to drug as well as all critical components,
> excipients and so forth, that is a high level. So, we are not
> requiring that because that system is adequate for intended use. But
> if somebody goes to that, the PAT guidance will allow that to happen.
> Then the question comes why would anybody do that? What is the
> incentive?
>
> I think the incentive would be what we have heard from many companies,
> to do the right thing. For first-time manufacturing it makes business
> sense. It makes all sorts of sense from an efficiency perspective. But
> also from a regulatory perspective there is another set of incentives
> that come through. It is the risk itself because now you have focused
> attention on the entire system and you are better able to control
> that. So, you have a lower risk leading to a lower regulatory concern.
> So, that is the added incentive that sort of can come through this
> process.
>
> \[Slide\]
>
> So, the new technology solutions and the PAT, just to sort of wrap up
> my thoughts on that, the draft guidance may include information on the
> use of NIR methods. I am not promising that but we will try to do
> that. The PQRI blend uniformity new technology group has already
> proposed validation criteria for NIR and it will be published as a USP
> PF article so that already is a source of information, plus there are
> other excellent monographs on NIR validation, and we have our own
> laboratory experience with NIR and NIR imaging methods so we are in a
> good position to sort of give some guidance on how one would do this
> at-line.
>
> The proposed PAT guidance will further elaborate on how to introduce
> new technologies to improve process understanding and efficiency. So,
> it is win-win and we are moving in a step by step fashion.
>
> \[Slide\]
>
> I will just sort of share some data with you. Here is our most recent
> publication that is on the web site of AAPS PharmSciTech. This was
> done in our lab by Rob Lyon and others where we looked at
> near-infrared spectral imaging for quality assurance of pharmacology
> products, focusing on analysis of tablets to assess powder blend
> uniformity. Here you can do this in a matter of seconds, and the issue
> of sample size and so forth is not an issue. Although the challenge
> here that we are facing is the scale of scrutiny, it is a fraction of
> a tablet so it is far more sensitive.
>
> So here are four examples of commercial blend of flurosemide tablets
> versus experimental blends with various degrees of blend homogeneity
> and you can see how easily one can pick this up. So, there is still
> some work that needs to be done with respect to acceptance criteria
> but the technology is there.
>
> \[Slide\]
>
> With the PAT concept, focusing on multivariate, I do want to sort of
> address the issue of dissolution. When we focus only on the drug there
> are many circumstances where there is a risk of noon-homogeneity with
> respect to other components. For example, here is a case study on what
> happens when you don\'t have adequacy or uniformity of mix with
> respect to magnesium stearate. Here dissolution failures occur at the
> early part of the run and the later part of the run. So, the
> stratified sampling plan for dissolution is a question but, at the
> same time, I think with the PAT we can address all these issues.
>
> \[Slide\]
>
> Just to illustrate that point further, here is an excellent example
> from Pfizer presented at our PAT subcommittee. If you look at the
> control blend, and the focus is on the green spots, and look at the
> problem blend, look at the green spots, control blend had normal
> resolution; poor blend had slow resolution. Matrix level differences
> relate to distribution and particle size of disintegrant within that
> blend. And, blend can lead to dissolution challenges too because of
> non-homogeneity of the excipients.
>
> \[Slide\]
>
> So, sort of in a continuum, I think the PQRI proposal is acceptable.
> It is a step above the current USP requirements, and it is an
> improvement in terms of focusing on the stratified scheme to making
> the sampling more representative. That sort of covers one aspect.
>
> In the future new technology will further help to improve but, as we
> have said already, PAT and new technology are not requirements. These
> are options available for companies which can do this. So, with that I
> will stop. The USP content uniformity is just for your information so
> that you know what all that is.
>
> DR. LEE: Thank you very much. Any questions for Ajaz? Yes, Marv?
>
> DR. MEYER: This is a somewhat political question I guess. Some people
> accuse the agency of implementing guidances while they are still in
> draft form. I notice on page five, under \"next steps,\" you have
> draft guidance training of FDA staff and then final guidance. Are you
> training these people to implement the draft guidance?
>
> DR. HUSSAIN: What we do is when we are ready to have a final guidance
> ready to go out, we train on that. Actually, the training just before
> the final should help us to fine-tune that. That has been our way of
> sort of making sure the final guidance has captured every part. It is
> done at a later point when we are ready to issue the final guidance.
>
> DR. LEE: Art?
>
> DR. KIBBE: When you are talking about the number of times you sample
> throughout the process, you are saying you are going to sample at 20
> different places unless you have a low percent RSD and then you will
> sample at 10 different places? Is that right?
>
> DR. HUSSAIN: No, the 20 locations are for the validation run. So, for
> the validation experiment essentially you have three samples collected
> at 20 different locations so you have a total of 60 units being
> analyzed. In routine production if you have classified your powder
> blend as readily complying, having less than four percent RSD during
> the validation, then you take 10 tablets from 10 different locations.
> Although you will take three tablets from 10 locations you will
> analyze only one each from different locations. If you don\'t meet the
> marginally complying or if you are marginally complying to that, then
> you will analyze 30 tablets from 10 locations.
>
> DR. KIBBE: I just got lost on your numbers.
>
> DR. HUSSAIN: During routine production the number of locations is 10.
>
> DR. KIBBE: So, 10 times during the tablet run.
>
> DR. HUSSAIN: Right.
>
> DR. KIBBE: And how many tablets at each?
>
> DR. HUSSAIN: Stage 1 would be one from each location, so 10 total.
> Stage 2 would be three from each location, so that would be 30 total
> during routine production.
>
> DR. KIBBE: And we expect to be able to get statistically significant
> understanding of the first million tablets by looking at one tablet?
> Right?
>
> DR. HUSSAIN: As I said, the question is, is it representative.
> Unfortunately, if you look at the current standards, these are minimal
> standards. These are the minimal standards of today so tomorrow you
> can have a better system with PAT. So if you want to go for lower
> risk, go to PAT.
>
> DR. MOYE: Can I follow-up on that?
>
> DR. LEE: Sure.
>
> DR. MOYE: There are standards for that methodology that have been
> available now for about forty years on determining the appropriate
> sample size for the given background rate, if you will. I take it that
> has not been implemented here?
>
> DR. HUSSAIN: It is a loaded question and the answer to that is
> two-fold. One is the GMP process essentially is a process that focuses
> on building quality in. So, the combination of all the GMP
> requirements of documentation, checking and so forth, and all that,
> allows one to use USP type standards to release and that is the logic
> that the current system works under.
>
> The sample has to be representative and GMP plus the USP type is sort
> of the minimum standard that we use today. A statistically based
> sampling scheme I think is what we started from years ago, in the
> 1950s is when that came about. Then, we have the current system of GMP
> plus compendium standards as being the minimal standards.
>
> DR. MOYE: Okay, that is where we have been but where are we going? Let
> me ask you formally, do you anticipate at some point in the
> foreseeable future being able to implement more standard methodology
> into this process, into the sampling process?
>
> DR. HUSSAIN: Well, I think there are two scenarios. Definitely, with
> the PAT we are moving in that direction. Just to share the example
> Pfizer shared with us at the science board, and so forth, our current
> standards are what we call zero tolerance standards. If you look at
> the USP, at stage 2 no tablet should be outside 75-125 labeled amount,
> and the RSD that we accept is about 7.6 percent. If you know it is a
> normal distribution, you know there are several units outside that
> 75-125. It is simply a matter of chance whether you find that unit and
> reject that lot or you don\'t. So, unfortunately, the current standard
> that we have does not fully take into consideration the underlying
> statistical principles.
>
> DR. MOYE: Well, what do we do about that? How do we agree that it
> doesn\'t? What happens next?
>
> DR. HUSSAIN: It has been the standard for years so what we are trying
> to do is help improve that in a step by step fashion, bringing more
> science into it.
>
> DR. MOYE: Then, just to push you, what is the next step here? I mean,
> now we are talking about sampling, if I understand right, one or two
> tablets per million.
>
> DR. HUSSAIN: It could be that.
>
> DR. MOYE: Okay, so what then specifically is our next step?
>
> DR. CHIU: Right now the USP sampling plan is that you take 10 tablets
> from a million tablets of a batch, regardless where you pick them. The
> new proposal, the stratified methodology, is that you will have to
> identify during the validation of these 20 locations which are
> critical. So, those are the locations which may have deviations
> because of blending. So, therefore, one way you look at it is that
> during the blending validation you identify the critical points. Then
> for product, at release, you also identify these 10 critical
> locations.
>
> Right now we know the initial location and at the end of the batch
> would be most vulnerable to be outside the limits. So, that would be
> definitely picked up. The rest of the locations will be based on
> manufacturing to identify other critical locations. So, those 10
> tablets will be much more representative of a batch so you can catch
> your deviation easily. That would all be performed, you know, during
> the validation period. So, I think this proposal is a much better way
> to assure product quality and it is an improvement. It is not perfect.
> If you want to do statistics on a minimum batch you probably need more
> than a thousand tablets to be tested. So, our idea is that you have
> process control and you have release testing and the testing has to be
> more representative per batch.
>
> DR. LAYLOFF: Let me comment\--
>
> DR. HUSSAIN: No, let me answer that. The answer I think is simply
> this, the testing is only one small part of the system. I mean, I
> think you have to look at it in that perspective because the GMP
> requirements require you to qualify every step of the way and you are
> monitoring every step. So, this is one small part of the entire
> quality system. Can the sampling be improved? Definitely. But for an
> entire systems approach, you have to look at it from that perspective
> because you have a validated batch and then you have minimal testing
> to essentially ensure that the validation worked every time. So, it is
> a gross failure test from one perspective.
>
> DR. LEE: Tom?
>
> DR. LAYLOFF: Yes, I was going to comment. I think we have lived with
> the statistical absurdity of assuming that the batch is a normal
> distribution and that a few tablets are representative of this normal
> distribution. However, I went through probably the content uniformity
> on 20,000 batches that we had analyzed in our laboratory and it is
> absolutely startling that it works. I mean, we don\'t find the
> failures there. I have actually taken cases where I had my laboratory
> with automated analysis run 600 tablets out of a batch and I think the
> controls, the GMP controls are what makes it work because it is
> statistically absurd.
>
> DR. MOYE: I guess if you have a problem that is hyper prevalent, then
> I imagine that this small sample might be of some benefit and I would
> agree that sampling four out of a million is better than sampling two
> out of a million, but I don\'t think it is very much better. But if
> you have a problem that is not so hyper prevalent then, of course,
> this is going to fail. If I understand you right, you are telling me
> that there are additional steps or assurances that you take and that
> it is inappropriate maybe to make too big of an issue about the
> statistical aspect of sampling because anything that this inadequate
> step procedure misses, the other fielder will catch. Is that right?
>
> DR. HUSSAIN: If you take a systems approach to that in the sense of
> raw material qualification with documenting that, rechecking that,
> every step is sort of followed and documented and signed by two
> people. So, that is the system. The redundancies that are built in, in
> many ways end-product testing, if you have built quality in, is
> redundant to start with. So.
>
> DR. LEE: I want to suggest that you two go for lunch, get together at
> lunch. I think from a statistical point of view it doesn\'t make
> sense. Is that right? But, yet, in practice it seems to work and I
> think that perhaps for products of high quality it really doesn\'t
> matter. It reminds me of getting speeding tickets. Hundreds of people
> get speeding tickets. But let me turn to Toby.
>
> DR. MOYE: In Houston more than one or two per million get speeding
> tickets!
>
> \[Laughter\]
>
> DR. MASSA: I think we have struggled with exactly the issue that you
> are talking about and Ajaz\' point. I think none of us agrees
> that\--you know, regardless of what sampling plan you use, I think we
> all agree that the rationale of sampling from such a large batch was
> something that we all questioned. I think where we will feel
> comfortable and where we do take comfort in the current situation is
> that most of us work toward building quality into the manufacturing
> process, not testing it in as a result of either end-product or blend
> uniformity testing. We look at critical process parameters and we know
> that when you add a drug to a blend you have gone through great pains
> in development and validation to look at critical parameters like
> mixing speed and mixing time to know when you have achieved
> homogeneity of the mix.
>
> Granted, some of the issues we have identified as a result of that
> process point to the fact that even though you may have achieved
> homogeneity at the time of blending, sometimes you get post blend
> transformations that cause you to want to look at the end-product. In
> parallel with our effort of looking at end-product testing, we spent a
> lot of time in our analytical technologies group putting a proposal
> together to USP on NIR testing of the blend because we think testing
> of the blend using NIR is probably a more viable alternative to the
> end-product testing because it is looking at a critical process
> parameter rather than looking at an end product.
>
> I also think that, on Ajaz\' point, we will all be very happy when we
> can all do content uniformity testing on every tablet going through a
> line. I don\'t know when that is going to happen and when that
> technology is going to be commercially feasible, but we have talked
> about that. As we do that, we are going to need a different regulatory
> paradigm because you are going to be testing every tablet in a batch.
> You are not going to test 10 tablets or 30 tablets, and they are not
> all going to pass.
>
> To your point, we may find that, you know, out of a batch of five or
> ten million tablets that we may have 10,000 tablets that we identify
> as we go through testing every tablet. That doesn\'t mean that the
> rest of that batch is bad as long as we can figure out where to
> segregate those failing tablets. I don\'t think that is too far in the
> future. I think the efforts that we are working on for PAT and the GMP
> initiative will ultimately get us there so that we won\'t have to
> worry about statistical sampling.
>
> DR. GARCIA: Toby, this is Tom, Tom Garcia.
>
> DR. LEE: Yes, Tom, could you speak louder please?
>
> DR. GARCIA: Sure. The blend uniformity working group, when we devised
> our sampling scheme, we used a lot of operating characteristic curves
> and we specifically tested the number of tablets tested per location.
