ATDEPARTMENT OF HEALTH AND HUMAN SERVICES

> FOOD AND DRUG ADMINISTRATION
>
> CENTER FOR DRUG EVALUATION AND RESEARCH
>
> **ADVISORY COMMITTEE FOR PHARMACEUTICAL SCIENCE**
>
> Wednesday, October 23, 2002
>
> 8:30 a.m.
>
> Georgetown and Montrose Rooms
>
> 1775 Rockville Pike
>
> Rockville, Maryland
>
> PARTICIPANTS
>
> Thomas Layloff, Ph.D., Acting Chair
>
> Kimberly Topper, Executive Secretary
>
> MEMBERS
>
> Gloria L. Anderson, Ph.D.
>
> Judy Boehlert, Ph.D.
>
> Arthur H. Kibbe, Ph.D.
>
> SPECIAL GOVERNMENT EMPLOYEE CONSULTANTS
>
> Thomas Layloff, Ph.D.
>
> Melvin V. Koch, Ph.D.
>
> G.K. Raju, Ph.D.
>
> GUESTS AND INDUSTRY PARTICIPANTS
>
> Eva M. Sevick-Muraca, Ph.D.
>
> Leon Lachman, Ph.D.
>
> Thomas Hale
>
> Kenneth Morris, Ph.D.
>
> Andrew Lange, Ph.D.
>
> Robert S. Chisholm
>
> Doug Dean, Ph.D.
>
> John G. Shabushnig, Ph.D.
>
> John C. James, Ph.D.
>
> Rick E. Cooley
>
> Steve Hammond
>
> Ronald W. Miller, Ph.D.
>
> David Richard Rudd, Ph.D.
>
> Jerry Workman, Jr., Ph.D.
>
> [C O N T E N T S]{.underline}
>
> Conflict of Interest,
>
> Kimberly Topper 4
>
> Introduction to the Meeting, Ajaz Hussain, Ph.D. 6
>
> Computer Systems Validation - Part 11 Issues
>
> Pertinent to PAT:
>
> Robert S. Chisholm, AstraZeneca International 26
>
> Guy Wingate, Ph.D., GlaxoSmithKline 38
>
> Deborah M. Thomas, Air Products
>
> and Chemicals, Inc. 62
>
> John Murray, FDA 75
>
> Subcommittee Discussion: Computer Systems Validation,
>
> Part 11 Issues Pertinent to PAT 94
>
> Open Public Hearing:
>
> Dr. Stanley A. Marash 130
>
> Dr. Gary Ritchie 136
>
> PAT Mock Submissions:
>
> Ronald W. Miller, Ph.D., Bristol-Myers Squibb 140
>
> San Kiang, Sc.D., Bristol-Myers Squibb 140
>
> S.M. Upadrashta, Ph.D., Bristol-Myers Squibb 151
>
> Glenn A. Thomson, Bristol-Myers Squibb 155
>
> Steve Hammond, Ph.D., Pfizer 160
>
> PAT Discussion 172
>
> Breakout Session Summaries:
>
> Rapid Microbiology Testing Summary,
>
> Michael Korczynski, Ph.D. 224
>
> PAT Summary, Kenneth R. Morris, Ph.D. 237
>
> [P]{.underline} [R]{.underline} [O]{.underline} [C]{.underline}
> [E]{.underline} [E]{.underline} [D]{.underline} [I]{.underline}
> [N]{.underline} [G]{.underline} [S]{.underline}
>
> \[The panel members, special government employees, and guests
> introduced themselves.\]
>
> MS. TOPPER: Thank you. 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 may apply to the general topics at hand.
>
> Because of her reported interest in pharmaceutical companies, the FDA
> has prepared a general matters waiver for Dr. Judy Boehlert, a special
> government employee, which permits her to participate in today\'s
> discussions. A copy of this 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 may 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 there may be
> potential conflicts of interest because of the general nature of the
> discussions before the committee and these potential conflicts are
> mitigated. In the event the discussions involve any other products or
> firms not already on the agenda for which the 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 financial involvement with
> any firms whose products they may wish to comment upon.
>
> I would also like to thank those people who are sitting in our
> overflow room. We understand that this is not the optimum facility but
> this is what we had available. If there are comments during the open
> public hearing, we do encourage them to come into this room to make
> their comments. Thank you.
>
> DR. LAYLOFF: Thank you, Kimberly. I\'d like to have the people who
> came in just recently introduce themselves, starting with Joe.
>
> MR. FAMULARE: Joe Famulare from CDER Office of Compliance.
>
> MR. HALE: Hi, I\'m Tom Hale from Hale Technologies.
>
> DR. RAJU: G.K. Raju from MIT.
>
> MR. HAMMOND: Steve Hammond from Pfizer.
>
> DR. LAYLOFF: Thank you and welcome.
>
> Now we\'d like to go to Dr. Ajaz Hussain, who will give us an
> introduction.
>
> **Introduction to Meeting**
>
> DR. HUSSAIN: Good morning and welcome to Rockville. We actually moved
> from a smaller room to a bigger room here and I apologize for the
> cramped quarters but that\'s all we could find at this time. It\'s a
> challenge, but it also reflects on the popularity of what we are
> trying to do here.
>
> Let me share some thoughts with you on the process analytical
> technology initiative, and the progress we have made, and what we
> expect to do at this meeting number three.
>
> So, in sort of an outline format presentation, I have shared with you
> some of the progress at FDA and talked to you about the PAT review
> inspection team. Also I talked to you about the blend uniformity and
> the decisions FDA has made with respect to the PQRI proposal and how
> it links to the PAT initiative; talked to you about the manufacturing
> subcommittee that we are planning, and then shared with you in a
> summary format what we have learned from the PAT subcommittee
> discussions so far, and sort of summarized for you a PAT conceptual
> framework and the type of regulatory incentives that would be
> necessary to facilitate this. And, then finally, what information are
> we seeking today.
>
> I\'m very pleased to share with you that we have been able to put a
> PAT review and inspection team together. This includes members from
> the Office of Regulatory Affairs, our field districts. The Center for
> Drugs, and Center for Veterinary Medicine has joined into the PAT
> initiative as a full member. So it is a multi-center team now.
>
> We actually held a meeting three weeks ago and we are in the process
> of moving forward with a training program. In that regard, we have
> developed a training curriculum at this subcommittee, the second
> meeting, and that was the basis of establishing contracts with the
> University of Washington, Center for Process and Chemistry; University
> of Tennessee; and University of Purdue to do or conduct the training
> program for this review and inspection team. This training program
> starts in December.
>
> We also have been very successful in putting together sort of a PAT
> policy development team. We have successfully recruited individuals
> who will be part of this team. We are also making progress in the PAT
> research arena, and we have had a couple of publications and
> presentations at the upcoming AAPS meeting and, hopefully, some of you
> will get a chance to sort of review that.
>
> Here is the PAT review inspection team and other teams that are making
> this possible. You are all familiar with the PAT steering committee
> which includes Doug Ellsworth, from our New Jersey District. He is at
> the table today. There is Dennis Bensley, from CVM. He is in the
> audience but, unfortunately, he is in another room. Mike Olson, Joe
> Famulare, Yuan-yuan Chiu, Frank Holcomb, Moheb Nasr and myself. That
> essentially is the steering committee now and we have a PAT policy
> development team. Raj Uppoor was introduced to you before. I am
> pleased to introduce Chris Watts. He is in the audience today. He is a
> biomedical engineer with an industrial pharmaceutics background. He
> has just joined us. Hiquan Wu is a chemical engineer with experience
> with on-line methodologies. He has also joined the team. We are still
> waiting for one more member to join and that will essentially complete
> the policy development team.
>
> We have PAT training coordinators. John Simmons and Karen Bernard are
> taking the lead on that, with the help of Kathy Jordan. The review
> inspection team includes investigators from Atlanta, San Juan, New
> Jersey and Philadelphia districts, and you see the names here. It also
> includes compliance officers from CDER and CBM and reviewers from both
> new drug and generic drug divisions and the Center for Veterinary
> Medicine.
>
> So this team is essentially set up. We are going through many team
> building exercises and we have had some fun also at the same time. So,
> there is some fun involved also in our team building exercises.
>
> In terms of research, I just want to show you quickly the publication
> that came out. I hope you will be able to critique it and give us some
> more comments. This is a web-based publication, by Rob Lyon and
> others, which looked at near-infrared imaging as a means for looking
> at blend homogeneity for tablets. There are many issues still to be
> resolved but I think this will establish some feasibility concepts.
>
> Let me move on to blend uniformity. At the advisory committee the day
> before we discussed the blend uniformity proposal and the comments
> that we had submitted to PQRI. In a sense, we have made a decision to
> move forward adopting the PQRI proposal. So, the stratified sampling
> scheme would become part of a new draft guidance that we are
> proposing.
>
> That sometimes raises the question of how does that link to PAT and I
> would like to share some thoughts on that. At the previous meeting we
> talked about the challenges with the univariate approaches that we
> currently adopt and advantages of moving to a multivariate approach
> for product quality, and that is where PAT takes us. But I think we
> have also said that PAT is not a requirement. It is an opportunity to
> improve but we still have the traditional methods. So, stratified
> sampling analyzed by traditional methods would still be acceptable and
> that is what the current PQRI proposal will sort of adopt.
>
> At the same time, you can also include near-infrared imaging,
> near-infrared assessment at-line for the same test methods for
> stratified sampling. I think Pfizer\'s Steve Hammond shared some
> examples of that with us. So, if the at-line method is simply
> replacing an HPLC method, we won\'t consider that as a PAT submission
> because there is no additional advantage, or lessons learned, or
> analysis of the process. But if you are using that to highlight some
> process issues and actually improve the process and have a better
> understanding of the process\--again, I will use Steve Hammond\'s
> presentation to the science board which said that we don\'t limit
> ourselves to 10 tablets or 30 tablets; we actually go and do many,
> many more. That raises the question of safe harbor. So that extended
> analysis sampling brings that into the PAT world. So, that is what I
> am trying to share with you because you will need a safe harbor
> concept to sort of come in there.
>
> So, that is the link between what the blend uniformity proposal
> at-line could be and how it links to PAT. The advantage of PAT
> essentially is a multivariate quality by design approach where we can
> actually go to on- or at-line test methods for all critical components
> and processes. Currently, blend uniformity focuses mainly on only one
> component, the drug. Under the PAT scenario you actually look at
> homogeneity with respect to every component or all critical
> components. That is what the proposed PAT guidance is going to adopt
> and describe.
>
> The question that then comes is what is the incentive? I think the
> incentive here is higher efficiency; better understanding of your
> processes; lower risk leading to lower regulatory concerns. So, I
> think those are the incentives for why somebody would do on-line or
> at-line blend uniformity under the PAT concept, also I think linking
> that to the total quality system approach where you can actually use
> that information to predict end-product quality not only in terms of
> content, but also possibly in terms of dissolution, and so forth.
>
> Moving on to the next update topic, we had talked about sunsetting the
> PAT subcommittee on several occasions, and I think the decision has
> come to this right now, that this will be the last meeting of the PAT
> subcommittee. We hope to have gathered all the information from these
> three meetings for the general guidance.
>
> What will happen next is that the subcommittee will sunset and a new
> subcommittee will be formed and that will be the manufacturing
> subcommittee. The goal of this subcommittee will be to provide input
> and advice to CDER and FDA on science-based CMC and GMP policy
> development, but also continue development of a PAT initiative.
> Actually, it will take on the GMP for the 21st century, a risk-based
> approach, and provide input and support to that initiative. So this
> subcommittee is being modeled after the PAT subcommittee. In fact, we
> have heard from many individuals that this was probably one of the
> most successful subcommittees we have ever had. Although we don\'t
> want to sunset that, I think it is time to sort of incorporate this
> into the overall scheme of things at FDA. It will be modeled after the
> PAT subcommittee. That means that the core membership will be based on
> expertise in manufacturing, quality assurance and R&D. I forgot to put
> R&D in there, development itself.
>
> Some of you will essentially move to the manufacturing subcommittee
> and we will actually create more focused groups or fact-finding groups
> which will sunset after their assignment is done. So, it is not
> discontinuing your activities. In fact, you are being one of the most
> successful subcommittees we have ever had, but it will essentially be
> expanding the role and broadening the scope of the initiative.
>
> Moving on to the next topic that I want to share some information on,
> what have we learned from you? Your input has essentially allowed us
> to create a conception or framework for PAT from the regulatory sense
> but also from a scientific sense and actually identify emerging
> regulatory incentives that we would sort of provide. The concept of
> safe harbor has been discussed many times. I think we would like to
> use the term research exemption for describing the same concept.
>
> So, we have started focusing on a risk-based approach. This risk-based
> regulatory focus provides an opportunity to reduce the regulatory
> burden when you have better understanding, more understanding of your
> processes and how they relate to quality, and so forth. As a result of
> all this activity, I think PAT is a part of and is an example of the
> new FDA initiative for cGMPs for the 21st century. So, essentially you
> can see how things are getting connected together.
>
> I would like to spend a few minutes sort of laying out a conception
> framework for PAT. This is sort of our understanding of the PAT
> concept through discussions with you. I don\'t expect you normally ask
> questions right away but I think toward the end of the day, if you
> have questions on this concept, I think we need to talk about that.
>
> The PAT conceptual framework addresses every aspect from incoming raw
> materials to optimization to continuous improvement, and so forth. If
> I look at the PAT concept, I think it starts with processability of
> the incoming raw material. At some point we would have enough
> information that incoming raw material processability attributes would
> actually be utilized to adjust your process parameters. We won\'t do
> that today, but that is a possibility under this scenario. The
> incoming material attributes can be used to predict or adjust optimal
> processing parameters within certain established bounds.
>
> Clearly, on-line assessment of attributes that relate to performance
> and quality is a key component of that, and for this we need to focus
> on identifying process critical control points and also move towards
> an endpoint approach. Instead of time as an endpoint, you move towards
> process endpoints. You granulate until you have the optimum granule
> size; you blend until it is homogeneous\--that concept.
>
> All this actually could be based on performance measures and be linked
> to that. So, the chemometrics information technology and real-time
> control decisions are a critical component of that, and that will be
> the discussion of this meeting to some degree. At the same time, we
> move towards direct or inferential assessment of quality and
> performance that could be at- or on-line. So, it goes from incoming
> raw material to end-product testing at all stages.
>
> But also I just want to sort of share with you that development
> optimization and continuous improvement are concepts that PAT allows
> us to realize. The design of experiments, the advantage of using
> design of experiments is that we can learn more but, at the same time,
> you can get advantages in a regulatory sense of doing that work.
>
> The concept of evolutionary optimization is not a truly viable option
> today but improved understanding of processes can actually open the
> door for evolutionary optimization thought processes to come in
> leading to improved efficiency. Also, I think it is important to
> realize that we will be thinking in terms of a multivariate systems
> approach where you take advantage of the built in redundancies that
> you have in the system and actually go towards risk classification and
> mitigation strategies which are far more sophisticated than what we do
> today.
>
> Just to sort of share with you, I think we have to learn how to take
> advantage of built in redundancies. Redundancies are not bad. I think
> if I use NASA as an example, you have six backup systems. In the case
> of PAT, I think the development of redundancy that we can have and
> take advantage of I think we will learn on a case by case basis. But
> if you start thinking about a systems approach to setting
> specifications to GMPs, and so forth, the whole concept comes together
> quite nicely.
>
> At the same time, I think the link between the PAT and cGMP
> initiative, at least from my perspective, is that quality depends on
> knowledge and PAT brings more knowledge and understanding of all
> processes, and this is a way where we can actually make science and
> risk-based decisions in terms of manufacturing.
>
> Briefly, I think the key question from a regulatory perspective is was
> quality built in or was quality by design built in? Either phrase can
> be used interchangeably. From a regulatory perspective, it is often
> difficult to assess that because of the limited data. Many companies
> do extensive development work and actually have a lot more information
> and understanding of their processes, but what gets transmitted to FDA
> and FDA understanding is obviously at a different level but, at the
> same time, we both have to make the same decisions\--was quality built
> in or was it by design?
>
> If we are making decisions based on data derived from experiments or
> decisions based on innovative approaches, it is often difficult to
> assess that. Therefore, I think we get criticized that our approaches
> are empirical but I think the reality is that those are the data sets
> on which we have to make decisions. If we are empirical, it is because
> the data is empirical. So, we have to be concerned with every step and
> that is the current system.
>
> As we improve our knowledge and understanding, we move up the
> knowledge pyramid where we establish causal links and are able to
> predict performance. There, I think that is where PAT takes us, and
> our ability to say that quality was built in is much improved,
> although limited to the experimental design base that we have but at
> least we now have a better, more sophisticated risk assessment than
> risk-management strategy which would focus on clinical process control
> points. That is where PAT takes us. Eventually I think with the
> mechanistic understanding and first principles you can actually go
> further but I think that will take more time because our systems are
> very complex systems in a physical and chemical sense.
>
> Just sort of to share with you the other aspect of risk management,
> quality risk classification, if I use the SUPAC concept of defining
> high, medium and low impact on quality and then sort of overlay that
> with what the GAMP-4 describes as matching risk, you have an
> opportunity, as we move towards quality by design in a systems
> thinking, to reduce the risk likelihood and, thereby, reduce the
> concern about impact on quality. So, what might be a level three
> change today in the SUPAC actually goes to a level two change, and
> that is one approach of saying that we do need a product approval
> supplement and this can be handled in a different sense.
>
> But this is just the first step. We can actually not only reduce the
> risk classification but also improve by increasing the probability of
> detection. That is what quality by design and systems approach does. I
> think the way this will probably emerge is with trying to connect the
> dots between development and manufacturing and review and inspection.
> The question that we start focusing on with PAT up front is was
> quality built in. So, that is one question that we ask at the IND
> stage. As we go through the clinical development and we have the
> safety and efficacy data, and we have to ask the question how do you
> set the specifications? If you set the specifications as stringently
> as we do today, not taking advantage of the complete understanding of
> the process and all this, then we will have made progress.
>
> If you have process understanding, then we can make decisions which
> are more relevant to how we set specifications, not only taking into
> account safety and efficacy but also process capability. Many times I
> think some flexibility is needed here so at the time of approval we
> may start thinking about an interim set of specifications which get
> finalized a year from that or at some period when you have more
> manufacturing history. At the same time, the knowledge that you
> develop for your product brings us into the mode of making your own
> SUPAC concept; change management which is specific based and derived
> from the data that you have.
>
> That was sort of the background and update that I wanted to provide
> for you. I just want to focus the discussion today on what we seek. We
> seek information on the following: One major question that is in front
> of you is computer software validation. There are several excellent
> guidance documents. For example, in your handout that was mailed to
> you we included several guidances developed by our sister
> organization, Center for Devices and Radiological Health. I could not
> send you the GAMP-4 but there are other such documents.
>
> My proposal is to adopt and/or to refer to some of these directly in
> the PAT guidance instead of reinventing the wheel. The question that I
> pose to you is what initial controls would you recommend for the PAT
> guidance? Taking the CDRH guidance that you have in your handout for
> software validation, possibly looking at GAMP-4, what controls would
> we need to consider in the PAT guidance?
>
> We also want to sort of address CFR Part 11 issues. I am very pleased
> to let you know that Joe Famulare is now the agency lead for this
> topic and, after my presentation, I would like to have him say a few
> words. Actually, I have asked him to lead the discussion on this
> topic. Having Joe as the lead for the agency, not just CDER but for
> the agency, helps us to sort of focus on the PAT concept better.
>
> But I just want to caution you that Part 11 applies to all systems
> generating electronic records. I would like to focus our discussion
> today within the context of PAT. We can not solve all the issues. If
> you could focus your discussion within the context of PAT, I would
> appreciate that.
>
> I have provided for you some questions that may be relevant. I think
> these are questions that we sort of pose to you as framing the goals
> and objectives of this discussion. For example, if you take
> near-infrared as an example, what incoming material data should be
> acquired? What incoming material elements should be retained? What
> in-process data element should be required, and so forth? What is an
> electronic batch record in terms of PAT? So, if you start thinking and
> working through some of these questions either in the case studies
> this afternoon or through the discussion this morning, this would be
> very helpful to us, especially I think what product release elements
> should be retained, and so forth.
>
> We would also sort of like to fine-tune some of the discussion using
> case studies. I think we have two wonderful examples. I am very
> pleased and thankful to Bristol-Myers Squibb for putting together an
> excellent case study for discussion this afternoon. We call those mock
> submissions. But we would like to use this and Steve Hammond\'s
> presentation, for example, to sort of go through the regulatory
> challenges and solutions that need to happen to facilitate PAT
> introduction.
>
> I also want to emphasize that rapid micro is an important part of the
> PAT initiative. Although we have not discussed this extensively, I
> think we need to do that. The general guidance will not get into
> details on rapid micro methods but, hopefully, will provide enough
> information to encourage use of rapid microbiology testing. We have a
> working group discussion on that this afternoon.
>
> To sort of help focus the discussion, I have asked Bob Chisholm to
> take the lead in some of the discussion in framing the computer
> issues. Although he is not making a formal presentation, he will work
> through some issues from his chair at the table.
>
> Joe, do you want to say a few words?
>
> MR. FAMULARE: Concerning Part 11 and PAT, I could just echo what Ajaz
> has said, that we have heard some concerns as this new technology
> develops about will Part 11 serve as a hindrance, just as we have
> looked at other regulatory processes and so forth? We hope to work
> through those in the proposed guidance. Here, today, we hope to have a
> good discussion of certain experiences that companies have had that
> have looked at the PAT systems and how they have grappled with Part
> 11. We could take that information back to the overall Part 11 work
> group that are meeting right now with representatives from all centers
> in the field in FDA. So, we hope to hear what the problems are from
> some perspectives; hear what the successes are; and at least be able
> to touch upon them in a practical sense in the guidance coming up.
>
> DR. LAYLOFF: Thank you, Joe and Ajaz. You can see that the PAT
> committee has been very successful and there is a long shadow that
> Ajaz has placed over it. His leadership has kept it driving.
>
> Clearly, when you talk about electronic records and record retention,
> PAT is electronic records, electronic acquisition. Part 11 is going to
> be a big player during the implementation of PAT. To go into those
> discussions we have invited some speakers, or Ajaz has.
>
> DR. HUSSAIN: Tom, I think it is not reflected in our agenda but I
> think what I had in mind was to have Bob Chisholm sort of lead the
> discussion and sort of frame the questions broadly, and then we will
> listen to the invited guests.
>
> DR. LAYLOFF: Fine. Go, Bob.
>
> **Computer Systems Validation**
>
> **Part 11 Issues Pertinent to PAT**
>
> **Invited Guests**
>
> DR. CHISHOLM: This handout was done very, very quickly because we
> didn\'t realize that we were going to be doing this presentation. In
> fact, we did a computerized presentation last night which, I am
> assured, is coming in the door as we speak.
>
> It is focused very much on the area of compliance, practical
> implementation of PAT and compliance, focusing, of course, both on
> computer system validation and 21 CFR Part 11, which is central, and
> the experiences we have had. Then, just at the end looking at the
> risk-based approach to quality management and what effect the PAT
> initiative may or may not have on that.
>
> So, taking an overview of that, what I really want to talk about\--and
> I also have some overheads which I clearly can\'t use either so it is
> not the best of days for me\--
>
> DR. HUSSAIN: Well, what we could do then is, in a sense, listen to the
> invited guests and then sort of refocus that.
>
> DR. CHISHOLM: Whatever you want to do. It is better presented than
> read out.
>
> DR. LAYLOFF: Okay, Bob, you have your slides.
>
> DR. CHISHOLM: Stand up or sit down?
>
> DR. LAYLOFF: Stand up; you have to stand up.
>
> DR. CHISHOLM: Sorry about that. We should be used to agendas being
> changed at the last possible minute, I guess. Is there any chance of
> getting the two overheads up? You have to have really good eyesight to
> see these but never mind.
>
> As I said, this is the focused part of the presentation. PAT is a
> means of achieving manufacturing excellence, which is what I am about
> really coming very much from a manufacturing background.
>
> Basically, what I wanted to talk about, and I will be brief\--how long
> do I have? About 15 minutes max?\--I want to talk about the different
> levels of PAT systems and what we mean by them, then moving on to
> level two and talking about our experience with validation and 21 CFR
> 11 considerations. That is a general solid dosage facility.
>
> Moving up into level three, which is something I don\'t think we have
> discussed very much here in the past. It is about diverse data
> management, storage, modelling and manufacturing execution systems,
> and that is where I think we come in actually to product release and
> how we handle that.
>
> Then talking very briefly about manufacturing execution systems as
> tools to manage the risk and manufacturing as opposed to end-product
> development.
>
> What I mean by three levels of PAT systems in our definition, the
> first one is level one, which is stand-alone, which would be typically
> the most frequent that is currently around, NIR analyzer and its own
> PC. Basically that is for material classification.
>
> A level two system is moving on to what we have done in our German
> facility, which is a total facility approach where you move in to
> basically real-time quality control and quality assurance, and you
> probably need to ethernet that data because you are beginning to deal
> with big and complicated data flows.
>
> Then, on top of that, to manage all that data and to use it
> effectively you have to develop the upper level IT compliant system,
> which I will talk about. Here is large volume diverse data storage
> management and modelling functionalities and the manufacturing
> execution system.
>
> I am obviously not going to demonstrate this list of computer
> validation documents because I have no way of putting it up at the
> moment but that doesn\'t matter. I think the first point I would like
> to make is that when you move into 21 CFR 11 in these systems you
> actually have to have a strategy document. I think you should have a
> strategy document which actually gives your whole principle in terms
> of password control, IT security, but your actual testing becomes part
> of your normal computer validation documentation. You actually test in
> a normal way because it is an inherent part of computer validation but
> I think it is best to lay out your strategy for the total system as a
> separate document. We could give some regulator comments perhaps later
> on that because it actually lets a regulator see what you are actually
> trying to achieve, and you prove you achieved it by testing.
>
> In this, I think what you need to do is take a risk-based approach,
> effectively failure mode effect analysis. You have to look at an
> ethernet system and you have to see the points where anybody can
> actually come into the system through an interface and interfere with
> data. You actually have to make sure that that doesn\'t occur of, if
> it does occur, you clearly have an audit trail.
>
> So, we are talking here about password hierarchies. We are talking
> about Windows 2000 IT security and your audit trail philosophy. If you
> look at a typical ethernet system, and I have one here but obviously I
> am not going to put it up at the moment, basically you actually have
> the operator or plant personnel coming in to what we define as a panel
> PC. So, you control that via password access. You could have system
> administrators or IT people coming in through the server because that
> is an associated keyboard. So, you have to direct your attention
> there. Also, you can have people from outside coming in if you have an
> ethernet or corporate system and you have to have protections there.
>
> That tends to be managed in general by, firstly, password control and
> that can be corporate passwords and, secondly, by the application of
> access levels and what you can do with the data. So, you can define
> whether people in an occurrence are read-only or whether they can
> actually write null to the data, and that would all be in the
> philosophy document for the agency to review.
>
> Any questions, just stop me. In terms of data transfer protocols, I
> just want to mention one particular thing. Traditionally in systems
> you would use a mailbox approach. In other words, your lower system
> would store the data and flag it up; in a higher system you
> effectively scan and take it up at intervals and that is perfectly
> okay provided you have an audit trail, etc., etc.
>
> The concerns begin to arise if your schedule log is down because then
> what actually is being transient data can actually become an
> electronic record. I think we will have to consider what we mean by
> transient data in terms of such occurrences and how you protect
> against that.
>
> What I am trying to do here is pose some questions for you because I
> think they are all relevant. I am not giving you the answers and I am
> not saying that we have the answers but they need to be discussed.
>
> Moving up to a higher system, what I have put up here is basically a
> level three system. We have some kind of database and what I have
> shown here are the different functionalities. So, you have your NIR
> data and met-data typically. You have your analytical data and
> meta-data coming in also. Then you have your research data for your
> original models, etc. having to come in.
>
> The reason we are using something called a filter is a software
> transfer function effectively is because you want to transfer that
> into whatever data protocols you want to use within your database and
> within your high level system. This allows you, on that basis, to take
> data from any source that is compliant and all you have to do then is
> clearly validated the transfer through that software filter. I think
> that is a very useful point. Modelling functionality clearly is
> necessary here. Manufacturing execution and reporting system I will
> come to, and long-term archiving I will come to.
>
> If we actually think about these systems, what do you have to do? I
> will just give you a brief example and try to make this fairly quick
> because this is actually normally quite a long presentation. You have
> actually developed a product using pharmaceutical development, people
> in R&D, and you have a model and that model is then imported into the
> system.
>
> You have to consider issues of model validation, approval, etc., etc.,
> but the first thing you have to consider is that that model is being
> done in R&D facilities, not in the actual plant. So, that model then
> has to be expanded to represent the plant. Clearly, what you have to
> do there is that you then have to actually create hierarchies of
> models. That model, when it comes in, I would suggest could be
> something called perhaps a development model.
