WELCOME AND OUTLINE OF SCOPE, PURPOSE AND OBJECTIVES OF WORKSHOP

Dr. Stephen Sundlof
Food and Drug Administration
Director, Center for
Veterinary Medicine

INTRODUCTIONS

Dr. Andrew Beaulieu
Food and Drug Administration
Deputy Director, Center for
Veterinary Medicine 

WHAT IS RISK ASSESSMENT, RISK MANAGEMENT AND RISK COMMUNICATION

Wesley Long, Ph.D.
FDA
Associate Scientific Director, JIFSAN

USE OF RISK ASSESSMENT IN REGULATORY DECISION-MAKING

Lester Crawford, D.V.M., Ph.D.
Georgetown University
Director, Center for Food & Nutrition Policy

THE IMPORTANCE OF RISK COMMUNICATION IN THE DEVELOPMENT OF SCIENCE-BASED REGULATORY REQUIREMENTS

Douglas Powell, Ph.D.
University of Guelph
Department of Plant Agriculture

ANTIBIOTIC BREAKPOINTS: METHODS FOR DETERMINING AND USE BY MEDICAL COMMUNITY

Dr. Al Sheldon
Food and Drug Administration
Center for Drug Evaluation Research

ANTIBIOTIC BREAKPOINTS: METHODS FOR DETERMINING AND USE BY VETERINARY MEDICAL COMMUNITY

Dr. Tom Shryock
Elanco Animal Health

EPIDEMIOLOGY OF CAMPYLOBACTER IN HUMANS

Kirk Smith, D.V.M., Ph.D.
Minnesota Department of Health

EPIDEMIOLOGY OF CAMPYLOBACTER IN ANIMALS

Dr. Paula J. Fedorka-Cray
United States Department of Agriculture
Animal Research Service

PRESENTATION OF CVM RISK ASSESSMENT

Dr. David Vose
Risk Consultancy

MATHEMATICAL VALIDITY OF CVM RISK ASSESSMENT

Dr. Tony Cox
Cox Associates

CHALLENGES IN ASSESSING AND REGULATING THE RISK OF ANTIMICROBIAL USE

Dr. Stephen Sundlof
Food and Drug Administration
Center for Veterinary Medicine

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SESSION 1: USE OF RISK ASSESSMENT TO EVALUATE HUMAN HEALTH IMPACT OF RESISTANT PATHOGENS

Chair: Wesley Long, Ph.D.

USING RISK ASSESSMENT TO EVALUATE THE HUMAN HEALTH IMPACT OF RESISTANT PATHOGENS
Dr. Scott McEwen
University of Guelph
Ontario Veterinary College

GEORGETOWN RISK ASSESSMENT
Dr. Steve Anderson
United States Department of Agriculture
FSIS-AAAS

EMEA RISK ASSESSMENT
Dr. Louise Kelly
Veterinary Laboratories Agency
Department of Risk Research

CVM RISK ASSESSMENT: ASSUMPTIONS AND UNCERTAINTIES
Dr. Kathy Hollinger and Mary Bartholomew
Food and Drug Administration
Center for Veterinary Medicine

PANEL DISCUSSION ON CVM RA MODEL
Wesley Long, Ph.D.
CFSAN

Dr. Paula J. Fedorka-Cray
United States Department of Agriculture
ARS

Dr. Scott McEwen
University of Guelph
Office of Veterinary College

Dr. Louise Kelly
Veterinary Laboratories Agency
Department of Risk Research

Dr. Steve Anderson
United States Department of Agriculture
AAAS

Dr. Randy Singer
University of Illinois, Champagne-Urbana
Department of Epidemiology

Dr. Mark Lipsitch
Harvard School of Public Health

David M. Bell, M.D.
National Center for Infectious Diseases
Center for Disease Control

QUESTIONS/COMMENTS FOR PANEL

PUBLIC COMMENT PERIOD

Keynote: - - - indicates inaudible in transcript.

DR. SUNDLOF: My name is Steve Sundlof and I am the Director of FDA's Center for Veterinary Medicine. And it is my pleasure to be able to host this meeting. Before we get started, just a little bit of background as to where this meeting fits into the grand scheme of things.

Back in January of 1999, we held a Veterinary Medicine Advisory Committee. And at that committee, we discussed a document which we referred to as the Framework Document -- I think there are copies out on the table of that document -- which basically described the Agency's best thinking at that time as to what might be a rational approach to regulating antimicrobials as it pertains to the human food safety aspects of antimicrobial resistance.

And at that meeting, we said that there would be additional workshops to discuss specific issues, specific parts of that framework. And this is one of those meetings. And since the meeting in January, we have put in a great deal of effort, listened to a lot of what people had to say, read through many, many comments and tried to respond accordingly.

So today is the continuation of that process. And, as you might guess, it will not be the end. There will be additional meetings that will be held. I would like to start off with just a few philosophical points. And these are my own philosophical statements, but to try and set the tone for the meeting for the next two days.

(Laughter.)

We don't have to worry about OSHA I am sure.

(Laughter.)

FDA as an agency is a science-based, public health, regulatory agency. It has all those three things. It is science-based. It is decisions. And it is regulations. By law, I have to be based in science. It is a public health agency and a consumer protection agency. And it is also a regulatory agency. We do have the authority to take regulatory actions to support the decisions that we make.