> What we demonstrated is that by increasing above the curve the numbers
> that are in the recommendation for both validation and routine testing
> we really didn\'t gain a lot of increased power in discriminating. For
> example, if you see ROC curves in the recommendation, each one of
> those points is a result of taking 5000 simulated samples from a batch
> of known standard deviations and in each one of those you could see
> that as we increased the higher numbers of samples, there isn\'t a
> whole lot of difference in the discriminating power of the curves. So,
> that is a strong argument for the question on the sample number.
>
> The second point I would like to make is that the group felt that it
> is more important how and where you take the tablets or the capsules
> in the batch rather than the number that you take. Right now we are
> just looking at random samples. For example, we take 30 tablets and
> subject them to USP testing. With the proposal that we are putting
> forth we are specifically targeting problematic areas in the beginning
> of the batch, end of the batch and during bin changeovers. So, you can
> see that if there is a problem with a batch we are a lot more likely
> to pick that up, even with the number that we are taking, than if we
> continue with random sampling. That is all I have.
>
> DR. LEE: Thank you. Art?
>
> DR. KIBBE: I think that statistically speaking the way we end-stage
> test is like the \"emperor\'s new clothes.\" We think we have
> something that makes sure that our batch is good and all the product
> we put out is good, but it really is ghosts and mirrors. There is no
> way of statistically proving that. However, that evolved over at least
> as long as I have been around. The beginnings of this all started with
> equipment was\--you know, if you could get 10,000 tablets out in an
> hour you were lucky, and now we are at a completely different stage.
>
> What has happened industrially is that the evolution of the method of
> getting to the point where we now turn the tablet machine on has
> gotten tighter and better, and what we are really depending on is the
> process and not the end-stage test. The end-stage test is kind of like
> Linus\' blanket. It makes Linus feel good but it is not really solving
> his problems. The sooner we can get to the described situation where
> we actually are running each tablet through NIR and looking at the
> uniformity on the surface of the tablet as an indicator of what the
> tablet looks like, and the sooner we get in-process controls that we
> are really happy with, the better off we are going to be in the long
> run. I am just happy that we are moving in that direction.
>
> DR. LEE: Very well. Thank you very much, Ajaz.
>
> DR. LAYLOFF: Could I make a comment also?
>
> DR. LEE: Brief.
>
> DR. LAYLOFF: Brief, okay. I was back on the ground floor of content
> uniformity when we were doing digoxin and developed the single tablet
> method instead of averaging 20 in a mortar and pestle, and we found
> tablets that ranged from 50-300 percent in the same bottle.
>
> Now, one of the things that you see with this variance level is that
> there is an analytical variance that is coming in there also. The HPLC
> procedures themselves will run about one percent on consecutive
> injections. However, you are talking about a sample workup there also.
> So, you are looking at about 2.5 percent CV for the identical amount
> of material for an analyst taking it from the beginning to the end so
> you are looking at an aggregate response. Content uniformity was a
> very big issue and it has been very well addressed. That is why I did
> about 20,000 batches to look at it.
>
> DR. LEE: Thank you very much. The next item on the agenda is open
> public hearing. There was one person expressing interest to do so but
> he could not make it. That means that there is no open public hearing
> for this session. I propose that we adjourn for lunch but because in
> the afternoon we have a couple of phone-ins we cannot be one hour
> ahead of schedule. Let\'s say that we come back here at 1:30 and I
> suggest that the committee members study the background about the
> issue to be discussed, polymorphism, over lunch. Thank you.
>
> \[Whereupon, at 11:50 a.m., the proceedings were recessed for lunch,
> to reconvene at 1:30 p.m.\]
>
> A F T E R N O O N P R O C E E D I N G S
>
> DR. LEE: The topic this afternoon is regulatory issues related to
> crystal habits, polymorphism. The committee is well rested and ready
> to go, and Gary Buehler is going to introduce the topic for us.
>
> **Regulatory Issues Related to Crystal Habits**
>
> **- Polymorphism Introduction**
>
> DR. BUEHLER: Thanks, Dr. Lee and thanks to the committee for inviting
> me to introduce this very important topic to the Office of Generic
> Drugs. I am Gary Buehler. I am the director of the Office of Generic
> Drugs.
>
> \[Slide\]
>
> The topic this afternoon is regulatory issues related to the crystal
> habits or polymorphism in ANDAs. I will give a short, brief
> introduction and, believe me, mine will be the least scientific of the
> presentations. Then Lawrence Yu will present scientific considerations
> of polymorphism in ANDAs. Our expert comments will consist of Ken
> Morris, from Purdue University, and Leslie Benet, on the phone, from
> the University of California. Dr. Harry Brittain wasn\'t able to be
> with us this afternoon so he will not be making an address.
>
> \[Slide\]
>
> The title of my presentation is polymorphs\--what\'s the problem? Over
> the past year or two we have asked this question a number of times to
> the advisory committee to address the polymorph issue. I know some of
> you have wondered why we are spending this much time on polymorphs; it
> seems like a simple issue to you folks. You are scientists; you
> understand it. I am sort of a quasi-scientist. I am a pharmacist; I am
> not a Ph.D. I have had difficulty in understanding this topic and
> people have explained it to me a number of times and it is my
> unfortunate position to have to explain this topic to lawyers many
> times because the polymorph issue often sort of flows over into the
> legal arena and we have to explain the issue to our lawyers. That is
> why somehow I have to figure it out and I have to have a fairly simple
> explanation of it.
>
> \[Slide\]
>
> I tell our lawyers that polymorphs are the same but maybe they are
> different. I say, you know, just take it from there. They just look at
> me with sort of a funny look on their face and they say, \"how can
> something be the same but, yet, be different?\" I say, \"well, the
> same crystal structure; different form. They look different but they
> are the same.\" So, they say, \"continue.\"
>
> \[Slide\]
>
> So Lawrence gave me this example, diamonds and coal. Diamonds and coal
> are obviously very different looking but they are both carbon. Take it
> one step further and we talk about coal in an ANDA. Is coal
> bioequivalent to a diamond? I don\'t think we will ever find that out.
> Does coal exhibit the same identity, strength, purity, quality and
> stability? Again, we probably will never find that out. But I think
> everyone in the room agrees coal and diamond are different.
>
> \[Slide\]
>
> Let\'s take one a little bit easier to understand and a little bit
> easier to apply to pharmaceutical formulations, crystalline sugar and
> powdered sugar. I don\'t know how many of you out there are bakers but
> you know that we can\'t substitute crystalline sugar for powdered
> sugar in many recipes that we use. They are both sugar and if we put
> them in water they both dissolve and they both will make our coffee
> sweet. But if you look at a box of crystalline sugar and a box of
> powdered sugar, pound for pound the crystalline sugar box will be
> twice a big. Two pounds of crystalline sugar equal about one pound of
> powdered sugar in bulk. When we dissolve them we probably could make a
> bioequivalent formulation but there would be some formulations that
> probably wouldn\'t be bioequivalent, depending on how the product was
> formulated.
>
> I use this example for our lawyers and they actually seem to get it a
> little bit; the light goes on a little bit. They all recognize
> crystalline sugar and powdered sugar; they have all seen it and they
> all recognize it as being quite different looking, and they will
> recognize that it is all sugar.
>
> \[Slide\]
>
> The 314.94(a)(5), which is an ANDA regulation, states the active
> ingredient in an ANDA is the same as that of the reference listed
> drug. All ANDAs have a reference listed drug that is the innovator
> product, and the active ingredient in an ANDA product must be the
> same.
>
> \[Slide\]
>
> What is the \"same\"? Our regulation preamble clarifies the definition
> of \"same\" to meet the same standards for identity as described in
> the USP. In some cases, however, FDA may prescribe additional
> standards such as crystalline structure and stereoisomeric mixture. If
> you have any questions as to what is the same and what isn\'t the
> same, you are directed to call the Office of Generic Drugs.
>
> \[Slide\]
>
> What is polymorphism? Different physical forms of the same chemical
> structure. This is a very simple definition. This is my definition
> that I use for the lawyers. Lawrence will give a definition that I
> believe will occupy three or four slides. But basically this is it.
> Different polymorphs may exhibit different properties, including
> stability, very importantly stability, and bioavailability. This is
> the critical consideration for ANDAs.
>
> \[Slide\]
>
> With modern technology, the identification of multiple polymorphs has
> become easier. Some people have made actual science out of identifying
> polymorphs for drug products. Because of their unacceptable properties
> however, the majority of these polymorphs have little utility and
> cannot be developed into quality products.
>
> \[Slide\]
>
> Let\'s go into a little history of what the problem is for the Office
> of Generic Drugs. Again, the problem overflows into the legal arena.
> On September 29, 2000 a citizen petition was filed by Glaxo SmithKline
> for cefuroxime axetil, the innovator product Ceftin. The petition
> requested the FDA deny approval of any ANDA for cefuroxime axetil
> whose active ingredient is wholly or partially in a crystalline form.
> The innovator product uses entirely the amorphous form for cefuroxime
> axetil, or require stringent drug substance and drug product
> specifications for solid state form, including the content of the
> individual polymorphs.
>
> \[Slide\]
>
> There was also a USP monograph petition because the USP monograph at
> that time specified that the polymorphic form of cefuroxime axetil be
> the amorphous form. We met with USP on the monograph issue and we met
> numerous, and I do mean numerous times with the lawyers in drafting a
> 37-page response that detailed our scientific position on polymorphs.
> This response is in the public record. I believe it has also been
> provided to the advisory committee as background information on a
> couple of occasions.
>
> \[Slide\]
>
> Another fairly important drug is omeprazole. About four months before
> the pediatric exclusivity for Prilosec was due to expire we were
> informed of a possible polymorphic issue. I really can\'t give a whole
> lot of information on this particular issue because although it was
> made public to the various generic applicants, it was not made public
> to the general public. But after significant review of the available
> data, and again many meetings with both the review division who did
> the initial review on Prilosec, the Office of Generic Drugs and our
> Office of Chief Counsel, the issue was addressed.
>
> \[Slide\]
>
> Lastly, fluoxetine; this is Prozac. On July 18, 2001, about two weeks
> before the pediatric exclusivity for Prozac was due to expire, we were
> informed that aaiPhARMA of North Carolina held a patent on one
> polymorphic form of fluoxetine. They asserted that their patent
> claimed the drug product or method of using Prozac and should be
> listed in FDA\'s Orange Book. However, only the NDA sponsor is
> authorized to request a patent listing in the Orange Book and
> aaiPhARMA was informed of that so they, therefore, requested Eli
> Lilly, the NDA applicant, to list this particular patent in the Orange
> Book.
>
> \[Slide\]
>
> Eli Lilly informed aaiPhARMA that they did not plan on listing the
> patent in the Orange Book because they did not believe that the
> polymorphic form claimed the approved drug product. aaiPhARMA appealed
> back to the FDA and FDA went back to Lilly and said will you reaffirm
> that this patent will not be listed in the Orange Book?
>
> Understand the significance of the listing of the patent into the
> Orange Book. If this patent were listed in the Orange Book the pending
> ANDA applicants for any pending ANDA for fluoxetine at that time, and
> there were 20-plus applicants, would have to certify to this
> particular patent as to whether they infringed it or they did not
> infringe it. The certification usually is in the form of what we call
> paragraph 4 certification which challenges the particular patent. In
> doing so, they would give either the patent holder or the NDA holder
> an opportunity to sue them. There would be a 45-day waiting period
> that would ensue immediately and during that period the innovator
> company or patent holder could sue each ANDA applicant, and that would
> trigger a 30-month stay of approval and the Office of Generic Drugs
> would not be able to approve any fluoxetine products during that
> 30-month period.
>
> So, that is the legal significance of this polymorph issue. In this
> particular case, Eli Lilly replied back to the FDA that it was not
> listing the patent. Therefore, it kept the door open for the approval
> of the ANDAs for fluoxetine and, in fact, on August 2, I believe, the
> first ANDAs for fluoxetine were approved. Those were the ANDAs that
> had 180-day exclusivity. Then the subsequent January, about 20-plus
> additional ANDAs were approved for fluoxetine. There are quite a few
> of them now.
>
> \[Slide\]
>
> aaiPhARMA then asked FDA to list the patent. aaiPhARMA was not giving
> up. They asked the FDA if Lilly wouldn\'t list the patent, they wanted
> us to list the patent. But we replied that only the NDA applicant can
> list the patent in the Orange Book. aaiPhARMA sued us. Well, we are
> being used to being sued. We get sued pretty regularly, and this was
> another one. We were sued in North Carolina I believe\--I think it was
> in Richmond. Eventually, to make a long story short, aaiPhARMA lost
> the lawsuit and they also lost the appeal. The lawsuit was not whether
> their patent should be in the Orange Book; the lawsuit was whether
> they could list the patent, they, the patent holder could list it and
> not only the NDA holder. The court affirmed that our regulations state
> clearly the NDA holder is the only one that can list the patent. FDA
> cannot do it and the patent holder cannot do it.
>
> These three cases just portray the problems that we have encountered
> in the Office of Generic Drugs over polymorphs. It is a simple
> scientific issue, we believe, and can be explained in fairly simple
> scientific terms, but as it overflows more and more into the legal
> arena, it becomes more and more complicated for the Office of Generic
> Drugs.
>
> \[Slide\]
>
> In summary, an ANDA applicant is required to demonstrate that their
> proposed product meets the standards for identity, exhibits acceptable
> stability, and is bioequivalent to the reference listed drug. We
> believe that is the criteria for polymorphs. We examine every ANDA
> through bioequivalence testing, through the data that they submit in
> the manufacturing and control section of the ANDA, and make sure that
> each ANDA meets the standards for identity and standards for
> bioequivalence, and we believe that that is the criteria for
> polymorphs. Thank you. Questions for me?
>
> DR. LEE: Questions? I don\'t hear any. Thank you. I understand that
> Dr. Nair Rodriguez is on the phone.
>
> DR. RODRIGUEZ-HORNEDO: Yes, I am on the phone. Can you hear me?