>
> Once you start to expand in your own facility, then it becomes
> effectively a working model but it has not been approved for use; you
> are not releasing product. Once you have validated it, you have
> another decision to make, do you validate it using spectral or image
> validation using analytical data from your plant, and these are all
> decisions that have to be made and a balance between the two.
>
> Once you actually get there, once you are approved, that is when your
> signature comes in and that is where the QA/QP could actually do the
> actual approval and then, and only then do you have a model which
> would actually be the model you are using in the plant, your approved
> model.
>
> What we have to consider really, the FDA and other agencies have to
> think, okay, a number of things about models. What do they actually
> want to see? Do they just want to see the algorithm, or do they want
> to see the algorithm, the data and the methodologies of getting to
> that algorithm? If they want to see that, do they want it demonstrated
> how the model was created? These are all things that could actually
> appear in some sort of way because companies will have to take these
> decisions. Is it enough just to have an algorithm and show that you
> have validated it, or do we have to go further back? I just pose these
> as questions.
>
> Again, advice from the agency would be welcome for archiving. How long
> do we have to keep all this data? Once you get to model revision ten,
> which may be after ten years, should we be keeping everything because
> we will have to archive it eventually? Is it on the life of the
> product? Is it on the shelf life? What exactly is it? Obviously, with
> clinical trails material we have to keep it for a long, long time.
>
> Again, stop me if there are any questions; I am going quickly
> obviously. Once you have the manufacturing execution system you have
> major opportunity I think, and that is why the level D system is so
> relevant once you take that into account. This allows you to do
> real-time statistical monitoring. This allows you to take real-time
> decisions. I will give you an example. You have your dispenser, all
> analyzers on the dispenser. The operator will go in. He brings up it
> up, pass/fail. What do you do then?
>
> Well, what you do then is bring in your audit trail immediately
> because you are out of GMP and it has to go back to the warehouse. So,
> that is a very positive thing so he has to bring the next level up to
> actually manage that. That is a typical statement but it is really a
> question, do you have to do that?
>
> Let\'s say that it actually passes but the operator then brings up the
> historical trending and sees that gradually over time the
> specification is changing. That is important. He needs to inform the
> plant manager supervisor about that because you are now getting into
> data mining.
>
> You can then use statistical distribution, etc., to look and see why
> and perhaps you can relate an increasing blending time to change in a
> certain raw material. I think this is what Ajaz was referring to in
> his presentation.
>
> But all these things are part of a manufacturing execution system and
> what is the relevance to regulatory authorities? How many records do
> we have to keep, etc.? It just becomes another one of these big
> questions. Is it a manufacturing company tool or is it something we
> all have to share? Posing that again as a question, I am in no way
> responsible for AstraZeneca regulatory strategy, I can assure you.
>
> So, we start to move on to product release or batch release. So, what
> do you actually have now? You have the ability, for instance if you
> monitor tablet quality but you have all the other variables leading to
> it, you have the ability to do distributions which we kind of hope are
> going to be normal distributions. How do you actually use this to
> release the batch? And, this is where I am going to stop, again posing
> questions to you because I think they are all very relevant.
>
> Well, I think we really need to work with the agency here because if
> we are going to start using statistics to release batches, or
> statistical distributions and their attributes, we have to
> decide\--when Ajaz talks about defining intermediate quality
> parameters, clearly, in terms of normal distributions that would let
> you work with a bigger set of standard deviations than perhaps you may
> be able to later. But all these things I think need to be explored,
> and I am talking quite generally and I think we are all talking
> generally in these areas and I think what the industry needs is
> certainly to get down deeper into these things because we are very
> comfortable with registering specifications plus/minus X percent of
> your spec. This is a very different world and we all have to be aware
> of that I think.
>
> What I would say is that ultimately risk is a statistical evaluation
> in manufacturing. You have already done your good process design, you
> are then manufacturing, and the nature of cybernetics\--and I speak as
> a control engineer, and it means that things may change over the life
> of a product.
>
> So, once you start using manufacturing execution systems you get
> distributions of tablet parameters, etc., statistically sampled. The
> actual statistical monitoring and control monitors the risk. The
> analysis of distribution then evaluates the risk and that is what I
> see as risk in manufacturing, and I think that is what a lot of other
> industries would see as risk in manufacturing. But it is not something
> we have done a lot of in the pharmaceutical industry. I am not saying
> we should stop; I am saying these are the areas that we have to
> investigate.
>
> There was one last one, in 1925 H.G. Wells said that one day
> statistical knowledge will become a very, very important item of
> citizenship, and I think this may be one area where that is going to
> apply. I will, hopefully, take any questions throughout the day. I
> have done this as quickly as I possibly can.
>
> DR. WINGATE: Hello. I have been invited, and thank you very much for
> the invitation, to speak around regulatory history, real experiences
> that GSK has had around computer validation and Part 11.
>
> So, I am going to take a slightly different tack from the previous
> presentation. Bob was looking at some of the technical details. I am
> again going to be prompting some questions but based on our inspection
> experiences, but also when we have done our remediation, the main
> issues which have affected us.
>
> I am going to give a brief outline of the particular inspection I am
> going to talk about. I am going to outline the remediation plans we
> went through at the top level, and I am going to touch on some
> validation key issues for us and some Part 11 consequences as well.
>
> I am going back to 1997, when then Glaxo Wellcome had an inspection at
> one of their U.K. secondary manufacturing sites. This particular
> inspection was a general inspection and covered computer systems. In
> particular, it looked at legacy systems and in one particular case a
> legacy MRP system that was developed over a decade earlier, quite a
> common problem; we weren\'t unique in this situation, being inspected
> on an older system, a custom-built system as well.
>
> Several computer validation observations were made, and this was a
> multi-site system shared across many sites, supporting many sites. The
> corrective actions to address these observations had to cover the
> sites affected.
>
> The company gave a commitment to the FDA to validate all their
> systems, and actually seven sites were affected at least within
> defined time scales. There was a massive mobilization staff in the
> company. You can imagine a seven-site MRP-2 type replacement program,
> a very large project indeed.
>
> In the meantime, while that project was being launched, there was the
> recognition that we needed to put in interim measures. So, while we
> are waiting for the replacement or a solution, you need to address the
> immediate needs to improve the confidence, the assurance you have in
> your processes. So, we brought in a series of manual ways of working
> and they complemented the automated processes by bringing in a
> verification, parallel verification of operation. That was very
> resource intensive. So, in a way, we had two massive mobilizations of
> staff, one to bring in replacement systems and one to bring in interim
> measures, and that was on an ongoing basis, the interim measures.
>
> To fix the situation we initially started thinking about retrospective
> validation, which is always difficult and can never really achieve the
> standards and the built-in quality attributes we have been talking
> about earlier into an existing system. We soon realized that we
> weren\'t going to be able to recover the quality standards achievement
> in that system so a replacement was then planned.
>
> In that replacement\--this is 1997\--we included Part 11 within that.
> The replacement system selection, right from the womb to the tomb of
> the project, was actually conducted over an 18-month period. That is a
> very accelerated process for such a large system. Many MRP-2 type
> rollouts occur over many years with a phased delivery and it
> represented a significant investment, and we maintained a dialogue
> with the FDA through that period.
>
> So, what were the lessons for us, all the issues that we uncovered? I
> guess when we are bringing in either a new computer system or new
> technology, if we are dealing with a retrospective validation issue
> this can be very difficult with the new standards which emerge at that
> time. For us, we had a batch investigation which went along the time
> when we had observations on our computerized systems, and this
> concluded that there was no evidence that we could find in the quality
> of the batches which indicated there was a problem created by the
> computer systems. We had an observation for lack of validation or
> incomplete validation when we looked at the batches, that wasn\'t
> actually impacting the batches.
>
> So, that is another key thing. I think when we are looking at the
> integrity of our processes and our systems validation we have talked
> about risk. It is the focus on the patient as an attribute. We have to
> get things in balance. We validate. We have integrity controls for
> Part 11 to bring assurance to our processes, but we have to balance
> the amount of effect we are putting in there, the amount of technology
> or grunt or sheer effort to validate these systems in balance with the
> benefit and performance they give.
>
> Part 11 brought its own challenges as well. We had an issue at that
> time, not too surprisingly in 1997. New regulations, standard
> commercial products out on the market\--they didn\'t come with Part 11
> built in. A lot of education had to be put in with our suppliers. Even
> today, although there is a higher awareness, Part 11 is not routinely
> built into products. A lot of products have developed over many, many
> years and they have historical bits of code themselves from five
> years, six years, seven years, more built in. So, as commercial
> products evolve, even when they label a brand-new version or addition,
> they tend to try and reuse as much as possible of previous products.
>
> So, there is an issue there as we move on with Part 11. The commercial
> products, they are struggling to build in a consistent interpretation
> of Part 11. There are still some evolving aspects in interpreting what
> exactly is required, but also there is a lot of historical software in
> products that we combine.
>
> Part 11 also drives a significant increase in the amount of data
> archiving presented, and that has been indicated by Bob has well. This
> is to do with when does a record get created. We refer to the
> predicate rules for that but that is sort of a summary list. It is not
> a very prescribed list. There is reliance on raw data and the
> processing of raw data, their intermediate values of calculation. How
> much do we have to apply for a full automatic audit trail, if you were
> absolutely fundamental in every bit of stored data, having its own
> audit trail you are multiplying the amount of data in your system many
> fold. It is not just a question of adding ten percent extra storage on
> systems; you could be adding many hundreds percent extra data storage.
>
> I think Ajaz had critical points in your process, identifying critical
> points, those are probably the critical area where you need the full
> integrity that Part 11 would bring in.
>
> We have also indicated the long-term archiving problems, the
> preservation of data. The march of computer technology is ever forward
> and changing. If you have personal computers, there is always the
> upgrade coming through and it is the same with the manufacturing
> systems that we have. As we create data and we start archiving it, we
> have to maintain it, maintain it in a fashion so that we can extract
> and return the data to store it, that we can make it meaningful and
> can use it if we need to access that information.
>
> As technology moves, that forces the migration through many different
> systems. Bob was talking about clinical data being over thirty years
> in some instances for retention periods. Manufacturing data, of
> course, is a lot shorter than that but still, with the evolution of
> software, we are forced to upgrade our systems and it is difficult to
> guaranty that with the historical data, that environment in which it
> was created, you can recreate to effectively accurately retrieve
> information.
>
> In order to get over that, you have to add in more technology controls
> to build in the assurances in the equivalents of your new systems to
> be able to make the data meaningful and accurate. So, that is a major
> issue too. For us, this is again a sort of open question. We are
> struggling with this. We are creating archiving systems but we don\'t
> have an archiving solution which will see us through ten years and we
> know that we have found the ultimate solution and we can guaranty
> access. We are going to have to go and replace systems again and again
> and again to maintain the data.
>
> In summary, validation Part 11, it is good business sense. We do it
> for a reason. We don\'t need the cGMPs to do validation or need
> assurance on our data integrity, but there has been a steady increase
> in interpretation around validation requirements and Part 11. There is
> still ongoing evolution of the interpretation at the moment. FDA is
> issuing a new draft guidance. It is not a fixed target. If we had a
> fixed target it would be easier to develop a strategy where you have
> confidence that I am investing so much money and I will achieve
> compliance; I will do that; I will also get business benefit; i is not
> an open-ended check book.
>
> Now, grand-fathering is an issue with legacy systems. We have many,
> many thousands of systems on sites. The amount of automation on sites
> is huge these days. From security, when you go in it is often an
> automated system; your laptop, everything is getting more automated.
> Retrospective validation is very difficult to achieve satisfactorily.
> So, it is almost forcing a replacement program. That is the way you
> stride forward. It is very difficult to go back and fix things if it
> isn\'t right. If there is a new requirement or a new interpretation
> you have to replace.
>
> Compliance is driving a large investment, particularly Part 11, in our
> companies, not necessarily directed at process improvement but
> directed at satisfying compliance requirements because of the
> grand-fathering issue and the difficulty of retrospective work.
>
> So, the main question I guess to conclude, for me, and we have raised
> risk assessment already is, we are reviewing the GMPs, or the FDA are
> reviewing the GMPs in the environment of a risk appraisal approach to
> get that balance. Industry wants to validate and assure integrity of
> processes but we need that balance. We need those processes, the risk
> tools. GAMP put up SUPAC. FEMAA was mentioned. There are others. There
> are lots of these tools. If we can formally get those incorporated not
> just on the process\--Bob was talking about risk analysis on the
> process, but also the risk assessment approach to data integrity and
> the validation approach, that would be a big step forward. Thank you
> very much.
>
> DR. LAYLOFF: Thank you. What operating system were you using thirty
> years ago?
>
> DR. WINGATE: I have no idea. Which one will we be using in thirty
> years time? Who knows?
>
> DR. HUSSAIN: I think I have a broad, general question. If you had a
> magic wand and had a solution, what would that solution look like in
> your mind?
>
> DR. WINGATE: To validation? You mentioned GAMP but I guess there are
> others as well, as you indicated, Ajaz. That is a mid-range, typical
> type of project size approach, a little practical sense in there and
> it includes a risk-based approach. That sort of approach for mid-range
> to look at the average requirements, don\'t pitch for the top level,
> allow pharmaceutical companies to determine how they scale up or scale
> down as appropriate but get all the fundamental guiding principles in
> there.
>
> Part 11, I would say it is around determining what is critical in a
> system for data integrity, not all data, allowing that determination
> of criticality in the process.
>
> DR. HUSSAIN: Would you be comfortable recommending that GAMP would be
> adopted by FDA?
>
> DR. WINGATE: Well, I have a vested interest\--
>
> DR. HUSSAIN: That is the reason I am putting you on the spot.
>
> \[Laughter\]
>
> DR. WINGATE: Sure. Yes, we participated as both GlaxoSmithKline and
> Glaxo and, indeed before that as Wellcome, within GAMP-4 because we
> thought it represented a good industry baseline. For us and many other
> companies I think it has been largely proven in practice to be
> effective, but it is averages. It is not the answer to everything.
>
> DR. LAYLOFF: I guess the added record-keeping, it is not a problem
> that you are addressing except the data systems themselves.
>
> DR. WINGATE: Right. When it comes down to inspection one of the
> problems we have is having a consistent expectation from individual
> inspectors, and that does vary a lot. It varies from one extreme to
> some inspectors saying, no, I don\'t want to touch the computer
> system; I don\'t want to go there. Just tell me about those computer
> systems, to others who go in, in depth perhaps when they feel there is
> due cause for an in-depth inspection and they are spending a lot of
> time on that rather than a broader portfolio of what we are looking
> for across a process.
>
> So, it is getting consistency, and then there are different
> interpretations even by individual inspectors. It is not just FDA,
> this is all inspectors about what they would expect in terms of a
> solution. A lot of inspectors themselves are struggling with Part 11
> as well. A lot of them are coming back to more the good practice
> expectations. Tell me about your security; tell me about your record
> controls and how you demonstrate an audit trail, not necessarily
> saying show me your exact audit trail contents.
>
> DR. MORRIS: Just one comment on your comment is that in addition to
> the general data trail concerns that you have raised, there is also
> this commercial aspect, the commercial vendors aspect. I think we are
> sort of missing that sometimes because it is quite a challenge,
> particularly for small vendors to know, even if they are willing to
> know, what to do and then for them to go back and find, you know,
> pieces of their code, even if they are sound code and validatable, in
> the strict sense of the word they don\'t have the trail to bring to
> the table to prove that they were compliant with Part 11. I think that
> is sort of an undiscovered country, if you will.
>
> DR. WINGATE: True. Remember that many vendors are not just supporting
> the pharmaceutical industry\--
>
> DR. MORRIS: Absolutely.
>
> DR. WINGATE: Pharmaceutical industry may be five percent less of their
> sales base. So, they are doing a good, robust product. It is proven in
> other industry areas. You know, what is the cost to them? Will it feed
> straight back on the pharmaceutical manufacturers to create a special
> product so you are customizing a product for a smaller use base and
> does that introduce more risk to the process? You certainly have a
> less widely used system then of proven capability.
>
> DR. LAYLOFF: More validation.
>
> DR. WINGATE: More validation and, indeed, then you have the
> integration between different vendors with different standards, some
> with Part 11, some without. It gets very complicated.
>
> MR. FAMULARE: So, when you went forward to bring your facility into
> computer validation in Part 11 compliance, you had to get many
> customized products from vendors to put in place.
>
> DR. WINGATE: Right, or we created, as it were, wrappers or customized
> modules to add on to commercial products. Right.
>
> MR. FAMULARE: Did you feel it was warranted in every case based on the
> criticality of the process, or in certain instances it may have been
> and others not in terms of having that flexibility?
>
> DR. WINGATE: I guess that is one of the biggest problems. It is not
> definitive when you look at the system exactly which records you have
> to provide audit trails for. If you refer to predicate rules it says
> production records. What exactly is capture in that? You apply your
> interpretation of what you expect. It is a bit like an iceberg. You
> start defining your records but then you have all these
> inter-dependencies on data, supporting data, which are then used\--
>
> MR. FAMULARE: The data that supports the records.
>
> DR. WINGATE: Right, and all the time you are trying to say, right, I
> need control over these key records. I want that anyway, but then it
> is the controlling of the records through the systems as they get
> compiled; as you apply electronic signatures to them.
>
> MR. FAMULARE: And the problem or the question is, is it all data or is
> it critical data when you look at the predicate rule.
>
> DR. WINGATE: Well, the predicate rules aren\'t all that helpful, I
> guess, in identifying what is critical data.
>
> MR. FAMULARE: For example, for a batch record the critical steps in
> the operation, but that doesn\'t lend itself to helping you in terms
> of designing a system.
>
> DR. WINGATE: Right. We tried basically to map what we had in the paper
> world. You know, historically there had been an evaluation of the
> critical steps and processes and then they were mapped into the
> computer systems to say that is where we apply our controls.
>
> MR. FAMULARE: So, if you had standard manufacturing in a PAT
> environment you would, hopefully, be able to identify critical steps
> where you would want to put your emphasis and then to be able to
> de-emphasize those steps which you think are not as critical.
>
> DR. WINGATE: Right. You typically do two activities. You have sort of
> a process map\--
>
> MR. FAMULARE: Right.
>
> DR. WINGATE: \--of the critical steps in the process where you wanted
> to apply controls. Then you would also do a data analysis, a data flow
> analysis. So you have those critical points of data, but how were they
> created; where were they moved from and to; and what are the controls
> that you need to bring in on that dimension?
>
> MR. FAMULARE: So, trying to map all that is where your problem lies.
>
> DR. WINGATE: Right, right. We were talking about an MRP system and
> there is an awful lot of data in an MRP system, and one of the issues
> that we are facing right now as a consequence, we think we did a very
> robust job in identifying which were the critical process steps and
> the control of the data supporting those, but it is now the archiving.
>
> The system is not that old. We have new replacement systems two or
> three years old, yet we already have a massive archiving issue just in
> volumes of data. Now, this is a higher level system so we are not
> getting into the very high volume in terms of data that you might get
> in a lower level PAT system, the real-time data acquisition systems.
> You could have a very, very high volume of data there. So, it is how
> much data are you going to apply controls to, and what is reasonable
> in that approach?
>
> One of the things that has emerged through recent FDA guidance on
> record maintenance is reprocessing of data. You need a lot of data to
> be able to reprocess in exactly the same way as it was created. You
> can demonstrate a level of assurance with evidence showing critical
> steps, which is what we did in the paper world through the batch
> record compilation where you would have supporting data or evidence to
> show, with a reasonable degree of assurance, that your data was
> accurate as you progressed. Possibly that is something else that needs
> to be thought about for the PAT type side of things, with reprocessing
> all the meta-data which was referred to, which is the computing
> environment, and then you have the hardware dependencies, software
> dependencies. That kind of thing really needs to be solved somehow to
> give industry a lead in, otherwise we are left with a very open-ended
> situation. In today\'s environment, you know, we can\'t afford to be
> out of compliance but also lose quality control over our products, and
> we need to find that agreement where the two shake hands, if you will.
>
> DR. KIBBE: A quick question. In the absence of a regulatory body, how
> much of the data would you keep for your own use?
>
> DR. WINGATE: Well, I guess we would be looking at key processes of
> what we would need the data for after the event. Perhaps an example
> there might be if we wanted to process a product recall, what data
> would we need to support a product recall, to effectively ensure that
> we captured all the product back in the market? If we wanted to
> conduct a batch investigation, what would we need to make a reasonable
> determination of cause of the recall?
>
> Now, there is still a balance there because you may have less data but
> then your definitive answer to what was the first batch affected, the
> last batch affected may be over a much wider generation because you
> can\'t pinpoint it. So, if you had more data you could possibly
> pinpoint it a bit more.
>
> DR. KIBBE: So, basically you would be almost drawn into keeping the
> same amount of data whether there was someone watching you or not.
>
> DR. WINGATE: Right. I mean, it is a critical business process, for
> instance recall.
>
> DR. KIBBE: There is no way to say, okay, we are keeping this much data
> because there is a regulatory body but we wouldn\'t keep it\--there is
> no way to balance. What I am looking for is, is there a way that you
> can come to terms with what you really need to operate your company
> well and then have the agency say, okay, that is enough for us?
>
> DR. SHABUSHNIG: Can I maybe disagree with you there? I think there is
> a difference, and I think the difference is some of the intermediate
> levels of data that one might decide to keep. In other words, I think
> you need to keep the critical information you need to, and I agree
> with you entirely in terms of either supporting or recall, and you may
> also choose to keep a more richer data set for future data mining, for
> process improvement but, to me, those are more business-driven
> decisions rather than regulatory-driven decisions. And, there may be
> levels of intermediate data that you would choose to discard if there
> wasn\'t a regulatory requirement to keep them, allowing you to have
> the critical results that you need to support recalls, to support
> process improvement. But there are certainly some levels of
> information that I believe would be appropriate to discard. If you
> looked at a cost-benefit analysis, the cost of maintaining those is
> probably not warranted.
>
> DR. KIBBE: Now to get myself into my typical trouble with everyone, if
> there is data that you don\'t want and the agency wants, why don\'t
> you just give it to them and just get rid of it and let them keep it?
>
> \[Laughter\]
>
> DR. LAYLOFF: I think you need outcome keep enough data to be able to
> pull off a kappa. If you don\'t have enough data you can\'t go
> anywhere with it.
>
> DR. SHABUSHNIG: Correct, but I think you said something very
> important, and that is that when we are talking about risk assessment
> and risk-based determinations we should be looking at it from the
> standpoint of the patient. We should be looking at it from a patient
> perspective. I think there are several other kinds of risk that are on
> the table that at the moment are all being lumped together, and we are
> casting a pretty broad net around risk which, using that model, means
> that we are going to keep a lot of data and we are going to generate a
> lot of new data if we are not careful.
>
> I think from the patient\'s perspective the risk is that we are going
> to add a lot of cost without a lot of true benefit to the patient.
> There may be some benefits in terms of the process, but not
> necessarily for the patient. If the patient had a choice of whether
> they paid for it or not, they may choose not to pay for it. So, I
> think we have to be very cognizant of what we mean by risk, and I
> think we have to put patient risk at the top. There may be other risks
> that we need to consider but I think that one has to be at the top.
>
> DR. MORRIS: Could I ask a question?
>
> DR. LAYLOFF: Did you have a question, Bob? No? Okay.
>
> DR. MORRIS: Actually it folds in a little bit with what Bob was
> talking about. You were talking about getting models, if you will,
> from R&D and, hopefully, the models you get from R&D have identified
> the critical control points, at the very least. Whether or not there
> is a lot of statistical treatment or not or get to the chemometrics, I
> don\'t know, and there are other people here better suited to speak to
> that than I am, but at the point where you are evolving your model,
> assuming that you have done your R&D well, not that that is a
> slam-dunk of course because it is not trivial to do, the PCCPs
> themselves shouldn\'t change. The values may change; the models will
> change; the chemometrics will evolve because you are working with such
> a small data set when you come out of R&D. If you are using training
> sets, by design you are not going to be done. Is what you are saying
> that, having identified these critical control points, if I can
> identify the endpoint and control by the endpoint, do I need all the
> data that leads up to it? Or, are you saying that the PCCP type data
> should all be archived, and it is the data that is associated with the
> ancillary activities that shouldn\'t be?
>
> DR. SHABUSHNIG: To be honest with you, a little bit of both. I do
> believe that you can generate a pathway focusing on the goal at the
> end. What is the critical information that you need to make a decision
> about lot quality and to release this lot? That is really the critical
> information that you have to have. There may be intermediate steps
> along the say where you don\'t need that information as long as you
> have a good linkage. In my mind, you can get to a point where we are
> talking about more or less reporting by exception, in other words, as
> you are going ahead and generating the data along the way, you are
> making sure that you are in conformance with your process as you have
> designed it, as it has been approved, as you expect it to run but not
> necessarily\--when you are showing compliance along the way, you are
> working more on a pass/fail basis to make that linkage to the final
> result as opposed to keeping all of the extensive quantitative data
> that you would need to generate along the way. So, that is really what
> I am thinking.
>
> Now, to your point, I think there is also ancillary information that
> is out there as well and there may be an opportunity to scale that
> down, but I was really looking kind of at the primary change.
>
> DR. LAYLOFF: Leon?
>
> DR. LACHMAN: Yes, I was wondering if you could define in your
> rationale or strategy document those critical control points that are
> most important for product quality integrity, and address those fully,
> and the other ones less fully? Would you define that ahead of time as
> an approach?
>
> DR. WINGATE: I would think so. To me, that is a good part of a good
> process\--
>
> DR. LACHMAN: That is right.
>
> DR. WINGATE: I think that is something that we are or should be doing
> today.
>
> DR. LACHMAN: Yes. So, I think that spells out really those elements
> that you need to have full documentation or full archival, and the
> other ones could be of less importance.
>
> DR. WINGATE: Some of the other ones, for instance, you may retain for
> a shorter period.
>
> DR. LACHMAN: Yes, define that ahead of time. I think that should be
> workable.
>
> DR. LAYLOFF: I think we will move on now. I think we have resolved all
> this.
>
> \[Laughter\]
>
> We have Deborah Thomas. She is coming.
>
> MS. THOMAS: Hi, I am Deborah Thomas, and I am the director of quality
> and regulatory compliance for Air Products and Chemicals, Inc., which
> is headquartered in Allentown, Pennsylvania.
>
> I work for a medical gas company, which is a little different than the
> pharmaceutical area here. Our medical gases that we produce are
> compressed medical gases in the form of oxygen, for example, which is
> a prescription drug so it is the oxygen USP that goes to the
> hospitals. It is also the nitrogen NF which is a prescription drug,
> medical nitrogen which goes to the pharmaceutical industry life
> science and medical device areas. So, it is a little bit different.
>
> On behalf of Air Products, I did want to say thank you to the agency
> for inviting us to certainly give our opinion and impressions of Part
> 11 and how it has affected our business.
>
> I do want to tell you that we were moving right along with the new
> technologies that are out there today with procedures, batch records,
> and doing a lot of different things with the electronic records. Then,
> on August 2 of 1999 one of our colleagues in the industry received a
> warning letter on Part 11 compliance. So, we kind of stopped and
> looked at the regulatory requirements and had great difficulty in
> understanding how we were going to get in compliance in a very short
> period of time.
>
> What we decided to do was go back to paper records for our medical gas
> requirements. So, we are definitely electronic for electronic grade
> gases or industrial gases and even some of our food grade gases, but
> we have duplicate systems right now, and when I mentioned that to
> Ajaz, I think that is why he suggested or requested that I give a talk
> and kind of explain why.
>
> I believe that the interest certainly in writing regulations to
> facilitate us moving forward in technology is a great thing. In fact,
> some of the regulatory requirements our IT folks used as a guideline
> to be able to create the systems that we have. The audit trails and
> all those requirements we certainly applied, and think that that has
> made our system really robust. So, we do have an electronic system.
> Again, we use duplicate records, hard copy, for all aspects of our
> medical production.
>
> What I did, and this will be pretty short I think, I came up with
> three specific sections just to show you the difference in
> interpretation that our IT folks had and our regulatory folks in
> interpreting this in our industry. Again, not being a pharmaceutical
> industry, it is a little bit different and when we produce our gases,
> by the way, it is contemporaneously done for electronic grade and
> medical grade.
>
> I don\'t have an IT background. I want to mention that right away. I
> had a little trouble with some of the commentary that you folks were
> talking about, so I am not an IT person at all. So, if you have any
> questions, I will do my best but let me just go through my three
> examples here.
>
> I think the key is, seriously, that we just really felt that we had to
> go to a paper system. This was one example, 21 CFR 11.70 where it
> talked about electronic signatures and handwritten signatures executed
> to electronic records shall be linked to their respective electronic
> records to ensure the signatures cannot be excised, copied, or
> otherwise transferred to falsify an electronic record by ordinary
> means.