I want to talk about the science part of it. It is very important to FDA and I think to society at large that our policies and our regulations are supported by the body of science as it is known at the time and at the same time, recognizing that there will always be uncertainties in that body of science.

The scientific method is by design contentious -- well, it is a messy process. It involves intense debate, critical scrutiny of underlying assumptions, experimental designs and interpretations of results. At times, it can become contentious and acrimonious. And for many people, it can become an uncomfortable event. But that is part of the scientific process. And in many cases, it is only through that emotionally charged process that science advances.

It is therefore important that we allow that process to play out and that we resist the temptation to cut off the debate prematurely. I am hopeful in the next two days that we will contribute positively to that debate. And that is my sincere hope for this meeting.

To help set the tone for the next two days, I would like to make a proposition with all of you. We at FDA will make a concerted effort to listen to you if you can all agree to listen to each other.

That doesn't mean that we shouldn't challenge one another to support his or her positions during the discourse. But it does mean that comments of a personal nature are off limits. And accordingly, that comments not be taken personally by those to whom they are directed. And I will try and set an example by intervening where appropriate.

But I think it is up to everyone to hold each other responsible for maintaining a high standard of conduct during the meeting. So that is a little bit of the philosophy. Now I will talk more about the meeting and I will try and set up what we hope to accomplish in the next two days.

(Slide.)

The objective of the meeting is to consider the merits of the risk assessment. We did do a risk assessment. It should be out on the front table. We apologize in advance for the short time that it has been available to the public. It has been available the same amount of time to us.

But we want to discuss the merits of the risk assessment as a potential model for evaluating the risk to human health from resistant food-borne pathogens associated with the use of antimicrobials in food animals. The risk assessment itself is very specific. It deals with one specific aspect of resistance. And we will discuss that considerably.

But what we really want to know, the real purpose of introducing the risk assessment is to ask the question is this a good approach; is this risk assessment applicable to dealing with the entire whole issue of antimicrobial resistance; where does it fit in. So those are the kind of issues that we would really like to get your opinions on. Not so much the specifics of that particular risk assessment, but how it might fit into a greater regulatory scheme.

And then what kind of criteria should CVM consider in evaluating the risk of certain pathogens; how do we define such things as an acceptable level of risk, as harm; what do we define as harm; what do we define as the population that we are considering protecting. These are questions that will come up during the course of this discussion.

(Slide.)

We started out a little more than a year ago. It was on November 18th. And we issued a guidance document in the Federal Register. And it said that -- it basically said that emerging scientific evidence indicates the therapeutic use of antimicrobials in food animals in addition to sub-therapeutic food uses may select for resistant bacteria of concern to human health.

It also said that the FDA believes that it is necessary to consider that potential harm, human health impact of microbial effects associated with all uses of antimicrobial drugs. So that is -- that started this process.

(Slide.)

That was followed last December, almost one year ago to the day, with a framework document that most people I think are familiar with. And that framework document said that it was an attempt for FDA, as I indicated earlier, to provide its thoughts on what might be a rational approach to dealing with the issue of antimicrobial resistance from a regulatory perspective.

And it says that FDA's position is that the regulatory system for antimicrobials for use in food animals should be modified to address the issue of microbial safety. And it should look at the importance of drugs. The framework document takes a risk-based approach in that it looks at the risk as it relates to the importance of the particular antimicrobial drug or class of antimicrobial drugs for human -- the importance in human medicine.

And it also talked about such things as setting acceptable levels of risk thresholds and those kinds of things that would be important from a regulatory standpoint.

(Slide.)

A number of comments were received. And I think one of the comments that we heard time and time again was that we, the FDA, before we take any regulatory action should conduct a risk assessment to determine exactly what the harm is from exposure to the public to resistant microbes.

And so we listened to that and we contracted with an expert in risk assessment. And you will hear from him later, Dr. David Vose. And he helped develop the model that you -- that we published last week. So CVM's risk assessment was really -- it was a pilot project. We weren't sure at the time when we entered into it if we would actually be able to pull it off. But I think we have.

We learned a tremendous amount just by going through the process. And we wanted to -- the risk assessment does model the risk associated with fluoroquinolone-resistant Campylobacter originating from chickens. That is the subject of that particular risk assessment. And we want to know if that model that we propose today in some form might be used as a model for looking at the whole entire issue of antimicrobial resistance.

(Slide.)

Some people had asked, well, why did we pick this particular microorganism and drug in chickens in this case as the model. Well, there were a number of reasons why we chose this particular combination of fluoroquinolones, chickens and Campylobacter. First of all, chickens are a reservoir of Campylobacter and Campylobacter is one of the most common of the food-borne diseases and Campylobacter -- excuse me -- Campylobacter do have the ability to develop resistance quickly to fluoroquinolones.

And fluoroquinolones are often used empirically in the treatment of patients that have food-borne disease. And probably as important as all of those other contributing factors is that we actually were able to obtain data, real data that we could use to model the risk.

So for all of those reasons, that is why Campylobacter was chosen as the first one. It is probably one of the simplest of the -- of all the food-borne diseases that we can model. And so that is why we chose that one.

(Slide.)