>
> DR. LEE: I don\'t think we can hear you very well. DR.
> RODRIGUEZ-HORNEDO: Well, I can hear you and I have no questions right
> now.
>
> DR. LEE: Can you hear me?
>
> DR. RODRIGUEZ-HORNEDO: Yes.
>
> DR. LEE: Good. If you have questions, just shout please. Welcome to
> the committee.
>
> DR. RODRIGUEZ-HORNEDO: Thank you.
>
> DR. LEE: Les Benet, are you on? It is past 1:30 already. Les, are you
> there? I guess not. Les will make a grand entrance.
>
> \[Laughter\]
>
> Lawrence, if the worst comes to worst you will need to repeat what you
> said.
>
> **Scientific Considerations of Pharmaceutical**
>
> **Solid Polymorphism**
>
> DR. YU: That is fine.
>
> \[Slide\]
>
> Good afternoon. Distinguished chair and members of the FDA Advisory
> Committee for Pharmaceutical Science, my FDA colleagues and
> distinguished guests, it is my pleasure and privilege this afternoon
> to discuss with you scientific considerations of polymorphism and
> ANDAs.
>
> \[Slide\]
>
> During my presentation I will try to address three questions. What is
> polymorphism? How does polymorphism affect pharmaceutical properties
> of drugs? To what extent should scientific considerations be given to
> polymorphism in ANDAs?
>
> \[Slide\]
>
> This is basically a sketch to differentiate habits, internal
> structures, crystalline forms, amorphous forms, as well as the hydrate
> forms. As you can see here, the compound could have a difference in
> terms of external habits and internal structure. Crystalline habit is
> defined as altered appearance of a crystal. If you go to the
> Smithsonian Museum you can see a variety of forms of altered
> appearance or in scientific terms crystal habits.
>
> You could have different internal structures. Here we show a
> crystalline or amorphous. The definition of crystal is uniform
> arrangement of atoms or molecules, while the amorphous form is defined
> as ununiform or disordered arrangement of molecules or atoms, as you
> can see here.
>
> For crystalline forms you could have two single molecules or you could
> have what we call molecule adducts. For single molecules and many,
> many other things the academic definition we call polymorphs. In other
> words, all kinds of crystal forms consist only\--only\--in the drug
> substance or active pharmaceutical ingredients. Otherwise we call it
> molecular adducts, which could be stoichiometric or nonstoichiometric.
> If it is stoichiometric you have a fixed ratio of compounds to the
> solvates. If the solvate is water, we call it hydrate; otherwise we
> call it solvate. There is a fixed ratio of drug molecules to solvates.
> If there is no fixed ratio we call them nonstoichiometrics. You could
> have a channel; you could have a layer or you could have the cage,
> which is really quite unusual for us to see in the pharmaceutical
> field. As I said, for an academic definition, sometimes polymorphs
> refer to all kinds of crystals of a single or pure drug substance, as
> shown here.
>
> Therefore, the ICH Q6A definition of polymorph is basically including
> crystalline forms, amorphous forms, solvates and hydrates. That is the
> regulatory definition of polymorphism, as you can see here. The ICH
> Q6A definition, again, includes crystal forms, amorphous, solvates and
> hydrates.
>
> \[Slide\]
>
> There is a variety of methods available to categorize the polymorphic
> forms of drug substances. A few are here, crystallography or x-ray
> pattern diffraction; microscopy; thermal analysis or DSC and TGA;
> apparent solubility; intrinsic dissolution; infrared absorption or
> Raman spectroscopy; and finally solid-state nuclear magnetic
> resonance.
>
> Although there are all kinds of methods available to characterize the
> crystallography or the form of drug substance, the key method to
> differentiate the polymorphism is non-equivalent crystal
> structure\--non-equivalent crystal structure. This is a definitive
> term existing of polymorphic forms. The other methods are what we call
> supporting resources. If the supporting resource is validated with
> crystallographic method, certainly this method can be utilized to
> differentiate the polymorphic forms or polymorphs of the drug
> substance. So, once again, the existence of polymorphic form is
> non-equivalent with crystal structure, for example, non-equivalent
> x-ray diffraction patterns. Other methods are supportive.
>
> \[Slide\]
>
> All kinds of physical chemical properties can be affected by
> polymorphs. What is relevant to the pharmaceutical properties here is
> the melting point; hygroscopicity; chemical and physical stability;
> apparent solubility and dissolution; bioavailability and
> bioequivalence and, finally, manufacturability.
>
> Although all these properties could potentially affect the polymorphic
> form, they do not always. In other words, if you see different
> polymorphic forms and you say you can impact different
> bioavailability, this is not true. It could potentially impact
> bioavailability but not always. Not always. I will try to use the same
> example to show you how the polymorphic forms potentially affect these
> properties listed in this slide.
>
> \[Slide\]
>
> First there is the melting point. About ten years ago when I was
> working in the laboratory on fluoroquinolone, we received a start form
> of this specific quinoline. Actually, this start form is very, very
> hygroscopic. In fact, if you take a few grams out and expose it to the
> air, a few minutes later, five minutes or so, the solid form becomes
> liquid. It is totally liquified. It is so hygroscopic that it is
> impossible to work with. So, you go through the soft form selection as
> well as what we call polymorphic form selection.
>
> Certainly as a scientist you have a microscope in the lab and the
> first thing you want to look at is what kinds of crystal form does
> soft form have. In this case we will also certainly increase the
> temperature. As you can see under (a), when the temperature increased
> about 142 degrees the polymorphic form, in this case solid, is melted,
> liquified and recrystallized. It gives you a very beautiful
> needle-like picture. When the temperature continues to increase to
> about 168, form II here, it is again melted, liquified and
> recrystallized. The melting point of form III is about 202 degrees of
> C after that and when the temperature increased beyond this, this
> basically is a form III, melted and degraded.
>
> So, if you started with a polymorph (a) you can see three peaks. You
> can see polymorphic I, polymorphic II and polymorphic III. However, if
> you look at (b), if you start with polymorphic (b) you do not see
> peaks in polymorphic I and polymorphic II. This is polymorphic I, this
> is a II and this is a III.
>
> \[Slide\]
>
> As we can see, definitely the polymorphic forms affect the melting
> point. This is how the polymorphic form affects the hygroscopicity.
> You can see here form I and form III. Form III is much less
> hygroscopic than form I, picking up 4.5 percent moisture from the
> humidity from 0.1 to about 80, while form III only picks up about 0.5
> or less percentage of moisture. That shows that the polymorphic forms
> or polymorphism will affect the hygroscopicity of the drug substance.
>
> \[Slide\]
>
> This is solubility. As you can see, polymorphism certainly affects
> solubility tremendously. The more stable the polymorph is, usually it
> is less soluble. This shows here that form III is much, much less, at
> least 30-fold less soluble than form I.
>
> \[Slide\]
>
> Having said that, in order to show the polymorphic form effect on
> bioavailability I will have to pick up a poorly soluble drug because
> highly soluble drugs are all highly different solubility but they
> don\'t necessarily translate a difference in bioavailability. So, the
> drug I picked up in this case is a carbamazepine, which is well
> familiar to you I am sure. With this carbamazepine you have a form I,
> form II and dihydrate form. This is basically an intrinsic dissolution
> experiment. As you can see here, form I has a much higher intrinsic
> dissolution than the dihydrate form and is higher than form II. Form
> II has a much higher dissolution rate than the dihydrate form.
>
> \[Slide\]
>
> How does this translate into the bioavailability? As you can see here,
> this is bioavailability conducted by comparing a solution versus form
> I and versus a dihydrate form. This is a suspension so you don\'t have
> exclude the potential effect of formulation. As you can see here, the
> solution is much more bioavailable with a much higher absorption
> compared to form I and compared to the dihydrate form. As you can see
> here, the dihydrate form has a Cmax value around 2, while form I has a
> Cmax value about 3.5 while the solution has a Cmax volume of 4.5. The
> same thing is true with respect to absorption, what we call the area
> under the curve or AUC. So in this respect, for poorly soluble drugs
> the polymorphic form does impact, does affect bioavailability under
> the same formulation conditions.
>
> \[Slide\]
>
> Lastly, the polymorphic form will affect manufacturability. With
> different polymorphic forms different manufacturing processes maybe
> have to be designed in order to manufacture quality products. So a
> polymorphic form will affect manufacturability. On the other side, the
> manufacturing process could potentially result in inter-conversions of
> polymorphic forms so we have to be careful. For example, milling or
> micronization, wet granulation or spray-drying, those processes will
> potentially result in polymorphic inter-conversion, for example, form
> I could potentially change to form II. I say potentially. It is most
> unlikely to happen but sometimes it does happen.
>
> \[Slide\]
>
> With this introduction, I want to discuss with you the decision tree
> developed for polymorphism in ANDAs. The objective of the decision
> tree is basically for evaluating when and how polymorphs in a drug
> substance in ANDAs should be monitored and controlled. Basically,
> during the development of those decision trees we have to consider two
> basic principles. One is ICH Q6A decision trees on polymorphism. The
> second is the biopharmaceutics classification system. The ICH Q6A
> decision trees were introduced on May 9 at the previous advisory
> committee meeting.
>
> These decision trees basically apply for the polymorphic screen of new
> drug applications, not for abbreviated new drug applications. We also
> introduced the concept of biopharmaceutics classification system into
> the decision trees for abbreviated new drug applications. So, before I
> talk about those decision trees I want to talk about this ICH Q6A very
> briefly and also spend three slides on the biopharmaceutics
> classification system.
>
> \[Slide\]
>
> This is basically an overview of the ICH Q6A decision tree:
> investigating the need to set acceptance criteria for polymorphism in
> drug substances and drug products for new drug applications. Again,
> this ICH Q6A is applied for new drug applications. They consist of
> three parts. Part one, do multiple polymorphic forms exist? Therefore,
> new drug applications tend to begin with polymorphic screening or what
> we call diligent polymorphic screening.
>
> Part two is routine polymorphic testing of drug substances. \"DS\"
> stands for drug substance. \"DP\" stands for drug product valuable.
> Part three is routine polymorphic testing of drug products valuable.
> So this is to see if there is a need to set up acceptance criteria for
> drug substances or drug products for new drug applications.
>
> \[Slide\]
>
> Now let me introduce very briefly biopharmaceutics classification
> system concept, which has been discussed many, many times at this FDA
> advisory committee meetings, previous meetings. As you can see here,
> when a solid dosage form, such as a tablet or capsule, is given to a
> patient the solid form tablet or capsule will disintegrate in the
> stomach. Where the disintegration of the tablet or solid dosage forms
> will occur, dissolved and undissolved drug will be emptying from the
> stomach to the small intestine where the solution or disintegration
> continues to occur so the dissolved drug will cross the intestinal
> membrane, going through the liver and reach the systematic
> circulation.
>
> So, the processes involved in this determines rate and extent of
> absorption including gastric emptying, transit, dissolution,
> absorption and metabolism. When we talk about the bioequivalence
> studies, the factors involved in dissolution and absorption have a
> potential effect of products\--gastric emptying, transit and
> metabolism will be involved but most unlikely. Because of that, we
> have a dissolution rate and we have an absorption rate. The solution
> rate can be expressed traditionally in equations as we have here. We
> have D as the diffusion coefficient; S as dissolution surface area; H
> as aqueous boundary thickness; C as solubility and Cl as concentration
> in the dissolution media. Absorption rate as a determining factor is
> the permeability. So for the dissolution rate another big determining
> factor is solubility. So, the key factors involved in limits to the
> oral drug absorption here are solubility and permeability\--from
> solubility to permeability, two key parameters.
>
> \[Slide\]
>
> So, basically this is how the BCS was developed. The biopharmaceutics
> classification system is a scientific framework for classifying drugs
> based on their aqueous solubility and intestinal permeability. When
> you have two variables, each variable has two levels. You have four
> classes, as shown here. Class I we call highly permeable, highly
> soluble compound. Class II is poorly soluble, highly permeable. Class
> III is highly soluble, poorly permeable. Finally, Class IV is poorly
> soluble and poorly permeable. This has bee a scientific investigation
> for the last ten years.
>
> \[Slide\]
>
> The title of the guidance was waivers for [in vivo]{.underline}
> bioavailability and bioequivalence studies for immediate release solid
> oral dosage forms based on the biopharmaceutics classification system.
> The guidance was mainly drafted by Dr. Ajaz Hussain, who is sitting
> here. This guidance basically correlates [in vitro]{.underline}
> dissolution to [in vivo]{.underline} absorption. That is why, on this
> scientific principle and knowledge, you can use [in vitro]{.underline}
> dissolution in [in vivo]{.underline} studies.
>
> \[Slide\]
>
> Having said that, we come back to the decision tree for polymorphic
> forms. Basically, we have developed three decision trees for
> polymorphic forms in abbreviated new drug applications. Decision tree
> number one investigates the need to set acceptance criteria of
> polymorphic forms. In other words, we want a decision tree if there is
> a need to set up acceptance criteria for drug substances and drug
> products. If there is no need, then there is no need for us to look at
> the decision tree number two and decision tree number three.
>
> If there is a need in decision tree number one, we come to decision
> tree number two. Decision tree number two, instead of evaluating if it
> is necessary to set acceptance criteria for a drug substance, it tells
> you how to set basic acceptance criteria for a drug substance.
>
> Decision tree number three basically illustrates if there is a need to
> set acceptance criteria for drug products and if there is a need how
> to set up acceptance criteria for drug products.
>
> \[Slide\]
>
> Now let\'s go into detail one by one for these three decision trees.
> That is the center for our discussion today. Starting with the first
> question, are there known polymorphs with different apparent
> solubility? If the answer to this is no, then basically no further
> testing of polymorphic acceptance criteria for both drug substance and
> drug product is necessary.