>
> I won\'t tell you the varied interpretations that I had when I sat
> down with a group of certainly IT experts on what this truly meant. I
> think the compromise that everyone came up with is that unless you
> have a complex system to meet the requirements of linking these
> records, they really felt that we had to have a person that actually
> had to be at the location to compare the handwritten signature against
> the electronic. And, our industry is a little bit different. We have
> unmanned plants. So, when we produce medical gases, at one period of
> time there is no one there. So, again, that is a little bit different
> than the pharmaceutical industry but we do produce prescription drugs.
>
> We also have remote locations where the agency has been gracious in
> allowing us to fax documentation back and forth, because even using
> hard copy records it is a little difficult to comply with cGMP
> requirements. So, for authorizations, when someone signs off on
> quality control for accuracy, completeness and compliance to
> specifications, we have controls in place so that if it is an unmanned
> site or there is only one person there or potentially no one there
> except the driver picking up the product\--I do want to tell you our
> industry is very safe, by the way, but if you are not familiar with
> it, it might concern you a little bit but there is no concern, I
> assure you. But we do have controls in place that allow faxing of the
> hard copy records to be able to do the appropriate and proper review.
> In this case, we do believe that if there are controls in place to
> prevent falsification of the electronic records we really don\'t
> necessarily need the electronic link here.
>
> A second example is persons using electronic signatures shall prior
> to, or at the time of such use, certify to the agency that the
> electronic signatures in the system used on or after April 20th of
> 1997, are intended to be a legally binding equivalent of traditional
> handwritten signatures. Certification needs to be admitted to the
> agency with the traditional handwritten signatures.
>
> This is not only difficult, it almost sounds impossible in our
> industry to be able to keep up with this requirement due to changes in
> our personnel. We also think it is a little different in the medical
> gas industry. So, where you might have electronic signatures recorded
> at the home office for some people at the plants, because of the way
> we release our product, our drivers are very key in the quality
> control process.
>
> So, they go to different facilities and, again, if you don\'t have a
> really robust computer system in different areas\--I mean, our
> production records are excellent. It is really easy to deal with some
> of those but we also have automated filling zones where the automation
> and the controls in place are excellent and we don\'t have any issue
> with product integrity, or any issue with being concerned about any
> kind of non-complying or non-conforming medical product, but the
> difficulty is to be able to keep up with the drivers that are quality
> control folks that are trained in that, as well as some of the
> customers that come in and although we do the first signature, which
> we would like to be certainly electronic as well, it would be very
> difficult, if not impossible, to ask for us to comply with.
>
> Lastly, in play are at least two distinct identification components,
> such as an identification code and password. This area was talking
> about in the event that you decided not to go with biometrics, which
> we tried, by the way. We tried a thumbprint machine to use a
> fingerprint which we thought was really great. Unfortunately, it
> failed our validation criteria and we thought that we could meet it in
> this case. But, in the event that the data in the computer cannot be
> modified by the users, we really felt that one distinct identifying
> component, such as an identification or password would be sufficient.
>
> Our business is a little different and in the home office or even at a
> large facility, which in some cases we have, these three examples can
> be met in a very short, easy period of time and that would not be a
> problem. But these right now are the ones that are really difficult
> for us to meet so we are less accurate and, unfortunately, make more
> errors because we did go back to hard copy records.
>
> Another suggestion that we had for some of these things would be to
> keep the signatures on file so that the agency would be able to audit
> that at that location for the individuals that came there. But so many
> things would be difficult, if not impossible, and this is very
> difficult for our folks to comply with. Any questions?
>
> DR. LAYLOFF: You say your system is more error prone and less
> efficient because of Part 11?
>
> MS. THOMAS: Let me explain. I think that Part 11 guidelines have
> certainly helped our electronic system, and we do use the electronic
> records for other parts of our industry but not medical gases right
> now. But, because of the requirements and because we don\'t feel that
> we can comply\--we really want to stay in regulatory compliance and I
> don\'t want to get a warning letter for Part 11, for violation of Part
> 11, but because we had to go back to a paper system, we believe that
> it is less accurate and much more subject\--that is why people are
> going electronic, to be able to have less errors and build those
> controls in place. So, I guess the answer to your question is yes.
>
> DR. LAYLOFF: Any more questions or comments?
>
> MR. COOLEY: I was wondering if you could maybe explain in a little bit
> more detail how you have gone to a paper system and have still
> controlled and complied to Part 11.
>
> MS. THOMAS: Oh, we are not audited to Part 11 because we don\'t use
> electronic records for our medical production. We don\'t use
> electronic records as far as signatures go. I am sorry, I am thinking
> signatures versus records.
>
> MR. COOLEY: How do you generate electronic records when you analyze
> the product?
>
> MS. THOMAS: Actually, what we do is when we analyze the product we do
> have the electronic records, but on the critical purity things we have
> people handwrite things now. The only thing is the form.
>
> MR. COOLEY: But your instrument that is making the measurements still
> generates an electronic record?
>
> MS. THOMAS: Right, and we don\'t have a problem with that, but it is
> the electronic signatures and also the electronic records associated
> with data input and review that we have gone away from. So, when they
> see our records, they consider those hard copy and manual. I
> understand what you are saying as far as the systems go, but when
> people come to our facilities, the inspectors, they don\'t audit us to
> electronic records when they see our hard copy system.
>
> MR. COOLEY: But the analyzer itself, then you are saying that you do
> comply with Part 11?
>
> MS. THOMAS: Yes, we do. But when we do calibrations and things like
> that, it is all handwritten. It doesn\'t have to be; it is all
> electronically controlled. We could just push a button and we would be
> really in good shape and be on our way but we have to transcribe
> things which can lead to transcription errors, you know, those types
> of things which we had really gotten away from up until 1997.
>
> MR. FAMULARE: Actually, I think you are going to a more basic
> requirement, and I think that is what you were going to in bringing up
> the question. If the record is generated electronically, the
> interpretation then is, well, then the record is electronic and,
> therefore, Part 11 applies. I think that is where you were going with
> that question.
>
> It seems that you may already have that but by creating the paper
> record, that is what you are showing during inspections so the issue
> hasn\'t come up for you.
>
> MS. THOMAS: That is right.
>
> DR. LAYLOFF: Wait a minute, Joe. All our instruments in the
> laboratory, you plug them into the wall\--
>
> MR. FAMULARE: Again, it is one of the interpretations of Part 11 that,
> again, is in the basic discussion and the difficulty that we have been
> dealing with. In terms of your filing the signature with the agency,
> that was meant to be a one-time thing for the whole company as opposed
> to trying to have the signature for every employee. So, I think that
> is one easily soluble that you wouldn\'t have to be concerned with.
> Once you register the facility, not the facility but every facility in
> your corporate entity, at least that would meet that requirement of
> Part 11.
>
> MS. THOMAS: You don\'t have to keep it up to date? The reason we are
> wondering is if we could do it and really get the most efficiency out
> of it, it would be all of the signatures of the individuals\--
>
> MR. FAMULARE: The idea of the declaration would be to have all of
> those signatures equal to a handwritten signature and just have one
> representative of the company sign it. We can discuss that. That is at
> least one easy one that we could solve for you.
>
> MS. THOMAS: That is good.
>
> DR. LAYLOFF: Don\'t forget to tell the investigator though.
>
> MR. FAMULARE: That is right, but as a whole, the agency did put out a
> compliance policy guidance around that same time that that warning
> letter was issued where, really, the enforcement would have to be
> basically on an important risk base type of approach, at least in
> terms of how the company is going towards compliance, and so forth. Of
> course, there has been a lot of evolution since then and a lot of
> discussion. Of course, one of the goals now of the reformed work group
> is to try and bring the principles of the GMP of the 21st century
> risk-based criteria control points, etc. to Part 11. So, that is the
> challenge we are looking at now.
>
> MS. THOMAS: That is great. Again, a lot of the concerns that we had in
> \'97, when I met to go over some of the things within the last couple
> of weeks, we certainly have moved ahead quite a bit. So, I think we
> have most of the other controls in place, which is great. Our folks
> really said that years ago we didn\'t have the technology we have now,
> so it is easier to comply but we are not there yet.
>
> MR. FAMULARE: I think Glaxo and Dr. Wingate paved the way by ordering
> all that equipment in \'97 when the rule was just passed and all of
> the vendors weren\'t up to speed.
>
> MS. THOMAS: Right, that was another difficulty, the vendors didn\'t
> have the offerings that we were looking for with the controls in
> place.
>
> DR. RUDD: A very quick question. I confess to being less interested in
> electronic signatures and more interested in product quality. Could I
> ask do you manufacture on a batch-wise basis in your company?
>
> MS. THOMAS: Yes, we do.
>
> DR. RUDD: So it is not continuous?
>
> MS. THOMAS: Oh, I am sorry, it is continuous but we do batch our
> product. It is a continuous process with product going into our
> storage tanks.
>
> DR. RUDD: So, in terms of sanctioning product quality, how do you do
> that? You mentioned handwritten purity data and that kind of thing,
> but is there individual data relating to individual batches?
>
> MS. THOMAS: Yes, our product is monitored all the time so in the batch
> we have on-line monitoring except when we switch to test tankers or
> containers, if you will, product containers. But what we do is we test
> the containers and do a pre-fill and also post-fill and we record all
> of that information, as well as product stream going into the storage
> tank.
>
> DR. RUDD: Good. Thanks.
>
> MS. THOMAS: Thank you.
>
> DR. LAYLOFF: Thank you very much, Deborah. Now we go to John Murray.
>
> MR. MURRAY: Good morning, everybody. I am John Murray. I work for the
> Center for Devices. I work for the director in the Office of
> Compliance in the Center for Devices. I am responsible for software
> policy, software validation, just about anything related to software,
> and I am also the CDRH rep to the Part 11 committee, and now I have
> known Joe for two months and I am sure that he loves me very much.
>
> \[Laughter\]
>
> I wish Joe would stop using the word \"reformed\" Part 11 committee.
> We call it the reformulated committee. We don\'t want to be reformed;
> we want to be reformulated.
>
> I do have a couple of things to say about Part 11. Actually, I am here
> today to kind of explain what the CDRH software regulatory model is in
> the simplest terms I can, in the hopes that you can use some of the
> information in your new 21st century GMP effort.
>
> The number one problem I find with Part 11 is what we call Part 11
> denial. People are buying systems and blindly trusting their vendors.
> I think you should apply the same scrutiny to your vendors that you
> apply to your own staff. If somebody wants to sell you a product that
> they say is compliant, they should be able to prove it. They should
> provide some documentation. I find a lot of vendors out there are
> using a little scare tactic because they know that you are on the hook
> to meet the regulatory requirement and they are selling product and
> forcing a lot of product into the market that really isn\'t Part 11
> compliant.
>
> Then we have an inspection and you get a citation for a Part 11
> violation, and then you go back and try to look at your documentation
> and you find out that your vendor really didn\'t provide it, or
> whatever. So, that is a problem. It is a Part 11 denial problem. You
> have systems that you don\'t do anything about.
>
> As far as the CDRH policy related to Part 11, it is definitely a
> risk-based policy. It is in accordance with our compliance policy
> guide. We have had several companies, and I am not even sure of the
> number, in the last year that have been written up or gotten a
> citation on a 43 for Part 11 violations. That comes into the Center.
> We review that and we look at the application and make a decision
> about the risk that is involved.
>
> In every Part 11 case that I know of, except for one, we have written
> a little reminder that goes in the warning letter, and I have been
> told by the regulatory experts, the non-threatening part of the
> warning letter. I am not sure what part that is\--
>
> \[Laughter\]
>
> \--it goes in the back, and it is a reminder that Part 11 does exist.
> It is a law. You should be working on it, and it is a requirement but
> currently no regulatory action is forthcoming and the risk is not
> apparent, or high risk.
>
> There was one case this summer. A company submitted a PMA and they
> went and did a PMA inspection, and during the inspection they found
> out that some of the data that was sent from one state to another
> state, to their statistician, when the data came back it was
> different. That raised our antenna, our risk antenna went way up in
> the air. This was clinical trial data and the issue was, well, how do
> you prove that your data is valid because we have some evidence that
> says your data is not valid so what about your Part 11 controls? They
> didn\'t have any controls. So, we had a high risk scenario, a
> violation of Part 11, a violation of the predicate rule.
>
> The recommendation was made and accepted that we withhold the approval
> of this PMA, which we did. The company came in and we had a meeting.
> Fortunately for this company, they had actually collected all their
> clinical trial data on paper originally, and they had taken it to
> their corporate office and entered it into the computer for analysis.
> So, they were able to go back to their paper copy and extract the data
> back out.
>
> The other thing in this Part 11 denial issue is that I see companies
> print out electronic data and then putting it in the FDA trophy case
> and saying, well, this is our FDA document. But when you go in and
> talk to them you find out that they are not actually using the paper
> documents to make regulatory decisions; they are using the electronic
> data which is in the database. They are pulling it for FDA inspection
> but when it actually comes time to make decisions related to Part 11,
> they use the electronic data. That is a prototypical example of the
> problem that we are trying to address by no paper representation of
> electronic records, which is the current interpretation of the rule.
>
> Actually, I could go on forever about Part 11 but I am here today to
> talk about the CDRH software regulatory model. I have found out that
> if I jump right into the regulatory requirements, the guidance
> documents and things like that, they will immediately begin to argue.
> They argue over definition of terms, meaning of phrases, what this
> means and all that kind of stuff. That is a huge problem in Part 11,
> in software validation and most of the computer validation
> regulations.
>
> So, I always like to go back to what I think is very fundamental to
> this issue, and that is that the quality of public health is highly
> dependent upon the quality of the medical software. We have medical
> software in drug manufacturing facilities, PAT systems, medical
> devices, clinical information systems, hospital information systems,
> everywhere you look there is some software involved in the
> decision-making process related to public health.
>
> So, my axiom is that public health is dependent upon the quality of
> the software and I think we can all agree upon that. The next question
> is, well, how do we measure that quality? I have invented what I call
> the YB scale, where one end is Yugo and the other end is BMW, and the
> quality ranges back and forth and everybody has a different
> interpretation of what that quality is or what quality you need. The
> quality you need is dependent upon the application and what is at risk
> here. This falls right into the whole risk approach for GMPs, which
> CDRH has been exercising for at least five years that I know of.
>
> So, you have to think in terms of on this quality scale from Y to B,
> you go to BMW, you look at a Microsoft product, where do you place it?
> Does anybody want to guess? But you all have an opinion. Maybe we
> should focus more clearly on the quality of our software.
>
> One of the fundamental problems is that traditional training of
> software engineering originated in the math department of most
> universities as opposed to an engineering department. So, for many
> years, fifteen or twenty years, we taught computer science in a math
> department. They have a different approach to problem solving than we
> have as engineers or as regulators. That is the first issue.
>
> The second issue is that most textbooks that I have read, and the
> number one selling software engineering textbook of all time, written
> by Dr. Roger Pressman, has a section on software risk management. The
> dimensions of risk in this textbook are schedule and cost, not safety,
> not effectiveness. Those are not in that risk model. So, traditional
> training of software engineers comes from this genre. So, when they
> enter the regulated environment they come with a different set of
> tools than they actually need to operate so that is a problem we need
> to solve.
>
> Software is different. I personally believe software is different and
> I have some examples here. Software doesn\'t wear out. If you put a
> hardware component in this system, eventually it wears out or it
> breaks. Software does not break after you install it. It is already
> broken when you install it.
>
> \[Laughter\]
>
> You just don\'t know it yet. There have been a lot of examples of
> this. Of course, we fully recognize that there is a huge benefit to
> computer software and that is what we are struggling with. We are
> struggling to get the correct balance here. There is a huge benefit if
> you get a good computer system, good validation. It can benefit many,
> many people\'s lives.
>
> The problem is that when software fails it is catastrophic, generally
> catastrophic. There is no little failure of software. There was an
> event last summer in Philadelphia where six patients were overdosed
> due to a failure of a computer system and inappropriate dosing of
> drugs. There were ten people killed in Panama last summer by
> over-radiation using a software system that had been in place for
> fifteen years.
>
> The problem is that when we design and develop a software system, it
> is designed for a certain usage but as time goes on we all get smarter
> and we learn new things, and then we try to use our old tools in
> different ways and that gets us into trouble because software is
> designed and developed to work a certain way, and when you try to use
> it in a different way it creates problems for us. Software is not
> physics based. There is no physical boundary placed on software. For
> example, if I dig some carbon out of the ground, it has certain
> resistivity so when I have a certain volume I have a certain
> resistance. That is based on physicals. There are physical limitations
> for hardware. There are minimum or no physical limitations for
> software so we need to deal with that issue.
>
> I think the number one thing that makes software different than
> hardware is that I used to design hardware systems and I had a
> prototype and I wanted to go build a prototype. I had to spend
> \$150,000, \$200,000, I would get to go to my boss and give him a
> voucher. We all know that any time you want to get your boss to sign
> to spend money, you have to prove that it is the right thing. So,
> traditionally in hardware engineering we would just have to show him
> that the design is going to work, everything is going to work, it is
> going to be fine. But in software we don\'t operate that way. We have
> these systems and people are hacking away and chipping away all the
> time. They don\'t traditionally go through this well-defined, step by
> step engineering process.
>
> The next two slides of my presentation are graphs. One is for software
> recalls from \'92 to \'98. Basically, it shows an ever-increasing list
> of software recalls. From about 3200 medical device recalls, 10
> percent were related to software. The most interesting fact of that is
> that of those 320 software recalls, 90 percent of those recalls were
> on software that was a version beyond the originally approved version
> by the FDA. So, if the FDA approved version 1.0 via PMA and at some
> point later, probably the next day, you need to upgrade your
> software\--most of the recalls occur on after market versions of
> software.
>
> I have had many discussions about what that means. Does that mean that
> we really do a good job, a regulatory job when we do initial
> submissions but we make changes as we go along and relax ourselves?
> That is a really good question. I think we all agree that software is
> important. I also believe that Congress believes software is
> important. The proof that I put forward is the fact that in our
> regulations there are very specific citing about software.
>
> Number one, under design controls there are three medical classes,
> Class I, II and III, III being the highest risk. Design controls are
> required for Class II and Class III devices but they are not required
> for Class I devices unless those devices contain software.
>
> So, the Congress of the United States decided that design controls
> will be required for all medical devices that contain software. So,
> that is number one.
>
> Number two is that under the design control provisions there is a
> section on design validation, device validation. It specifically calls
> out the requirement to validate the software in a medical device. It
> doesn\'t specifically call out the requirement to validate the medical
> processors, the hydraulics, the electroshock therapy, but it calls out
> that the software has to be validated. So, that is another place where
> software is specifically cited in the regulation.
>
> In the third instance, under the section for manufacturing and quality
> systems controls, there is a requirement that all manufacturing
> processes or quality system processes that are automated by computer
> are required to be validated. That software must be validated.
>
> So, that is three specific places where the device law culls out
> software as being special. One is that design controls apply all the
> time if you have software. Two, you have to validate your medical
> device software. Three, you have to validate your manufacturing or
> quality systems software.
>
> The medical device law is pretty simplistic. It basically requires
> that all medical devices be reasonably safe and effective. From that,
> I construe that that means that the software contained in those
> devices must be reasonably safe and effective.
>
> The problem is relatively safe and effective changes with each
> application and with each device. A relatively safe and effective
> digital thermometer is different than a relatively safe and effective
> implanted pacemaker. So, we have to have flexible rules and flexible
> logic here when we apply these regulations. One size does not fit all.
> But I do believe that the model, which I hope to present to you
> eventually, will address that issue.
>
> I wish I could invent what I call a safety and effectiveness meter.
> The FCC has a big room when they want to test electromagnetic
> interference. They will put a device in a room, they close it all up
> and they measure it. We don\'t have such a device. So, we need to go
> about the business of defining what we consider to be safe and
> effective software.
>
> This is what we cal the CDRH software message. It is not written in
> the regulations but people often ask us, \"what do you mean? What do
> you want us to do?\" We believe that to make safety and effective
> medical device software requires three components used in appropriate
> measures in the appropriate way.
>
> The first one is that appropriate software engineering must be applied
> to the problem. Number two is appropriate risk management must be
> applied to the problem. Number three is that appropriate quality
> system measures must be applied to the problem. This is very similar
> to the slide that you showed up there. Standards and guidances and
> regulations are written to be applied by properly trained
> professionals, whether they be regulatory affairs professionals,
> chemical engineers, electrical engineers, whatever. The idea is that
> you use the professional training and knowledge to apply these three
> concepts in the appropriate way to your device and your design and
> your risk management, and together to come up with a design that is
> relatively safe and effective, or reasonably safe and effective. Does
> that make sense to everybody?
>
> I think people spend way too much time getting wound around specific
> words in the regulation or the guidance. The guidance is an attempt to
> explain what I try to explain when I talk to folks. You need to apply
> your best engineering judgment. You need to have the documentation to
> show that you did so. That is where people get into trouble. They do a
> lot of the work but they are not very good at taking credit for it. I
> like to compare lawyers and engineers in this case. I think engineers
> spend about 95 or 96 percent of our time working really, really hard
> and only three or four percent of our time taking credit for it. That
> may be the exact opposite from lawyers.
>
> \[Laughter\]
>
> We have several guidance documents on our web site. The first one is a
> general principles of software validation, which was published in
> January, 2002. I take great note and pride that a lot of the material
> in the GAMP manual is the same as in the general principles of
> software validation. I think collectively the two groups together went
> back and forth over the last five years and came to this conclusion.
>
> I think both groups also believe that software engineering is software
> engineering is software engineering. Whether you are making a medical
> device, a manufacturing system, a PAT system the same general
> principles apply. We went back to existing standards, IEEE standards,
> NIRCC standards, Department of Defense standards and extracted from
> those what we thought applied to our problem. What we discovered is
> all of the basic stuff was there but some specific things were
> missing. In the IEEE standards they don\'t address risk. That is not
> an element in there. So we added that to our guidance documents. They
> don\'t address quality systems. They think quality systems are a
> separate entity, a separate thing, and that is oxymoronic in my mind.
> How can you have good software engineering without a quality system?
>
> We also have a guidance out on what is required to be submitted in a
> premarket submission for a 510(k) to a PMA. We also have a document on
> the use of off-the-shelf software in a regulated environment. Much to
> my surprise, this is like one of the only documents in the whole world
> that existed because now the people from DOD are coming to us, well,
> can we read your document? Sure. Everybody is looking at this as a
> method. Really, the off-the-shelf software use guide is really a risk
> management model. It tells you what to do if you are going to use the
> stuff for a low risk application or high risk application. It gives
> you sort of a risk management model.
>
> We have been at this for a long time. I guess the first document CDRH
> published was in 1991. One of the slides in this documentation is a
> calendar that a consultant in our working groups has put together of
> all the events that have occurred in CDRH software over the last 12 or
> 13 years.
>
> We recently were able to work st AAMI and get the publication of our
> American National Standard on Medical Device Software Life Cycles,
> AAMI SW 68. AAMI SW68 I believe is consistent with GAMP, consistent
> with the general principles software validation. We are not all
> departing anymore. I think we are all converging to the same place and
> I think that is a good thing.
>
> Now that that is a U.S. national standard there has been an
> international working group set up, joint working group number three,
> which is going to take SW 68 and make it an international standard
> because the idea is that we want to have one software standard
> worldwide. That standard addresses a lot of issues I talked about here
> today.
>
> In addition to that, there are some very specific areas where the
> questions come up all the time. One is software hazard management.
> What does that mean? How do I deal with risk management related to
> software? We formed a working group at AAMI, and they are currently
> writing a TIR, technical information report, to report and gather
> information related to software hazard management. It should be very
> informative and very interesting, and very helpful in trying to
> address some of the inconsistencies from inspectors, reviewers, and
> all that kind of stuff in industry.
>
> We have another TIR being written on the validation of high risk
> software, and a third TIR is being written, it is just getting off the
> ground, on the validation of production software and quality systems
> software, which I think is going to be it because I think there is a
> distinct difference because I think the risk model is different for
> product software than it is for medical device software for a couple
> of reasons. One is a medical device you are going to give to a patient
> or someone who has much less training than a trained person who is
> running a system in manufacturing under quality system control, and
> all that kind of stuff. So, the risk is different and that needs to be
> incorporated in that.
>
> So, we are working on a lot of documents. The next effort, that just
> got started on September 1, is a training program. I have been trying
> to push for this for quite a while. We need one training program to
> teach all the compliance officers in CDRH. We will also make this
> available to all the companies out there so we teach everyone the same
> thing all the time. There are no secrets here. Software safety is not
> a trade secret. That is very, very important.
>
> So we are trying to initiate a software training program. We are
> working on the first module right now, and the first module is going
> to be a two-hour module and the title of it is the top ten things
> every compliance officer should know about software. We are trying to
> jam all of that in one package but that is becoming more difficult
> every day.
>
> Once we get that done, then we can get into more details. Somebody
> talked about writing down the fundamentals and misunderstanding the
> wording. That is what our goal is. I think that is all I have. I will
> take any questions you have.
>
> DR. LAYLOFF: Thank you, John. Are there any questions for John?
>
> DR. HUSSAIN: John, actually at the very first meeting of the PAT it
> was mentioned that METLAB and other software very useful for
> chemometrics could not be validated. When I went to the CDRH workshop
> on software validation, I didn\'t see anything that stopped METLAB or
> any other software to be validated. Any thoughts on that?
>
> MR. MURRAY: There is no policy that prohibits the use of any
> off-the-shelf software, none. The question here would be you have to
> be able to clearly identify the risk related to using METLAB. If you
> use METLAB to calculate critical arterial pressure or diameter, then
> that immediately goes into the physician\'s surgical instrument and
> that is what happens. There is a huge risk there. It would not be
> acceptable to just say, well, I can\'t validate METLAB. You have to
> figure out some way to address that risk in an appropriate way, risk
> control, risk measure, whatever.
>
> On the other hand, if you are using METLAB to do statistical analysis
> of some kind without a significant risk impact, that would be
> different. So, it is all about the risk.
>
> DR. HUSSAIN: Exactly, and if you are developing a chemometric model,
> say, in R&D, and so forth, essentially the end-product is that that
> model then gets used in certain different ways. So, from that
> perspective, I mean there is nothing that hinders that process today
> but the perception out there, or at least what we heard at the first
> meeting was that that is a problem. I wonder whether anybody from the
> panel could share some light on that.
>
> MR. COOLEY: I have one comment on that, Ajaz. Within our company our
> regulatory groups, not necessarily with METLAB but with other common
> software, like Excel for example, they are requiring that if you use a
> spreadsheet to do any kind of calculation, then you have to validate
> the spreadsheet. But we are not going back and trying to validate the
> actual software itself.
>
> MR. MURRAY: That is a good question and that is addressed in the
> general principles of software validation. You are only required to
> validate your software for its intended use. You get to define the
> intended use but you need to write down what that intended use is. The
> whole idea is that you have to define what the intended use is and
> validate that the software actually does that. For example, a company
> that makes collagen, a bone replacement material, in their process
> when the material comes out of the oven, it used to get inspected by
> inspection under a microscope. The concept there was that they had to
> verify that the triple helix configuration was maintained, otherwise
> the product was no good.
>
> So, they wanted to computerize this, to put in a computer, a
> microscope and all that stuff, and they sent in this 400-page
> validation. They validated everything in this microscope, and I said,
> \"what\'s the intended use?\" They were, like, \"what do you mean?\"
> They had validated every function of this system but they failed to
> validate the intended use. Why did you buy this thing? What are you
> doing with it? I think that is very important. You need to write down
> what the intended use is.
>
> DR. LAYLOFF: Thank you very much, John. We will get a copy of your
> slides. Kimberly will make them and we will have them available here.
> It is time for a break now. We will reconvene in 15 minutes. So, it is
> 10:33\--10:48.
>
> \[Brief recess\]
>
> DR. LAYLOFF: Before we start our discussion, Eva came in late and did
> not introduce herself. Eva, will you please introduce yourself?
>
> DR. SEVICK-MURACA: I am Eva Sevick, from Texas A&M Department of
> Chemistry and Chemical Engineering.
>
> DR. LAYLOFF: All right. I guess we could move on with our discussion,
> computer system validation Part 11 issues pertinent to PAT,
> subcommittee discussion. We will start with Judy. What are your
> thoughts?
>
> \[Laughter\]
>
> DR. BOEHLERT: I have to think for a minute and see if I have any. I
> think I want to hear some of the discussion that is going to occur
> later but, clearly, I think there have been a number of important
> issues raised here. Will Part 11 be a deterrent to PAT, any more so
> than it already is a deterrent to any other part of manufacturing
> systems? It is there; it is a requirement. It is going to have an
> impact.
>
> I think there are several issues that were clearly identified this
> morning that we need to focus on, that is identification of critical
> control points, and making sure that we implement requirements where
> they are really important, to the extent we can, identify those points
> where clearly the requirements may not be necessary, and that is going
> to be a challenge because you can\'t always predict in advance what is
> going to be important and what is not. You need to have sufficient
> data, as was pointed out this morning, to conduct good manufacturing
> investigations when something goes wrong and you learn through those
> experiences.