Let's talk a little bit about the agenda for the meeting. For this morning, we will have a general description of risk assessment tools, a discussion of the epidemiology of Campylobacter, and presentation of the risk assessment, the risk assessment that we published. This afternoon, we are going to talk about the use of risk assessment by various other agencies, looking at the issue of food safety or water safety.

The second part, we will have a discussion of the epidemiology of Campylobacter -- oops, not -- we will have a panel discussion looking at risk assessment. And we will adjourn at 5:30 sharp. That is what time our transcriber has indicated that she needs to leave. So we will try and, again, adjourn at 5:30 sharp. There is going to be a small reception that will occur at some other time, somewhere between 5:30 and 6:00 as I understand.

Okay, Friday. On Friday, we will meet again in the morning. Session 2 will look at the overview of the assessment of risk by U.S. regulatory agencies. In the afternoon, we will have a panel discussion on how based on all of the things that we have heard to that point, looking at what other agencies are doing, etcetera, how should CVM evaluate the risks; how should CVM look at antimicrobial resistance within the context of the other regulatory agencies.

And we are going to on both days seek public comments. We want a lot of public comments. Finally, we will end the session by talking a little bit about what the next steps are about how we might go about with the process of setting regulatory thresholds for resistance.

(Slide.)

Okay. In addition, because we are not going to be able to get everything decided here at this meeting, we think this meeting will provide a lot of food for thought and the people will want to go back home and reflect on what has occurred, read the risk assessment a little bit more carefully, look at the Framework Document, all of these things, and then provide comments on their own personal thoughts about what should be done.

And the comments can be sent to this docket. And we will provide a full transcript of this meeting. It will probably be put up on our home page sometime following the meeting so that everybody has the opportunity to determine -- to know what actually transpired at this meeting. We really do need a lot of public input on this.

(Slide.)

Before I turn the podium over to Dr. Beaulieu to introduce the first panel, I would like to take this opportunity to recognize some of the people in CVM who went way, way beyond the call of duty to bring us to this point where we could hold this meeting.

First and foremost, I would like to recognize Dr. Sharon Thompson, Associate Director for Veterinary Medical and International Affairs at the Center for Veterinary Medicine. Sharon is one of those exceptionally rare individuals that I can charge with an impossible assignment and know with complete confidence that she will accomplish it on time, under budget, and exceeding all expectations.

I would also like to recognize Kathy Hollinger. Kathy is a veterinarian and an epidemiologist par excellence. During the course of developing the risk assessment, we were told repeatedly by the experts that what we were trying to do was impossible because the data needed to support the model simply didn't exist. And Kathy proved all the experts wrong.

Through self-motivation and shear tenacity, she was able to obtain data that were thought to be unobtainable. And I believe the term that we use for that today is data-mining. And she is the best miner that we've got. So I want to recognize her.

Mary Bartholomew -- I put "Dr." up there, but it is pretty close to the truth now. Mary is our statistician who expended a great deal of effort in assisting our risk assessment consultant, David Vose, to develop the mathematical and statistical elements of the model. So we really want to recognize her.

Marsha Larkins is CVM's ombudsman. But in addition to her regulatory duties, she was responsible for coordinating CVM's response to the enumerable comments on the Framework Document. And, again, that should be available out on the table.

Alita Sindelar is the newest member of the CVM team. She assumed the responsibility for planning three public meetings on antimicrobial resistance including the one that you are attending here today. And this is how it worked, this is how the CVM management works. CVM management decided that to get to the point that we are today, we needed to respond to all the comments from the -- on the Framework Document, develop a risk assessment, and then through some miracle hold a public meeting before the millennium.

Marsha Larkins got the framework comments assignment. Sharon, Kathy and Mary got the risk assessment assignment. And Alita got the miracle assignment. And she has performed outstandingly.

Finally, I would like to recognize Ms. Linda Kawatch for her help in putting this meeting together. All the myriad of minute details that go into putting a meeting like this together are something that most of us never consider, but are so terribly important. And what Linda has done in the past few weeks alone is the kind of work that is usually done by whole staffs and other organizations. So we really wanted to make sure and recognize those people.

(Slide.)

I want to recognize a number of organizations that contributed to this. And we absolutely could not be where we are had we not had a tremendous amount of assistance from these various organizations: Centers for Disease Control and Preventions, especially the National Center for Infectious Diseases is a critical partner in our being able to not only obtain a lot of the data that went into the risk assessment, but also NARMS could not exist, absolutely could not exist without CDC's input. So an absolutely critical player.

A similar critical player is USDA's Agricultural Research Service who are -- whose laboratory is helping us in actually doing the antimicrobial resistance monitoring for the animal specimen. NARMS couldn't exist without ARS either.

Food Safety Inspection Service of the USDA has been wonderful in providing us with access to the animal isolates from the HACCP programs from the slaughter houses so that we can conduct the NARMS system. Economic Research Service, the Census Bureau, the National Chicken Council and the University of Pennsylvania all provided valuable information that went into the risk assessment.

(Slide.)

And finally, I would like to recognize the American Veterinary Medical Association for -- under the heading of risk management for their outstanding commitment to develop and promote judicious use of therapeutic antimicrobial drugs in veterinary medicine. They have supported it with their dollars. They have supported it with their resources and efforts and convening people. And I didn't want to get -- let the opportunity get away to express how important CVM thinks that committee is.

And with that, I am going to turn the meeting over to the Deputy Center Director for Veterinary Medicine, Dr. Andy Beaulieu.