>
> If the answer is yes, we come to the next question, are the known
> polymorphs highly soluble? In other words, are all these polymorphs
> highly soluble? If this answer is yes, then you come to the no further
> testing of polymorphic acceptance criteria for drug substance and drug
> product. If the answer is no, you go to decision tree number two.
>
> I spent three slides to introduce the biopharmaceutics classification
> system. What this means is I introduced the solubility classification
> in order to answer this question. Are all known polymorphic forms
> highly soluble based on the BCS solubility criteria, classification
> criteria from BCS classification system?
>
> Let me explain, first, there are known polymorphs with different
> apparent solubility. Why do we ask this question up front? Let me
> introduce that.
>
> \[Slide\]
>
> In the ICH Q6A decision trees start with due diligent polymorphic
> screening. This is for innovators, for NDAs. For ANDAs we tend to
> receive many, many applications, sometimes up to 20, for the same drug
> substance. So, because each company uses a different route of
> synthesis or sometimes uses a different process it gives FDA reviewers
> a good picture of what might be happening, what might be going on for
> this specific drug substance. In general, each applicant needs to have
> adequate knowledge of drug substance polymorphism to make appropriate
> decisions, otherwise we don\'t know whether it is necessary to set up
> criteria or not. So, we have to have adequate knowledge of the drug
> substance polymorphic forms to make appropriate decisions. Each
> applicant has a unique approach. They may use different unique
> approaches to address polymorphic issues. The knowledge or information
> on polymorphic forms may come from literature; may come from patents;
> may come from compendia; may come from experience or whatever approach
> the generic company uses.
>
> DR. LEE: Oh, I think this is Les.
>
> DR. BENET: Yes, this is Les.
>
> DR. LEE: Les, welcome to the committee.
>
> DR. BENET: Thank you. I can\'t get on to the video because I don\'t
> know my password, or something.
>
> DR. YU: Shall I continue?
>
> DR. LEE: Yes, please.
>
> DR. YU: I want to repeat this slide since it was interrupted. In
> general FDA receives many ANDA applications for the same drug
> substance. Each sponsor will need to have adequate knowledge of drug
> substance polymorphism in order for them to make appropriate
> decisions. Each applicant has a unique approach to address polymorphic
> issues and the polymorphic information may com from literature,
> patents, compendia, their own experience or whatever approach they
> prefer or they want to use.
>
> The key point here is that decision tree number one emphasizes
> knowledge to convince us, FDA, to say you now can reproducibly or
> consistently manufacture generic products which are equivalent to the
> reference listed products. We emphasize knowledge; we emphasize
> information in the decision tree for different approaches. You may
> choose your own approach and we want to know that knowledge and
> information to convince us that you can consistently, reproducibly
> manufacture the quality product which is equivalent to the reference
> listed product.
>
> \[Slide\]
>
> Also I want to discuss examples of polymorphs appearing and
> disappearing, sometimes called the mystery of polymorphism. As you can
> see for this specific product, we have alpha, beta and gamma. The
> melting point for the alpha is 59-60, beta 63-64, gamma 69-70. So,
> there are three polymorphic forms. In 1921 alpha and beta were
> discovered in Australia. All alpha converted into beta. As you know,
> there are many, many polymorphic forms. The most stable form tends to
> survive. When you start with polymorphic screening you tend to
> discover the least stable form first and the most stable form you will
> discover last. So, once you discover the most stable form, in many,
> many cases you actually cannot go back to discover the least stable
> form or even use the same approaches, in this case alpha converting
> into beta but not gamma.
>
> About 15 years later the gamma was discovered in a different country.
> In this case either alpha or beta converted into gamma. This basically
> follows the principle of a theory of thermodynamics because the most
> stable form will exist. So, the unstable forms, like alpha and beta
> convert into the gamma. However, 50 years later alpha was discovered
> in India, and no beta and even gamma is mentioned. So, what I want to
> say with this slide is with the current technology that we have right
> now it is very difficult, even with due diligent screening, to say I
> have discovered all the polymorphic forms. It is very difficult to
> say. So, in this regard we have to take risk management. We have to
> evaluate risk versus benefit\--risk versus benefit.
>
> \[Slide\]
>
> Also, in decision tree number one we have to address thoroughly the
> stability. This BACPAC guidance applies to new drugs as well as to
> ANDA. Generally, only two physical properties of the drug substance,
> morphic form and particle size, are considered critical for evaluation
> of equivalence. So, in order to show the equivalence of physical
> properties conformance to established acceptance criteria for morphic
> form, or where acceptance criteria do not exist, the isolation of the
> same form or mixture within the range of historical data. This is the
> basic BACPAC I.
>
> What I want to show is that even though it is not necessary to set
> acceptance criteria under all kinds of scientific considerations,
> there is not much risk to not setting up acceptance criteria but
> scientifically it is a good idea to have initial scientific
> characterization of the polymorphic forms using different approaches,
> such as x-ray powder diffraction, DSC/thermoanalysis, microscopy
> and/or spectroscopy, to provide historical data even though FDA does
> not ask for acceptance criteria for drug substance forms and drug
> products, it is still a good idea to have initial characterization so
> in the future if a manufacturing process changes you know that the
> polymorphic form is equivalent to the original form manufactured.
>
> \[Slide\]
>
> Now let\'s move to decision tree number two. In decision tree number
> two the first question is, is there a polymorphic specification in the
> USP? If the answer is no, you basically set up new polymorphic
> acceptance criteria. If the answer is yes, you basically evaluate if
> the USP polymorphic specification is adequate. If it is adequate, if
> it is okay you basically set up USP polymorphic specification. If it
> not, you set up new polymorphic specification.
>
> Why is that? Let me explain why. In general USP does contain melting
> point ranges but not necessarily polymorphic specifications. So even
> though the melting point range may be considered as a specification,
> FDA wants to evaluate to make sure that the melting point in the range
> of the specification is specific, unique and what is the intent of the
> so-called polymorphic specification. If there is no polymorphic
> specification in the USP, certainly we will say set up new criteria.
> Even if for the generic form you use different polymorphic forms, even
> though the USP has a very good specific specification, this
> specification may not be sufficient for the generic firm so this time
> we have to set up a new specification. So, decision tree number two is
> a little bit straightforward.
>
> \[Slide\]
>
> Let\'s move on to decision tree number three. That is a little bit
> complicated for drug products. The first question we ask is, is there
> sufficient concern that polymorphic acceptance criteria for a drug
> product should be established? This time we ask a scientific question
> for each individual application to see if there is concern. If the
> answer is no, certainly there is no need to set polymorphic acceptance
> criteria for drug products. If the answer is yes, go to the next
> slide.
>
> Let me explain what is sufficient concern. It sounds ambiguous; it is
> very difficult to understand. Let me explain why. If there is in
> general\--I want to emphasize the two words, \"in general,\" not
> always but in general so there are exceptions. In general, there
> should not be a concern if the most stable polymorphic form is used or
> the form is used in a previously commercialized product. That gets a
> little bit tricky because for a specific drug substance where there
> have never, ever been discovered any crystal forms and the only form
> we have had is an amorphous form. So, we know amorphous exists, exists
> very nicely as relatively stable.
>
> So, in this case most likely it is not necessary for us to have a
> concern. However, if we know that a crystal form exists and we know
> the reference listed drug uses the amorphous form there is a potential
> for this amorphous form to convert into a crystal form and under this
> scenario there is a concern. So, therefore, we have to look in general
> in many cases we have to look case by case, but the principle is that
> in general there should not be a concern if the most stable
> polymorphic form is used or the form is utilized in a previously
> commercialized product. In your background information we say
> extraordinary formulation or manufacturing process effort. This has
> sometimes been deleted. This means work in progress.
>
> \[Slide\]
>
> If the answer is yes, the next question is does the drug product
> dissolution testing provide adequate controls if the polymorphic ratio
> changes? If the answer is yes, you basically use the solution as test
> to set up criteria, otherwise you will have to use solid state or
> other criteria. For the acceptance criteria for the drug product you
> may use other approaches such as solid characterization method, which
> is much more complicated.
>
> Why do we think in general dissolution can be utilized for the testing
> if the polymorphic ratio changes? Let\'s look at the BA/BE guidance
> here. It is recommended that the sponsor select the agitating speed
> and medium that provide adequate discriminating ability, taking into
> account all the available [in vitro]{.underline} and [in
> vivo]{.underline} data. So, we believe that the solution test can
> frequently detect the potential conversion of polymorphic forms. In
> rare cases solid characterization methods have to be utilized.
>
> \[Slide\]
>
> So in this presentation I have discussed what is polymorphism; how
> does the polymorphic form affect pharmaceutical properties of drugs;
> and to what extent should scientific considerations be given to
> polymorphism in ANDAs. Thank you for your attention and thank you for
> your time.
>
> DR. LEE: Thank you, Lawrence. Are there any questions for Lawrence?
>
> DR. MOYE: Yes, I have two points that are really going to demonstrate
> my ignorance about this. This discussion of polymorphism is bringing
> back memories. Not all of them are good memories but they are
> memories.
>
> You made, I thought, a very clear demonstration for the argument that
> polymorphs are worthy of investigation. You set up a scheme which
> reflected the observation, I think, that we have to be concerned about
> more than solubility. We also have to be concerned about permeability.
> Right? That is why you have the 2 X 2 table.
>
> DR. YU: Correct.
>
> DR. MOYE: So it is possible that polymorphs could have low solubility
> and high permeability.
>
> DR. YU: Correct.
>
> DR. MOYE: It is also possible that they could have high solubility but
> low permeability.
>
> DR. YU: Correct.
>
> DR. MOYE: So now I am confused. When we go to your flow chart on the
> first slide\--and I didn\'t want to interrupt your presentation when
> you were bringing it up\--can you explain to me if polymorphs can be
> highly soluble but have low permeability, why you say there is no
> further testing if all known polymorphs are highly soluble? Isn\'t it
> possible that they could be highly soluble but have low permeability
> and wouldn\'t you want to know that? I mean, what did I miss?
>
> DR. YU: Thank you for your excellent question.
>
> \[Slide\]
>
> What this means is if all known polymorphic forms are highly
> soluble\--what this means is in general the solution of a drug
> substance will have a limited effect on bioavailability. Now, they
> could have a different permeability, like ranitidine, but as long as
> the polymorphic form is highly soluble the effect of the polymorph on
> bioavailability, the chance is very low. Therefore, we feel it is not
> necessary to do any further testing or acceptance criteria.
>
> DR. MOYE: So, to make sure I understand your answer, you are saying
> that if all of these polymorphs are highly soluble\--
>
> DR. YU: Correct.
>
> DR. MOYE: \--you are saying it is unlikely that you will have some
> with high permeability and others with low permeability?
>
> DR. MEYER: I think the answer to that is probably that if they are
> highly soluble they go into solution quickly, and once they are in
> solution then all things are equal in terms of permeability.
>
> DR. MOYE: Thank you. I have one other question. I was trying to follow
> this BACPAC acronym you mentioned. Let me just ask you directly, could
> BACPAC be used to avoid complete testing of the characteristics of
> polymorphs using state-of-the-art procedures? In the interest of time,
> let me ask what I really want to ask here.
>
> DR. YU: Could you say that again, please?
>
> DR. MOYE: Yes, could this BACPAC be used as a way to avoid complete
> testing using state-of-the-art procedures for the characteristics of
> polymorphs? Are you providing a way for people not to test with
> BACPAC?
>
> DR. YU: No. In the decision tree we basically take account mainly of
> solubility. We have not taken account of stability. Hopefully,
> stability will be taken care of by BACPAC I. That specifically means
> if there are no acceptance criteria for drug substance or drug
> products, if there is any possibility\--number one, if there are no
> acceptance criteria for a drug substance and drug products with
> respect to polymorphic form, that is number one. Number two, under
> this scenario if there is any possibility of something going wrong
> with respect to the polymorphic form change, this is where we want to
> go back to BACPAC I because BACPAC I is suggested to have an
> equivalency test. In other words, if you make some process changes,
> make sure that the polymorphic form has not been changed.
>
> DR. MOYE: So, is the idea that it is too burdensome to replace that
> last phrase with further research has to be carried out to examine the
> characteristics of polymorphs rather than rely on historical data? I
> guess I am just asking why rely on historical data if there is the
> opportunity to gain new data even in the absence of acceptance
> criteria.
>
> DR. YU: You are basically suggesting if it is always necessary to have
> acceptance criteria.
>
> DR. MOYE: I think I am just revealing my ignorance here.
>
> DR. YU: Certainly, if there is no need\--there is a difference in
> terms of initial categorization of polymorphic form and so-called
> acceptance criteria. Acceptance criteria just means you need to test
> every single batch. For initial historical data, this means you do not
> have to test for every single batch once it is released. For
> scientific data it is not necessary for the firm to do extra work
> without value added. That is what we mean here. Certainly, we want to
> make sure the form has not been changed and then we have the BACPAC I
> guidance.
>
> DR. LEE: Anybody else? Do you have any questions for Lawrence?
>
> DR. RODRIGUEZ-HORNEDO: I have a brief question. Can you hear me?
>
> DR. LEE: Yes, we can hear.
>
> DR. RODRIGUEZ-HORNEDO: Lawrence, I would like to hear your comment on
> whether the term polymorphism on your molecular adduct will cover
> other than solvates. Say that you have an excipient within a
> crystalline matrix that is not a solvate\--I don\'t know of anything
> on the market like that but we may be seeing something in the future.
> Say you have an active excipient and you have a sugar in a crystalline
> matrix.
>
> DR. YU: I am not quite sure I understand the question but I will try
> to answer. If not, please ask again. I have one slide to differentiate
> crystalline form, amorphous form, hydrate and nonstoichiometric. I
> think your question, to come back to this specific case, is whether a
> crystal form, such as stoichiometric solvates or hydrates, or
> nonstoichiometric inclusion compound\--you could have a channeling,
> layering or caging. What you are referring to is probably caging
> instead of solvate or hydrate.