>
> You don\'t always anticipate up front what data you are going to need.
> I have looked at a lot of investigations over my career and been
> amazed sometimes with where the fault really was. You didn\'t
> anticipate it but you learn from those experiences. So, I think the
> identification of critical control points, and focusing the impact of
> those requirements on those points is going to be important.
>
> DR. LAYLOFF: Thank you. Any comments? Questions?
>
> DR. LANGE: Yes, I have a question regarding the electronics
> presentation and Joe\'s comments about electronic signatures. As I
> understand it, electronic signatures have to be equivalent to current
> handwritten signature and the way we handle those is we have a log of
> each person\'s significant and initials and how they are supposed to
> appear, but Joe had mentioned a company-wide electronic signature,
> kind of an umbrella type of thing. In that case it wouldn\'t be
> equivalent because once a person leaves a company his signature, at
> least his handwritten signature disappears. Otherwise, if that were
> still around it could be used somehow. Someone else in the company
> could use it to falsify data, etc. So, I just wanted a little
> expansion on that.
>
> MR. FAMULARE: I was just referring to Debbie\'s middle slide about
> registering with the agency the fact that your company is even going
> to use electronic signatures. It is in the preamble to the regulation.
> Basically, that is just a way of having the company as a whole, or all
> its facilities, send in a notification to FDA that they will use
> electronic signatures as a full equivalent of their handwritten
> signatures. It is by no means any sort of a record equating every
> signature of every person in the whole company to whatever
> identifications you are using. I just looked at that and I said I
> think that was somewhat of a misinterpretation of that requirement and
> that that was an easy one to solve. It is just one statement for the
> company, \"we\'re using electronic records,\" and you send it actually
> to our Division of Field Investigations of ORA. That is where I was
> going.
>
> DR. LANGE: But your company would still have a record of individual
> electronic signatures the way we do with handwritten signatures.
> Right?
>
> MR. FAMULARE: That is right. You would have to have the proper user
> name, password or whatever other controls. Some examples are given in
> Part 11 to identify that individual in the company.
>
> DR. LAYLOFF: Dr. Kibbe, we haven\'t heard much from you today.
>
> DR. KIBBE: I already decided that we should send all the data to the
> FDA.
>
> \[Laughter\]
>
> I don\'t see where I could do much more damage!
>
> DR. LAYLOFF: Mel?
>
> DR. KOCH: I guess the comment that I would make is that the way I see
> it the problem isn\'t going to get any easier. The amount of data that
> is being generated with some of the new technologies is only going to
> increase what is coming at us. Even today\'s nominally acceptable
> chemometric approaches aren\'t going to be able to handle the massive
> amounts of data. There are a lot of demands in the development stage
> of getting more and more data from which to make decisions on the next
> experiment, etc. But the use of data mining and genetic algorithms is
> something that is going to be improving in order to keep up time-wise
> but that is going to present still additional problems.
>
> So, the topic is very appropriate but I think the sooner one gets down
> to finding methods to look at the data on which the decision was made
> or the critical points that we have been talking about, the quicker
> one can gear into that, I think the easier it is going to be to handle
> the increasing amount of data that is coming at us.
>
> DR. MORRIS: Actually, part of what I was going to say is a little bit
> of a combination of what Judy and Mel said. Spending more time in
> development early on is going to be a critical part of this, and I am
> not sure that there isn\'t a significant energy barrier to that that
> has to be addressed somehow, maybe not by formal committee but maybe
> internally by companies. But along with the identification of the
> points sort of implicit is that you have identified the right eyeball
> to monitor the point. We have heard Steve and others talk about new
> types of sensors that are available which are more appropriate for
> monitoring different aspects of the processes. So, in addition to
> generating more data during development, it means that we are going to
> have even different kinds of data to deal with. It may not just be
> spectroscopic data; it may be sonic and it may be thermal data. So, it
> is not just a question of the raw amount of data, but it is what are
> the appropriate data to collect as you change from technique to
> technique in addition to the magnitude of the data collection.
>
> DR. HAMMOND: I would like to comment on that. In fact, it is
> interesting to hear people debating about how much data we should
> collect or what type of data. If we look at control over a blender and
> a tablet press in one plant that we are putting together now, every
> day is going to generate 20 megabytes of raw data. If you look at the
> peripheral data of tracking and things around that, it is probably
> less than five percent of that value. So, if you are going to keep the
> raw data, the rest of it just becomes not worth talking about; you
> might as well do it anyway.
>
> DR. HUSSAIN: Just sort of a general statement to that effect that I
> tried to make in my presentation was that decisions often are not
> based on data; decisions are based on information. So, essentially the
> raw data is processed into some information and that is where the
> decision-making point is. So, in terms of what is retained and what
> needs to be archived, I think from that perspective the manipulations
> that lead to the information content of that are probably what should
> be critical.
>
> DR. DEAN: I would like to come back to a point that Bob Chisholm made
> early on in the day about execution systems when he was talking about
> the three-level model. I think that manufacturing executing systems
> will become [the]{.underline} critical software in terms of how we
> apply process analytical technologies. Some of the original work that
> was done using these systems to assess the mix of resources that go
> into a processing step before the process actually runs and based on
> historical and empirical knowledge and know before the process
> executes with we are going to get a good result or not. This becomes
> absolutely critical to making sure that we have got designed in and
> built in quality.
>
> But where that takes us then is to systems that are complex to a
> degree that is even an order of magnitude or more than what we
> currently are faced with and, therefore, the validation issues become
> even more critical and more complex as well. I think what we need to
> do is take a step back here. We are talking about incremental changes
> in the approach we are taking with validation, but I think we really
> need to look at something that is maybe a little bit different. I
> don\'t know what the answer is here but I am not sure that incremental
> approaches are going to be sufficient when we are looking at step
> changes in the way that we are approaching building quality in here.
>
> DR. HUSSAIN: So, one question that I think I am facing is in terms of
> the general draft guidance that we are planning, what level of detail
> would be needed in that? Because in many ways, especially with
> software validation, the desire right now is to rely on existing
> guidances, especially the CDRH. When I look at that from an
> engineering perspective, I found those extremely logical and they fit
> quite well in my way of thinking. So, instead of the draft guidance
> sort of defining of this, we simply refer to that and there are some
> Part 11 issues that I think we will have to address or at least
> clarify to sort of alleviate some of the fear that is out there.
>
> MR. COOLEY: I would encourage that approach because those are
> standards where there has been a lot of input from many people, many
> organizations. As far as the Part 11 issue, their interpretation is if
> you generate an electronic record you have to maintain that electronic
> record for whatever number of years. That gets into the situation like
> Steve brought up of 20 megabytes of data. If you are going to go to
> the expense of putting in a \$150,000 Raman instrument on a reactor,
> it is there, available. You may only need to see that at the very end
> of that reaction to determine that you have met your processing
> criteria and move it on. But if you have that investment and you can
> get data out of it, people are going to turn it on and use it during
> the whole reaction. So, from a business standpoint, if something
> abnormal occurs you would know about it. The interpretation from our
> regulatory people would be that as long as you are generating those
> electronic records, those need to be maintained even though those are
> not really being used in the final decision. I think maybe if we could
> build kind of an analogy between PAT and the laboratory, if you have
> an analyzer on-line monitoring a reaction, you know, prior to that you
> took one sample, you submitted it to the lab and you set processing
> criteria that is obviously a very small set of data. Just because you
> put an analyzer on-line, are you now going to be required to maintain
> all those megabytes of data because you are monitoring through the
> whole reaction? So, we are improving our process but in a way we may
> avoid implementing those improvements because we are concerned about
> all the other overhead that comes along with that.
>
> DR. MORRIS: Could I just ask a question? Could that fall under the
> category of if you are collecting through the whole process because
> you want to be able to real-time see it, would that not fall into the
> category of retaining it for a shorter period of time, much shorter
> period of time versus the information content that Ajaz is speaking
> about?
>
> MR. COOLEY: I think the issue becomes how the interpretation is going
> to be within our internal organizations. Obviously, because of concern
> over consistency and how regulations are interpreted during
> inspection, we take a more conservative approach than probably the
> agency even intends. But we do that to make sure that we don\'t get
> into an issue.
>
> DR. SHABUSHNIG: But I think Ajaz\' point is a good one, and that is if
> there is a clear statement, a clear position from the agency that the
> focus is on information content and not raw data, that, to me, is a
> very significant step forward. In particular, I think the concern that
> keeps being raised is the issue around filtering, and are you
> filtering out information and, therefore, we take a very cautious
> stand where you end up keeping all of the raw data. If there were some
> clear guidance that at least opened up that door that recognized that
> it is appropriate, focusing on information content, to discard some
> data or not maintain it over as long a period of time, then that opens
> up the door to I think some good science and some good rational
> justification to support those kinds of decisions. I think right now,
> I agree with you, it is not strictly the agency\'s position but I
> think we, as individual companies, are taking are taking a very
> conservative view to that and, therefore, holding much more data than
> really is appropriate, particularly with the focus on information
> content. Yet, there isn\'t a clear guidance, not necessarily a
> prescriptive rule that says here is what you have to keep; here is
> what you should throw away but, rather, an approach to making that
> decision that meets the agency\'s needs and also meets the industry\'s
> needs in order to move forward, again, with good scientific
> underpinnings and with the focus on information. I really think that
> that is a key distinction to distinguish data from information.
>
> DR. DEAN: Just following on from that, part of the issue here is that
> we can all be very reasonable and we can talk about scientific bases
> but when lawyers get involved it is a little bit different. We are
> talking about risk. So, if there is risk lawyers will be involved
> because there is never a hundred percent certainty on this stuff. So,
> someone has to make a decision at some point that there is a cut-off
> and above that the risk does not justify further intervention or
> further investigation, whatever. We all know here that as soon as you
> draw the line for a risk and think that it is not going to happen,
> well, it will eventually.
>
> DR. SHABUSHNIG: In the end, yes.
>
> DR. DEAN: So, I think there is a very slippery slope here and I am not
> sure what the answer is but we are going to have to address it.
>
> DR. KIBBE: In the absence of a direct directive that is very specific
> from the agency, I think your internal lawyers will say that we have
> to keep it because if the agency ever thinks that we were cheating we
> have to have it to show that we weren\'t. And, if we get rid of it, it
> leads them to suspect that we might be covering information up that we
> knew that we could get rid of. That whole quagmire has to be cleared
> up somehow, and not just because the people in this room would all be
> nice about it, but because there are lots of companies out there and
> lots of inspectors who aren\'t sitting in the room with us.
>
> DR. DEAN: Let\'s just blame it all on the agency. You can just imagine
> a situation where, in spite of built-in quality, there is a problem;
> something goes horribly wrong. You can just hear the lawyers saying,
> \"just a minute, you didn\'t actually test this product before it went
> out the door. You were relying on information of a process? What were
> you thinking about?\"
>
> DR. LAYLOFF: That is the case with sterility. You know, they test
> every lot just because of that even though the data assures the
> sterility, not the testing.
>
> DR. LACHMAN: Can you use some kind of quality certification of the
> data before discarding it to certify that the data met the critical
> control requirements for the process, and put that as part of the
> documentation? So, you do have a record but you don\'t have the raw
> data after that point.
>
> DR. MORRIS: I think, Leon, I understand Rick\'s point and I think it
> is something you talked about earlier, in one of your earlier
> meetings, the data that approaches the data that you used to establish
> the endpoint may not fall into any specific model even though,
> hopefully, it would eventually. Maybe you just keep the data that you
> use for your decision-making for a period of time. It would serve the
> same purpose.
>
> DR. LAYLOFF: Wouldn\'t you define it in SOP as to how you acquire
> data, how you compare the data, how you decide you reach the endpoint
> and what you store? And, you set up an SOP for each of them.
>
> MR. COOLEY: I would agree with that, Tom. I think the issue, again, as
> I said before, is the interpretation of what Part 11 says, and our
> interpretation is that if it is an electronic record you have to keep
> it. It doesn\'t matter whether it is the one you actually use for
> making that decision or not. You generated an electronic record and
> you must keep that electronic record. I didn\'t hear Joe comment on
> Ajaz\' interpretation but my interpretation of Part 11 is that you
> have to keep the raw data, not the process data. So, that is kind of a
> different interpretation I think.
>
> MR. FAMULARE: You know, there are two issues. What is required by the
> predicate rule, and I keep going back to that although Bob doesn\'t
> seem to think it offers a lot of help. Normally, when a paper record
> is generated, a paper batch record, you would record each critical
> step of the process and those critical steps that cause you to release
> the batch, and so forth. Now you are faced with continuous data coming
> out of a batch from a continuous on-line monitor and now we have to
> look at the predicate rule. I will go away from Part 11 and decide,
> well, what are the critical steps and what are the critical data that
> cause me to go forward with this batch, and the question would be is
> that every piece of data? I think that is what we have to answer in
> the GMP realm before we even get down to our thoughts and
> interpretations of Part 11.
>
> DR. KIBBE: Would that imply that it would be better to go back to
> paper data so that you could say, well, I have recorded the key things
> on this. This is my documentation and the electronic stuff is\--
>
> MR. FAMULARE: In terms of looking at the practicality of what you save
> electronically, what did we require you to save on paper in the first
> place in the predicate rule? Maybe we could use that as a starting
> point in terms of putting sense into the process of what we record
> electronically. Because you can create all these electronic data
> points because the equipment allows you to, do we need to save them
> all? Are they all really part of the batch record?
>
> DR. MORRIS: But I think the question is not so much whether it is
> part\--I mean, even if everybody agrees that if you use a sensor for
> drying your endpoint is two percent or something, which is the
> predicate case. The question is what do you do with the data that you
> collected approaching that? And, you are saying, well, don\'t turn on
> the sensor until you are there. That is the implication of what you
> are saying, in a sense.
>
> MR. FAMULARE: No, the issue is what do you need to record out of that
> data and preserve.
>
> DR. HUSSAIN: Let me sort of put an example on the table. Suppose you
> are doing blend uniformity as sort of a model process, and instead of
> taking samples at ten minutes, you monitor the blend for the entirety
> of the blend process so you have, say, a hundred thousand data points
> that you have collected. But in terms of a batch record you would have
> probably recorded the ten samples that you had collected for sampling
> and that is the analysis that you do. So, instead of those records, if
> you take the mean and average of some of the numbers that you collect
> on-line, would that be considered acceptable?
>
> DR. KIBBE: Let\'s look at an example with HPLC analysis. When we do an
> HPLC analysis we really are interested in the amount of the ingredient
> we are analyzing but doesn\'t the agency ask us to keep all the
> tracings? So, now we are looking at blend uniformity using IR and we
> are watching the blend to the end, and do we need to keep the entire
> tracing? Now that we have a different instrument and we are not doing
> gravinometric measurements anymore; we use HPLC; we are using blend
> uniformity instead of doing single analysis at the endpoint or 12
> minutes. Now is the agency going to apply the same rule it did to this
> system? If it keeps going and going, and I think the companies are all
> thinking of how many tracings and how much storage of electronic data
> that tracing represents when it is not just a single line but it is
> the fingerprint that you get from the IR or the Raman, and how much of
> that are we going to do? Of course, the agency has in the past
> required tracings. So, can we throw the tracings away?
>
> MR. FAMULARE: I think the issue is how specific does the agency need
> to get in guidance as we get to these more modern technologies in
> terms of what is practically needed to be recorded? I think we have to
> bring our discussion\--at this juncture, if we implement this
> technology and we get all this data, how much do we practically need
> to record to meet the agency\'s needs for record-keeping in the GMPs?
> A mention was made of what lawyers and companies may require, and so
> forth. What practically needs to be kept? If it is not feasible to
> save all of the data, then we have to come up with an approach that is
> based upon risk. You know, there has to be some practical answer
> because although storage and archiving capacity has increased with the
> advancement of technology, what I am hearing is that obviously there
> are still limitations of what you can keep and then move on to the
> next iteration of hardware or software that will support that as time
> goes on.
>
> DR. LAYLOFF: Let\'s go down to the end of the table. I think two or
> three people wanted to make comments.
>
> DR. CHISHOLM: There are a lot of things I was going to say. I think
> there is a danger, it seems, in confusing a number of different
> problems again. First of all, if you have an inter-stage process, if
> you have an endpoint determination, surely all you have to keep is
> that. I think once you get to statistical distributions, that is to
> say that you are going to do it for tablet parameters, or whatever,
> then really you have to give us some advice because to prove that is a
> statistical distribution we have to keep the data. But to release a
> batch, a qualified person only has to see the data because, let\'s
> face it, we all believe we are honest at the end of the day. So, that
> is a decision area I think that you have to look at.
>
> In terms of the question I posed earlier on, original data, when you
> actually create models, you don\'t have a lot of choice. You have to
> keep that because you are going to have to update and refresh these
> models and if you don\'t have a data bank you can\'t do it. The
> question there is do you have to keep it in such a way that you can
> recreate the algorithm so that an inspector can see that being done? I
> think that is the question that needs to be answered. But I don\'t
> think we should get too hung up on the vast quantities of data. You
> can keep a lot of data in the assessments. That is not a problem
> anymore. But if you are starting to get beyond things like five years,
> it is beginning to get a bit impossible. And, it is not the archiving
> of the data; that is simplistic. It is that with all the technology
> changes how do you get it back? That is the problem .
>
> DR. RUDD: I think Bob said it very well, but maybe just to embellish
> that, I think we have to go back and remember why we are interested in
> PAT-based measurements in the first place. I think you can almost
> reduce it down to two things. The first is, if you like, a development
> aid mechanism for process understanding, process optimization,
> development of the kind of models that are being talked about, and
> those models will need to be refined. So, that is there on the one
> level and you may use none of that on a routine basis for product
> sanctioning.
>
> Conversely, the second principal reason for wanting to make PAT
> measurements is to, let\'s say, eliminate the end-product testing and,
> therefore, you have to keep whatever it is that allows you to sanction
> product quality.
>
> I think the exercise we probably still haven\'t done in this group yet
> is the one that we tried to do with the attempts to release a
> parametric release guideline in Europe, and that is to take the
> classical end-product specification for whatever product type you
> might be talking about, take a tablet. The quality parameters that
> define tablet quality have been built up over the years. They are
> established\--assay, content uniformity, dissolution etc., etc. They
> don\'t go away. Just because we stop making measurements differently,
> they don\'t go away. What we have to do is work out what it is, what
> test or what combination of measurements we might make in the process
> that is predictive of those end-product quality attributes. So, if we
> are able to make a content uniformity prediction based on a real-time
> powder blending measurement, then that is the bit that we need to
> keep. Twenty megabytes of data could reduce down to one number, a
> blending time or a point at which an RSD replicate specter reaches a
> predetermined minimum. That is the bit that is predictive of finished
> product quality. So, let\'s just keep that in mind. Let\'s remember
> why we are interested in PAT. I think it gets down to those two
> things, and the bit that is missing is we haven\'t developed the
> relationship between the end-product quality attributes and the PAT
> measurements we might make.
>
> MR. HAMMOND: Just to enlarge on that, one of the reasons that we want
> to collect the data and actually store all of the raw data on every
> batch is that we can go back and do historical trending. I mean, that
> really is information that for our use only but we do need to keep
> that otherwise we don\'t get the best benefit of PAT. Obviously, if we
> are going to keep that, then we have to abide by the rules of keeping
> it but it is a huge amount of data, but it is worth keeping. Bob is
> absolutely right, with modern-day systems it is not that difficult.
>
> DR. LAYLOFF: I wonder if you keep too many records if you confound
> inspections. You make a smoke screen. We haven\'t heard from Eva. Do
> you want to make a comment?
>
> DR. SEVICK-MURACA: No, no.
>
> DR. MORRIS: This is a question actually, what is the goal in terms of
> the guidance, I mean, what level of detail needs to be included for
> the guidance to address this? I guess that is an open question but I
> think that is really what we are trying to get at. Steve, you are
> saying we have 20 megabytes a day and it would depend on the system
> you are looking at. On the other hand, you are saying it is not that
> hard to do that. On the other hand, you are saying\--Bob is saying you
> can\'t retrieve it in five years, so what good is it? Then, some
> people are worried about whether or not it is going to be audited. I
> think we have to say what ought to be in the guidance in terms of
> direction so that the internal lawyers don\'t have hemorrhages.
>
> DR. HAMMOND: I think a number of those general points are going to be
> discussed as general issues probably outside of this committee. There
> is one thing I would like to bring up, and I would certainly like
> Eva\'s opinion on this because it is an issue for us, as we are
> developing the systems we are actually start to install an on-line
> sensor in a commercial production area, and you almost have to be an
> oracle, predicting everything that is possibly going to want to be
> developed and known about the software before you actually ever get it
> in there. When you get it in and you suddenly decide, well, the
> communication routines with the plant DCS system isn\'t quite right,
> or we could actually get a better control if we had this extra bit of
> data manipulation here, or you find bugs in the software that have to
> be corrected, we find that we spend something like 80 percent of our
> time updating documentation to be allowed to change software. I mean,
> the FDA say this is not their fault. The agency is very quick to point
> this out. It is not their fault. The trouble is it is the perception
> of their internal regulatory groups, but if they don\'t get specific
> instruction from the FDA and they are allowed to make up their own
> mind about these things, then installing a PAT effort can be like
> running in sticky toffee purely because of the perceptions of internal
> regulatory groups on what you have to do to change something, bearing
> in mind that you are not actually generating any information for
> release of a commercial batch but purely just developing the system.
> The one thing that this guidance must do is to slacken the reins on
> being able to change things easily while you are developing the
> system, otherwise applying PAT becomes like running in sticky toffee.
>
> DR. SEVICK-MURACA: Now I have a comment. I am involved in two areas of
> technology development. One is in the blend content uniformity and
> also in medical device where I impact patient care. I think the
> speaker from the FDA gave an interesting comparison, but whenever I am
> developing new technologies that directly interface to a patient, as
> long as any of the information that I develop or any of the data that
> is generated in the development of that technology for that use, as
> long as that information is not used to make a clinical decision or a
> diagnosis, then it is a feasibility study and it is just data that is
> generated. It is separate from the treatment of the patient.
>
> I guess I see the same situation with PAT. If you are generating data
> in a development phase where you are trying to get that technology
> on-line, learn some information about that process, is that
> information consistent, congruent with other information that you have
> about the process, that information shouldn\'t be used in deciding the
> outcome of that batch. So, it is off-line. It is not there. I wish I
> could convince the FDA that when we are developing technologies, we
> don\'t know the robustness of that information and that information
> can\'t necessarily be held against us. Am I getting my point across?
>
> It is done in the medical device community where the risk to the
> patient is even greater\--well, maybe not even greater but it is
> significant. You can\'t say that the risk of putting a PAT on blend
> content uniformity has a greater risk than my medical device that
> directly makes contact with the patient. So, why can\'t we have that
> same type of regulatory structure for the development of new
> technologies?
>
> DR. LAYLOFF: Now we will have Joe tell you why.
>
> MR. FAMULARE: Actually, we are very open to the development of new
> technologies and we really would not want to in any way hinder or bar
> research data at all, or put any type of regulatory restriction on it.
> In fact, I think Ajaz introduced that term in his presentation this
> morning of using it in a research way in terms of how to craft the
> safe harbor.
>
> Certainly, if it is in the development phase, we certainly wouldn\'t
> want to have any hindrance on the ability to change it, develop it,
> etc. So, I think we are already there where your concern is. I think
> the real concern is that once you get to the operational level and are
> actually using this to make batch release decisions, how do you deal
> with the data and the electronic record-keeping requirements, and so
> forth? But in terms of developmental, we are certainly open to the way
> you have expressed those ideas.
>
> DR. SEVICK-MURACA: I guess that in the process of taking your
> technology, once you have validated your technology so that now it can
> be used as criteria for releasing a batch, and in that process of
> validating that technology you identify the data that you keep, the
> endpoint, the decisions, I guess I just don\'t see the difficulty
> here. Am I misinterpreting this?
>
> DR. HAMMOND: I don\'t see that there is any problem at all in keeping
> the data. That is just my perception I suppose, as far as I can afford
> to do this. I am in a little bit different position. But coming back
> to Joe\'s point again, you can say, yes, we are in agreement and the
> safe harbor concept covers this, but you haven\'t really made that
> plain enough. There are validation groups in Pfizer plants where we
> are trying to go into GMP areas and distil this technology, who are
> almost tying their legs together and one hand behind their back
> because of your perception, or at least your inspectors, think of it.
> So, it is still a bit like muddy water out there.
>
> MR. FAMULARE: And this is something that you want addressed in the
> guidance?
>
> DR. HAMMOND: Absolutely.
>
> MR. FAMULARE: In terms of being able to development existing processes
> and not take this research data, or whatever we end up calling it, and
> use it as a tool to penalize the existing process that already meets
> today\'s standards.
>
> DR. SHABUSHNIG: To me, the emphasis there should be on will the
> intervention that you are making, will installing this sensor, etc.,
> have a negative impact on the product? There should be that sort of
> minimal level of documentation, but as far as how you use the data,
> recognizing that there is still a development activity that is going
> to be ongoing at that point as opposed to expecting the full level of
> validation and full level of documentation that would go with that. I
> think what we need to say is that there is that step that gets you at
> least into that commercial process, but then there is still a data
> gathering phase that can go on ion that mode. But I agree, I think
> that having that stated more clearly in the guidance will help us both
> with our internal organizations as well as the general advancement of
> the implementation of PATs.
>
> DR. LAYLOFF: Down at the end?
>
> DR. RUDD: Thanks. Yes, just to endorse the comments that Steve and
> John have been making, so you know it is not just Pfizer but GSK as
> well, I think there is an extra dimension though. It isn\'t just about
> applying PAT technology to existing processes. I think it is about
> getting the message across and maybe it is an internal validation
> group problem that we have.
>
> Maybe I shouldn\'t say this but we are running into a problem at the
> moment with implementation of some new technology where we are getting
> close to the point of saying, well, let\'s just not bother doing this
> because our internal validation group is expecting us to do, you know,
> a perfect job on it. I think this message needs to come out. It is the
> product critical quality attributes, or the measurement and the
> judgments that are related to those where, clearly, nobody want to
> back off from a full validation program. That is entirely right, but
> to expect to cover absolutely everything to a gold standard could
> preclude the implementation of the technology and we mustn\'t get into
> that situation.
>
> DR. LAYLOFF: Doug next.
>
> DR. DEAN: Just a very quick one to Joe\'s comment about research data.
> One of the comments Ajaz made was on continuous improvement. So, there
> is an element of research on an ongoing basis.
>
> DR. LAYLOFF: Leon?
>
> DR. LACHMAN: Yes, If I recall, during the first subcommittee meeting
> we discussed that implementing this approach is going to involve a
> more intensive or longer development phase or optimization phase, and
> I think that has to be considered here. As part of that, the
> optimization will be continued during the run of the process on a
> routine basis, but that should be a separate component from the
> release component.
>
> DR. LAYLOFF: Ajaz?
>
> DR. HUSSAIN: I just want to clarify. I think all the points made were
> excellent points. Just to go back to the point Steve made and I think
> David also made, what they are asking is that as a PAT process is
> being investigated or the suitability is being determined on an
> existing line, there are two issues there. One is that clearly from a
> regulatory risk perspective we would like some assurance that that
> does not have an adverse impact on the quality of the existing line.
> That is the bottom line. Everybody agrees with that.
>
> The question I think Steve has posed is what sort of validation
> requirements should be placed on a research probe on an existing line,
> and what should the FDA position be? From my position, I think we
> summarized this at the end of the second meeting that when a company
> is doing suitability evaluation or research, that is research data
> which sort of falls under the safe harbor concept and all the
> decisions for that product will be based on existing approved
> regulatory methods.
>
> The challenge is that in a sense the internal regulatory affairs and
> validation groups require full validation on every research probe, and
> that is not what it should be. I think the research probe is to first
> investigate whether it is suitable or not before you plan to validate
> it. But that is an internal argument where I think you are seeking FDA
> help to address that.
>
> I think we would be very clear in the guidance that we encourage
> continuous improvement, continuous optimization and, as part of that,
> you would need to do sort of when it does not adversely impact an
> existing product line; be flexible enough to do this; and we will not
> penalize you for that. The level of validation is sort of a graded
> level as the suitability is confirmed and then you proceed, not up
> front.
>
> DR. LAYLOFF: We will take you two and then we will have our open
> hearing.
>
> DR. HAMMOND: Just outcome make absolutely plain, I think the hardware
> of the sensor itself is not really the issue because before we get
> into a manufacturing facility we have thoroughly established exactly
> what that is going to do. The issue is the software more than anything
> else.