DR. BEAULIEU: Thank you. Steve. Good morning, all. I am Dr. Andrew Beaulieu, recently appointed Deputy Director of the Center for Veterinary Medicine. I want all of you to know that up until July 19th of this year, all of this hair used to be brown. And a large part of the reason for the change is the issue we are here to discuss at this workshop.

In fact, this change may be one more potential effect of antimicrobial resistance that we may want to investigate in the future. Actually, it is not true about the hair, but it feels like it should be.

This is -- I have to say that this is the most complex scientific and regulatory issue that I have encountered in my 27 years in CVM. There are no simple solutions to this problem. It will take all of us working together to devise a regulatory system that appropriately protects both human and animal health.

As part of that process, I welcome you all to what I hope will be a very constructive discussion of what may become an important component of such a regulatory system, quantitative risk assessment. And on that note, I have the pleasant task of introducing our speakers this morning starting with Dr. Wes Long.

Wes Long began his government career in 1991 in the Center for Food Safety and Applied Nutrition's Office of Pre-market Approval. Wes' current position is at the FDA -- is as the FDA Associate Scientific Director for the Joint Institute for Food Safety and Applied Nutrition, typically known as JIFSAN, with primary responsibilities for coordinating the development of collaborative programs between the University of Maryland and the FDA in the area of risk analysis.

In addition, he chairs the Interagency Risk Assessment Consortium composed of 18 federal agencies with food safety risk analysis responsibilities. And Dr. Long will speak to us this morning regarding the question what is risk assessment, risk management and risk communication. Wes.

As Wes is making his way up, I would ask our speakers -- Wes and the rest of our speakers to try to allow a couple of minutes for questions at the end of their presentation. I will facilitate that process by allowing a couple of minutes on the timer for that purpose.

DR. LONG: I want to thank the Center for Veterinary Medicine, Steve and Andy and Sharon for inviting me to give you a little bit of a primer on risk assessment, risk management and risk communication. I think it is to CVM's credit that they thought it was worth their time in a very busy agenda for today to allow a little bit of time to make sure we all have a common basis and understanding for this area of risk assessment and how it fits into risk analysis.

(Slide.)

I think that -- well, I know that there is potential for a great deal of confusion when you start to talk about risk assessment. I spent the last three days at the Society for Risk Analysis Annual Conference in Atlanta. And these are 2,500 risk analysis professionals. And even they can't agree on what is the difference between risk assessment and risk management. So you are not alone if you have trouble with this, these different concepts and sorting them out.

You are going to have a lot of information coming at you over the next two days, a lot of science, a lot of sort of hard core science. You are going to have some risk assessment modeling that you may find difficult to understand. There will be discussions of legal statute. There will be opinions. There will be discussions of standards.

And I think it is important that as CVM is actually here to learn what you think, that it is useful to provide you with the tools to effectively communicate with CVM your opinions and your needs and your perspectives.

(Slide.)

So we are going to start off with a little test. I hope everybody got a good night sleep. No, not really. If we just look at the title of the meeting, Workshop on Risk Assessment and Establishment of Thresholds, actually right here in the title, some of you may know and maybe most of you know that actually risk assessment is risk assessment. Establishment of thresholds is risk management.

So already -- now, risk assessment, of course, is a tool for the risk management aspect of establishing thresholds.

(Slide.)

Let me explain. First of all, I will show this slide. And if a Power Point slide could get tattered, this would be my tattered slide. Risk analysis actually is composed of three components that are interrelated: risk management, risk communication and risk assessment.

(Slide.)

All right. Well, what is risk assessment? One way to describe what risk assessment is is that it is a tool to predict the likelihood of the occurrence of an adverse event.

(Slide.)

Now, if this is a little bit too complicated and we want to back up a step, then we can think of risk assessment as looking at what can go wrong, how likely hazard is likely to occur and what are the consequences if it does happen.

(Slide.)

Again, while risk assessment is a tool to predict the occurrence -- the likelihood of occurrence of an adverse event, it is also a science-based technique for organizing our information and separating what we know from what we don't know, and then taking this information and presenting it to our risk managers as well as to fellow risk assessors and fellow scientists for their critique and analysis.

So this presentation of relevant scientific facts needs to be structured to clearly tell what we know, what are the data sources we used, what information did we rely on. It needs to characterize how well we know what we say i it is that we are knowing. And it needs to be transparent to reveal any biases that the risk assessor might have and also to really pull out the simplifying assumptions because it is often necessary with data gaps to make simplifications and assumptions that may affect the analysis.

(Slide.)

All right. Well, but that is not enough. Risk assessment really has to try its darnedest to answer the question. Whose question? It is the risk manager's question. And without a good communication between the risk assessor and the risk manager, then the risk assessment can end up coming up with something that really does not address the needs of the risk manager to make the decision that the risk manager needs to make. What happened here?

(Slide.)

Okay. So what are the questions that this risk assessment is trying to answer, like Dr. Sundlof said? What is the extent of the risk to human health from resistant food-borne pathogens associated with the use of antimicrobials in food-producing animals? That was the question put to the risk assessors.

(Slide.)

What questions does this risk assessment not answer or not attempt to answer? It is not going to tell you what the level of risk that expresses a quantitative definition of acceptable risk is.