>
> DR. RODRIGUEZ-HORNEDO: I was referring to a stoichiometric system. Say
> that you have a 1:1 ratio where instead of water and an active product
> ingredient you have a sugar and an active product ingredient. Would
> that substance fall into this category of polymorphs?
>
> DR. YU: Ken, you seem to understand, can you repeat the question?
>
> DR. MORRIS: Yes, this is Ken. You are saying essentially if you have
> either a co-crystal or a solid dispersion with another substance in
> addition to the chemical entity. Right?
>
> DR. RODRIGUEZ-HORNEDO: That is correct, Ken.
>
> DR. MORRIS: Right. So, she is asking whether or not if in addition to
> my molecule I now have a 1:1 correspondence between not a salt or a
> pro-drug but a separate molecule that co-crystallizes into the same
> regular structure, does that get considered as a polymorph since the
> chemical entity is the same?
>
> DR. SHEK: Is the chemical entity the same?
>
> DR. MORRIS: Well, you are assuming another solvate. You are assuming
> that the co-crystal component is not the active ingredient. Is that
> correct?
>
> DR. RODRIGUEZ-HORNEDO: That is correct. Instead of water, let\'s say,
> a hydrate or another solvate you would have a sugar.
>
> DR. MORRIS: So, you have a glucose\--
>
> DR. RODRIGUEZ-HORNEDO: Yes.
>
> DR. SHEK: What will be the difference between that to a complex, and
> the question is whether that is still the same entity.
>
> DR. YU: So, what will be different between solvates\--
>
> DR. HUSSAIN: I think that is not just one entity; that is more than
> one entity. Solvates is slightly different. If there is an intentional
> co-crystallization it becomes a slightly different question I think.
> That is not what I think what the polymorphism discussion is about.
> So.
>
> DR. RODRIGUEZ-HORNEDO: Well, perhaps that is something that could be
> discussed.
>
> DR. CHIU: If a crystal contains the sugar and the active ingredient in
> a complex, you know, it depends on what kind of bounding it has. If it
> is covalent bound, then it becomes a new molecular entity. If it is
> not covalent bound it would be a complex. So, based on our
> classification of drugs, the first one would be classified as type one
> and the other one would be type two. So, it is not considered
> polymorphous anymore.
>
> DR. RODRIGUEZ-HORNEDO: Thank you for the answer. That is something to
> be discussed later I think because if we think of water, water is
> hydrogen bounded to the active ingredient in the crystal, to the
> active substance. What I am thinking of is uncovalent bounding.
>
> DR. LEE: Go ahead.
>
> DR. MORRIS: I was just going to say I think the precedent, in part, is
> if you are going to distinguish that with the crystal, then what
> happens when you start talking about glass solutions, which is already
> approved as the same thing in some cases? So, you are treading a thin
> line there. It has to be negotiated I think.
>
> DR. LEE: Well, let\'s focus on polymorphism and then move on to other
> entities.
>
> DR. YU: Correct, yes.
>
> DR. LEE: Thank you very much, Lawrence. Let me call on Ken Morris and
> then Dr. Les Benet.
>
> **Expert Comments**
>
> DR. MORRIS: Thanks, Lawrence. Thanks for inviting me, Ajaz and Vince.
>
> \[Slide\]
>
> What I was asked to do by Lawrence was to comment on the questions
> that you have regarding the decision trees. I should preface this by
> saying that at the last scientific advisory board, where I was a
> guest, I made a couple of observations on the presentation Steve
> Miller gave about the results of the workshop on deciding what
> polymorphic screening strategy should be employed, and one of the
> things that we discussed was impurities, which we will get back to.
>
> This led to a discussion from OGD that included the concept of sort of
> focused screens for the purpose of ensuring purity with respect to
> generics. So, that is sort of the backdrop of this and how my hat got
> into the ring. In case you don\'t know, I am from Purdue University.
>
> \[Slide\]
>
> The questions are detailed here that were posed to us, myself and Les.
> Do the proposed decision trees adequately address the key polymorph
> issues? Decision tree number one specifically; decision tree number
> three specifically; and then additional considerations. I have sort of
> broken this down\--I only have ten slides here I think\--into those
> subdivisions as a framework for what I am going to say.
>
> \[Slide\]
>
> I had to take this opportunity though before I start because it is
> going to look like I am taking some shots at the decision trees, but I
> want to state at the outset that the decision trees, to me, represent
> a real advance over the old check-list approach, and having grown up
> in industry using check lists and being frustrated with the fact that
> you couldn\'t use them very effectively much of the time, I really see
> this as a big advantage. It really encourages the inclusion of proper
> scientific processes. It gives you the opportunity to make decisions
> based on the science and proceed based on your decisions, and gets rid
> of a lot of this incentive for testing into compliance so you can
> finish your check list in time to not be the bottleneck in
> development.
>
> It also allows the industrial scientist to logically develop
> appropriate tests. This is fairly important and one of the things we
> will talk about. I think that if you are faced with a check list and
> you are restricted to certain tests you will use them and try to make
> them work even when it flies in the face of the logic.
>
> It also, in my experience, facilitates rational risk assessment by the
> regulatory and management teams within industry as well as FDA.
> Finally, and perhaps more relevant for today\'s discussion, it really
> does level the playing field for generic companies by allowing
> establishment of reasonable expectations based on the science instead
> of holding them to unreasonable goals.
>
> \[Slide\]
>
> Let\'s sort of progress the way we outlined. The first issues
> were\--and I sort of combined these a little bit\--do the proposed
> decision trees adequately address the key polymorph issues?
> Specifically for one, are there other issues with respect to
> characterization that FDA should consider?
>
> I have couched these comments basically in the contest of sameness
> rather than the definition of sameness, rather by the fact that
> amorphous forms, solvates, hydrates are considered under the same
> umbrella. We talked about this last time a good bit.
>
> Given that, the first comment I have for decision tree one is that if
> polymorphs are not known, or no monograph is available, do they have
> to be screened for? I think you have sort of answered this question to
> a degree, Lawrence. I think the answer to the question is yes. The
> open literature will very often contain a fair amount of data on older
> compounds and high profile compounds but there will be some for which
> it doesn\'t exist, or if they are so old that it didn\'t get the sort
> of scrutiny that you want, or if you are changing dosage forms. We
> will get to this later but it sort of reflects on Prof. Rodriquez\'
> question.
>
> Additionally, the solubility determination of meta-stable forms really
> has to be scrutinized for conversion artifact. So, if you are looking
> at the criteria of are all known polymorphs highly soluble, aside from
> the question of what constitutes high from not high solubility, which
> I think is a little more straightforward for most of us, you have to
> be very careful when you are trying to determine the solubility of
> meta-stable forms. It has been well established for years that you
> will get conversion. So, if you measure the solubility at an infinite
> time scale for any form it will always be the solubility of the most
> stable form. The question of the kinetics of conversion and of other
> techniques which are relatively well known for estimating the
> solubility of meta-stable forms would have to be included in this sort
> of a rationale and certainly in terms of the review of such an
> application.
>
> \[Slide\]
>
> Just a comment on melting point as an ID test for all of the forms
> under consideration, again given the fact that this includes
> everything from amorphous forms through solvated forms, we have to be
> pretty careful when we use a melting point as a test. The reason is
> sort of illustrated here with a paper from Matsuda that shows the
> powder x-ray fraction DSC and TGA for\--what is it?\--six different
> forms of the same compound in principle.
>
> Sort of like the example that Lawrence had shown, if all you do is do
> a quick melting point scan, either using a melt temp or even an
> inexperienced thermoanalyst, you will end up with one melting point
> for all these forms, yet they are very dramatically different not only
> in their crystal structure but in their thermal behavior. Some are
> solvates; some are hydrates; and some are what would traditionally be
> called polymorphs. Lawrence and I have spoken about this before his
> presentation, but the more revealing yet common tests may be much less
> ambiguous and require similar resources. By the time you determine
> melting points and determine that the melting point is what you think
> it is, it may have been just as cost effective to run a powder x-ray
> diffraction pattern or have it contracted out.
>
> \[Slide\]
>
> Moving on to number two, which is highlighted here in blue with
> Lawrence\'s point of different polymorphic forms and allowing tighter
> specification, tighter specifications may have to be negotiated with
> changing suppliers. This is a little bit similar to the excipient
> discussion we had earlier today. One of the things that came out of
> the last scientific advisory board was this fact that on sale-up
> perhaps the largest source of unexpected polymorphic forms showing up
> is differences in purity profiles. Nair has several elegant examples
> of this but I think those of us who have worked in API can tell you,
> as Steve Berne always says, the best polymorph screen is to scale up.
>
> This is in part because as the chemists get better at developing their
> synthetic pathways, the material gets purer and typically impurities,
> if anything, will tend to stabilize meta-stable forms, and this is
> often the case with these disappearing polymorphs that David speaks
> about in his talks. As a note, virtually all of the disappearing
> polymorphs can be recrystallized using sometimes Herculean efforts but
> can be found again, which speaks to the same issue. Therefore, when
> you are changing a supplier, whether you are changing your own process
> within your company or whether you are getting it from a different
> source, differences in impurity profiles really should be included.
>
> Also, included in this, I would say for your own safety if I am using
> raw material, particularly API that I am getting from a third party, I
> would very much want to know, if not have a say in the final
> crystallization and drying conditions. People are very reluctant to
> open up their DMFs even if you are a good customer, but typically they
> will share that with you. Even if they won\'t share the specifics of
> synthetic pathways, they will almost always share that with you.
>
> \[Slide\]
>
> Another issue that I think comes from that decision tree and speaks a
> little bit to what we talked about last time is what is reasonable.
> So, if you are going to ask companies\--instead of an innovator
> company that may only have three to five projects a year, if you are
> going to ask a company that has forty projects a year to do this sort
> of an assessment early on in their program, what is a reasonable
> request versus an unreasonable request when you are doing what I would
> call a more focused polymorph screen?
>
> This comes actually from the workshop that we had with OGD but I have
> sort of broken the levels of difficulty in terms of characterization
> of polymorphs into what is routine; what is difficult and sometimes
> unreasonable; and what is sort of cutting edge and not realistic to
> expect unless something is really on fire.
>
> In the routine section what I have included is identification and
> quantitation of mixed phases in the API itself. I wouldn\'t say this
> is trivial to do but it is really quite routine. It can be done by
> powder x-ray diffraction, thermal analysis and spectroscopic methods.
> These days, as we talked about last time, you can buy a relatively
> inexpensive powder x-ray diffraction unit for about the same price as
> an HPLC. So, it is not really talking about a different level of
> investment in terms of resources.
>
> The other thing that I consider to be quite routine is identification
> of high levels of mixed phase in product. It has to be relatively
> high, obviously, for reasons that we can discuss if anybody is, you
> know, still dying to talk about this. I know Art is.
>
> What is difficult and perhaps unreasonable on a case by case business
> is quantitation of trace amounts of phases in API and product. But if
> you have very small amounts of a phase in an API, forget the product
> for the moment but in the drug substance itself, it can be very
> difficult to determine.
>
> One of the most sensitive methods is differential scanning calorimetry
> but because of the tendencies for transformation during the experiment
> this may be problematic. X-ray is, of course, our sort of gold
> standard by the levels of detection can be quite high, and we will
> talk about that in a moment. You can do it by synchrotron which is
> becoming more accessible. This is why it is in the difficult and not
> impossible or cutting edge section. Raman mapping, which is becoming
> very much more common and, in fact, Ajaz showed some spectroscopic
> maps that sort of reflect the fact that the technology has really
> caught up with the need in terms of a lot of these mapping strategies.
> Advanced powder x-ray diffraction\--I will show you a quick example
> which allows us to look at small amounts in API and product.
>
> The other difficult category I have here is quantitation of phases in
> drug product. This is particularly true of amorphous systems because
> with a crystalline compound you have the advantage that you have
> specific signature or fingerprint of the crystal structure to deal
> with. With amorphous, by definition, you have an amorphous signature
> to deal with which means it is not distinct and it is certainly not
> directly relatable to a structure as far as we know.
>
> But even with two crystalline phases, two or more crystalline phases
> in drug product, if it is not at the high level that we talked about
> in the routine, it immediately drops into the difficult and perhaps
> unreasonable.
>
> Finally, for cutting edge I have here as prediction of structures from
> powder patterns. This is becoming more and more prevalent and,
> hopefully, within the next five years will become, if not routine, at
> least be promoted into the difficult category which will allow us to
> look at changes that may occur, relate them to a specific structure
> and then be able to reproduce the material and determine any
> liabilities.
>
> \[Slide\]
>
> I won\'t go through this chart but this is something I use when we
> teach solids to the graduate students. Basically, it is the sort of
> thing that I think would properly be in any sort of document that a
> generic or innovator company, likewise, would be using in terms of
> looking at their screen. That is, to detail the solid modifications
> that are possible and then at least give a representative response
> that you might expect to see for specific methods of analyses. We have
> an analogous table that talks about the levels of detection and the
> levels of quantitation to be expected as well for different types of
> systems.
>
> \[Slide\]
>
> Moving on to number three, which starts with the previous slide and
> now talks about the drug product, and with the notation that you saw
> earlier with dissolution testing frequently detecting potential
> conversions which certainly is the case often. There are a couple of
> caveats here. One of those is that dissolution testing may often be
> correlated to known transformations, but if you don\'t know the
> transformation then the chances of correlating this become much
> smaller of course. In fact, you may get transformations during
> dissolution testing that are relatively unimportant [in
> vivo]{.underline}. You don\'t really know that from the face of it
> because if dissolution occurs quickly enough and absorption occurs you
> may not really see the effect of it until you get to bioavailability.
>
> Given the demonstrated liability, if you know you have a liability for
> inter-conversion during dissolution, should the statistics be
> improved? That is, should you be looking at larger numbers of samples?