>
> I will give you an example. We had to have a new set of software
> written to be Part 11 compliant. So, we did that. We installed it. It
> took almost a week to validate the installation of the software. We
> ran a couple of batches and realized there were a number of issues
> with the communication with the plant systems, also the data it was
> giving us we knew we could improve. So, we decided to go back to the
> software vendor and ask them to do what we were asking. It is a new
> version of software. So, we get the new CD and the first thing we have
> to do is spend a week revalidating the installation. That is the type
> of issue that really needs addressing in these guidelines.
>
> DR. MILLER: Just a comment that the flavor and theme of what we are
> speaking of need to be reflected in the new GMP guidance that will
> come forward post or pre these regulations. It would also I think be
> valuable to push ahead these validation concepts from that GMP
> perspective because essentially that is what these groups have as
> their bible, if you will. It is GMP first and it is the GMP pathway.
> So, the flavor and the pathway of that thinking could be embellished
> in that guidance also.
>
> DR. LAYLOFF: I want to open the session for the open hearing. We have
> one individual who has requested time. Dr. Stanley A. Marash has
> requested ten minutes of our time so he can make his presentation now.
>
> **Open Public Hearing**
>
> DR. MARASH: Good morning, and thank you for the opportunity to share
> with you some thoughts and some practical applications of the
> inter-relationship between PAT and six sigma. I don\'t know how many
> of you are involved in six sigma programs in your organization, but we
> have found that there are kinds of things that I would like to share
> with you, and what I have done is borrow some of the transparencies
> that have been used in some previous meetings and tried to look at the
> relationship between those items.
>
> I guess I should tell you that my organization is a non-profit
> organization that has been involved for many years in these
> relationship kind of things. I personally was directly involved in
> helping to develop the medical device GMP and to provide training
> around the country for that. I also was involved as one of the
> co-authors of the early version of the Food and Drug law course that
> is being taught within the FDA.
>
> In the aspects here where there is a need for improving the
> efficiencies of pharmaceutical manufacturing and regulatory processes,
> and there exists the capability of realizing this, and for the last
> 15, 20 minutes or half an hour you have been talking about what is the
> realization and how do we deal with this. Six sigma and PAT have a
> number of things in common. Both of them are process oriented. They
> are approaches to achieving efficiencies, reduce cycle time and
> improve quality.
>
> PAT is trying to move the approach from testing to document to
> continuous quality assurance. Now, continuous quality assurance or
> continuous quality improvement are major components of what many
> people today are looking at in their organizations. It also talks
> here, and I have heard Ajaz a couple of times make the comment to
> ensure that the quality was built in or was there by design. This is
> an important aspect in terms of all activities.
>
> If you look at the six sigma process, it embraces both continuous
> improvement and breakthrough performance. The process includes models
> for manufacturing, administrative services and for design. There are
> two major models in here. One is referred to as DMAIC, defined measure
> analyzing improvement control. The other is referred to as design for
> six sigma, DFSS, which is the defined measure analyzed and verified.
> It really should say verify and validate. But most of the places where
> this comes from, this is where the focus is.
>
> The key here is people will talk about analytical tools and I go into
> many organizations and they tell me, oh, yes, we do that all the time;
> we do those analyses; we use design of experiments; we use regression.
> We know all of that. We know all the manufacturing. When you get out
> and look at what is happening, it is not happening. There are places
> where it is being used. There are people who are using it, but when
> you look in the larger sense of what is really going on, it is not
> really happening.
>
> What has happened in the last five years is this activity of six
> sigma. More and more companies are actively involved in looking at six
> sigma and trying to utilize it. They are training people of all kinds
> to utilize tools. Now, people come and say, well, we know those tools.
> We have used them all along. What is different about six sigma is its
> focus on a process that takes people through the use of a series of
> tools to be most effective in finding out what needs to be done and
> how to do it.
>
> When I look at what is going on in the objectives for PAT, we are
> talking about a regulatory framework; we are talking about
> manufacturing technologies. But we get hung up about eliminating
> perceived or real regulatory hurdles. A lot of the discussion here is
> around how are we going to get over that hurdle? Why am I using paper
> when I could have used electronics and I was using electronics before?
> These kinds of things and these kinds of questions really raise the
> issue of can this be successful. Can PAT win industry\'s confidence or
> are the perceived or real regulatory hurdles too difficult to
> overcome? That is a question that needs to be answered.
>
> On the other hand, does six sigma have the advantage of no or less
> regulatory constraints, at least built into them, and the perception
> of the industry is that it is an industry program, not an agency
> program, will then make a difference.
>
> The next question is do I really need to decide between the two? One
> of the methodologies that we have been looking at is something that we
> call fusion management. What fusion management is about is taking many
> of the programs that are going on in companies and putting them
> together so if you see PAT here and you see six sigma, but you also
> see management systems, you see performance excellence which would be
> things like the Baldrige Award, you are looking at TQM or LEAN, many
> companies have used these and are using them today, what we are
> looking at is a structure to do all of that.
>
> Visualize the following, visualize a four-phase set of activities. The
> first phase is a step that talks about the management system. What
> kind of management system do we talk about here? We talk about the
> GMP. The GMP is a management system that has associated with it a
> series of other activities, other requirements that are specified, but
> it is still a management system. So the base of this thing is a
> management system to start with.
>
> The second phase is process control. We must get our processes under
> control. We talk about validation; we talk about other things; but
> unless you have the basic processes under control things are not
> really going to happen. There is a lot of discussion about continuous
> improvement. Well, improvement is nice and part of that could go back
> to doing the process control activities or process capability
> activities or the process validation activities. Eventually you are
> going to get to continuous improvement and ultimately you are going to
> get to breakthrough methodologies.
>
> DR. LAYLOFF: One minute.
>
> DR. MARASH: Okay. I would like you to visit our web site, which is
> statamarix.com/fda. In that web site you will find a copy of the
> slides. You will find a number of discussions of published papers
> around fusion management, around six sigma, around the tools. We put
> those together very specifically. We have taken them out of our main
> site, which you can go to also, but to make it simple this is where
> the material is and we invite you to visit that site. Thank you.
>
> DR. LAYLOFF: Thank you. Dr. Gary Ritchie has asked for an opportunity
> to present to the group.
>
> DR. RITCHIE: Actually, I didn\'t formally but I got so passionate
> about the concept that Joe and Dave and others were bantering around
> about a specific concept or way to approach the language in the
> guideline. What dawned on me was a specific example that I was
> involved with. In going from measuring dissolution at a single
> endpoint where you are looking for a Q of 75 at 30 minutes, in
> validating that we changed from an endpoint measurement to continuous
> monitoring. I just saw very much similar issues that we dealt with
> when you talk about putting a probe in a dissolution bath and now
> documenting taking continuous measurements, and at what point do we
> say we have a process measurement, in the same respects as we are
> talking about putting in a process batch monitor or something?
>
> What dawned on me was method equivalence was a point to say that we
> had the same method, and what were those things that we used to do
> that? Single-point spectra at the points where we said Q was supposed
> to be, up to an after for instance. So, documenting the measurements
> in terms of the computer data coming from the UV became very easy
> because we took spectra, then we took computer data that was
> associated with that spectra for the continuous measurement. Then we
> put it side by side with what we were typically doing with the
> endpoint measurement. Now we have a package that says equivalence.
>
> So, that was just a model. I think the chromatography idea was given
> as a model, but I think one that might be utilized that I think the
> FDA has some experience is with is to go back and look at the
> dissolution model going from a single endpoint measurement to
> continuous measurement. That might be a good place to start.
>
> DR. LAYLOFF: Gary, did you identify yourself?
>
> DR. RITCHIE: Gary Ritchie, Purdue, PhRMA.
>
> DR. LAYLOFF: Is there anyone else in the who would like to have two
> minutes during the open hearing? If not, we will break for lunch. We
> are breaking early. We will get back at one o\'clock. So, we will see
> you here at one o\'clock.
>
> \[Whereupon, at 11:46 a.m., the proceedings were recessed, to be
> resumed at 1:00 p.m.\]
>
> A F T E R N O O N P R O C E E D I N G S
>
> DR. LAYLOFF: I want to make a few remarks. I think our FDA colleagues
> and friends have heard the message about getting something in the
> guidance concerning research. So, we will put that to rest now. I
> think we have hammered that enough and they believe it, as they have
> for the past three times I think, but I think we are done with that so
> we are not going to bring that up again. We are going to have the
> presentations here so we can get started.
>
> DR. HUSSAIN: If I may, to manage this sort of situation properly, what
> we have tried to do is have the presentations in the same format as we
> had this morning. That means presentations for both rapid micro and
> the BMS and Pfizer mock submissions will occur as this morning. It
> will sort of be shared between both rooms, and then we will sort of
> shut the audio-vision system and have the breakout discussion in two
> separate rooms. Sorry about the confusion. I think we didn\'t
> anticipate so many people showing up for this.
>
> DR. LAYLOFF: I thought you were giving away free drug approvals or
> something!
>
> \[Laughter\]
>
> If we can get started this afternoon then, we will start with the PAT
> mock submissions, Ron Miller.
>
> **PAT Mock Submissions**
>
> DR. MILLER: Just a few brief words. Bristol-Myers Squibb put together
> an eclectic team of individuals that we felt would foot the bill to
> handle this mock presentation, chiefly Dr. San Kiang will handle most
> of the technology elements in the presentation. Sathyanarayana
> Upadrashta will report from our regulatory viewpoint our concerns and
> issues and express them. Then, Glenn Thomson will handle our Part 11
> compliance issues as he is our quality Part 11 compliance director in
> this area for the corporation. I will be on the supporting cast,
> promoting questions and trying to raise some provocative issues as we
> go along. Again, we will go through this roughly in about 30 minutes
> and allow 15 minutes for questions in this part of the phase for
> additional questions and answers to move this forward. Thank you very
> much. With that note, San?
>
> DR. KIANG: My name is San Kiang. I am the director of process
> validating in Bristol-Myers Squibb. I like the comment that John
> Murray made this morning about engineers and lawyers. I am an
> engineer.
>
> \[Laughter\]
>
> I want to thank the agency and Ajaz in particular on behalf of BMS. To
> tell you a little bit about how, on the drug substance side, we are
> also able to use PAT during our process development, therefore, the
> title, PAT for drug substance. In this case we want to demonstrate how
> we use particle size monitoring during the development and scale-up of
> a process.
>
> In drug substance development there are quite a number of PAT
> applications and this is just a table showing, at BMS, some of the
> common instruments, like NIR, Raman, FTRI. I will explain a little bit
> about FBRM and how, in different processing, they are used.
>
> The outline of this case study\--I am going to tell you a little bit
> about why we are doing this and the issues involved, and how we use
> PAT in monitoring\--PSD stands for particle size distribution during
> crystallization\--downstream processing multi crystals, which is
> filtration and drying, and how we use it in subsequent scale up.
>
> Product A has issues during formulation. It has dusting issues. It is
> a wet granulation operation and in the beginning of the development we
> found out that the performance of the drug product is very much
> dependent on the type of formulation equipment, especially the
> granulator we use. Also, the binder, in this case water\--the amount
> of water needed during the operation also varied in quite a large
> range, and we are going to find out why at the end of this talk.
>
> On the drug substance side there is also a curious effect. I am sure
> other companies have the same thing, when a drug substance was
> manufactured in different types of equipment, it also gives different
> performance in the formulation. As usual in our industry, at this
> juncture of the development there is no performance-indicating
> parameter of the drug substance that we can measure and, therefore,
> predict its performance in the formulation.
>
> Again as usual, at the boundary between process and formulation the
> question is always is this unpredictable performance due to the drug
> substance itself? As you know, during the development stage and before
> routine manufacturing\--actually, before filing\--there are changes in
> chemistry which affect impurity, and there are solvent changes which,
> again, affect the attributes of the crystals and even the
> crystallization protocol itself changes. Then, there is also
> equipment-dependency of the drug substance.
>
> The question for formulation obviously is, is the formulation process
> itself robust. The question engineers usually ask is why can\'t we
> develop a robust formulation process that can handle a wide variety of
> solid state properties of the drug substance? Then there are some of
> the process issues, for example, understanding of the granulation;
> understanding of the binder effect on the formulation.
>
> There are two reasons really to be able to follow the crystallization
> and, therefore, the crystals. One is it has a critical impact on how
> the drug substance is isolated. Obviously, the particle size
> distribution will have a large impact on the filtration
> characteristics, as an example. A poorly filtered cake also led to a
> poorly washed cake and, therefore, affected its quality. So, those are
> issues on the synthesis side and may or may not be related to the
> formulation issues.
>
> This is the investigation of the formulation problem. In the beginning
> what we found out is that some of the drug substance, in this case
> capsules, performed poorly in the dissolution test. This is the
> initial investigation. What we did is take some of the granules and
> took Raman pictures of the cross-section of the granules. You can see
> in the top picture that there is really a mixing or distribution
> problem with the API. The excipient is the green and the drug
> substance is the blue. You can see that the particle size distribution
> very much affects the dispersion of the excipients in the drug in a
> uniform way during granulation.
>
> Before I show you how we monitor this process, the crystallization
> procedure itself is very simple and straightforward in operation. You
> use five percent seed. The drug substance is a sulfate salt so the
> crystallization procedure is started by the addition of sulfuric acid
> at a controlled rate and the material crystallizes and precipitates
> out. So, it is a very simple procedure.
>
> This is a schematic of how this procedure is carried out. The reaction
> mixture comes in on the left and then goes to the crystallizer and is
> crystallized as I described before by the addition of sulfuric acid.
> It is filtered and then dried. You can see that PAT is used in
> monitoring the crystallization procedure in the crystallizer, and it
> is also used, instead of on-line, at-line to monitor the effect of
> filtration and drying operations on the crystals.
>
> Just a brief description of the particle size measurement method. The
> vendor is Lasentec. The technique is focused beam reflectance
> measurement. You can see that there is a laser beam that is focused at
> crystal slurry so it is in the crystallizer as the particles move
> across the beam. Down here is to show that as the particles move
> through the beam the edge to edge dimension is measured and recorded.
>
> This is a record of doing this procedure at a 15 L scale in the
> laboratory. You can see the progress. The X axis is the dimension in
> microns. The Y axis is the number of the crystals per second. Stage 1,
> 2, 3, 4 and 5 means different rates of addition of sulfuric acid. That
> is really the control parameter in this case. It is important to point
> out that as we progress in time you can see that the particles grow in
> numbers in all dimensions. You can follow the particle size over time
> using this technique.
>
> This black background is supposed to show the same stage, but you can
> see we follow the same stages of crystallization over time. This is
> the seed again. The stage moves from this curve up to this curve in
> the black. But now we are doing the same operation at large pilot
> scale, at about 100-fold the size.
>
> In the crystallizer, as we mentioned, we use the in-line monitor. You
> can see this red arrow pointing to this shiny tip. That is where the
> tip of the FBRM is. Obviously, it is put in an area that is
> representative, that has sufficient mixing. This is one of the
> crystallizers in the pilot plant.
>
> Now we took this one step further. We ran it in one of our
> manufacturing sites. Now we are at the 4000 L scale. Again, we use the
> same technique to follow the progress of the crystallization over time
> and over the addition rate of the sulfuric acid. Again, the same
> curves are traced to show us how we are doing on the scale.
>
> This is the pay-off slide. This is the slide that superposes the final
> distribution of the crystals at the laboratory, at our pilot plant and
> manufacturing scale. You can see how closely the particles track each
> other.
>
> As is often the case in our business, we spend a lot of time, at least
> we do at BMS, in designing the crystallization procedure, but
> oftentimes the crystals themselves are very much affected by
> downstream processing. In this case we took a look at how agitator
> drying\--as most of you know, on a small scale the dryers are static.
> We put it on a tray, put in the oven and take it out. Really, the
> crystals do not see much stress. But as you scale up the dryer,
> because of practical reasons, has to be agitated. It usually has an
> effect on your particle size, obviously. In this case, using at-line
> FBRM\--the red line shows the original\--SQM stands for square mean
> radius; a mathematical expression of the measurement. Using different
> types of dryers, in this case these are common manufacturing scale
> dryers, filter dryers, tumble dryers and we also subjected a batch to
> milling. You can see that there is a shift to the left. The particles
> are getting smaller under stress.
>
> We also monitored the filtration operation, which obviously has an
> effect, again, on the crystallizer. Everything you do to the crystals
> in the crystallizer has an effect of changing them because a
> crystallizer is an API operation to fix the properties. In this case,
> using a centrifuge filter and looking at the blue line and the green
> line, they really trace the crystallizer distribution very well. So,
> we concluded from this that the centrifuge operation really did not
> have much effect on the particle size distribution.
>
> Again, a more specific monitoring of a filter dryer at-line, this
> really shows how we control the operation of the dryer. If we
> continuously agitate it or we use intermittent agitation, which is a
> timed program operation, you can see if we do it without stress versus
> with stress, which is continuous agitation, again the continuous
> agitation leads to smaller particle size.
>
> With another type of dryer we basically see the same effect, a
> continuous operation versus a more controlled, intermittent operation
> of the dryer leads to a better preservation of the particle size.
>
> This is microscopic evidence of what PAT sees in a more microscopic
> way with high shear drying. This is recorded with our FBRM technique
> and you can see that the particle size does get mowed down.
>
> With a different type of shear you can see there are ways you can
> control the process using PAT to try to control the morphology of your
> crystals.
>
> This leads basically to some theoretical thinking. For this product,
> when you apply shear to individual crystals it seems that they
> consistently shear in one plane of the crystals. With this molecular
> modeling, and based on the distribution of the chemical groups, we
> find out that the shear-exposed faces are the 1.0 phase which tends to
> be much more hydrophilic than the rest of the crystals.
>
> So, this led to the explanation that the varying amount of binder you
> need because in different batches we are generating a different amount
> of fines by shear and create more hydrophobic surfaces, and explains
> the non-uniformity because in the presence of water these faces tend
> to come together very rapidly and actually seize up the granulator.
> So, this explains some of the phenomena we see using PAT and also at
> investigation.
>
> This is a summary page of the critical information we need. From this
> monitoring you can see how the mean particle size pans out with these
> operations.
>
> In summary, I hope this little story demonstrates that using PAT, in
> this case the FBRM, to monitor crystallization\--we can use PAT using
> process development and crystallization. As you can see, we have
> scaled this process up in three different sizes.
>
> This kind of data gives us a lot of confidence in how we scaled up. We
> also demonstrated that the crystals are affected by downstream
> processing operations. In this case we monitored the filtration and
> the drying in different types of dryers, and showed that using PAT
> data we can monitor and, therefore, control our process operations.
>
> Obviously, the PAT being able to be monitored, to use in a
> crystallizer, allows us greater flexibility in controlling particle
> size, in this case the addition rate of sulfuric acid.
>
> Finally, using PAT we are able to better control API attributes which
> leads to consistent performance of the formulation process as well as
> the drug product, which in this case is a capsule.
>
> This ends this part of my talk. I think my cohorts in regulatory and
> quality will come up and tell the engineers how we can do better.
>
> \[Laughter\]
>
> DR. UPADRASHTA: Good afternoon. I am director for the global
> regulatory sciences, industry, manufacturing and control, the
> submission group.
>
> There is really no substitute for science and engineering. San and his
> group, they always make my life easier because when you have a solid
> science for us life is really easy in terms of determining what
> package should be sent to the agency to get the approval.
>
> With that, we have seen this slide from San on crystallization
> kinetics. He certainly demonstrated that a very good protocol, indeed,
> for the crystallization process was developed and designed. That is an
> illustration that the process is under control and is reproducible and
> validated.
>
> With that, I would say that that would provide us in regulatory
> submissions, or the CMC, a package to deal with the agency and
> negotiate. That gives me much better assurance of the API quality, the
> dosage form performance through improved control of the particle size
> and particle size distribution.
>
> What I am trying to provide here right now is a regulatory overview.
> What do I look for when I put a submission together, the factors and
> the data that is given to us. Now, the particle size is scale and site
> dependent. It was studied at these scales and these sites and that was
> pretty scale and site dependent.
>
> The question to keep in mind for later on in the discussion would be
> how we demonstrated adequate process validation. That is the key
> question there. This focused beam reflectance measurement technology,
> of the FBRM technology, may be applied now to other BMS products where
> particle size is a critical performance measure to provide any
> regulatory relief.
>
> Now, in-process acceptance criteria is something that I would also
> look for. What kind of in-process criteria is in place? We know that
> we have some confidence right now in the process. It was under
> control, well duplicated, maintained the same particle size during
> filtration and drying, downstream processing. What that tells me is
> that particle integrity is really intact and is maintained.
>
> The question again that we should keep in mind at this time is could
> this replace the existing final release test, particle size release
> test, the routine particle size release test that we perform in a QC
> laboratory? Or, is it redundant? Is it really necessary? That is a
> question that we should ask based on science.
>
> Validation of PAT\--how do we validate this FBRM? We know that the
> process has been clearly demonstrated to yield us uniform particle
> size and particle size distribution, so that shows us the validation
> of the process capability in a way.
>
> What else do I look for? Consistent impurity profiles and how we
> accomplish that is through better control of the filtration, washing
> and the other downstream operations; particle size or particle size
> distribution; consistent process of the API and the dosage form and
> this is via crystallization; downstream processing; formulation and
> all those aspects of that.
>
> Once we consider all these things we need to get a tangible benefit,
> and that is that actually you prepare a submission and submit it to
> the agency, and initiate negotiations with the agency in a favorable
> way. So, if it is a new molecular entity where we are trying to
> introduce process analytical technology, of course, that will be the
> NDA route. If it is a marketed product and you would like to introduce
> this technology, it will be the supplemental NDA or the SNDA route.
> But if we do have something pending, for example under review, of
> course, I don\'t like to see the review clock impacted so I would like
> to work with the agency and submit an amendment to the existing NDA,
> in consultation with the FDA.
>
> Again, for requirements safety is always a concern. So, we need to
> make sure that using this technology or implementing this technology
> or converting to this technology, does this create any impurities in
> the process somehow? So, we verify the impurity profiles and I would
> like to have the physical characteristics compared, and would get some
> kind of assurance for myself as to validation of the process itself
> and the particle size and particle size distribution acceptance
> criteria, and process description and demonstrate material equivalency
> for the SNDA. How we do that is by a side by side comparison.
>
> Stability data\--we all know that there is really no difficult from
> the current practice and for the supplemental NDA a stability
> commitment only would suffice and, therefore, the NDA on a commercial
> scale, a pilot or lab scale, whatever the ICH guidelines would
> require.
>
> With that, I thank you for this opportunity and please keep those
> questions in mind as to have we demonstrated adequate validation, or
> how do we validate this technology and any of those things. We would
> like to get some input from the audience. Thank you.
>
> MR. THOMSON: Thanks. Good afternoon. My name is Glenn Thomson. I am
> the associate director of quality for Bristol-Myers Squibb. I
> certainly appreciate the opportunity. I worked with Ron\'s team as we
> put together some of the PAT materials.
>
> I think as we talk through this, we talked quite a bit this morning
> about Part 11 and what Part 11 represents. As we look at our mock
> submission and those types of things, we have to start to address what
> the expectations are for Part 11 in regards to those approval
> processes as well as we go forward.
>
> What I did on this slide is basically highlighted some of those
> particular components, audit trails with date and time stamps; data
> available for review and copying, and we want accurate and complete
> data, those sorts of things; device checks and the ability to look at
> the devices that are actually accumulating the information, and those
> types of things which are very important relative to how we look at
> PAT. Obviously, security in the sense that we want trained and skilled
> operators, particularly in this type of environment to make sure that
> those people have access to it. The changes that they are making from
> a configuration standpoint is important, going back into the audit
> trail and date and time stamps.
>
> We talked a lot this morning about computer validation, but it is
> interesting in the PAT world because what we see is kind of a marrying
> together of process validation, computer validation and even what is
> happening from the analytical side for precision and accuracy as we
> talk about moving applications really from the laboratory down to the
> shop floor.
>
> What is neat about this, this is really exciting stuff. You know, we
> talked about the large crowd that we have here today, and I think
> everyone is excited about doing this. I think in many respects this is
> what PAT and Part 11 is supposed to be all about. It is supposed to be
> a marriage that enables us to move forward. If it is not doing that,
> then obviously we have derailed somewhere and I think we need to
> figure that out.
>
> We want to promote the use of technology as we go forward and be able
> to address that. I think the other thing with this is that in some
> respects, as I have worked with Part 11, it is much easier to build
> than it is to go back and rebuild. Some of the areas that we struggle
> with certainly, as I think we heard a little bit about this morning,
> is legacy systems and what that means. You know, it is kind of like
> who wants to go back and look at that stuff? The exciting part is we
> should, if we are doing things correctly, be able to utilize the Part
> 11 expectations towards making a robust and effective process that
> promotes product quality, patient safety and all those kind of neat
> things. That is really what we are talking about here.
>
> I guess from a risk standpoint\--I think there was a question about
> risk earlier or, gee, if you had to do something different, what would
> it be, I kind of sort out new systems and legacies and say, you know,
> the legacies I have been using for thirty years, to go to Dr.
> Wingate\'s presentation this morning, this GMP thing has been around
> for a long time; it probably works okay. Let\'s focus attention on the
> new stuff and try and move forward. One suggestion is to look at it
> from that perspective as well to see what that might represent.
>
> The other point here is that the GMPs were really developed in the
> sense of the paper world. What we are trying to do is look at that
> relative to how we implement electronic systems in that regard. So, it
> is very interesting because as I listen to this, we have PAT that is
> kind of this core thing and then we have, like, GMPs that are kind of
> wrapped around that, then there is the broader umbrella of Part 11. I
> am not sure if you will solve the problem going this way, kind of from
> the outside in, or from the core, from PAT out. So, I think it is an
> interesting kind of an approach. It is something we have to figure out
> but, certainly, as well look at what we are going to do from a
> submission standpoint and the enabling opportunities we certainly need
> to sort those questions out.
>
> Some of the area that we run into we heard a little bit about this
> morning. We talked about things like data requirements. In this
> example we are collecting relatively large amounts of data as we go
> through, and there is certainly expectation to not just hold it but to
> process it and to reprocess it over time. If we look at the current
> guidance document and those types of things that are out there\--I
> think there is a draft guidance document out there from the FDA right
> now for comment, it certainly starts to enumerate those expectations
> around reprocess ability. The question is why would we want to do
> that?
>
> If you look at this example, if you look at the particle size
> distribution, and the mean, and deviation, you could probably
> reprocess that until you are blue in the face and you are going to get
> the same answers. So, is there any basis for having to maintain that
> data over a period of time?
>
> So, those are some of the questions that we have from a Part 11
> perspective, to try to put some framework around it and, hopefully, we
> can talk a bit more or have some questions.
>
> DR. MILLER: Essentially that is the Bristol-Myers Squibb presentation.
>
> DR. LAYLOFF: Thank you. Steve, are you presenting?
>
> DR. HAMMOND: I guess so. I have a question. Bearing in mind your
> comments about not wanting to go over the safe harbor during research
> parts of it, shall I skip most of my talk and cut to the end?
>
> DR. LAYLOFF: Just give your talk.
>
> DR. HAMMOND: I am going to skip through the middle of my presentation
> because it does talk about the development effort and the effect of
> validation on that. Maybe I will emphasize at the end some other
> concerns that we have.
>
> Essentially, I really want to talk about internal perceptions of
> validation and the problems that that might cause in terms of
> implementing PAT, either slamming it to the point where it becomes
> very difficult to do or even making it impossible to do.
>
> Some of my objectives here are to just look at this idea that PAT is
> going to take a lot of resources to implement and, if validation is
> not handled very carefully, it will slow it down and it will stop it.
>
> This is the wonderful statement that we heard from the FDA, that
> enforcement policy is not to impede innovation or introduction of new
> manufacturing technologies. Great! Let\'s see that in writing.
>
> \[Laughter\]
>
> I want to describe just a few of these things. I may be going over a
> little bit of ground that we have already covered, but I also want to
> talk about the cart before the horse paradigm because that is one
> thing we suffer from a lot at Pfizer where our regulatory group wants
> us to almost have a crystal ball, and you can\'t possibly do that.
>
> I am briefly going to describe the activities that we get involved in
> when developing PAT. I am going to skip very quickly through the
> software validation part of it and I am going to talk about instrument
> PQ tests and some of the concerns we have for the future where we
> might see USP testing applied to on-line sensors which, again, will
> make it almost impossible to do what we need to do.
>
> The implementation activities that we go through\--hardware
> development. We identify an instrument and we very often can\'t accept
> the instrument as it is off-the-shelf. We have to persuade the vendors
> to actually change their instrument. That is actually the way but
> because it is all totally based on science. We can do that in our own
> labs and come up with what we need to do.
>
> Software specification is very often easy to do as well because it can
> be based on the data we need to get. The validation issues, and we
> have already discussed this morning Part 11 compliance. The problem is
> that very often that means that we have to ask the instrument vendor
> to submit to an audit, and the audit very often reveals that they need
> to at least write a new version or very often write their software
> from scratch. That is a huge financial burden for some of these
> companies. At the moment we are looking at one on-line particle size
> technology, not FBRM, but the company says that it is going to cost
> them a quarter of a million dollars to write the software that is Part
> 11 compliant. Will it improve the measurements we do? No, but it has
> to be done.