(Slide.)

And if that is too much gobblety-goop, it is not going to tell you what the appropriate level of public health protection is.

(Slide.)

The risk manager -- those are all considerations for risk management. And there are a number of considerations that risk managers have to consider when they go to make a decision. And certainly the science is critical as Dr. Sundlof noted. FDA is a science-based organization and we try our darnedest to base our decisions on the science.

(Slide.)

But there are other factors, as well. There are public values. There is an expectation from the public about the safety of the food supply and the degree of protection that is necessary. And there is a relationship between those expectations and the perceptions of the public of where we stand at this point in assuring that sort of safety. Public values also include stakeholders from producers, farmers, manufacturers, as well.

(Slide.)

There are economic factors that have to be considered. And if there is a result in rule-making down the road, that rule-making will include an economic assessment that will look at the costs and benefits of any alternatives, as well as looking at the competing benefits of different technologies and the cost of those technologies, as well.

(Slide.)

Statute, I think you will hear more today about how statute describes FDA's authority to act, but it also places some limitations on what those actions can be that FDA can take.

(Slide.)

And finally, there are always going to be political factors. And here when I say political factors, I am not talking about Congress putting the thumb screws on Dr. Sundlof based on his decision. But rather about the political priorities and how this fits into the broader range of concerns of the Center and the Agency and the needs of the Congress and White House.

(Slide.)

Okay. Briefly I am going to mention risk communication. I have already mentioned the risk communication between risk managers and risk assessors. This is in framing the question and monitoring. While you try to maintain a functional separation between the risk assessors and the risk managers, they have to communicate with each other.

(Slide.)

There is communication between the risk assessors and the scientific community. And I hope that we are going to hear some of that communication today as this greater scientific community evaluates the risk assessors' use of the available science.

(Slide.)

There is communication between the risk managers and the stakeholders. And all of you here today are stakeholders in one way or another.

(Slide.)

And finally, and sort of in a separate category is the risk managers communicating their decision, the final outcome of this meeting and the rest of the meetings when FDA does get to the rule-making stage. How do we get the message out?

(Slide.)

Okay. So to summarize, risk analysis is composed of three components: risk assessment, risk management and risk communication. Risk assessment is the technical work. Risk management is the decision-making. And risk communication is the way we get risk management and risk assessment to work together in conjunction with stakeholders.

(Slide.)

Okay. So what is CVM hoping to get from this workshop? I think in terms of your input today, we are spending most of our time critiquing the assessment, understanding risk assessment principals. And so the questions are is the risk assessment understandable, does it have utility, is it a fair presentation of the available data and information.

And speaking as a risk assessor, risk assessors always want to make their risk assessments better. And one of the best ways that they can make those assessments better is to have more and better data. So certainly if you are knowledgeable about data that is available that wasn't utilized that perhaps should be utilized, I am sure the risk assessors in the audience would be thrilled to have that information.

(Slide.)

Okay. So today -- I say tomorrow on the slide. But today and tomorrow, the risk managers are going to be listening. They want to know what you think about the risk assessment. As they evaluate the assessment, they want to know your evaluation of the assessment, as well, to incorporate it into their decision-making process.

And they are also going to be looking for your opinions on risk standards and the role on how this risk assessment fits into developing and setting those standards and thresholds. So I hope you all can use this information a little bit to help direct your questions and your comments today. Thank you.

DR. BEAULIEU: Any questions for Wes?

(Applause.)

DR. BEAULIEU: Sorry. My question was premature. Any questions for Wes? Thank you, Dr. Long. Our next speaker this morning will be Dr. Lester Crawford. Les has a D.V.M. and a Ph.D. from some places down south. He is currently the Director of the Center for Food and Nutrition Policy at Georgetown University.

In former lives, he was an administrator of FSIS/USDA and an Executive Vice President of the National Food Processors Association. And he was an Associate Dean at the University of Georgia and also something I am having -- oh, yes, he was former Director of the Center for Veterinary Medicine.

(Laughter.)

Les is going to talk to us this morning about the use of risk assessment in regulatory decision-making.

DR. CRAWFORD: Thank you very much. Congratulations to Steve and to Andy on the risk assessment and also on this meeting and thanks for asking me. I, among all of you here, probably are the only one that remembers when your hair did turn white, Dr. Beaulieu.

(Laughter.)

And it was one of the most astonishing moments of my life. I was sitting there being grilled by the Honorable Ted Weiss. And I was trying not to look at him because that was an unspeakable thing to have to do. So I was turning my head away. And I could see the friendly face of old Andy Beaulieu in stark terror.

(Laughter.)

And then Weiss invoked the name of Andy Beaulieu. And I turned and looked at Andy. And all of a sudden, his hair had gone from deep brown-black to white in one fell moment.

(Laughter.)

Risk assessment, the use of risk assessment in regulatory decision-making is what I am charged to discuss this morning. And I would like to begin by talking a little bit about the transition between toxicological risk assessment and microbial risk assessment and then finish by the recent adaptation by U.S. Government and also WHO to microbial risk assessment as a tool in the evaluation of antibiotic resistance and how that fits into the regulatory climate and calculus worldwide.

The first real use that we made when I was in the government of risk assessment happened in a curious way because we had showed the courage to ban DES, diethylstilbestrol, in the year 1979 when I was Senate Director. And if you think this will turn your hair white, Steve, you should have seen those days.