> It is a little bit like our discussion earlier, but here you have a
> very focused target with respect to the numbers of tablets if you are
> using dissolution testing, and it depends not only on just the raw
> number of tablets but on how reproducible the profiles are.
>
> As the final point on this topic, there may be other techniques. Even
> though it says in rare cases solid characterizations may have to be
> used, in some cases it may be that other techniques are less energy,
> less resource intensive than dissolution testing which might allow
> better statistics with less incremental investment. This falls fairly
> neatly into the PAT discussion actually but, for those of you who are
> not aware of that, there are some other techniques that are in play.
>
> \[Slide\]
>
> The observation on the last decision tree that the most stable form is
> used or the form used in a previously commercialized product means
> that there shouldn\'t be a concern, and certainly this is logical on
> the face of it but there are a couple of points that center on
> amorphous and hydrated forms that Lawrence touched on. I have sort of
> detailed here in brief fashion. Amorphous forms may have been
> stabilized by unique formulation or processing strategies not easily
> reproduced. Under those circumstances this should be included as a
> cautionary statement. In other words, if you are formulating with an
> amorphous compound that has been the subject of some specific
> formulation strategy to make it stable, which is usually the case.
> There are I don\'t know how many amorphous forms that are stable on
> their own but not very many, I can tell you that. Then, this may be an
> additional caution for somebody reformulating.
>
> Hydrates are easily altered in subsequent processing. This has been
> demonstrated over and over again. So, I would say that this statement
> in general should not be a concern if there may be a number three here
> that encompasses something of a caveat with respect to amorphous and
> hydrated forms. We should realize, given these statements, that it is
> possible to build in in-product characterization as a requirement if
> you have established that there could be changes. So, you have to
> establish whether or not that is important fairly early on, otherwise
> you may be building in a level of testing that need not necessarily
> relate to the performance.
>
> \[Slide\]
>
> The second to the last part of the question was on approaches and
> challenges for establishing specs for polymorphs in products and also,
> in your experience, how often would you anticipate such a spec is
> necessary?
>
> Let me answer the second part first. I would say only occasionally
> usually. On the other hand, when it is important it is very important.
> To this end, I would reiterate something that Lawrence alluded to and
> I said last time, which is that a focused polymorph screen early in
> the development process for a generic is a great investment. It is a
> relatively low resource activity and it could save you an awful lot of
> problems down the road.
>
> These are just examples of powder x-ray diffraction methods for drug
> substance in a product. This is again a relatively high dose so it
> falls into our almost routine category. But in the range from 3-30
> percent we have an RSD of 5 percent and good recovery. This is from
> work that Dave Bugay and Ann Newman have done, and I believe published
> when they were still at Bristol-Myers Squibb.
>
> \[Slide\]
>
> Here is an example of the analysis on a pretty much traditional powder
> x-ray diffraction lab machine using a bit of an alteration of parallel
> optics, showing the calibration curves of glycine compacts. So, we are
> analyzing the whole compact now in transmission mode x-ray
> diffraction. Here we are getting down to approximately 0.5 percent
> calculated detection limit, and very good linearity for the two forms.
> Now, even this is within a compact, this isn\'t a tablet; this is all
> drug substance so this is just a hint of things to come. I would not
> call this routine in any sense of the word.
>
> \[Slide\]
>
> The last slide I have is on the additional considerations that should
> be addressed on the issue of manufacture ability or process ability
> when different forms are present.
>
> This is a great question. The downside is that so little is known that
> it is a little too early to answer it. It is a subject of ongoing
> research in Minnesota and Purdue and in many companies, many of the
> companies discussed here today. The issue should be addressed when the
> potential is identified in formulation or process development,
> however. This could be acknowledged in the charts. The idea that by
> the time you get to processing, that is not really the time you want
> to start doing your exploration in terms of what problems you are
> going to have during processing. You would like to try to identify
> those early given all of the subtleties and vagaries of scale-up in
> the way we do it. Maybe this will become valuable as background for
> companies in subsequent trouble-shooting as well and, certainly, when
> looking for root causes you would like to have this in your back
> pocket.
>
> That is the extent of what I had to share. I will be glad to entertain
> questions if there are any.
>
> DR. LEE: Thank you, Ken. Any questions from the committee members?
>
> \[No response\]
>
> Thank you. Les, are you available?
>
> DR. BENET: I am here.
>
> DR. LEE: Good. The AV specialist asks you not to use your speaker
> phone, if possible.
>
> DR. BENET: Okay.
>
> DR. LEE: Thank you. Please proceed.
>
> DR. BENET: I can\'t get off it. I have to call you back.
>
> DR. LEE: No, don\'t go away.
>
> DR. BENET: I can\'t get off the speaker phone without disconnecting.
>
> DR. LEE: I see, okay.
>
> DR. BENET: I can do that; I will call you right back.
>
> DR. LEE: Thank you. Nair, are you still there?
>
> DR. RODRIGUEZ-HORNEDO: Yes, I am here.
>
> DR. LEE: Are you using the speaker phone?
>
> DR. RODRIGUEZ-HORNEDO: No, I don\'t have a speaker phone.
>
> DR. LEE: Good, Les, you sound much better. Thank you very much. Please
> proceed.
>
> DR. BENET: Thank you for giving me the opportunity to make a
> presentation. I apologize for getting on late but I was having trouble
> connecting to FDA because I didn\'t know my password. In addition, as
> opposed to last year when I did this, I can\'t get a very large view
> of what is being presented so I am really having difficulty seeing the
> slides but I will move forward to my first slide.
>
> \[Slide\]
>
> Lawrence asked me to discuss considerations of polymorphism in
> therapeutic equivalence.
>
> \[Slide\]
>
> So, my short answer is no altered regulatory approach is necessary,
> Vince, if you are running out of time, I can stop right now.
>
> \[Laughter\]
>
> DR. LEE: No, Les. No, we encourage you to elaborate a little bit.
>
> DR. BENET: Okay. So, under those conditions, let\'s look at the
> definitions and the criteria related to therapeutic equivalents and
> where polymorphism considerations might be relevant.
>
> \[Slide\]
>
> If we look at the FDA definition of therapeutic equivalents, it is as
> quoted here: drug products are considered to be therapeutic
> equivalents only if they are pharmaceutical equivalents, and they can
> be expected to have the same clinical effect and safety profile when
> administered to patients under the conditions specified in the
> labeling. So, we have terms that need to be defined within there,
> pharmaceutical equivalents and expected safety and efficacy profile.
>
> \[Slide\]
>
> On this slide we have the four criteria that are listed for
> pharmaceutical equivalents: The product must have the same active
> ingredient; must have the same dose form, given by the same route of
> administration; and identical in strength or concentration. We will
> return to these four criteria in a minute.
>
> \[Slide\]
>
> Let\'s go back to the definition of therapeutic equivalents in terms
> of the criteria of same clinical effect and safety profile.
>
> \[Slide\]
>
> Under FDA regulations what criteria must be met for expected same
> clinical effect and safety? First is the products must meet compendial
> standards, and we will talk about that for a second. So, if a
> particular polymorphic form or the limits of a particular polymorphic
> form in terms of physical chemical criteria are required in the
> compendial drug product monograph and a product fails these criteria,
> then the product cannot be considered therapeutic equivalent.
>
> There are things that at least look like there are these kind of
> criteria in the compendial standards. If we look at warfarin sodium,
> it talks about a crystalline form versus an amorphous form. But if it
> did not meet the compendial standards, then there is no way that a
> compound can be therapeutically equivalent independent of any biologic
> studies.
>
> \[Slide\]
>
> The second area is that to have expected same clinical effect and
> safety, it must meet appropriate bioequivalence standards. As you all
> are aware, that means that it must have comparable bioavailability,
> and the FDA published definition says the rate and extent of
> absorption of the test drug does not show a significant difference
> from the rate and extent of absorption of the reference drug when
> administered in the same molar doses, the same therapeutic ingredients
> under similar experimental conditions in either a single or a multiple
> dose.
>
> \[Slide\]
>
> So, what we need to look at is significant difference and under
> similar experimental conditions, as I show highlighted on this slide.
> The significant difference definition is 80-125, and I have been very
> pleased this past year with the FDA changing the terminology in the
> Orange Book in terms of the what the criteria are and the fact that it
> is not just 80-125 but it must be within the 90 percent confidence
> interval around the Cmax and AUC.
>
> \[Slide\]
>
> So, the question on this slide then is can polymorphism affect rate
> and extent of bioavailability? The answer of course is yes. But does
> that have a consequence in terms of the adequacy of the present
> bioequivalence criteria? My answer is no because, as Lawrence showed
> in his introduction\--and I am not really sure I needed to make this
> presentation because he covered this\--no, the product either passes
> or fails the bioequivalence criteria. So, this makes the assumption,
> going back to therapeutic equivalents, that the definition of
> pharmaceutical equivalence is adequate.
>
> \[Slide\]
>
> That pharmaceutical equivalence states, as we see on this slide, that
> the two different formulations contain the same active ingredient.
>
> \[Slide\]
>
> On my second to last slide the question would be are two different
> polymorphs the same active ingredient? In the response to the
> questions raised earlier in discussion and also Lawrence\'s slides, it
> was the assumption that only drug in solution is active. So, if we
> believe that only drug in solution is active, then the bottom
> statement there is that two different polymorphs will always be the
> same active ingredient.
>
> However, if there is the possibility that the action of drug occurs
> through interaction of a receptor, for example, with solid drug
> particles, then two different polymorphs could possibly not be the
> same active ingredient.
>
> \[Slide\]
>
> But my conclusion is that drugs, to get across membranes and to be
> active, must go into solution and, therefore, as shown on the last
> slide, I don\'t think we have a problem at least in terms of
> therapeutic equivalents. No altered regulatory approaches are
> necessary. Thank you very much.
>
> DR. LEE: Thank you, Les. Any questions for Dr. Benet?
>
> \[No response\]
>
> I think we are convinced.
>
> DR. BENET: Great.
>
> DR. LEE: Good job, Les. Any other questions? If not, since Dr.
> Brittain is not coming, we are now going to take a break. So, I
> propose we take a break and come back at 3:15 and then the committee
> will address the different questions. Les, are you going to stay with
> us?
>
> DR. BENET: I will come back at 3:15.
>
> DR. LEE: Thank you very much.
>
> \[Brief recess\]
>
> **Committee Discussion**
>
> DR. LEE: Nair, are you there?
>
> DR. RODRIGUEZ-HORNEDO: Yes, I am here.
>
> DR. LEE: Les?
>
> DR. BENET: I am here.
>
> DR. LEE: Very well, thank you. Feel free to participate. We have
> Lawrence who will show us decision trees one and three again at the
> appropriate time and he will show us the five questions. In a way the
> consultants have provided answers for us and I think it is time for
> the committee to speak up on how the committee feels about those
> questions, the answer to the questions. I have asked Nair to study the
> background and more or less lead the discussion. Are you ready, Nair?
>
> DR. RODRIGUEZ-HORNEDO: I will be happy to do that, however, I need
> some help since I do not have the FDA slides through the video.
>
> DR. LEE: Oh, no, you don\'t need the slides.
>
> DR. RODRIGUEZ-HORNEDO: That is okay. I will try to lead the discussion
> on the phone.
>
> DR. LEE: Okay. So, question number one, do the proposed decision trees
> adequately address the key polymorph issues, stability and
> bioavailability, that should be considered in FDA\'s regulatory
> assessment on an ANDA? That is the question.
>
> DR. YU: Vince, do you want to address the following question first and
> then come back to the first overall question?
>
> DR. LEE: All right. So reading again for the benefit of Nair, decision
> tree number one, are there other issues with respect to
> characterization of polymorphic forms that the FDA should consider?
>
> Decision tree number three addresses the necessity of having a
> polymorph specification for drug product when using the most stable or
> previously used form.
>
> Please comment on methods, approaches and challenges for establishing
> specification for polymorphs in drug products. Also, in your
> experience, how often would you anticipate that such a specification
> is necessary?
>
> DR. MEYER: Vince, let me ask a couple of questions that would help me
> understand whether the decision trees are adequate or not.
>
> DR. LEE: Okay.
>
> DR. MEYER: I don\'t know whether the answer is it is theoretically
> possible, or it is probable, or what. Let\'s say we have an NDA
> approved with polymorph 1, an ANDA with polymorph 2 and they both have
> been shown to be bioequivalent and have similar dissolution but the
> ANDA polymorph 2 can convert during storage to polymorph 3, which then
> affects its bioavailability. Is that possible? If so, is it probable.
> If so, how can we control that and monitor it?
>
> DR. MORRIS: Yes, it is clearly possible. In fact, that is one of the
> issues that actually Nair had raised last time. The propensity of
> transformation between forms may not be the same, and this is true of
> amorphous forms as well. If you have two different forms, both of
> which are bioequivalent, they may or may not have the same propensity
> to transform to yet another form. I think the decision tree addresses
> that by assuming that you are using the most stable or marketed form
> but, to answer your question, that is certainly possible.
>
> DR. LEE: Yes, Leon?
>
> DR. SHARGEL: Well, I think that question could be both for the
> innovator side as well as the abbreviated or generic side because in
> stability how long it stays on the shelf, we wouldn\'t know that. But,
> in general, both sides of the industry do dissolution and do
> bioequivalence, at least on the initial ANDA batch, followed up by
> periodic stability studies. So, at least we do know something about
> the characterization at that point in time. You may or may not even
> notice an inter-conversion.
>
> DR. BENET: Vince, can I make a comment?
>
> DR. LEE: Yes.
>
> DR. BENET: I think the criteria that Marvin raised, under our present
> operational procedures, could definitely happen. We immediately get to
> decision tree number two where it says are all known polymorphs highly
> soluble, and the answer would be no. Then, if we went to decision tree
> number two, I don\'t think we have criteria today\--let\'s go back a
> minute. We don\'t have any criteria that say that you must meet
> bioequivalence, that a generic or an innovator must meet
> bioequivalence criteria during the shelf life of that product. We only
> have it when you carry out the study. Some of us have said that we
> should have criteria like that. So, I think under the present
> situation we would not have adequate protection and the decision trees
> wouldn\'t be adequate unless we had a USP polymorphic specification
> that actually addressed that.