>
> There is also system validation during development where we have to
> plan and document what we are going to do. The perception always,
> within Pfizer plants, is that we need a full GMP validation protocol
> even if we are going to be developing a system. If it is in the GMP
> area, there are no exceptions; it must be the full protocol. What that
> does involve though, I have to say, does vary from plant to plant and
> country to country, and I have to say that in Europe they do tend to
> be more pragmatic about what that means. If the document has to be an
> inch thick in Europe, then it is almost invariably three inches thick
> in the U.S.A.
>
> It is not just the software either; it is the instrument qualification
> protocols that we have to perform sometimes when developing this
> technology in a lab where we can\'t actually get at full scale
> production lots. Recently we have been developing these technologies,
> OEB-4 and OEB-5 technologies where we are not even allowed to go near
> the real stuff until we get to ICH batches. Yet, we have validation
> people asking us to predict exactly how we are going to manipulate the
> data before we have collected any. Well, this is a new concept for
> them, that using these modern chemometric techniques you cannot do
> that. You get some data; you look at it and then you decide how you
> are going to process it. It is sort of the way science is done. You
> collect something and then you decide what it means, not what it is
> going to mean before you collect it.
>
> Very often our efforts are slowed or made a long process by continuing
> revising and updating documentation for a GMP area when the data we
> are collecting has nothing to do with product release at all; it is
> just for the development of a system that later on will go on to a
> full manufacturing facility or be used in a manufacturing facility for
> release of a product when we have finished. When we finish, yes, we
> undergo what should be our final validation.
>
> I guess this repeats what I have said before. We are forcing small
> instrument vendors to produce software they can\'t really afford to
> produce, which often means they don\'t do it very well. We go round
> and round in circles with them with our auditors going back again and
> again to look at what they have done.
>
> One of the side effects of Part 11 compliance is these new versions of
> software, and it has happened to us that we have a perfectly good
> software that runs an instrument and we collect really good data on
> it, and then we say, well, no, you have to go to GMP compliance; we
> need a new version of this. We get the new version and then for six
> months it is a nightmare running it because it is full of bugs. Even
> the best software writing programs in the world will produce software
> that has bugs. So, moving to Part 11 compliance software can often be
> a nightmare.
>
> I guess the issue with Part 11 compliance is that it is only
> temporary. In a few years time probably it will just become a way of
> life and then will not be an issue, but at this point in time, and I
> would say for the next two to three years, it is a serious anchor that
> we are dragging along in the development of PAT.
>
> Again, often these things are a real issue not because of the
> FDA\--well, I will come back to that. They are a problem because of
> the internal perceptions of our regulatory groups. They have a fixed
> idea about what these things mean, particularly things like
> qualification of software. Again to repeat what we talked about this
> morning, but a small bug fix in a software can cause a change control
> document. Someone has to write it; someone has to approve it, and so
> on. Large bug fixes generally have validation groups say, well, that
> is a new version and then they expect us to do a requalification.
> Sometimes qualification of these complex software packages can involve
> a week\'s worth of work, just testing the functions that you want to
> use. So, you get a big bug fix and you are looking at a week for
> requalifying these things.
>
> Again, the internal regulatory groups want us to predict data
> processing protocols. My colleagues for the last month have been
> sending me almost nasty e-mails about when are you going to tell us
> what you are going to do with the data. I write back and say when I
> get some, I will tell you.
>
> \[Laughter\]
>
> So, this is a \"Mission Impossible.\" They really looking to have the
> cart pulling the horse rather than the horse pulling the cart.
>
> To summarize, the development of an on-line blender system in a GMP
> facility in our Brookland plant involved about 15 man-weeks in terms
> of development of the hardware. We specified what we needed in the
> software. It took about a man week to do that because what we needed
> was just additions to existing software. But system validation
> protocols, something that we were just purely developing, took about
> 101 man-weeks, almost two man-years. That is really because at every
> stage along the way, when we discovered something and needed to change
> something we were confronted with huge amounts of documentation to
> update, go before a validation committee and get approved.
>
> That is all I want to say about that. I want to now talk about
> instrument performance tests because generally if you use an
> instrument in your laboratory there is a defined monograph on how you
> prove it is working correctly. For near-infrared instruments there is
> a monograph in the USP and in the AP. They both tell you how to test
> your instrument to make sure it is fit for the purpose.
>
> These tests generally involve the use of NIST traceable samples which
> you present fairly easily to the instrument that is in the lab. But if
> you start putting probes and sensors into reactors, into crystallizers
> you can\'t do those sorts of tests.
>
> I have to say that I think that the number of the tests that are in
> the USP are based purely on being able to test the lowest common
> denominator of an instrument. They really are based on just having
> documentation, a box you can tick; they are not based on the
> scientific logic of what the sensors are going to do. It really
> frightens me that we will find the USP type standards being applied to
> on-line instruments because in a lot of cases it is just impossible to
> do it.
>
> We can ask the vendors to come up with ways of checking their
> instruments work correctly. In fact, most of them can do this in an
> automated fashion. That would essentially be based on the scientific
> principles that we need to prove that that sensor would work with the
> samples that we are going to be looking at, not an arbitrary thing
> that is based on availability of standards from NIST or from other
> recognized suppliers or standards.
>
> The problem is you talk about a near-infrared instrument nowadays and
> there are almost ten different varieties and they are very, very
> different in their performance, everything from an FT instrument with
> really high resolution to instruments that, again, you couldn\'t test
> using the USP system because they just don\'t have the right sort of
> output for testing using those standards. So, it is something that
> really needs addressing in any guidelines, the wide variety of
> instruments that we are going to have out there; the fact that you are
> going to have permanent installations of sensors in processes where
> you can\'t take out the probe every day and look at it or you are
> probably in danger of blowing up the plant.
>
> I want to give one example of this. The UPS states that you must test
> the wave length accuracy of a near-infrared instrument using a NIST
> 1920 standard. That is the rate curve, at the top there. For our
> processes we are going to use an FT instrument because we need pretty
> good resolution. What we are actually interested in is the distance
> between that fine structure in that plot at the bottom. So, internally
> at Pfizer, we want to know about the high resolution of that
> instrument and the USP says all we need to do is to test and find the
> top of the peak on the rate tracks. This is a very good example of a
> documentation-based system that really has nothing to do with science.
>
> The interesting thing is that if we stuck to the USP we would not be
> allowed to use the standard that we used for the bottom there, which
> is actually water vapor. We must somehow try and get that NIST
> traceable 1920 into our instrument, which is actually contained in a
> containment enclosure, to try and tick a box. It tells us nothing
> about the performance of the instrument; it is just a regulatory
> requirement.
>
> We can just about do this for this system because it is an on-line
> system but the sample interface is fairly simple. But when we start to
> get into other things in crystallizers, in reactors we just can\'t do
> this and there needs to be some science brought to bear on instrument
> performance tests.
>
> Just in conclusion, proper validation of PAT systems must, of course,
> be performed. But it should be done after development is finished, and
> information gathered during the various development stages needs to be
> considered. The safe harbor approach, I guess, is one way of looking
> at that, although the safe harbor approach we generally thought meant
> data you collected on a process, not development data during the
> development of a system. l
>
> If we don\'t take that view, we are going to drastically slow the
> progress or the development of PAT that is actually used in GMP
> facilities. What we need is to have the horse pulling the cart and not
> the other way round, and be flexible in the approach to validation
> development.
>
> One thing we need to be very, very careful of in the future is how we
> test the performance of instruments that are inserted into processes.
> That really must be left to individual companies, individual vendors
> to work out how you do that. We don\'t want the documentation-based
> restrictions of USP tests. Thank you very much for your attention.
>
> DR. LAYLOFF: Thank you very much, Steve. We will move on now to the
> next set of presentations on microbiology. We are going to split now.
> Micro people, go across the hall but we will take a 15-minute break
> now. It is 1:57 and we will reconvene at 2:15. Rapid micro across the
> hall, PAT people here.
>
> \[Brief recess\]
>
> **PAT Discussion**
>
> DR. LAYLOFF: I would like to get started now. I would like to get
> started now. One comment, the USP NIR chapter is number 1119, which
> means it is an information chapter. It is not used in any monograph;
> it is strictly an information chapter. On to discussion.
>
> DR. MORRIS: One thing that sort of seems to have been a theme
> throughout the meetings we have had is that there are the technical
> issues to be dealt with, and we heard a fair amount about that. I
> think there are a lot of examples that companies which have been
> proactive, like San had described during his talk for the technical
> side\--it seems like there is this internal regulatory group barrier
> that essentially is going to, in some way, the customer for the
> guidance.
>
> That is the sort of feel I get. I don\'t know if this is my
> imagination or if I am just too literal, as they always tell me. It
> makes me wonder if the guidance has to be more specific with respect
> to some of these issues that Steve, Dave and Bob have talked about
> earlier, and Rick alluded to earlier.
>
> DR. LAYLOFF: I don\'t know, we talked about safe harbor. We talked
> about the guidance and, you know, putting the research box in a
> different position. But I am not sure what that is going to mean to
> the people in regulatory affairs.
>
> DR. MORRIS: That is the question, yes.
>
> DR. LAYLOFF: I mean, the question is why are they interpreting that
> way if the guidance doesn\'t require it?
>
> MR. FAMULARE: Actually, I think it is even beyond PAT. Even if you
> were going to do any type of development work on an existing process,
> just listening to Steve\'s presentation, you would face this issue. It
> is not a PAT issue; it is a larger issue.
>
> DR. KIBBE: It is an issue of culture that has been developed since
> 19\--whenever the agency started inspecting. The benefits of being
> extremely conservative to the bottom line of the company have been
> well documented, and the benefits to being inventive when it comes to
> things that are regulated haven\'t been shown and what we are going to
> end up having to do is, first, the people who come here and who
> actually believe the agency really wants you to do this\--and that
> isn\'t saying that the agency is just saying that because Congress is
> in favor of the agency saying it and when the Congress changes the
> agency will go back to the way it is doing it. We have to go back and
> sell it. Then, when the rubber meets the road, if you will, when the
> agency actually goes to a company that has done it, they have to go
> there as a partner in the process and walk away saying, \"well, you
> made some mistakes but we are not going to stop you because they are
> not critical. Let\'s just keep rolling.\" Then word gets out and it is
> going to take a while. It is just going to take time.
>
> DR. LAYLOFF: We have run into this in another area, which is on
> laboratory equipment validation where you might buy a piece of
> laboratory equipment and the validation group may keep it held up for
> a year making sure it meets some specifications. I think part of that
> is \"blah-blah\" from the instrument manufacturers which infringes on
> good science. Anyhow, that is another issue; that is another story.
>
> DR. CHIU: I think maybe there are actually two aspects of this. If you
> look at the IND and then go into the NDA, it doesn\'t seem to be a
> problem because you do developing work; you do validation later. Even
> the three production batches are validated after the NDA is approved.
> So, you know, the reservation that we have to do validation before we
> do development\--however, it appears to me that when you make changes
> post-approval, you become very conservative and you have to do
> validation before you do development. I don\'t think that is correct
> because why can\'t we just follow, you know, the IND philosophy for
> the post-approval changes? If you have this misconception, the agency
> can definitely clarify this through the guidance and the issue in
> writing. So, you always can do development before validation.
>
> DR. LAYLOFF: I think also it is a control mentality. As you move
> closer and closer to the production facility you start moving a
> culture of locking everything in place so it will always behave
> properly all the time, and that clobbers you. Like, if you go to
> McDonald\'s, they are going to cook the hamburgers at a certain
> temperature, fry them a certain way. If you want to be innovative and
> say we are going to drop the temperature on hamburgers down by ten
> degrees on the cooking they will throw you out the door.
>
> DR. MORRIS: Just one point, not to be too critical of the internal
> regulatory folks because, for those of you who were at the meeting on
> Monday, I mean the reason that, in part, you can have relatively small
> statistics sampling result in a very high quality product, which we
> have over all these years, as Art pointed out, means that conservative
> approaches have their place.
>
> I think the difference that I sort of hear and sort of intuit is that
> if you are going to use a chemometric approach for the ultimate
> validation of a process, then by the time you have enough data,
> because you have to collect it over a large number of batches, you may
> already be a lot further down the line when you have to make the
> changes, and then it is a question\--I think this is what you are
> saying, Steve\--then it is a question of being able to make those
> changes more facilely. Is that correct? Whether it ends up being in
> the software or just in the algorithm training.
>
> DR. HAMMOND: No, it is before you actually have to collect any data
> you have to forecast what data you are going to collect and how you
> are going to manipulate it, and not being allowed to change anything.
> It is when you get into a GMP area that is the problem. When you do
> research, no, there is no problem. Well, in one case we have when we
> were doing ICH batches of a new product, even then this GMP lead
> weight fell on us.
>
> DR. MORRIS: But isn\'t that the same thing though? I mean, if you are
> saying that you have to have\--I don\'t know, a hundred batches before
> you really have your chemometrics in hand that you are being asked to
> forecast before you have those data? I think it is really the same
> issue, and it is one that I think scientifically is addressed
> relatively facilely. I am just not sure that it is internally
> viewed\--it is obviously not viewed as an easy process.
>
> DR. LAYLOFF: One mike on at a time, and Steve is going to finish and
> then Ajaz is going to comment and then we will go back over here to
> Joe.
>
> DR. HAMMOND: Well, the biggest problem really is that within the
> regulatory groups there isn\'t an understanding of what we are trying
> to do. They look at an on-line analyzer as no different than an HPLC
> system which is, of course, not true. They also don\'t understand that
> you need to develop this actually on a commercial process in the
> commercial facility. You know, we do that in the lab and that is
> another issue. It is just a mind set.
>
> DR. LAYLOFF: Ajaz?
>
> DR. HUSSAIN: I think we have understood the challenge, and I think the
> guidance will address this issue. I think we tried to summarize that
> at the end of the second meeting. So, I think the safe harbor, the
> research exemption, I think will really alleviate that and then make
> sure that that is there. I think the guidance can only do that much
> and then I think it will be up to the company itself to make the case.
> So, we can\'t go beyond that. Those are the limitations I am sort of
> expressing.
>
> But I just want to go back to the Bristol-Myers PAT team. I think it
> is a wonderful example and I again want to thank them for making that
> effort to present that. But if I sort of pose the question to that
> team now, you have a regulatory affairs person; you have the
> technology group and you have the entire team together. How or what
> did it take to sort of work on some of the challenges, or was it a
> challenge at all, at least internally, for BMS? If they could share
> that with us.
>
> DR. KIANG: The product that we showed\--all I can say is it is a late
> stage product. We are doing this because we have some issue with
> formulation as well as the isolation of the product. So, we have a
> real issue to deal with. I think we solved the problem to our
> satisfaction. So, when we were doing that I think there was very
> little concern about regulatory at that point but, you know, the
> motivation is to solve a real problem. I think the consideration of
> regulatory and data management comes second. So, that is how it was. I
> think it is a very healthy evolvement.
>
> DR. LAYLOFF: So, if you have a crisis, any paddle works.
>
> DR. MILLER: That being said, I would like to add as part of this
> comment that in regards to the preparation the backgrounds of the
> individuals that are participating are leaders in their regular work
> areas and have been sensitized to the PAT publicity, of course, and
> where this is going to go, and it is pretty much a good spirit, we
> feel, within the corporation across quality lines, develop lines,
> research lines, technology lines, regulatory lines, and there is
> anticipation, high anticipation throughout, we can say, the corporate
> world but down to the manager levels across these groups and that
> takes some persuasion and it takes internal and external presentations
> and publication to get the word out.
>
> Then, you know, there is the hope to also benefit the corporation in
> each one of these disciplines and technical endeavors to take
> advantage of this opportunity. Very clearly, that is how we view it,
> and we are viewing it across the board. I can say that I don\'t sense
> we have any fiefdoms with regard to this whatsoever at Bristol-Myers
> Squibb. In fact, we have a loose group representing roughly 25
> segments of the corporation, crossing all kinds of disciplines within
> the U.S. at this time. They will be tied together in a group that will
> be, on a routine basis, working together in some parallel, some
> non-parallel activities but San and I are responsible to move this
> group ahead in a leadership way to manage these resources and thinking
> of where and how we can employ our skills and talents for the benefit
> of the corporation.
>
> I think it has to be that kind of spirit which is internal and
> external. Without that kind of big point of view and smaller points of
> view, this could get lost and not be acted upon in an efficient and
> effective way. So, we try to resolve some of these questions that have
> been posed as road blocks and stumbling blocks by this means of
> communication.
>
> I think that is a key summary. We are looking for some challenges from
> this committee and anyone with regard to some specific questions that
> were posed during that presentation. We have away to that question
> period this morning was to facilitate the other speakers. So we want
> to get some feedback, if not at this very moment, within the next few
> moments so that we can respond.
>
> DR. LAYLOFF: Leon, then Gloria.
>
> DR. LACHMAN: Can I ask Ron, this was an excellent presentation from an
> R&D development point of view. Now, do you plan to extend this to
> routine in-process quality control?
>
> DR. KIANG: What we show is an approach to understanding
> crystallization and the control of the physical attributes of the API
> or drug substance. So, I think the approach is a general one. I think
> it is not specific to this product. Some of the other things we do,
> like molecular modeling and microscopic examination, may go further
> than we usually would do, but I think the PAT application allows you
> to understand the process but it is general for other types of similar
> processes.
>
> DR. LACHMAN: Do you use this for routine API production to monitor the
> crystallization in the process?
>
> DR. KIANG: Personally, I am not sure if this needs to be routine.
>
> DR. LACHMAN: Okay.
>
> DR. KIANG: It opens the question of what is process validation. Do I
> need to monitor after I, you know, do certain things to show I can
> reproduce it? So, it is a question that I am not sure I know the
> answer to.
>
> DR. LACHMAN: I think if you use it up to that point there is less of a
> regulatory problem. It is a problem when you start using it on routine
> in-process quality control and optimizing the process even further as
> you get more batches made, and you may have to do tweaking later on.
> That is where I see the difficulties coming in and regulatory change
> in thinking that is needed.
>
> DR. LAYLOFF: Gloria?
>
> DR. ANDERSON: That was impressive data that you gave on the
> crystallization and all of the other things. That was a salt that you
> were using. Have you done any similar work on non-ionic compounds? If
> you have, how do they behave?
>
> DR. KIANG: I think most of the drug substance we work with usually,
> for practical purposes, are some kind of a salt. So, I have no
> personal experience in scaling up a non-salt.
>
> DR. ANDERSON: So, if someone wanted to adopt the procedure, they would
> have to work out the details of the non-ionic?
>
> DR. KIANG: It would be only different in the way you introduce
> crystallization, but I think the approach of using FBRM to monitor
> particle size would be the same because you crystallize by changing
> the solubility. You increase the solubility and the material comes out
> of solution. It is must thermodynamics.
>
> DR. ANDERSON: The problem is the attractive forces are different when
> you get those other kinds of molecules. I have another question. On
> your first page, I guess it was slide one, you list some PAT
> applications, and you have reaction monitoring. I think I understand
> what endpoint determination is and kinetics and mechanism. What is
> control of selectivity?
>
> DR. KIANG: This refers to monitoring of reactions. Using some of the
> PAT instruments, for example FTIR, you can monitor the reaction
> itself. But in the process of monitoring the main reaction\--not all
> reactions go 100 percent to one compound. There are many times when
> side reactions can happen. So, by using in-line monitors such as FTIR,
> you control the reaction profile, hopefully, to minimize the formation
> of byproducts.
>
> DR. ANDERSON: Well, how does that differ from endpoint determination?
>
> DR. KIANG: Endpoint determination is a single point indication that
> your reaction is finished. It doesn\'t mean that you have a
> distribution profile.
>
> DR. ANDERSON: When we finish can I talk to you about this control
> selectivity?
>
> DR. KIANG: Yes.
>
> DR. ANDERSON: Because I don\'t understand how FTIR could do this.
>
> DR. KIANG: No problem.
>
> DR. LAYLOFF: Ajaz?
>
> DR. HUSSAIN: I have sort of two questions, and that question is
> directed at the BMS PAT team and also, in some ways, to Steve Hammond
> because I have seen some very similar data from Steve on
> crystallization monitoring and sort of endpoint and actually targeting
> that to get a desired particle size range.
>
> The two questions I have are\--and I will just state the questions so
> you can answer them one at a time\--the issue of a representative
> sample. When you do this on a routine basis what are the challenges in
> sort of justifying or making sure that what the probe is seeing on a
> routine basis is reflective of the process?
>
> The second is sort of a question as to how does this on-line add
> value, especially in terms of building confidence in the process,
> compared to an off-line test where the sample size is a few grams or a
> few milligrams, and from a large bulk how do those few milligrams
> represent the entire batch? So.
>
> DR. HAMMOND: Well, in terms of the FBRM system it actually depends on
> the suspension that you are measuring moving. So, you are actually
> agitating it and over a period of just a few seconds you probably see
> several million particles. So, in terms of getting a good
> representative measurement, FBRM is actually hugely better than doing
> an off-line test. I don\'t think there is any doubt about that at all.
>
> One of the problems with FBRM is when you do it in a pilot scale
> reactor it is very easy. You can put that probe straight into the
> tank, but you when get a 2000 gallon reactor and you get the probe
> into the reaction mixture, that is a big issue and that is something
> that we are working on at the moment. How do you get a representative
> sample if you start to put it in the recirculation loop, that is an
> issue. But generally those measurements are much, much better in terms
> of their representative sample.
>
> DR. KIANG: In order to put one of these FBRM probes into a vessel of
> any size, I think it requires some understanding of the mechanism of
> mixing in the vessel of your size. So, that really requires some
> engineering work and thinking. You can do it theoretically, but I
> think with experience\--for example, I showed a picture of one of
> these probes in a 2000 L vessel, and we have an idea where the area of
> good mixing is.
>
> Also, we do two other things. One is, obviously, we calibrate the
> probe before we stick it in. But in the vessel, and knowing the
> process, you know many things. You know, for example, the number of
> particles that you should be counting in any given stage of
> crystallization, and we do compare that with actual expert database in
> a sense. We also vary the positioning of the probe within the vessel
> to show that you get a reproducible and consistent result.
>
> So, all those are done during the stage of implementation in any of
> these scales. In this particular case, there happens to be a story at
> the end and we show that there is no difference between 15 L and up to
> manufacturing of 4000 L. In many cases that may not be the same. So,
> we deal with it case by case.
>
> DR. HUSSAIN: Just to sort of follow-up on that, when I talk about PAT,
> for instance, I always have to keep reminding myself that it is part
> of a system. I think what I want to express to you is sort of the
> concept that PAT in a vessel and representative sample collection
> process depends not only on the position but also on the flow and
> other parameters of that process. The reason I am saying that is
> because if you had a range of particle sizes and particle densities,
> what comes before the probe will depend on the flow and the mixing
> process. So, we cannot look at the PAT in isolation from the rest of
> the process.
>
> That actually challenges us to think in a systematic way, in a
> systems-based approach way, and I think that is the good part of it.
> But it also poses challenges for validation. Validation of that
> measurement itself, from that perspective there are two challenges.
> One is if we propose that validation would be comparison of samples
> collected and microscopic examination, is that a valid comparison to
> start with?
>
> The second question is shouldn\'t the validation be then based on how
> does that measurement relate to the performance of that material?
> Wouldn\'t that be a better way of validating that measurement? Because
> the challenge would be validation from sort of that perspective.
>
> Then the second question is when you start to set specifications, our
> specifications then tend to assume more often absolute specifications.
> When you have particle size you have this method, so this is the
> particle size. Here, the measurement may be related to that but may
> not be absolutely due to that. So, could you comment on that?
>
> DR. KIANG: Yes, I think it is, you know, just simplistic to assume
> that sticking a probe in a vessel is going to give you representative
> samples all the time. I think, like Steve suggested, you might try,
> especially in the beginning of implementation, different
> configurations. You can put three probes in at different depths. One
> common technique obviously, which we learned from gaining a
> representative pH from a vessel, is to design a circulation loop. So,
> most of the time that gives it to you a little bit better. But, you
> know, what we do in this process is that we continuously take
> microscopic pictures of the slurry where we actually measure. You
> know, the principle of working with FBRM is pretty much shake
> dependent, as you noticed. So, a needle might have bimodal
> distribution just because of the narrow end and the long end.
>
> So, the measurement of particle size is a controversial one and you
> can bias it one way or the other by massaging the data or using the
> kind of technique you use. You can use sieves which pharmacists like.
> You can use FBRM. You can use a lot of other techniques. So, I think
> it goes back to your original question, it is what is being used. I
> think it very much depends on how you calibrate. Some crystals are
> heavier and they will settle and there is no way you can have an
> accurate measurement.
>
> DR. HUSSAIN: No, I think the point is well taken, but the other aspect
> is with respect to particle size analysis. We don\'t have good ways of
> comparing particle size by sieving, and so forth, today because the
> methods themselves can create artifacts to start with, at the same
> time, I think how we count the particles and how we calculate the
> diameters, and so forth, are subjective. So, we have to recognize the
> limitations of what we think are gold standards and sort of keep that
> in mind as we look at the new technologies.
>
> DR. LAYLOFF: Leon?
>
> DR. LACHMAN: Can I ask the BMS group, in your studies did you use
> multi probes in the scale-up tanks to see which area of the tank takes
> the longest to get the distribution or the particle size uniformity?
>
> DR. KIANG: We did not use particle probes at the same time. We varied
> the location of the probe at different parts of the vessel.
>
> DR. LACHMAN: You weren\'t able to determine, from a time point of
> view, how much time it would take to get the distribution to be
> consistent through the tank?
>
> DR. KIANG: The process is a transient one because we are trying to
> monitor a kinetic process. We are trying to measure both the number
> and size of particles. So, there is an endpoint but the system is
> changing all the time so there cannot be a consistency check. Only by
> comparing with laboratory data do you have some indication that you
> are doing the right thing and the same thing at different scales.
>
> DR. LACHMAN: But isn\'t there an equilibrium point after a time period
> where the particle size will not change?
>
> DR. KIANG: That is right. That is the end of crystallization, and we
> did show that in one of the slides. You know, at all scales they call
> come to the same endpoint.
>
> DR. LACHMAN: But could you say that for the entire tank distribution?
>
> DR. KIANG: We are inferring that. We are saying that the location that
> we put the probe in is representative of the entire vessel.
>
> DR. LACHMAN: You have done some initial work to demonstrate that that
> is the case?
>
> DR. KIANG: Yes, we did that by varying the location of the probe, and
> also from our own experience during process development we know, for
> example, the number of counts we will have at every stage, and it has
> to match that.
>
> DR. COHEN: I have a question regarding the actual data part of it.
> Let\'s assume that we actually went ahead and validated the scientific
> basis for your method and we are now in production. You actually did
> talk about the production scale results of a vat of 4000 L. You go
> ahead and generate the data, and you have the graphs at the endpoint
> and now you determine, based on those, that the product quality is
> appropriate for release. What do you do with all the data that you
> generated to get these graphs, and how much of it do you have to keep
> and how long do you have to keep it? The question would be posed,
> first of all to Glenn as far as what do you intend to do and what did
> you do? But also maybe for Ajaz to point to some of the people on the
> FDA side as far as what is your thinking that we should do?
>
> MR. THOMSON: I think as far as the amount of data to keep, we keep it
> all. There are reports that go out, those types of things but
> essentially that is part of the question. You know, we are keeping it
> all but the question that we have is why. Is it really necessary that
> we keep it all from a scientific basis, particularly because if you go
> back and reprocess it you essentially have the same results? So, those
> are the questions. But right now we keep it and that is part of the
> expectation. But that is one of the things that I think we are hoping
> for some feedback on as to what we should do in the longer term and
> how we might want to address that.
>
> MR. FAMULARE: That is the question that we keep circulating around. At
> one point I thought that Steve had proposed it and actually answered
> it for himself, and I guess Bob a little bit as well, that the
> capacity is there to keep the data in terms of technology. Storage
> space isn\'t really the problem.
>
> But what happens over time when the data has to migrate? I don\'t have
> a magic answer for that. I know that what I called reformed and John
> Murray corrected me and it is reformulated\--I certainly didn\'t mean
> to reform John, but the group in existence before Part 11 actually
> attempted an archiving called maintenance of records document. Again,
> it goes through some proposals in terms of different options of
> storing data, including migration and so forth, and it doesn\'t sound
> like that provided all the answers that folks needed.