We were not -- we had the courage to ban it. But the cattlemen of the United States did not have the courage to stop using it. So we faced a Constitutional crisis. And one fine day, FDA/CVM had to take possession of 500,000 steer throughout the United States.

And we had people like the Under Secretary for Food Safety at USDA calling for their euthanasia. And the only way we got out of that was to do a risk assessment which showed that the cattle could be held for 63 days, their ears surgically excised or amputated depending on the situation. And we had that done to half a million head. And it was based on a risk assessment. And I suppose that is probably the first time I had ever heard of risk assessment.

And then following that, the risk assessor, who was Joe Rodericks, now is one of the principals in Environ, contracted with the National Academy of Sciences to do a series of three meetings similar to this and similar to what WHO did to develop toxicological risk assessment using the DES risk assessment as a model.

Some of you, like me, may have attended and participated in those meetings. But when we came out of there, we had both routinized risk assessment and we also had made it available as a regulatory tool and as a legal tool which we needed the latter most desperately at that time.

It remained for us to decide what the level of risk was. And so the Commissioner of FDA, Dr. Hayes at the time, ordered what he considered the four risk managers in the area locked up at the Xerox Center in Leesburg, Virginia to decide on a level of risk for a number of exercises and for FDA in general.

Those were Mark Novich who was Associate Commissioner for Medicine -- Medical Affairs, Sandy Miller, me and Tom Scarlett who was the General Counsel. And the issue was to decide whether or not we would have one in 100,000 risks, one in a million or one in a billion. And it was not possible given our dim understanding of risk assessment to decide which was best. And, of course, we were prone to use the political route.

And about 11:00 p.m. on the last night that we were to be freed the next day to go back to our jobs, we all had a different figure except for Tom Scarlett who as a lawyer was wise enough not to give his opinion. But he was finally forced into it and he did it in a way that I shall never forget. And I suppose this is the reason we have the risk assessment and risk figure that we have.

He said, "Well, I haven't said anything now in about six hours. So it is time for me to say something." And he said, "I was just sitting here thinking. We are still struggling between one in a million, one in a billion and one in 100,000." He said, "I think one in a billion is just out of the question." And he said, "I have never heard, I don't think it would be popular to use one in 100,000 because thinking about it, I have never heard a young man say to his sweetheart, 'My darling, you are one in 100,000." So we voted then for one in a million. And we went home.

(Laughter.)

Following those exercises, the next thing that happened of note was the World Health Organization under the leadership of Fritz Kafferstein who has now become something of an American put on a series of four meetings starting in 1995 and finishing in last spring, 1999, to define risk assessment for microbial concerns.

And these four reports, including the last one, are now available. And some of the same people who were out at Leesburg chaired those meetings. And I think they will be used now throughout the world, certainly in the countries that belong to the World Health Organization which is virtually all.

And many countries, particularly in this last one that I was involved in, made major investments in time and in funding in order to make sure that they had this tool done by this international organization. So the time of risk assessment as a regulatory tool is certain here.

Now, I like risk assessment. And I think that I would live a lot longer had I had it and had it been routinized and been the subject of some rigger when I first started out in my regulatory career. I think it takes the politics out of food safety to some extent. And I will give you some examples of that.

You recall in the European Union-U.S. dispute over hormones, when this came before the World Trade Organization three years ago and the ruling came down, the EU pleaded not to have to yield to the finding of the WTO which, of course, found in favor of the United States and specifically in favor of FDA/CVM. The EU appealed not to have to do that until they could do a risk assessment.

And they assumed it would take 15 months to the day to do the risk assessment. And they proceeded then to hire some risk assessors for the first time, and also were painfully at a loss to explain the fact that they had never done a risk assessment before on this subject which meant that they didn't know whether they were safe or not safe because they had never thought about it.

But the power of that as a political and regulatory and public health tool was I think forever enshrined in the world as a result of that. If a risk assessment was so important to the decision process in something that is probably one of the major regulatory disputes of all time historically, if that was the case, then we have risk assessment as a tool that is enshrined then forever.

And then a little later, they decided to evaluate feed-additive antibiotics. And in the pressure of the moment in having forgotten their commitment to risk assessment, they took action against several antibiotics without benefit of clergy or of a risk assessment.

I think probably they will now have to go back at some point in history and do that. So the lesson to me is clear. And also, the concept of the risk manager.

I have been involved since the WHO meeting last spring in a number of seminars and meeting with various governments -- we are doing this with Brazil next month -- and trying to the ministers -- never have I met one that was qualified in regulatory affairs or in medicine or science -- explain to them that the role of risk manager is what they really are and what is a risk manager and how do you react and what is risk assessment, and isn't it great that you are the risk manager for this country and you are going to have more fun with less trauma than you ever thought you would because of that.

And it is working. It is working around the world. And it links in a fundamentally important way and mathematically even the risk assessors with the risk managers. And the public is all the enriched buy because it is a transparent affair. It is not something that sneaks up on them.

And it really is what the world is demanding, for example, in the battle in Seattle on biotechnology. That is really what they want. And I am not sure they would be willing to live up to the outcome. But that is what they want.

And the other thing I would say is that risk assessment is becoming the international language of food safety. Food safety, you are either going to have a risk assessment mentality and a risk assessment that is enshrined in government or you are going to have a situation where you have a learned oligarchy making decisions for the people.