>
> DR. HUSSAIN: The aspect I think of a bioequivalent study at the
> beginning and towards the end of shelf life, the way I look at that
> scenario is we have adequate in-process and other specifications that
> are tested throughout the shelf life. In fact, part of the stability
> requirement or dissolution is part of that. So, we do test for
> dissolution. If we have confidence in the dissolution test as an
> indicator of change or no change, if your dissolution criteria are
> being met you address that scenario that way. If you have doubts in
> your dissolution test, then that opens up that possibility.
>
> DR. LEE: That seems reasonable to me.
>
> DR. MEYER: But that is assuming your dissolution test can detect
> differences between polymorph 2 and 3 let\'s say in the generic. I
> agree with Leon that this applies also to the NDA product. But we are
> assuming that the dissolution can detect that change.
>
> DR. MORRIS: Can I just state something? I guess whether or not
> dissolution correlates directly to bioavailability is sort of a
> different question in a sense, but if there is a difference between 2
> and 3 that is significant enough in free energy to cause changes in
> solubility, then if it doesn\'t show up in the dissolution you would
> have to say it doesn\'t; there is not a large enough solubility change
> to make a difference, I mean just from a practical standpoint. That is
> not commenting on whether or not dissolution to bioavailability
> correlate. That is not my area.
>
> DR. MEYER: Which is kind of the issue I am raising. Have they been
> shown to correlate? I guess maybe there was one example shown today,
> polymorph 1 and polymorph 2 that had different dissolution
> characteristics, but I don\'t know if that was carried out to
> bioavailability or not. It seems to me that one way to handle that,
> and I am not an expert in that field and I have no idea how difficult
> it is to test for polymorph 2 and 3 in the intact dosage form\--if
> that can be done fairly readily, then it seems like that ought to be
> what is done.
>
> DR. SHEK: Well, I think that is a technology issue because you might
> have mixtures and not purely one or the other, and that is where it
> gets complicated. But if I might just add to the points here, talking
> about in general there should be a concern. If the most stable
> polymorph form is used, that is okay, but number two, it is a
> previously commercial product. I can see a scenario where an innovator
> might choose to use a less stable polymorph and stabilize it in the
> formulation, or the synthesis of the API is such that this polymorph
> is stable.
>
> Now, when you have somebody else coming in, and if it is an ANDA with
> only three-month stability data being accepted, how do you have the
> assurance that now you don\'t have something in the formulation, a
> different excipient that can trigger and now the most stable polymorph
> will be less soluble? The question still coming back is, is that
> biologically significant? I think that is basically the litmus test.
>
> DR. HUSSAIN: That sort of hinges on how you establish your dissolution
> specification and how it relates to bio.
>
> DR. BOEHLERT: I was going to comment along the same lines because I
> think it is certainly possible. If I were to formulate a product and
> have a dissolution test and get results in the high 90s on a general
> basis and set a Q that is low enough I could, indeed, also produce a
> product that meets requirements and is quite different, and that could
> be due to a polymorph or it could be due to something else. And, how
> would one distinguish? It still meets requirements but it is clearly
> not the same and I don\'t know if bioequivalence is impacted in that
> case.
>
> DR. YU: Could I comment? Essentially based on Marvin\'s comments,
> there is a possibility, I would say a distinct possibility. Now, when
> you come down to the possible dissolution and solubility, those that
> are potentially affected by variability the likelihood is that those
> are poorly soluble. When it is down to the poorly soluble, usually
> when you use free energy for forming conversion\--we have to take it
> case by case is what I mean. If there is a possibility to convert from
> polymorphic 2 into polymorphic 3 and there is a great possibility,
> then we have to look at if this happens, the conversion and there are
> two products with polymorphic 3 bioequivalent or not because that is
> only in rare cases that that might be happening. Certainly we have to
> make sure that this can detect a potential impact. I say this is
> theoretically possible. In reality it may not be happening.
>
> DR. HUSSAIN: Let me throw in one more wrinkle then. In a sense, you
> could have changes in polymorphic form of excipients and that could
> affect dissolution and could affect everything else and we don\'t even
> want to ask that question today.
>
> DR. KIBBE: I was going to go in that direction just a second ago; you
> beat me to it. Right now we look at the changes in dissolution for
> anything in terms of shelf life. We don\'t test bioequivalency at the
> back end. Those changes in dissolution can be a result of anything
> changing, ignoring polymorphs, excipients, aging, whatever. If we see
> those changes, then we use that as a quality control so why should
> polymorph concerns be any different than the general concern we have
> in the general product?
>
> Now, if we really are concerned that we are missing a significant
> change in bioequivalency because our dissolution profiles aren\'t good
> enough, then we need to go back and do two-year old bioequivalency
> studies on already marketed innovator products to see if there is a
> change because we know the dissolution profiles are good because they
> collect that data. Now we are asking a different theoretical question,
> which is we are all comfortable with dissolution projecting
> bioequivalency and once we have established it we are happy that
> dissolution will allow us to catch any changes in that, but have we
> tested it? That is independent of a polymorphism issue. Right? Which
> is I think one of the things which Les was getting at. Because we know
> that dissolution is indicative of bioavailability but not guarantied.
> Have we ever really done that test? And, that is completely different
> than the issues we are talking about today.
>
> Looking back on polymorphism might be just one factor that might
> create a problem but we don\'t know that for a fact, and as long as we
> are happy with dissolution as a measure of changes with aging, I think
> we should be happy with dissolution as a measure of changing with
> aging regardless of whether it is a change in excipients, which I
> think might be more likely, than a change in polymorphs.
>
> DR. MORRIS: If I could just add to that, there are a number of cases
> where different particularly hydrated and amorphous forms, as well as
> polymorphs, show differences in dissolution and they are also
> translated into plasma concentration. There is a fair literature on
> that. We work on trying to develop methods for quantifying polymorphs
> in dosage forms, however, to Art\'s point and to Tom\'s point as well,
> he didn\'t tell you but when we were talking he was saying that even
> if you determine differences in polymorph ratio in the final dosage
> forms, there is no guaranty. You could pass spec fine with that
> determination and still fail dissolution because of particle size and
> other issues that Art had raised. Not that I am a big fan of
> determination but it is just not the only variable with respect to
> dissolution and availability I think.
>
> DR. BENET: I am convinced that the dissolution is satisfactory in its
> present state.
>
> DR. LEE: Would you repeat that please, Les? We could not hear what you
> said.
>
> DR. BENET: I am convinced that we have adequate protection with
> dissolution criteria at the present time for the dosage form over its
> shelf life because if I change that then I feed in problems.
>
> DR. LEE: Okay, thank you.
>
> DR. MEYER: Lawrence, under decision tree three, I guess the second
> diamond down, the question is does drug product dissolution testing
> provide adequate controls to determine polymorphic ratio changes? How
> are you going to test that? Are you going to make different
> formulations or several formulations with different polymorphs and
> look at dissolution and then look at something else? How are you going
> to know that?
>
> DR. YU: Sometimes you look at other decision trees and you tend to
> adopt them, you know, but you don\'t know how to answer them. This is
> actually similar to ICH Q6A, and the decision tree over there
> basically says does drug product performance testing provide adequate
> control if the polymorphic ratio changes, such as dissolution? If we
> truly want to know, if there is a concern, unlikely as it is that
> there is a distinct possibility\--we have to ask this question first.
>
> So, the likelihood is extremely low but for us, we, indeed, want to
> demonstrate that the dissolution testing can provide adequate control
> for polymorphic ratio changes and then we will have to prepare product
> with different polymorphic forms and evaluate the bioequivalence
> study. Sometimes if there is greater possibility for potential
> conversions\--we know there is a variety of crystal forms exists, for
> all kinds of reasons if an amorphous form is used the chance is
> extremely low and, certainly, we are confident that this dissolution
> method can detect potential polymorphic changes for the long run but
> at the initial stage we may have to do bioequivalence studies, yes.
>
> DR. HUSSAIN: I think in general, especially while developing the BCS
> guidance, we did a lot of data mining to look at how good the
> dissolution is. In general, I think it tends to be quite sensitive to
> changes in formulation, and so forth. But I think as we look forward
> to more complex drugs, dosage forms and so forth, there is a strong
> need for understanding dissolution and how we set specifications more
> based on physical chemical attributes. So, that is sort of a concern
> that I have. I think we need to keep in mind how we set dissolution
> specifications and make sure those are set appropriately. I think
> there is room for improvement in that also.
>
> DR. MEYER: Under decision tree number one you define highly soluble in
> terms of the BCS classification. Now, are we really going to have
> whatever it is, six or seven pH\'s for each of the polymorphs?
>
> DR. YU: The chance certainly is very low but we define that as known
> polymorphs that are highly soluble. Looking at it another way, you
> look at the most stable form. The most stable form actually determines
> our own answer to this question because the meta-stable form tends to
> have high solubility in the most stable form. So, what we actually
> look at for solubility when we as this question is the solubility of
> the most stable form. It is not necessary for you to get all the other
> information in order to answer this question. In other words, it is
> not necessary to get the solubility of a meta-stable form to answer
> this question because we know the solubility of the meta-stable form
> will be higher than the most stable form under the same conditions.
>
> DR. MEYER: My objection is if they are all known polymorphs, highly
> soluble as defined by BCS\--
>
> DR. YU: So, you are suggesting we should have considered change, for
> example, the most stable form?
>
> DR. MEYER: Either you do all the forms, like you say, and all the
> pH\'s, like BCS says or you have some modification of that.
>
> DR. YU: Excellent. That is a good suggestion, yes.
>
> DR. LEE: Leon?
>
> DR. SHARGEL: I want to address this first part in terms of the more
> stable form or less stable form. I think Gary Buehler hit it on the
> nose that litigation is often the driving force in this area, as well
> as patents. When a generic is coming on the market, looking at the
> API, we will certainly look at whether the polymorphic form will or
> will not infringe on the innovator patent. So, it may certainly be a
> different polymorph than the innovator.
>
> The second is that if the product, once made, is shown to be
> bioequivalent in similar dissolution, do we really have to worry so
> much about this part of the decision tree if our final product is
> going to be bioequivalent, stable and show adequate dissolution?
>
> DR. MORRIS: Can I ask you when you say this part of the decision tree,
> are you talking about the solubility part?
>
> DR. SHARGEL: I am talking about characterization or trying to always
> choose the more soluble or more stable polymorphic form. If there,
> indeed, is patent literature or something, perhaps taking the
> cefuroxime axetil as an example, the amorphous was used by\--was it
> Glaxo? In any case, the crystalline form would be naturally more
> stable than the original form in this particular case but they both
> seem to be adequately bioequivalent and the USP modified the monograph
> accordingly.
>
> DR. YU: Yes, the case you are talking about\--I don\'t know this case,
> but if all these forms, amorphous form and crystalline, are highly
> soluble, therefore, most likely they will not affect the
> bioavailability so it is not necessary to do any further testing or
> polymorphic acceptance criteria for drug substance and drug product.
>
> DR. MEYER: But the argument in this case was the crystalline form was
> less soluble than the amorphous form in terms of greater solubility,
> and that was the rationale. The crystalline form, of course, was more
> stable but less soluble in terms of rate of solubility.
>
> DR. YU: Yes, the crystal form\--maybe one form is less soluble than
> the other but this does not necessarily mean these two forms are not
> bioequivalent.
>
> DR. MEYER: Why do we need the first part then?
>
> DR. MORRIS: No, they are not bioequivalent, if you look, the pure
> crystal and pure amorphous is what Leon is saying. He is saying that
> they are not bioequivalent as the final drug product. The formulation,
> the way it was made, is bioequivalent and produces the same within the
> confidence intervals or demonstrates bioequivalence.
>
> DR. YU: So, Leon, what exactly is your question?
>
> DR. SHARGEL: I don\'t know how much we need to worry about solubility
> and such at this stage as the real stage is in the product itself. We
> characterize the polymorphs anyway as a necessity, as I said, because
> of the science and maybe political science from the point of view of
> patents but the final analysis is the finished dosage form.
>
> DR. YU: In other words, what you are suggesting is we don\'t have to
> worry until we go to decision tree two to set up the specification.
>
> DR. SHARGEL: We do need specifications. I am not arguing about that.
>
> DR. YU: Certainly, decision tree number one is to give you a
> scientific justification to provide an opportunity to not set up any
> specification at all. If you want to go through this one and set up
> specification, that is okay. Your answer to the first question is yes;
> the second question is no; and you go to set up specification if you
> like. That is okay too. Yes.
>
> DR. HUSSAIN: A question that sort of comes up, I think the language
> and the terminology we are using become critical beyond the political
> science that comes in. The decision tree says are all known
> polymorphs\--do you see a problem with that? I think with the software
> we are seeing now we can predict all possible polymorphic forms based
> on the chemical structure but, in reality, in terms of getting those
> polymorphs in a physical sense is not always easy. So, can you just
> give some advice on the language, how this should be structure?
>
> DR. LEE: Well, I think what we are looking at is if polymorphism is
> believed or suspected to be the cause of the problem\--right?\--what
> should we do?
>
> DR. YU: I think Ajaz\' question is what defines \"known.\" What does
> \"known\" mean? So, should it be experimentally verified or just
> verified by the computer?
>
> DR. KIBBE: I think to change it from \"known\" to \"available.\" If
> one company uses a particular polymorph and I can get my hands on the
> same polymorph I am finished. Okay? So, it is are there available
> polymorphs with different apparent solubilities, and am I using the
> same polymorph or does mine have the same solubility as theirs? I
> don\'t think someone making a product needs to have clearly available
> to them all the possible polymorphs or all that have ever been
> discovered. They have to deal with what is available in the
> marketplace that can be used.