>
> Actually, we just had a short discussion off-line, and the way I was
> trying to go this morning is that what would we normally expect to be
> kept as a record in terms of a GMP record, the predicate rule? I think
> we always have to keep that in focus. There is a little bit different
> problem when you really want to preserve the data for a long period of
> time because of your development work and, you know, what will happen
> if the system that brought that data up twenty years from now doesn\'t
> exist. I don\'t know that I have that answer, but at least in a
> routine GMP type of basis I think we have to really\--and I have said
> this earlier\--establish what you need in a batch record; what are the
> critical steps that you need to record. Once you set that down, pretty
> much as John discussed, if you set your parameters first, then I think
> you could answer those questions logically for risk-based, criticality
> and those other factors there. I think FDA needs to look at that too
> from a reasonable standpoint, with it is the overall application of
> GMPs or the underlying Part 11. It is something, quite frankly, we are
> struggling with ourselves in terms of what to give you back as a clear
> message. That is something that a larger group, in terms of Part 11,
> is, of course, tackling under the GMP initiative.
>
> DR. LAYLOFF: We will have Eva first.
>
> DR. SEVICK-MURACA: I have a question for you. You utilized this PAT
> just to get an understanding of your manufacturing process. Right? It
> was not to dictate the quality of a batch, or did not impact the
> decision to release drug? Right?
>
> DR. KIANG: Absolutely. This is pre-NDA.
>
> DR. SEVICK-MURACA: Therefore, you were not necessarily concerned with
> the regulatory aspects of this instrument, other than it did not
> impact the process itself on a commercial line? Is that correct?
>
> DR. KIANG: Right.
>
> DR. SEVICK-MURACA: And that is consistent with FDA? That is fine. So,
> how is it that we can\'t get internal regulatory groups to understand
> that this is something that the FDA encourages? Is there any
> possibility that, as with other regulatory agencies, we have a
> facilitator at the FDA that helps us so that we can overcome some of
> these internal\--
>
> \[Laughter\]
>
> You are the facilitator? So, if I come with a new technology and a
> number of companies are interested but say that they would like to
> solve some of their problems under the GMP environment but they can\'t
> do it, you would be able to help me out so that I might be able to
> help them? Who is the facilitator?
>
> DR. HUSSAIN: We just keep going back to this and I just want to get
> over this and move on. Well, I think FDA has done probably all it can.
> Let me just sort of reiterate in essence what we have done. We said,
> all right, there are perceived and real regulatory hurdles. We wanted
> to examine that and we did that in the first two meetings. Based on
> that, we said I think that the real hurdle, if any, is the concern
> that we do not have the right amount of training. So, we focused on
> the training for our internal folks.
>
> So, training is a key. Because of that, I think we have created a team
> approach so that the review and the inspection side are on the same
> page. We also have a situation where you have a focal point for PAT so
> at least the agency is speaking with one voice and you are not going
> to get different signals.
>
> Beyond that, I think the guidance will outline the research exemption,
> safe harbor concept. I think what BMS has done had no regulatory
> impact on that at all, but the regulatory impact will only come if
> they were trying to collect data on an existing line, which is a
> commercial line, and they wanted to optimize that. We will work with
> them to make sure that that is consistent.
>
> The only concern I think we may have in the first meeting discussion
> point would be does that adversely impact the ongoing process. If it
> does not, then I think the protocol essentially would define that they
> will be collecting the data as research data and all regulatory
> decisions will be made only on the established regulatory method so
> they don\'t have an adverse impact of that. When they do validation on
> their research, that is their business, and so forth. So, I think we
> have done all we can. Anything beyond that, I don\'t see what we can
> do.
>
> DR. MORRIS: Just a comment, I think we have sort of been posing the
> question of how do you engage the internal regulatory group but I
> think you guys already have. I think it has been done at least once.
> So, this sort of springs hopeful.
>
> The other point I just wanted to touch on was that similarly, I think
> with respect to data retention, I mean if you really have concerns
> that your software is going to be out of data in five years, which it
> undoubtedly will be, if not less than that, this is where the
> spectroscopists for years have been saving ASCII files so that they
> are sort of independent. Then you have to make sure you don\'t change
> the level of magnetization or something, but other than that.
>
> DR. HUSSAIN: I think this is not a unique problem to PAT. This is a
> common problem. In fact, there is an ASTM standard being developed for
> that. There is a whole group development for archiving chemical
> structures, XML and so forth. There are all sort of activities. You
> are not unique in that.
>
> I think what is unique to PAT for data archiving purposes is what do
> we keep? Because we are collecting a lot of information. So, the
> question becomes what is, from a regulatory sense, not from a business
> and R&D sense, is to keep for regulatory purposes? I think the
> discussion this morning sort of evolved, at least in my mind, was that
> the predicate rule I think is the defining criteria in terms of not
> only the time for keeping something as well as what to keep.
>
> At the same time, I think the complication is the definition of an
> electronic record and the definition of a paper record. There are
> differences. In fact, we don\'t have a definition of a paper record.
> So, that is where the problem starts.
>
> \[Laughter\]
>
> I think as we start working towards this, and I think Joe and his
> group will sort of be working on that for all aspects, not just PAT so
> that will happen in parallel, but I think a risk-based approach to
> what we keep and what we keep for the purposes of making decisions as
> well as for archiving\--somebody mentioned this morning I think we
> need to look at risk base from a recall perspective. What information
> would be necessary at the time of recall if, unfortunately, we have a
> recall? So, that would be sort of one way of thinking about the
> long-term storage of this data, long-term in the sense of shelf life
> or whatever.
>
> At the same time, I did make the proposal, which is not totally
> consistent with Part 11 but I think we need to look at that, and that
> is what information is being used to release a batch? I think it may
> not be consistent with what we might perceive but I think if it makes
> logical sense we will pursue that and then sort of see what needs to
> be done to make it consistent.
>
> The aspect is this, in a sense you have data streams that come through
> and that could be saved in some form, but what becomes a batch record,
> at the time of release of a batch what does the QC department need to
> make that decision to release that batch? What is the summary
> information that will be recorded as a batch record? It could be
> something that we also look at, and how long should that be saved, and
> what do we do with the rest of the data? So, we will sort of look
> through this.
>
> DR. LAYLOFF: A couple of things. I think the PAT has the paradigm
> shift which says you look at consistency and uniformity tied to
> product performance rather than using univariate snapshots. I think
> also the records required to release the product are one aspect. The
> other one is what do you require for a kappa if there is a problem?
> How do you reach back into the data system and pull a corrective
> action to adjust it? Because you do have all that power on the data
> stream that should allow you to reach back very far into the system.
> So, I think you may want to keep it, not so much for FDA use, but for
> your own use. If you look at the process as a system, you set out the
> system to yield a product and then you accumulate data on it and you
> then want to have enough data to be able to pull a kappa. If you dump
> too much data you can\'t catch it.
>
> MR. FAMULARE: The GMP has the annual record review requirement. Of
> course, all this was written in the paper world but it was not written
> in the sense to require you to keep additional records beyond the GMP
> records in order to do that evaluation. You know, it is under records
> and reports, a review to determine trends, problems\--that is not the
> exact wording\--etc. Under PAT or any of these other paradigms it
> should also be doable, but it doesn\'t have to be doable from the
> sense that you have to keep records required beyond what is required
> for a batch record. I think we have said that now about four different
> ways. It is just that the implementation I think is troublesome.
>
> DR. KIANG: I have another suggestion for data management. It seems
> like if you use PAT to understand your process you have a lot of data
> to collect. Let\'s get back to engineering science. You know, when use
> PAT you are measuring kinetics, rate of changes whether you are
> changing crystal size, you are changing the blending, the profile is
> changing. You can store all the raw data you want. Eva, you are an
> engineer. You understand that the ultimate understanding of a process
> goes back to the ability to model and simulate the phenomena.
>
> With our presentation, it is possible with the data we monitor to
> construct a simulation to predict what will happen. That is the
> ultimate information. Right? We are going to separate data versus
> information. So, you can store all the raw data you want and keep it
> for as many years as you want but if you are able to distil that into
> a simulation model I think we have achieved the goal of understanding
> the process.
>
> DR. UPADRASHTA: As I saw San\'s presentation develop I kept wondering
> if we were going to do a disservice to PAT by showing you the
> presentation we showed you today because, frankly, it all worked
> great. So, I have basically two aspects of the same question. What if,
> as we went from the lab to pilot scale to commercial scale those lines
> didn\'t align the way they did? And, how would we treat that?
>
> Number two, what if we were releasing it, say, based on the percentage
> below 25 microns, or whatever and we see variations from batch to
> batch that we didn\'t know were there? Have we shot ourselves in the
> foot here? I think this is one place where if I were looking for
> guidance from the FDA, this goes beyond research exemption. You know,
> how are we going to handle that situation?
>
> DR. LAYLOFF: Thank you. Eva?
>
> DR. SEVICK-MURACA: That is the question that I was having. It is great
> that you got the results that you got, but what if you did not get the
> results? Excuse me, you and I know there is no such thing as that
> perfect model and there are always going to be errors; it is just a
> matter of how closely you look. So, now we are starting to use these
> new technologies and we are gaining more information. So, how does
> this impact? If you put this on a product line and you get something
> you didn\'t know, what does the FDA say about that? It is still safe
> harbor; I understand that.
>
> DR. HUSSAIN: The issue is simply this, in a sense what do we want to
> do? I think we all want to do the right thing. If you find some
> problem that exists because of new technology, we have dealt with that
> and I think Yuan-yuan Chiu would like to say something about that and
> Joe also.
>
> I think we have to reflect back. We know there is a problem. We don\'t
> want to know there is a problem because the product is working. Keep
> that in mind. At the time of approval, the current product was fit for
> intended use so we have defined that. Any other variability that we
> find, I think it is best to sort of improve on that but not penalize
> that. So, the safe harbor concept essentially says as part of the
> approval process, yes, this is what was fit for intended use; this is
> what the clinical trials were based on; this is what the approval
> decision was based on. Now we find that we have an opportunity to
> improve it further, so why not? But to improve it further you don\'t
> have to penalize.
>
> DR. CHIU: I thought that the PAT has two purposes. One is in-process
> control so you sort of like have feedback. So, if you see something
> like blending that is not going in the right direction, during the
> process you may be able to adjust certain parameters. The second
> purpose is to make sure the end product, the blend is uniform or the
> crystals have the same particle size in the range you are looking for.
>
> So, for regulatory purposes we are more interested in the end part
> because we are interested in the performance of the final product. But
> from a manufacturing perspective, you are also interested in the
> process so, therefore, you can adjust. You have feedback so,
> therefore, you will reach the endpoint.
>
> So, in terms of what data you need to choose to keep, I think the data
> for the end product and intermediate is proper. I think that is
> absolutely essential. But in terms of in-process and what data you
> need to keep will depend on what the process is and what the product
> is. So, you have to identify the critical endpoint and you will need
> to know certain data in order to trace back in the future, to look at
> the trend and to look which direction will give you the best end
> product. So, from a regulatory point of view I think the most
> important part is the end product, data to support the end product or
> the intermediate.
>
> DR. LAYLOFF: Art?
>
> DR. KIBBE: Let measure just say, first, we can bias the way we look at
> information by giving it a label. If we put a new system in place or
> one that seems to be working well enough to get a quality product and
> we find variation we didn\'t see before and we call it a problem, it
> is a problem. If we call it a variation that was undetected, it is not
> a problem. I mean, Heisenberg told us we can\'t know anything
> absolutely so we have to get over that.
>
> \[Laughter\]
>
> And PAT is a way of getting us closer to six sigma because what we are
> doing is looking more closely at the variability. We are getting a
> better statistical handle on variability. We are getting better
> confidence in the output and we don\'t need to change to goal posts
> that the output has to go through. We just use this to the best
> benefit of the manufacturer in terms of making sure that they have
> less batch failures; they have less problems meeting their end goal.
> So, when we apply PAT we are not looking for new problems to uncover.
> We are looking for improvements in the system to get to the same goal
> post. Okay?
>
> DR. LAYLOFF: We will go with Joe and then Ken.
>
> MR. FAMULARE: I think my FDA colleagues already reflected much of what
> I had to say. It is just that we should realize that, as Ajaz said, we
> have already established that the current paradigm is suitable for its
> intended use. So, if a company is to bring on PAT on an existing
> process the idea would be, if it came out as the Bristol-Myers example
> with everything overlapping; everything consistent, that is good. You
> know you are headed in the right direction. But if it doesn\'t overlap
> like that, how can you optimize that process? How can you better
> improve your process?
>
> This brings things to bear or to light beyond what you have
> traditionally been doing for process validation. It brings to bear on
> how to deal with root causes when you expend so many hours on out of
> specification results, recalls, recalls based on dissolution. We heard
> what the number one reason was yesterday and now I am bringing up the
> number two reason, dissolution failures.
>
> So, I think you have to look at it from positive motivation as opposed
> to what will happen if we do it and FDA sees that there is a
> variation. You know, there is variation. Now you are going to be able
> to quantify and identify it and, if possible, at least to have an
> explanation for root cause failures that are unexplained or to put
> things in place that can better control the process or the cost to
> manufacturing.
>
> DR. MORRIS: That was sort of my point too. To San\'s point, buried in
> the signature of the data you collect are the elements that need to be
> addressed and if you can tie those back to specification
> properties\--sort of what Joe and you were saying, Art, then this
> gives you the ability to not only refine your model but to go back and
> look at what really are process critical control points because at the
> end of the day if you don\'t have those you are not going to improve
> it anyway.
>
> MR. COOLEY: One of the questions, and maybe I missed it during your
> presentation and maybe you could expand a little bit on it, you
> obviously went through and tried to identify what were the critical
> attributes that affected particle size and particle size distribution,
> but in the presentation I didn\'t see if you are proposing a new
> control scheme at production scale that will address and provide a
> feedback means of controlling within that distribution to make sure
> you have a good product, or what was the plan once you go into
> manufacturing?
>
> DR. KIANG: We have demonstrated this process at a manufacturing scale.
> In this particular case the process critical control parameter is the
> additional rate of the acid which induces the crystallization. Now, in
> the event, if we actually implement this consistently in manufacturing
> and if during crystallization you do see a variation, then there is a
> control of the acid rate. So, there is the link there but it is not
> necessary in our case. It is kind of internally taken care of by
> designing the five stages of acid addition. But, you know, not all
> processes work like that. In some other crystallization procedure that
> may be the case. You might take the feedback loop to control heating
> and cooling of the solution, or that kind of stuff.
>
> MR. COOLEY: You have determined what the optimum rate is to get to
> that particle size, but is there a plan that if you start seeing your
> particle size distribution shift one way or the other that you would
> modify on the fly what that addition rate is to try and bring it back
> into your gold standard?
>
> DR. KIANG: That is one of the things you can do, yes. The addition
> rate, in crystallization jargon is a cubic addition. It is actually
> designed to minimize the effect on agitation. It is a classical way to
> seed and, therefore, allow the initial crystallization to be in the
> growth mode rather than the nucleation mode. In a sense, that
> minimizes a lot of scale issues. But you are absolutely correct, if
> there are deviations from the desired outcome, changing the addition
> rate of the acid is one way to do it. There are other techniques but,
> you know, I don\'t want to get into that now.
>
> DR. LAYLOFF: Ajaz?
>
> DR. HUSSAIN: To sort of work off that example, if the critical control
> point here is the rate of addition of acid to initiate the
> crystallization process, the rate is controlled by the flow, or
> whatever. So, you already have a controller on the rate of addition of
> that acid. So, having an on-line monitor for a crystallization process
> would be a redundant system but that is the redundancy that you sort
> of build on that.
>
> The second redundant system could then rely and provide information to
> do two things. One is to make sure that the process worked. Also, you
> may not have to do an end product release test for that if you can
> correlate it to that.
>
> The second aspect is if, for example, as a redundant system if there
> was a kappa or there was an event that led to certain changes in the
> rate of addition of acid, suppose there was a failure there, the
> redundant system would be sort of a backup system to sort of recognize
> that and correct for that failure. For example, if I now add another
> variable to it, or if I work on Steve\'s example that he shared with
> us before, if now you are aiming for minimizing find particles in your
> vessel, one of the techniques that Steve showed was to reheat to make
> sure that the small particles are gone.
>
> So, now you can sort of have the second redundant system doing much
> more than that. It is not only a redundant system but it also brings
> into play a second level mechanism, or whatever, a control mechanism
> to make sure the particles were what we wanted. So, there are many
> different variations of what this could do. I think what is
> appropriate for a given system would depend on what the system is. It
> will be a case by case decision whether to do this in what range of
> applications. The validation then would sort of vary with the
> application.
>
> DR. KIANG: If we did not have this monitor, what we would have done is
> tell the plant these are the five addition rates you have to use
> during these five hours, or whatever. If anything goes wrong and, say,
> the particle size is too small, then you cannot release the batch. But
> with PAT in place you can actually do something about it. That is key.
> You know, at the end of the batch there is nothing you can do other
> than rework the batch. In this case we can do something about it and
> very likely we can save the batch from being rejected.
>
> DR. RUDD: Could I just have a go at creating a \"what if\" scenario,
> and it is a bit stronger than \"what if.\" It is actually a scenario
> that I believe we are in within GSK at the minute, kind of on the
> theme that I have been hearing. It goes back to some of the work that
> we have been doing using acoustic monitoring for tablet granulation
> processes.
>
> The way it goes for most of the products we have been looking at, this
> idea of scale-up, we have to kind of move away from our idea of
> overlaying traces. If you look at the typical acoustics signature that
> you get at a given scale for most tablet formulation processes, it is
> a wavy line. It is kind of like a spectrum but it is not a spectrum.
> It is just a signal against time.
>
> This will be heresy, I know, but if you run that process under
> so-called identical conditions you do not get lines that overlay. It
> is just a feature of the signal and, dare I say, pardon the pun, the
> noise in the signal. But what you do see are repeatable and
> reproducible features. Imagine lines that don\'t overlay but certain
> characteristics, points of inflection, these things turn up
> reproducibly.
>
> What we have found is that if during the development you establish the
> kind of features, the signature which is the fingerprint, the term we
> have been using, if you can establish that during development you can
> use that as your endpoint determinant. So, if you then change scale
> once again you will get a line and it will not overlay with the line
> you got on the previous scale but there are regular and consistent
> features that will appear. So, you have the model, the endpoint to
> work towards.
>
> What we have been finding, and I will be talking about this at the IVT
> conference on Friday, is that granulation processes are critically
> dependent on the quality of input raw materials. It is kind of obvious
> really; let\'s kind of accept that. The signal you get will depend on
> the quality of the raw materials. The salient features will
> consistently reappear. So, what you have with that particular PAT is a
> brand-new application that says if I can modify my process, and it
> could be addition rates, binder rates or whatever you wanted to do, if
> I can recreate the profile to compensate for the variable quality of
> the raw material, then I am guarantying product quality and it will
> allow me to say, having reached the endpoint, that this material is
> now suitable for further processing.
>
> A big buildup but here is the question. What do you think the
> regulatory expectation of a piece of work like that might be? I would
> imagine not doing this in routine manufacturing\--I am going to apply
> this acoustic monitoring to my granulation process. I am going to vary
> the granulation process to compensate for variable quality of raw
> materials, and I am going to guaranty quality of output by getting a
> defined endpoint. The reason I am guarantying the quality is that I am
> going to reproduce the signature that I know I have to get.
>
> The benefit to all of this is nothing more than the successful
> processibility of my granule. It is not the final product. It is not
> what the patient sees, but I am doing all of this so I know that when
> my granule is of defined quality it will compress; it will give me
> good tablets. Like I was saying this morning, it is the table end
> product specification that never goes away. All of this is a buildup
> to final quality of the tablet. What would be the regulatory
> expectation of the data that I would need to show on a routine basis
> for the quality control of that granule, which at the moment is not
> currently specified? Sorry, it is a long question. I hope the answer
> is short.
>
> MR. FAMULARE: Can you repeat the question?
>
> \[Laughter\]
>
> DR. CHIU: I don\'t think this is anything new that we have faced
> because what you are saying is you can have ranges of your processing
> parameters. You have different time or different speed. One example
> where we have faced this before\--you know, we are here to talk about
> chemical substances, that the drug substance is well defined, the
> right potency, however, when we deal with biological drugs they are
> not because each batch may have slightly different specific activity.
> So, in order to get the final potency right we label that as units per
> milliliter and you fill with different amounts for each batch, and we
> just establish a range and that is what, you know, you do. So, I think
> this is very similar, analogous. I do not see this as anything
> revolutionary.
>
> DR. RUDD: The bits I wanted to bring out, and this is probably the
> underlying point that I want to make, is about changing the mind set.
> We have talked about overlapping. We have talked about validating
> processes and measurements and being able to overlay and compare data.
> I think we have to move away from that. We are looking at measurement
> technologies that take us into a different realm and this idea of\--I
> will call it feature detection when you get a signal, when you get a
> signal against time, the idea of being able to identify distinct
> features in there is a chemometric, or maybe an eyeball-metric
> approach, I don\'t know, but the ability to say, okay, these two lines
> are not the same but they are telling me the same thing.
>
> I just want to kind of bring that in because my feeling throughout the
> day has been that we are a little bit locked into\--and it is
> understandable; we have all been in this industry a long time and we
> have all developed sort of a mind set. We are tending to think in
> traditional ways for what is a very novel approach and we have to be
> careful that we don\'t minimize the potential of the approach because
> we are not broad enough in our thinking.
>
> DR. LAYLOFF: Ajaz and then Ken.
>
> DR. HUSSAIN: David, I think the concept that we outline sort of
> incorporates that thinking already in a sense, and I think the
> question in my mind is, in a sense, if you have features in a
> fingerprint that are reliable indicators of certain attributes of an
> in-process material, which are important attributes for the next step,
> I think the question that comes is how do you build confidence in
> those features rather than the entire fingerprint?
>
> Once you are able to do that and demonstrate that this really is
> predictive of the end product or that material property that comes out
> of that process, then I think that is what we would like and it is
> perfectly compatible with our thinking that, yes, the raw material
> variability can be addressed by having a process which is flexible
> enough to produce a material at the end of the process which actually
> is more consistent now. So.
>
> DR. MORRIS: Yes, just a brief follow-up on that, not to fly in the
> face of your conclusion but it is sort of not that different than some
> precedents because if you look at powder diffraction, if you look at
> the way powder diffraction reflects crystalline material we are used
> to thinking of it as being a monotypical system and that you are
> looking at the D spacings but, in fact, there is intensity and
> everything else. We focus on D spacing. If form is your goal, if you
> are doing on-line monitoring of diffraction and if your peaks are in
> the same place, the intensities and widths can vary all over the place
> and we say it is the same form. And, that is already an approved
> process. Vice versa, of course, if shape is the issue.
>
> DR. HUSSAIN: We didn\'t talk about Steve\'s case study, if you want to
> do that, but what I would appreciate since this is the last meeting
> and this is the opportunity to really sort of give us in a nutshell
> what the key salient features are that you want to see in the guidance
> and sort of give us a summary of what the committee feels needs to be
> done, that would be really helpful as we sort of encapsulate the
> thought process and make sure we capture that.
>
> DR. LAYLOFF: We have an e-mail address for PAT, don\'t we?
>
> DR. HUSSAIN: We do. We also have a docket. The e-mail address is
> simple, PAT@CDER.FDA.gov.
>
> DR. LAYLOFF: So, anyone, if they think about something later on, can
> send it on in. When will the guidance be appearing?
>
> \[Laughter\]
>
> Sorry I said that.
>
> DR. HUSSAIN: What we actually did was we drafted something and we
> actually put it on hold because our thought process had not
> crystallized at that point, and I think the conceptual framework has
> come together now. We are not thinking of this being an extensive
> guidance. This is a general guidance, maybe five, six pages at the
> most. So, what we will do after this meeting is regroup and rethink
> and sort of start working towards that. I cannot promise a date for
> the guidance. Unfortunately, I cannot do that but we will do our best
> to get it out as soon as possible.
>
> DR. LAYLOFF: I agree, the committee\'s views have matured and we are
> seeing some repetition on it. I think Joe\'s comments that the product
> was approved; it is not a hazard to health out there and it is
> consistent; and if it had a pimple on it when it was approved, that
> pimple is still there even if you find it now.
>
> MR. FAMULARE: I think you just wrote the whole guidance.
>
> DR. RITCHIE: Gary Ritchie again, Purdue PhRMA. Ajaz, one of the
> questions I have in general with regard to the guidance is about this
> schizophrenia that kind of exists. Some of the leaders in the industry
> and the companies are providing a lot of data, a lot of material and
> how we should be proceeding on this. On the other side of the coin are
> companies that have investigated the use of it but don\'t quite know
> how to proceed and are waiting for the FDA to provide the guidance.
>
> Then the question comes up, well, you know, who goes first? Do we
> provide data and then see what you think about it? Or, do you provide
> the guidance and the internal argument that you get is, well, there is
> no business incentive for us to proceed unless the regulators provide
> us a reason to do so. How do you think that is going to resolve, or is
> there any reason, do you think, that anything in the guidance should
> appear to help resolve that problem?
>
> DR. HUSSAIN: I think the BMS team will lead the way! No, I think from
> a regulatory perspective what our goal was, and we are trying to reach
> that goal very quickly, is to make sure the perceptions that we are
> the hurdle are removed very quickly and effectively. So, when the
> blame comes down, we are not to be blamed.
>
> No, on the serious side, it is simply that in a sense we cannot be
> innovative. That is not our role. Innovation is your responsibility. I
> think, as has been pointed out many times, this is an innovative
> industry when it comes to new products. When it comes to manufacturing
> it does not innovate, and that was a concern and that is what we are
> trying to do. I think the innovation will come. I think people around
> this table from industry are the leaders and we are very fortunate to
> attract them. These are the leaders. If they do it, the rest will
> follow.
>
> DR. LAYLOFF: The last comment is going to be from Mel.
>
> DR. KOCH: I just wanted to inject something here that kind of fills in
> some of the comments during the day and also maybe builds on some of
> the stuff that David was talking about. We are finding, not only the
> pharmaceutical industry but other industries, that there is far more
> interest nowadays in performance measurement and developing
> technologies that measure that performance than there has been in the
> traditional analytical profile. The analytical profile still has its
> characterization value but in terms of product-related things these
> inferential measurements and other product performance things are
> becoming more and more important.
>
> As with the acoustical example, there are a number of technologies
> that are jumping out that are indicative of those final product
> predictions. So, we are going to find newer technologies coming in and
> we are also going to find that many of the technologies that we are
> introducing, like the acoustics, we are finding more and more that it
> is wave phenomena and the interferences or the different things that
> make up the acoustical signal are very similar, I think, to what is
> happening in the light scattering. We are just talking about photons
> or the sound waves.
>
> So, we see things coming back at us in terms of how do we interpret
> those signals, and then we get back into this morning\'s discussion in
> terms of the amount of data that is being generated. Then, one other
> thing that is going to jump right on top of both of these is that the
> sensors and measurement techniques are going to become smart. They are
> going to start to do remote transmission. They are going to start to
> do self-diagnostics. That goes back to some of the probes we talked
> about before because it is one thing to see a variation in the size
> that could be either the reagent that is being added to cause it, or
> it is a failing of the probe. So, you are going to have different data
> entering into the mix and there is going to be need for clarification.
> Although it is possible to store all the data today, I wouldn\'t
> necessarily step away from the issue and say so long as we can store
> it all today, let\'s keep it all because it is going to overwhelm you
> at some point.
>
> DR. LAYLOFF: Thank you very much. We are going to adjourn now until
> 3:45. It is 3:34 so you have an 11-minute break.
>
> \[Brief recess\]
>
> DR. LAYLOFF: We should have some breakout session summaries. Who is
> going to give a summary on this?
>
> DR. HUSSAIN: Mike is.
>
> DR. LAYLOFF: We have a summary from the rapid micro group.
>
> **Rapid Microbiology Testing Summary**
>
> DR. KORCZYNSKI: I think the consensus probably is that the industry
> perception is that the greatest force to implementation of rapid
> microbiology methods is acceptance by the regulators and the
> complexities and uncertainties associated with validation of these
> methodologies.
>
> Now, we think there must be, and I spoke briefly at the PAT in April
> so I am repeating myself in certain cases but, for sure, there must be
> an impetus behind this. The FDA, and we feel the USP, must be
> advocates of these new technologies and also many of the companies. It
> takes a bold and risk-taking company to approach the FDA and say I
> have this new method and basically I want to review it and implement
> it.
>
> Another thing to keep in mind, if you look at in-process both chemical
> and micro testing between conventional classical products and
> biotech-derived products, it is more likely that your in-process
> assays will increase six- to eight-fold for the biotech-derived
> products. So, as we look out there and start manufacturing more
> biologically-derived products, it is going to make sense to move
> forward in rapid methods at the end-process stages.
>
> Again, there are two categories of rapid methods. This would make more
> sense if we had time to show slides, but we have qualitative methods,
> are the microbes present or are they absent? That is, for example,
> sterility testing. And, the quantitative methods provides the most
> likely number of microorganisms present, and that could be widely used
> in the microbial limit tests that I just described.