And I have been somewhat part of that and I thought it was great. But the public doesn't think that's too great. And the first time I ever heard how hateful it was was when we were trying to sell the general agreement on tariffs and trades in the sanitary and phyto-sanitary amendments to that.

I appeared around a lot of different places telling them how great this was going to be. And I had that unhappy assignment. And what people would say, "Well, what CODACS really is a bunch of little gnomes meeting in Rome and in Geneva every two years. And they decide all these horrible things for the world. We don't want any more of that. It is not transparent."

And up until that time, I had always thought transparent applied to a window pane. But I knew then what it meant and I knew that risk assessment was probably the way we would get out of that. And we actually wound up having to pledge to go in that direction.

In the United States, as all of you know, there is pending in Congress a bill called the Regulatory Improvement Act of 1999 which would make risk assessment law and would require it for all regulations that have to do with public health and virtually any other thing. Whether or not the bill passes this year is academic.

It was introduced last year. I think it will continue. And I think it will eventually pass. And it would require the Office of Management and Budget not to lick their fore finger and hold it up to the wind, but to actually evaluate what these regulations are going to do for the public, or do to them. And I think that is great.

And then the next thing is we had a meeting at Georgetown last month. And the World Trade Organization representative talked about the fact that they are now incorporating the requirement for risk assessment in all of the issues and disputes that they take on. And that is now a matter of legality with them.

And he modeled -- he said he modeled their amendments after the Regulatory Improvement Act of 1999. So it is passed worldwide and it is still pending in the U.S. like some other things have throughout history.

So -- and then, of course, CODACS has further more enshrined it. The EU has. And I think we are seeing history being made. And I would mention several models that I think are -- in closing, Dr. Beaulieu -- that I think are going to define this for us.

The Georgetown model that Steve Anderson will present a little later on we had a great deal of fun with. And we also learned. Some of the lessons we learned were difficult. But we are now ready to do them and we are starting another one which Steve will also mention.

The FDA model which I got the same time all the rest of you did certainly plows new ground. It is a document of historical significance. The model in Canada by Anna Lamberding. There was work done in the United States by Bob Buchanon and others which we will hear some more about today.

It is just actually like a textbook to me. I think if you want to learn about how you use it in regulatory decision-making, you need to get that first and foremost. And then the Listeria monocytogenes, which is being broadly trashed around the world even as we speak, but nonetheless will be a good risk assessment model and I think will probably plow even better and newer ground than the SE model did.

So we now have -- we have had the philosophy. We developed the science thanks to WHO. And now we have what is needed in order to make this a discipline and a very strong discipline in regulatory decision-making. And that is some actual models to look at, teach from and learn from.

So with that, Dr. Beaulieu, I will conclude my remarks. Thank you.

(Applause.)

DR. BEAULIEU: Maybe time for one quick question for Les if there is one. Okay. Thank you, Les. Our next speaker is Dr. Doug Powell. Dr. Powell has a Ph.D. in food science from the University of Guelph. He is currently an Assistant Professor in the Department of Plant Agriculture at that university.

He is co-author of a text -- or maybe not a text, but a book on Mad Cows and Mother's Milk which is a series of case studies involving risk assessment, management and risk communication. And he is here today to talk to us about the importance of risk communication in the development of science-based regulatory requirements. Dr. Powell.

DR. POWELL: Always fun going after Lester. AV person? There we go. It keeps moving. There we go. Okay. I am going to make my comments brief and talk about the role of risk communication. You are going to hear a lot about risk assessment over the next two days. And Lester certainly gave a good overview.

I want you to keep in mind though the risk assessment works best when your expectations are not too high. And the reason why is other industries have gone through this where if we can just get the science better, we will have a resolution to these difficult public policy questions. And they are disappointed.

(Slide.)

This is the model. I know FDA uses this in some of their other regulatory areas. It is from a 1997 Presidential Commission on Risk Management. And basically what it says is -- you know, in the past, it was assessment and then management and then communication, a very linear separation.

This is more than just circles. It is not just because it is the '90s and we are all holistic and draw circles. It actually is a very powerful model that says to integrate all three of those things. And what it really says is you need really good science, but you also need really good communications. And the reason why is because there is so much uncertainty in a risk assessment that you can't just rely on the numbers.

(Slide.)

For consumers, they often view these things as stigma or stigmata. And the risk assessment isn't actually that important. Consumers might not know all the details of bovine spongeiform encephalopathy and new variant Creutzfeld-Jacob disease. But if I say British beef, there is generally a yuck factor. That is a stigmata. That is a short-cut that consumers use.

And for a regulatory agency, they have to be aware of that and keep that in mind. And the characteristics apply quite nicely to the use of antimicrobials in animal agriculture. There is a hazard. There is a potential for risk, a standard of what is right and natural. You know, why are we doing this is somehow violated or overturned. Impacts are perceived inequitably. Lots of scientific uncertainty. This is normal for any risk scenario.

The bottom line is the management and the hazard is brought into question. And that is critically important and that is why you have meetings like this, is so that you have a clear and transparent management of hazard.

For example, think of the dioxin in Belgium crisis that happened earlier this year. We just reviewed about 300 stories. I mean, it gripped Europe for a couple of weeks. People were talking about, "Oh, my God, we can't even get food on the table." Grocery stores were empty.