>
> DR. MORRIS: Yes, I sort of see where you are going there but I think
> there is a problem there. I would agree to the extent that there are a
> lot of compounds that are known to form solvates that might have 20
> different solvates, and I agree that if you are not using that in your
> process there is not a lot of reason to go after it. But because of
> some of the differences, as Leon was talking about, the differences in
> the development process and the raw material supplier, I think you
> have to screen to the extent that you know that you are not probing an
> area and confirmation space, which is the software that Ajaz was
> referring to, that will now be stabilized by your system. If you go
> into polymorph predictors you can find, you know, a thousand forms
> and, obviously, if you can isolate, you know, ten of them that
> wouldn\'t be unusual. Of those ten, maybe only two are really in an
> energetic range to be significant. But even the polymorph predictors
> don\'t typically predict solvate forms and certainly nothing is going
> to predict amorphous forms very well at this stage. So, I think you
> are still forced on the empiricism of screening to the extent that it
> encompasses the exposure that you expect your material to be subject
> to, particularly if you are doing wet granulation, as we talked about
> before. If you are going to DC or direct compression, maybe there is
> an even little narrower focus to your screen.
>
> DR. HUSSAIN: That sort of brings me back to what Leon was trying to
> get at probably. In a sense, the regulatory question essentially then
> becomes if you have selected a supplier of drug substance for your
> product, then that becomes your material of interest. Why go to
> anything beyond that?
>
> DR. MORRIS: Well, in terms of your supplier that is fine but, again,
> if you look at the examples of conversion during processing even or
> storage, particularly if you are using a different form than already
> has a history, I don\'t see that that let\'s you off the hook in any
> way. I just think that it focuses much more on what you have to worry
> about so you don\'t have to worry about the hundred forms. If you are
> just using an aqueous-based system, then you are not going to use\--
>
> DR. HUSSAIN: What I was driving at was, in a sense, to qualify any
> given product formulations, hopefully, you go through the development;
> you go through the stability; you go through the bioavailability
> anyway. But now your material is what you are starting with and you
> just focus on that material rather than looking for all possibilities
> and sort of the physicochemical attributes would just focus on that
> material rather than looking at all possibilities.
>
> DR. MEYER: Maybe that could be in the sense of does your polymorph
> convert to another form, and are the two forms, two or more forms, do
> they have different solubility? Are they both highly soluble? So, you
> focus in on what is being used in that application.
>
> DR. HUSSAIN: And when there is a change in supplier, then everything
> kicks in.
>
> DR. MORRIS: I see what you are saying. Yes, certainly and that is what
> we were talking about earlier. If you change your supplier and they
> have a different crystallization step or a different profile\--I guess
> one of the exceptions would be in a case, as you were discussing,
> where you are now seeding amorphous material with crystalline
> material. That is very nerve-wrecking. I realize that so far it has
> been, you know, okay but, to me, that is the sort of thing that really
> bears monitoring because here you are sort of setting things up to
> fall down the thermodynamic hill.
>
> DR. KIBBE: What you are suggesting I think is that it is really easy
> to get past the beginning and to decision tree two; that it is hard
> to, say, blow off any concern about polymorphism. What I was saying is
> that if yours and the innovator\'s are the only available forms, then
> you are done. I mean, if the two are the same polymorphic forms, you
> are done. That is the only way you would get out of here without doing
> any\--
>
> DR. YU: That is correct and, actually, in many cases despite the fact
> that the computer predicts ten solvates, in reality we can only
> discover one or two or, in many cases one polymorphic form and we
> don\'t have to worry about this in the future. So, if we can use
> decision tree number one at least to avoid unnecessary testing down
> the road\--if you want to go to decision tree number one and if you
> want to always test to set up specifications, that is okay.
>
> DR. MORRIS: And to your point, Art, and it is sort of something I
> talked about in the slides I presented, inclusive of amorphous and
> solvate or hydrate forms you have to have the caveat that if there is
> something in the innovator product or even in other generic products
> that has been specifically done to stabilize an otherwise highly
> meta-stable phase, then you are adding another dimension to the risk
> that has to be assessed. I am not saying that it still doesn\'t pan
> out to be\--you know, once you have settle on that form it gives you a
> much higher level of confidence.
>
> DR. LEE: I guess what we are hearing is that there is an attempt to
> write specifications but there are so many exceptions.
>
> DR. HUSSAIN: It is sort of a balancing act where we actually bring the
> right science to bear on the type of questions we are asking because
> one of our challenges, I think, that we face is that generally in the
> drug approval process we have much more limited data as opposed to the
> new drug review process. So, some of the decisions with respect to
> stability, and everything, is on somewhat more limited data. So, I
> think it is a balance that we have to strike that has enough
> characterization to work on some of the other challenges that we face.
>
> DR. LEE: Or, to sum things up, you can say that science will take care
> of itself.
>
> DR. YU: It all comes down to if the firm has provided adequate
> information to convince us that they can produce the generic product
> which is high quality, which is equivalent to the reference listed
> product. It all boils down to this question.
>
> DR. MORRIS: Yes, if I can sort of summarize what I think, I mean, it
> is a case by case basis in a sense but that is not a bad thing because
> the decision tree still gives you the framework to work by, but no
> matter how much we try to take the science out of the decision-making
> process, not at the FDA but in terms of our general techniques for
> coming down to specific cases, you are always going to apply the
> science that is appropriate at the level that it is appropriate. I
> think that is all that the decision tree is trying to do, to say where
> do you need to apply what science. That is what it boils down to. What
> science there is will depend on the case. Otherwise, you can\'t
> classify anything. I mean, we have a separate decision tree for
> polymorphs and hydrates and then hydrates and amorphous which is just
> too cumbersome to even do. So, I think that the concept is sound and
> it is just a matter of us, as a community, saying, you know, you have
> to give your scientists freedom to do what they need to do when they
> need to do it. In that case it works pretty well.
>
> DR. LEE: Thank you. Is everybody comfortable with that?
>
> DR. MEYER: Let me raise just one question about the footnote in
> decision tree three. It bothers me, unless you have data to back it up
> which you may very well have, in footnote two it says dissolution
> testing with appropriate dissolution may frequently detect potential
> conversion of polymorphs during storage of the product. It refers to
> the product I believe. In rare cases dissolution testing is not able.
> How many \"frequent\" examples do you have where you are able to see
> the polymorphic conversion in a product during storage that was picked
> up by dissolution?
>
> DR. YU: I guess this comes back to the same question about drug
> products or drug substance, interactions, excipients, drug substance
> interactions. It comes down to this, that in this case, for example
> for some poorly soluble drugs, like carbamazepine, you can develop
> dissolution to detect the difference. However, for highly soluble
> drugs, and most polymorphic forms are highly soluble, probably it is
> very difficult. So, what you come down to in the decision tree is the
> likelihood that the drug is poorly soluble, therefore, if there is a
> potential conversion, potential solubility change, the likelihood very
> often will be that it can detect potential changes.
>
> DR. MEYER: I don\'t disagree with your statements. I am curious as to
> whether Gary can talk to lawyers or appear in court and say, oh, we
> frequently can detect and someone then will say, well, give me twenty
> examples, or ten, or something other than carbamazepine.
>
> DR. YU: We actually have a working group which is collecting approved
> ANDAs to see those decision trees. So far our situation is pretty
> good.
>
> DR. HUSSAIN: Let me sort of rephrase that. That is an important point
> because I think the language matters here. I think our knowledge base
> or database that we have for dissolution, in a sense when you look at
> dissolution you are looking at a complex system, not just polymorph
> changes. The entire system is changing, and so forth. So, what that
> essentially does tell me is that that box could essentially read that
> dissolution testing is a sensitive indicator of changes that occur
> that relate to dissolution changes. I mean, that is what we are
> talking about, not per se a polymorph change.
>
> If you break it down to polymorphic conversion, I don\'t think anybody
> has the data. The argument is supported that dissolution changes are
> reflective of solubility changes and, therefore, the logic is there
> but I am not sure the data is there that goes to that point.
>
> DR. RODRIGUEZ-HORNEDO: I agree with what Ajaz said. I am more
> comfortable with the terminology based on solubility because actually
> I have seen some cases, and we have studies some in our lab, where if
> you have very fast polymorphic conversion to the more stable form the
> dissolution test is not going to be discriminating. So, I would think
> that the terminology in footnote two is a little bit confusing.
>
> DR. SHEK: But wouldn\'t then the question be is it significant? If the
> dissolution doesn\'t pick it up, is this conversion from one polymorph
> to the other significant biologically?
>
> DR. HUSSAIN: It won\'t be. I mean, that is the basis of the current
> system.
>
> DR. LEE: It seems to me that there are some suggestions for changing
> the wording. Anything else? No? Done. Any other comments? It seems to
> me that obviously polymorphism is quite important for certain drug
> substances. I think that specifications might be useful as some kind
> of guidance but I don\'t think we can be rigid in the wording. I think
> that is the message.
>
> DR. YU: Yes, thank you.
>
> DR. LEE: Is there anything else?
>
> DR. MEYER: You didn\'t cover number C, about the extraordinary
> formulation or manufacturing process.
>
> DR. YU: I am sorry, that was deleted. The working group realized that
> that sentence is very vague. We had to delete this sentence. Thank
> you.
>
> DR. LEE: Thank you very much. I think that is about it for
> polymorphism.
>
> Ajaz asked me to make a comment about my observations on this
> committee, and I promise I will not spend lots of time on it.
>
> First of all, I think it is a wonderful experience and it is wonderful
> because of the diversity, and because of diversity I think we have to
> learn how to be quick thinkers and also to act in a fair manner.
>
> I am very please to see that a subcommittee structure is evolving. As
> I said earlier this morning, it is very scary to be able to understand
> all the issues and I think the subcommittee structure will help to
> deal with some of this a little bit.
>
> I think I also began to see, as Helen said this morning, that there is
> kind of follow-up, continuity. I think we are getting there but
> oftentimes my concern is that some of the issues kind of last for a
> long time so that what we have recommended today or talked about today
> may not be shared, or our successors may not be privy to what has been
> discussed before and I think that maybe some kind of archives would be
> useful. I think I see that some kind of structure is evolving in the
> sense that we have these\--what are these called, Ajaz?\--awareness
> and some things will follow down the line. I often wonder whether or
> not a two or three times a year meeting is sufficient. Everybody is
> busy but I hope that with the subcommittee there will be more informed
> discussion about the issues.
>
> When I first took over the chair, I was not really aware about the
> statute. In fact, as scientists we tend to be spontaneous; we like to
> discuss matters ahead of time but because we also wear another hat all
> the discussions have to occur in public. So, I think that may be
> something that needs to be changed in some way. But in the end, I
> thought there is a strong partnership between the regulators and the
> scientific advisors. I think in a way we are a member of the
> community. I think today we have seen several of these scenes play out
> again. Questions were asked from the statistician\'s point of view;
> things don\'t seem to make much sense and, yet, it worked.
>
> So, I just as I begin to understand how the operation goes, it is time
> to go, not that I want to stay on forever. But I think some of the
> things I see changing are, number one, the subcommittee structure, and
> I think there may be a better access to the information database. I am
> rambling here, but maybe how the focus is organized would be quite
> useful. I think the presentations are getting to be very constructive
> in the sense that you kind of point out important issues and
> oftentimes for those of us who might be busy, may not study every
> single document carefully. I tried to set up the subcommittee
> structure. It seems to work but I think, again, that we are still kind
> of hindered by how readily the information is available. So, if you
> have a web site you can instinctively go to where to find the actions,
> the suggestions that we have.
>
> Committee members, other opinions? I think everybody is anxious to go.
>
> DR. HUSSAIN: All right, just a few thoughts to close this day, I think
> this morning we have seen a whole host of topics from the PAT
> subcommittee report on what we are trying to do there with respect to
> blend uniformity, with respect to CMC risk-based review and
> polymorphism. If you look at the underlying discussion and themes,
> there are many common issues. I think ending the discussion today with
> polymorphism sort of reinforces some of the basic fundamentals that we
> have, for example the dissolution test; how good is it; how do we set
> the specification; and how do we do the right type of testing. So, the
> bulk of this committee in trying to bring more focused discussion on
> the science of our test procedures, and so forth, really comes home to
> sort of bring standards that are well grounded in science.
>
> At the same time, I think what the PAT initiative also serves is to
> take the next step. If you look at polymorphism, if you want to
> characterize polymorphic forms or particles size you are going to do
> that from a very small sample size. Where is that sample coming from?
> Is it representative? Because we are making major decisions on all
> these aspects on few samples. If we are just figuring out sampling
> strategies for blending, a fifty-year old operation, you can imagine
> where we are in that sense. You can also see why the CMC review is so
> important, and the risk-based approach is so difficult to adopt
> because of the unknown aspect that we struggle with.
>
> So, I think what we have tried to do is set up challenges, and
> identify challenges to be addressed by the current system and also, at
> the same time, develop a new system which actually overcomes some of
> these challenges. So, I hope you can see all these interconnections
> between the topics we have discussed and will continue to discuss with
> you. Again, thank you. It was a wonderful day.
>
> DR. LEE: I think in a way you mentioned a very important point. I
> wonder whether it would be useful for the committee to identify two or
> three issues to work on. I think it is very important for us to
> anticipate where science is moving in the next five years. We have to
> respond to the issues that you raise but, hopefully, we, the
> scientific community, response more in a proactive way. Again, I want
> to emphasize the partnership, members of the same community.
>
> Thank you very much for today\'s discussion. Tomorrow we are going to
> come together at 8:30 again. Have a good evening.
>
> \[Whereupon, at 4:05 p.m.., the proceedings were recessed, to resume
> at 8:30 a.m., Tuesday, October 22, 2002.\]
>
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