>
> Then, there are three basic areas of microbial determinations. So, you
> could have qualitative testing for the presence or absence. You could
> have quantitative testing for microbial enumeration and then, three,
> microbial identification.
>
> So, I would say that, by far, microbial identification probably has
> the most rapid method systems out there and quantitative testing for
> microbes probably has the least detection systems.
>
> Now, what would you say would be the ideal attributes of a rapid
> quantitative test for microbial count? It should be able to process
> variable sample volumes. It should detect more microbes than plate
> counting. It should detect low numbers, and we are seeing
> methodologies that will detect one cell, one or two cells. We are down
> in that level. Detect non-culturable cells. There is a discussion
> sometimes that current culture media doesn\'t detect everything that
> is present, and maybe some of these new methods, where you basically
> filter and then through laser scanning look at the surface of the
> filter, you might be able to discern a wider number of microorganisms.
> The system should be portable. Definitely, data should be corroborated
> by or compared to a conventional or compendial method. I will get into
> that when we talk about validation. I would rather use the word
> comparability testing. Of course, I think there ought to be a
> reasonable return on the capital equipment investment.
>
> Again, I said the use of a qualitative rapid test to replace the
> compendial sterility test is a contentious issue at this time. I do
> sit on a USP microbiology committee and I know that this issue is
> going to be discussed and I can already see among colleagues varying
> opinions, pros and cons, at this time to permit some alternative
> method to the classical sterility testing method, but we won\'t get
> involved in that at the moment.
>
> But the only thing I can say is that, you know, we know statistically,
> at least microbiologists know and they have heard this many times,
> that there are certainly limitations in the current test. In the
> current test, based on the sample size you take, one could have a five
> percent contamination rate and you would only detect it 64 percent of
> the time. Now, certainly a rapid method that could detect the presence
> of one cell or less is an improvement over that methodology.
>
> Then, the gentleman from Smith Glaxo\--
>
> \[Laughter\]
>
> I can\'t keep up. All I know is that about six, seven years ago I read
> a book by a USP think-tank group on vision 20/20 and they talked about
> the consolidated number of pharmaceutical companies by 1210, and I
> will tell you, that was a futuristic book!
>
> Cultural and organizational constraints\--convincing executive
> technical management and regulatory management that this is a good
> thing to do, and they are not going to see it as a good thing to do
> unless they have a feeling that there is a vote of confidence in some
> manner from the regulators regarding the technology.
>
> There may be some increased resources initially to develop and
> implement. Right now it is unclear relative to what the regulatory
> attitudes toward acceptance might be but, certainly, I have heard very
> encouraging words at this meeting regarding the ability to go in and
> talk to a division about your methodologies, and hearing more of that
> is going to bolster the confidence in industry.
>
> There will only be a partial benefit\--I said that before, if the
> chemical methods of measurement are implemented and not the microbial.
>
> Now, a problem that we all have, if one works for a pharmaceutical
> company, is sometimes the interpretation by the field inspector versus
> perhaps a more scientific interpretation by the reviewers in
> Rockville. I think it is going to be very important, and I hope it
> emanates from our group, that we can develop a guidance for field
> inspectors. There is a series of questions that one could ask
> regarding the new method and the conventional method and, you know,
> the comparability of the methods to give that field inspector some
> confidence that data is in place. I would hope that we could develop a
> guideline such as that and share it with industry so industry, in
> advance, could make sure that they have the so-called punch list or
> check list satisfied and they have done some of these technical things
> that they should do for implementing the method.
>
> There are questions and I won\'t go through them all but some thoughts
> are will the firm adjust their action levels as a result of this new
> technology? Because these new technologies in many cases are going to
> be a little bit problematic for some people because they are going to
> give you a better data yield than the conventional methods.
>
> What is the firm\'s justification for maintaining or adjusting the
> action level? Of course, very key, which would be part of the
> so-called validation, does the new method generate data equal to or
> better than the conventional method or compendial method?
>
> I would say that the interpretation of the compendium, USP EP and JP
> is that they have been slow or non-existent relative to information
> concerning these conventional methods. At least at the USP level, that
> is starting to change. We heard from Jeanne Moldenhauer. Dr.
> Moldenhauer talked about the different validation documents that are
> out there and USP has a draft, 1223 validation of alternative
> microbial methods.
>
> Now, one thing that that document, the draft, in our discussion
> initially included were many of the attributes that you would look at
> if you were looking at equipment per se or a chemical method\--you
> know, robustness, precision, a number of things that to a
> microbiologist are sort of words and don\'t carry so much of a
> meaning. You know, what is the end result?
>
> So, some of us microbiologists believe what we need is comparability
> testing. If I had a lab running a test I would want to know does this
> new method give me a data yield as good as or better than the
> conventional method, and run enough replicates under enough conditions
> that I can see, indeed, that that is the fact. So, we are modifying
> the USP draft to talk about that testing. I think when you hear words
> of \"equivalent\" I think that is misused. What it means is, is the
> new method giving you data that is equal to, and it is silent on the
> part that it could give you data better than, and that is what you
> need to know.
>
> I would think that we need\--and we talked about this briefly at the
> meeting\--a vehicle for seeking perhaps approval of these methods. So,
> I would hope that we could develop a scenario. One of the FDA
> delegates indicated that his division would be open and receptive to
> having people coming in and reviewing the methodology. That is good.
> If a company had the data they felt confident enough to go in, they
> could review it. They we receive some confidence from the FDA that the
> method looked good. Maybe the next step is to write a stimuli article
> to the USP. At least that would force attention, you know, provide
> information for one of the expert groups to review and consider that
> methodology. So, I think somewhere along the line we should provide a
> guideline for basically acceptance of a specific new method.
>
> I know that this is sort of the old apple pie statement but we think
> that the technical transfer of valid rapid methods to the
> pharmaceutical industry will result in the use of consistent and
> accurate assay methods that will expedite corrective action. That is
> important. Reduce manufacturing time; increase productivity; and
> reduce expenses. And, we hope that that can be passed along in some
> manner to the consumer. Thank you.
>
> DR. LAYLOFF: Any questions for Mike?
>
> DR. CHIU: I would like to make a comment about adoption of the new
> microbiological methods by USP. We do not need to implement any
> methodologies if it is not in the USP \[sic\]. So, if anything is new
> and is properly validated, then we would be able to permit the firms
> to use the methodologies, the new ones, before USP has adopted them.
>
> DR. LAYLOFF: Any other comments for Mike?
>
> DR. HUSSAIN: In terms of the draft guidance, at least my thoughts are
> that we include a paragraph on rapid microbiology methods and how they
> may be different from the chemical methods, and how they should be
> handled differently, especially in the context of safe harbor which
> would be sort of I think different for micro than chemical methods.
> Could you share some thoughts on what you would like to see in the
> draft guidance, if anything, in terms of promoting adoption of these
> methodologies?
>
> DR. KORCZYNSKI: You mentioned the safe harbor concept. Do you want a
> little elaboration on that?
>
> DR. HUSSAIN: In terms of chemical methodologies or PAT methodologies,
> what we are saying is if, for example, you start looking at these for
> an existing product and you find variability which is not visible or
> not apparent with the current methodologies, you would still consider
> it research data and sort of work toward that. I think Dr. Kibbe
> mentioned that we don\'t want to call that a problem because this is
> fit for intended use. So, I think in a chemical sense I have an
> understanding of how to handle that. In microbiological sense, I was
> hoping to get some feedback.
>
> DR. KORCZYNSKI: Well, I would say if something is going to develop
> that would be part of the PAT system, first of all, relative to
> microbiology I would like to end this confusion over just perhaps
> rapid methods being used for sterility testing. So, somewhere in the
> document we have to delineate quantitative testing, qualitative
> testing and maybe, as a separate category, qualitative for sterility
> testing, and also list\--I know we may not be able to use commercial
> names, but at least the technology that could be applicable under each
> of those and even maybe the sensitivity levels.
>
> Within that document one thing that is going to be disconcerting to
> people is that they might find higher numbers than their
> specifications currently include and one has to deal with that. As a
> group, we are going to have to talk through that. I think most of the
> scientific individuals would feel science is true data, real data and
> you have to in some manner address and deal with that if the numbers
> are higher.
>
> Now, just because you have higher numbers doesn\'t necessarily mean
> that it impacts the product negatively. All of that would have to be
> considered. So, I see that document sort of undertaking that scenario.
>
> I would certainly like to see, because people are asking this
> question, how do we validate? How do we gain acceptance of a method?
> Some guidance, you know, even a suggestion that they go into an FDA
> division and review it if they wish. They may not get a positive or
> negative answer but they would generally know technically whether it
> is sound from that viewpoint, and then maybe giving them some
> encouraging advice to take it through the USP.
>
> Then, I think it is important to document, contained in one of the
> last elements I talked about, guidance to the field inspectors because
> that is where it is going to get tacky.
>
> DR. HUSSAIN: I think sort of in the PAT world, the chemical physical
> world we have sort of moved to the PAT concept, and I think we have
> some thoughts on adopting something similar. We haven\'t sort of taken
> the next step to building that concept in the micro world and I think
> we will start moving in that direction. I have actually talked to PDA
> in terms of training with rapid micro methods and for the PAT
> chemistry world we have already identified a training program. For
> rapid micro, PDA has expressed an interest in sort of working with us
> to put together a training program also. So, we will in some ways have
> a parallel process to that although we are starting late on that.
>
> DR. LAYLOFF: I think one of the problems is going to be that the
> microbial counts are going to be higher, consistently higher, and the
> question is does that pose a pathogenic risk. I don\'t know how you
> fish that out of there. But I think these issues have been aired by
> Mike and I think people should go home and contemplate them now and
> send e-mails in to PAT@CDER.FDA.gov. I have asked Ken to give some
> closing remarks. Sorry?
>
> MR. FAMULARE: I think with the application of the rapid micro to PAT
> is going to be very important that the field be part of that process,
> as they are now, because a lot of that is actually going to take place
> on site and the investigators will have to be trained. I don\'t think
> we can start with the assumption that they are automatically going to
> look at it and look at it in a negative light. Just as we have, you
> know, addressed it through PAT and the safe harbor concept,
> investigators will have to be on board and the person that we send out
> in the field organization has to be versed and trained as to what the
> consequences are of this type of methodology.
>
> DR. LAYLOFF: Thank you. Ken?
>
> **PAT Summary**
>
> DR. MORRIS: I have put together, hopefully, a little summary of what
> we have done today, but sort of in the light of what we have done over
> the three meetings.
>
> If you look at the genesis of this, you have the FDA initiative which
> is the attempt to continue to improve quality and help healthcare get
> cheaper, which would be nice, without in any way influencing its
> quality, and the industrial recognition by the scientists and the
> industrial community at large of the need for these techniques and the
> business cases that all have to be made. So, we are charged with
> helping to formulate enough of a consensus to be able to put it into a
> guidance that would be a guidance for industry in a general sense on
> PAT.
>
> In that light, one of the things that came out of this was the
> proposal from the agency for training. In this sense, we were just
> talking about training of teams of investigators and reviewers in
> order to make sure that the consensus, the learning and the general
> knowledge that exists on the committee is transmitted faithfully to
> the field as well as the reviewers.
>
> So, if we just look at some specific topics that we have summarized
> today, the research exemption or safe harbor\--I have started calling
> it research exemption but I think it will forever have the moniker of
> safe harbor\--is the idea that you are not to be penalized for
> processes or products that are under compendial approval already, and
> the compendial tests always have the ultimate say when there is an
> issue. Particularly this is important when we are developing these
> tools.
>
> I think one of the things that has come out of these meetings is that
> certainly I have got a better appreciation for the idea that by the
> time you have enough data to actually use your chemometrics, you may
> be a lot further down the line. As we heard earlier today, this means
> that you have to be able to facilitate changes in software without
> building a new plant every time this occurs. Which means that there
> has to be an awareness within the internal regulatory groups, more or
> less along the BMS model, so that they understand what the limits are
> and what the liabilities are so that they don\'t over-regulate
> themselves.
>
> We also talked today about the data storage and retention issues. I am
> not sure that there was a clear consensus on that. I thought we had it
> pretty well defined but Mel just gave us this caveat to be careful
> because in the future you could have more data than you can store. I
> think that is a well-advised caveat.
>
> The alternate side of that is that we all feel I think that one of the
> highest and best uses of the data that you can generate and that you
> can archive and mine is for looking at trends that you might not have
> identified from the outset. This is sort of the source of the dilemma.
> But, certainly, the predicate testing is the ultimate winner in cases
> of a tie.
>
> The other issue that has come up, and David talked about this earlier,
> and this actually was raised at the first or second meeting, is the
> idea that we are not looking at univariate signatures here or
> univariate variables. We are looking at signatures of the whole
> system. This, while creating some additional challenges with respect
> to analysis, is a much richer way of understanding processes as well
> as controlling them. I think we have heard that in the spirit of the
> guidance and perhaps in a letter this will be acknowledged.
>
> The other similar point that Art raised was sort of a warts and hair
> approach, that is, if there are variances that you observe in your
> data, given the research exemption and the fact that there are
> compendial tests on which to release it, we should embrace these
> variances as other methods of getting to the information that we
> really would like to have in order to control the processes.
> Certainly, with the chemometrics there is the opportunity to mine
> those signatures to get at the root causes for the changes, as we saw
> in the BMS presentation with the addition of their precipitant.
>
> What underlies all of this, and I think was actually the first comment
> that was made at the first meeting, is that in the development stage
> or at least at some point the PCCPs, process critical control points,
> have to be identified as well as how you are going to monitor those
> PCCPs. I guess the strength or the whole process rises or falls based
> on whether or not you have accurately identified those critical
> process control points. The example that we saw today, where the PCCP
> was actually identified by looking at the final product, or in this
> case the crystallized size distribution as the measure, becomes a
> redundant test, yet, may in itself offer opportunities for control.
>
> Another topic that we hit this morning a lot and we talked about in
> the breakouts before, that I think is a summary of what has come out
> of the three meetings, is this clarification of the Part 11 issues. I
> think clearly the consensus was that we should draw on existing
> guidances for Part 11. I think that is well-founded and well-accepted
> criteria. But we still have to couch this in terms of the research
> exemption, and we still have to team with the internal regulatory
> groups within the companies in order to get them to accept this so we
> don\'t reinvent this wheel or force our vendors to rewrite their
> software every time we make minor changes.
>
> The vendor certification and the vendor involvement is another issue
> that was raised, and it has come up several times. They have to be
> aware enough of what is going to be required not only by Part 11 but
> by general knowledge about IQ and OQ for their instruments. I can\'t
> remember who but somebody said probably in a few years time this is
> going to be a routine activity for vendors anyway, but in the
> transition period this can be an issue that adds a lot of resource and
> when you are trying to make the business case, which ultimately all of
> this rises or falls on, you have to include that.
>
> I think we got a tacit commitment from FDA for involvement on a case
> by case basis with respect to advice during resolution of questions
> that come up during implementation of PAT. Is that a fair statement,
> Ajaz?
>
> DR. HUSSAIN: I am not sure I understand.
>
> DR. MORRIS: Well, the question came up. I think Eva raised the
> question. If she has a question that comes up during the course of
> looking at a process, can she call and ask for advice\--
>
> \[Laughter\]
>
> Am I mistaken? Was I sleeping then or something? All of this
> culminates, hopefully, in a guidance which will be out sometime. We
> have\--what?\--at least a month, I would say to send additional
> comments. Just to recap though, the guidance should be, or is intended
> to be a concept-based guidance in a very general sense but should, I
> think, for everybody represent what is clearly a good faith effect on
> the part of both industry and the agency to further the use of PAT and
> the implementation of PAT.
>
> That is basically what I have. Did I miss something, Art?
>
> DR. LAYLOFF: Any questions or comments?
>
> DR. KIBBE: I really felt like the three meetings we had on this were
> really productive. First, I would like to compliment the three-letter
> companies, GSK and BMS, for all of their input. It shows, to me, that
> clearly there are real and perceived barriers to implementing PAT at
> various companies. When it happens, it is one of the old 90-10 rules.
> That means that 90 percent of the progress is made by ten percent of
> the people. The company needs an internal champion or it will go
> nowhere and I encourage all of you here who represent your company to
> put on the cloak of championship and move it forward.
>
> I would suggest that we have agreed that science should predominate
> over tradition; that we are recognizing that we are using either
> fingerprints or signatures in a lot of different technology and we
> should be able to change the way we evaluate the endpoints for those
> technologies and match those technologies. We have done it before when
> we went from gravinometric to chromatographic analysis; we can do it
> again. It really shouldn\'t be a terrible barrier to us moving
> forward.
>
> I love the opportunity here to replace statistically unreliable
> end-stage testing with robust process control technology. I think that
> we should think that would be a boon during the next century for our
> industry.
>
> I believe that the guidance should include within it an ombudsman at
> the FDA, someone in the field office who would take the responsibility
> of being an interface with the companies, that would accept the
> responsibility in helping them feel comfortable about the next time an
> inspector shows up because they have gone somewhere where they
> haven\'t gone before.
>
> I think that the manufacturing subcommittee, as it looks at the new
> cGMP, is going to have to reflect in those new cGMP guidelines the PAT
> efforts that we put together, including of course the rapid micro, and
> include in it on some process engineers on its committee, something
> that we don\'t use often enough and what we need to have.
>
> I think field inspectors, and I can\'t emphasize enough, over all the
> years that I have been involved with the agency, either running around
> irritating them during a generic thing or afterwards, how important it
> is to cross-train between internal review staff and external
> inspectors so when the people write guidances the inspectors know what
> they have written about and what they intend, and when inspectors see
> things that the internal reviewers know what they have seen and can
> understand where that issue is so that they are not at cross purposes.
>
> There are those that are concerned that if they go directly to the
> FDA, within the FDA they will have a reputation and if they have what
> they think might be tough questions to get asked\--let me offer
> myself, as a tenured full professor who can\'t be fired, that I would
> be happy to ask any really hard question. All right? Now, whether I
> will get the answer you want or not, I will be happy to do that. If
> you will just e-mail me the hard question to Kibbe@wilkes.edu, then we
> will formulate it into a question and try to get a decent answer.
> Okay?
>
> DR. MORRIS: If you have questions for me, you can e-mail Art too.
>
> \[Laughter\]
>
> DR. LAYLOFF: Any other questions or comments? Okay, Ajaz?
>
> DR. HUSSAIN: I think one other concept that the microbiology group
> proposed, and I think we probably could also think about that from
> chemical and physical, was the comparability. So, as we sort of think
> of validation of the new method compared to the old, comparability
> might be better terminology there. Any thoughts on that?
>
> DR. LAYLOFF: That is the terminology used in biotech a lot for process
> changes, comparability criteria. For complex systems that is not an
> unusual statement.
>
> DR. RUDD: If I can just add to that, we have certainly thought about
> the implications of blindly applying ICH method validation guidelines
> to process measurement methods. I think the conclusion we have come to
> is that while you can do that, you are certainly making not exactly a
> square peg for the round hole but the match is not as good as you
> would like it to be. So, I think the compromise ought to be, yes, the
> comparability idea is a very good one but I wouldn\'t want to lose the
> essence of the micro assay philosophy as far as method validation is
> concerned. That whole set of guidelines are based around good science
> and that is the principle we need to use. So, however you do it,
> however you dress it up, we need to keep that principle I think.
>
> DR. LAYLOFF: I agree. I agree with that. That is a good concept. I
> think the problem, of course, with ICH is that it is wrapped around
> HPLC but the scientific concepts are good.
>
> DR. HUSSAIN: Two other sort of comments. One of the thought processes
> was, from a software validation perspective, I think the CDRH
> off-the-shelf software validation, as well as other software
> validation guidances that are out there plus GAMP-4, I think we have
> to work with ISBE and see how we can use that.
>
> In addition, with respect to validation, Rick Cooley sent me some
> information. I think the ASTM standards on validation for petroleum
> on-line measurement, I think we can learn a lot from some of those.
>
> So, our thoughts are that with this guidance we are not going to
> reinvent the wheel but essentially highlight some of the aspects which
> have already been established and how they may apply to
> pharmaceuticals and sort of build on to some of the existing
> principles rather than reinvent the wheel. So, that is what we also
> plan to do. I believe there was consensus that that is a good thing to
> do. So.
>
> DR. LAYLOFF: Ajaz, would you like to make some concluding remarks?
>
> DR. HUSSAIN: Yes, I will and I think I would like to give Doug a
> chance to say a few words too.
>
> DR. ELLSWORTH: I guess having been to several of these subcommittee
> meetings and I guess being one of the field representatives, I have
> heard a number of concerns about investigators and how they will apply
> standards with this new technology.
>
> One thing I would say is that our investigators are charged with
> enforcing and applying public standards. I think it is obvious that
> they can do a better job the more precise we are in terms of what
> those public standards are, which is one of the reasons I think\--a
> multitude of reasons, but one of the reasons why we are undertaking
> guidance develop. But I think we all recognize that some of this
> technology we are going to begin to learn as we begin to see it and
> begin to apply it. So, both CDER and ORA have agreed and set up a
> specific team that will be especially trained and be able to initially
> focus on some of these new PAT technologies so we will have consistent
> application of the standards.
>
> DR. HUSSAIN: I prepared my closing remarks before the meeting\--
>
> \[Laughter\]
>
> I do want to emphasize and I do want to thank the PAT team. I just
> want to remind us\--I don\'t think we have ever had a chance to work
> with Doug and Joe. I think they are working closely and the team
> concept is really working so I really thank them for their
> cooperation. Just to remind everybody on the PAT team, we won that
> game. So.
>
> Let me sort of summarize. At the end of the second meeting I had to
> sort of come back and sort of hammer it in that the quality of
> products today is good because the sense I received is that everybody
> was expressing concern on the quality. Keep in mind, with the current
> state what we are saying is that product quality is not in issue. In
> fact, I had sort of alluded to that at the end of the second meeting.
> Based to the small number of recalls due to product quality, we are
> probably already close to six sigma level from a quality perspective,
> although six sigma from a patient perspective\--that is what I want to
> emphasize. From a patient perspective the quality is at six sigma. But
> how do we get to that? I think the processes are not efficient. Our
> processes are at a very low sigma level, and if I look at what the GMP
> requires, I think GMP requires the minimum standard less than 2 six
> sigma based on 10 percent failure rate or rejection rate.
>
> So, I think what PAT is all about is improving further the efficiency
> of the system. The process quality, on the other hand, ranges from
> poor to good, and we have one size that fits all system. I have a
> difficult time distinguishing bet poor and good, and poor process
> quality can have a catastrophic effect on the reputation and economic
> health of a company, and I have seen that more so in the last decade
> than ever before. Poor process quality can lead to drug shortages, and
> so forth. So, there is a public health reason. There is a business
> reason and there is a scientific reason for the PAT concept.
>
> It is the right time to focus on process quality because you don\'t
> have to be reactive. That is what is different here, we are not in a
> reactive mode; we are in a proactive mode. And, high level process
> quality is desirable from both public health and business perspective.
> Reducing risk of releasing poor quality product is definitely a public
> health objective.
>
> Keep in mind that, in a sense, as we get to more complex drugs, more
> complex products the current system I think can be stretched to its
> limit and we really need to understand our processes better. I think
> we ought to take that as a blessing, that we are not in a reactive
> mode. By improving the processes, we are not only reducing regulatory
> risk and cost, and this is where I think the six sigma concept also
> comes in. The risk-based approach idea has adopted the classical
> definition of quality in modern thinking. There are essentially two
> levels. Level one is meeting the specifications. Level two is customer
> satisfaction. With six sigma, if you think of FDA as a surrogate
> customer, because we are essentially responsible for pharmaceuticals
> we are not able to judge the quality in the clinical setting and it is
> too late to judge the quality. So, FDA essentially becomes a surrogate
> customer and the risk-based approach allows us to move in that
> direction. Reducing regulatory risk or concern gives you benefits.
>
> Reduced time to market, I really think this will have an impact on
> time to market although I think people have a hard time seeing that
> right now, but it will happen. But it will reduce stress and
> frustration because we are spending so much time, we are spinning our
> wheels trying to get the product out with deviations, exceptions, long
> cycle times, QC, and so forth. I think we need to improve our quality
> of life, on both the FDA and industry side, and today we can be
> proactive.
>
> The road ahead is not simple. The road ahead is not easy, but if it
> was easy then somebody would have done it. Let\'s put it that way.
> Keep in mind, most pharmaceuticals are complex, multivariate physical
> chemical systems. We have to rely on iterative empirical development
> approach, guided by experience. In some meetings\--I am a pharmacist
> by training\--it is hard for me to sort of go to some meetings where
> this is black art, and people have said that to me to my face. I say,
> wait a minute. But in reality it is empirical. I think we have the
> time and the opportunity to take it away from empiricism to science
> based.
>
> I actually look at the Handbook of Pharmacy and Handbook of Chemical
> Engineering and that is the ground I want to cover. I think Dr.
> Lachman\'s book on theory and practice of industrial pharmacy is where
> I learned industrial pharmacy. I think that is the trend in the sense
> that you can see, in his book, that you go from art to
> science\--practice to theory. I think that is what we are trying to do
> here and get to that in a more effective way.
>
> There are challenges here. We have subjective measurements of material
> functionality. One of my first projects was computer-related
> formulation design and when you start to develop an expert system you
> have to think of lactose, how do you define lactose for a formulation
> system because we don\'t have measures of functionality. That is
> difficult. That inhibits learning because it is subjective. There are
> many variables and long waiting periods for lab data to do this. What
> we have learned from MIT data is that with on-line, and Ken Morris\'
> publication, is that we can actually do kinetics of complex processes
> and gather information in a fraction of a second so we learn more.
>
> There has been no regulatory incentive for formulation process and
> optimization. Validation is a minimum standard. Now we can think of an
> optimization which is not a requirement but an opportunity, and all
> the regulatory incentives are coming together I think like never
> before.
>
> So, those are sort of my closing thoughts. I want to reflect back on
> 16 or 18 months of this effort and I want to thank Steve Hammond for
> being brave enough to come to our FDA science board. G.K. is not here
> but I think that was a starting point for some of the discussion. You
> can see what has happened at FDA.
>
> I got this from a book. I forgot to reference it, and I also got it
> from a presentation by Lee Pecan. I am not sure who the author is, but
> these are not my words, author unknown: Why transforming efforts fail?
> Not establishing a great enough sense of urgency. I think we have done
> that with PAT at a time when we didn\'t have a reason to do that. FDA
> tends to be reactive but we try to be proactive and, yet, I think we
> have created a sense of urgency for this.
>
> Not creating a powerful enough guiding coalition. I think more and
> more PAT\--I don\'t have to go and speak about PAT; you guys are doing
> that. Everybody is doing that now. Lacking a vision, I think we have
> created a shared vision for the future for this. Under-communicating
> the vision by a factor of ten. I have to look at Helen, she is going
> to stop me any moment. But I think we have communicated a factor of
> 100.
>
> Not removing obstacles for the new vision. I think we have removed, at
> least from an FDA perspective, all the obstacles we could find and we
> are working as a team. Not systematically planning for and creating
> short-term events. I think we have the short-term events coming with
> the general guidance and other steps, and so forth. Declaring victory
> too soon. In a sense, we are not going to declare a victory at all
> here; this is an ongoing process. Not anchoring changes in the
> corporation\'s culture. Just imagine, we have an FDA-wide initiative
> on cGMP. How much more could you ask for? This is at the highest level
> of the agency.
>
> So, I think from an FDA perspective we have looked at these efforts
> that are challenging and have addressed them in many ways, and I think
> you will be doing the same thing in your corporations too.
>
> Thank you, and I really think these three meetings have been very
> valuable and I cannot thank you enough. We will sort of miss the PAT
> meetings. I got addicted to those already. So. But many of you will
> sort of join us on the manufacturing subcommittee and I think we will
> continue the process. So, your involvement will continue although the
> PAT meetings will not. We have other fora to sort of do the
> communication and we will do that.
>
> Just to alert you, we have three workshops planned. There is Arden
> House U.S., Arden House U.K. and IFPAC. These are all upcoming
> meetings and I hope to see some of you or all of you there, especially
> the Arden House and IFPAC in the U.S. So, thank you again.
>
> DR. LAYLOFF: Thank you, Ajaz. This is our sunset meeting, the PAT
> committee is going to sunset after three sessions. I think it has been
> an extraordinary effort. What has come forth I think is a coming
> together of academics, industry and FDA in an open dialogue to try and
> deal with these issues.
>
> I think the only time you really get something successful to happen
> you have to have a champion, and the champion for all this has been
> Ajaz. He has done a fantastic job of going out and looking at the
> GMPs, looking at Part 11, looking at the training, and always open to
> doing new things. So, I think the whole PAT is Ajaz\' shadow and I
> would like to give him a hand and then we will adjourn. We will stand
> with the hand.
>
> \[Applause\]
>
> \[Whereupon at 4:35 p.m. the proceedings were adjourned.\]
>
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