And out of those 300 stories, we found one, one that talked about the actual risk to human health and safety in terms of consuming the stuff. The other 299 were all about how the hazard was managed and the fact that the Belgium government knew for six weeks and didn't bother telling anybody and directly led to their electoral defeat.

So management of the hazard is critical in terms of -- because what happens is something is stigmatized. Things go off the rails. And it is very difficult to have a meaningful discussion using all the great science of risk assessment.

(Slide.)

So we need good surveillance systems. And I would argue that you generally have that. They can be improved. Good communication. A credible, open and responsive regulatory system. That varies from agency. It varies by country. Demonstrable efforts to reduce levels of uncertainty in risk and evidence that actions match words.

(Slide.)

Surveillance, I am not going to go through this. You basically have a good system through FoodNet, PulseNet and NARMS. You are getting some of that basic data which can feed into the risk assessment that needs to be improved.

(Slide.)

Risk communication has been around for at least ten years if not more. This is the long definition from the National Research Council. The short definition is any conversation about risk which is usually with your spouse.

(Slide.)

This is the history of risk communication. And there are some powerful lessons in here as you embark on risk assessment for antimicrobials. Baruch Fishoff pulled this together a few years ago. In the early days, it was thought all we have to do is get the numbers right, make the risk assessment better. We will get better numbers. We will have answers. The nuclear industry went through this.

It doesn't work that way. It's like you are one in 100,000. People only remember the one. All we have to do is tell them the numbers. You know, if we educate the public, then clearly we will be able to understand this better and we will resolve conflict. Say what we mean by the numbers. This is risk analogies, you know.

These numbers, one in a billion or one in a million. People can't get their minds about it. So we have to use analogies like, you know, well, it is like a marble in a beach full of marbles the size of the United States or, you know, analogies like that. And that tends just to make people mad because what you are doing is trivializing concern.

Show them they have accepted similar risks in the past. Well, you know, you drove here so what are you worried about this for? How many times have you heard that one? You know, these guys have figured it out to get rid of this about 15 years ago. But we still hear it all the time.

Show them that is a good deal. Can you buy people off? Actually, you can sometimes in citing hazardous waste facilities. They always promise, you know, a lot of jobs and there is usually one part-time that ends up getting employed.

Then we went into -- in the early '90s, we went into what I call the happy talk phase of risk communication. And that is if we just treat people nice, we can get rid of conflict and come to some solution. We make them partners. And, you know, Clinton was certainly a man of the time. Remember, when he was elected originally in '92, he was the empathetic President. He was apparently a little too empathetic. He felt a little too much pain.

(Laughter.)

And now we've gone past that. Canadians export Canadians and hockey players. I am trying to uphold that standard.

(Laughter.)

And the bottom line is all of the above, we need all of that. It is not enough just to talk nice to people. You've got to have the data to make it meaningful.

(Slide.)

Now, with antimicrobials, this is generally the state of public discussion. You get stories like this. I am not going to go into it.

(Slide.)

The New York Times, oh, look, fluoroquinones and chicken. That was last -- two years ago.

(Slide.)

Certainly, there has been a dramatic increase in media coverage over the last couple of years of antimicrobials, in particular, the agricultural use of antimicrobials leading of course to a huge increase in antibacterial products out there, both for microbial food safety concerns and other concerns which do nothing but accelerate development of antimicrobial resistance. However, they are all out there.

(Slide.)

FDA has entered into the fray. It has gotten a lot of public coverage since last January on a proposal to manage antimicrobial resistance. And I think there is good recognition that these things are not direct anymore, that there are environmental impacts and that really we aren't talking about the environment.

It is not just a matter of plants are over here and animals are over here and humans are here. There is -- while there are different arenas, there certainly is a lot of cross-fertilization. And I mean that literally with manure.

(Slide.)

One of the solutions then in the absence, while the risk assessments are going on, while you are improving your science, it is important also to demonstrate the management of that risk. And we have judicious use principles or prudent use guidelines. I think the Americans are on the judicious use. And a lot of the species have these things.

But what is important then is, you know, it is not just a matter of talking nice to people. You have to have data where people are actually doing it, evidence that actions match words. So in order to do that, I am going to talk about tomatoes.

And you may be wondering what's that got to do with it. Well, actually a lot of antibiotics are used on field tomatoes to control bacterial diseases. And this is another one of the environmental loads. And I think there is a growing recognition of that.

(Slide.)

When you work with producer groups in order to implement these things, and we do this sort of stuff, we always find it useful to go out and survey them. You know, people always talk about surveying consumers to get their perceptions. We are also interested in perceptions of producers because if they are actually going to implement something to reduce and manage risk, they've got to own it.

And we've done this three times now with three different groups. And we asked people the same question we ask consumers which is an unprompted what is the greatest threat in the food supply today. And the producers always say imports. And it doesn't matter what country we ask, they all say imports.

And this is expected from a risk perception viewpoint because individuals are impervious to risk. In the United States, you know, there are surveys done every year: Is drugs a big problem for society? Absolutely. Is drugs a problem in your family? Uh-uh. Well, where is it all coming from then? Well, it is out there. It is someone else. So you need a mind-set change to demonstrate that it is their problem and they have to own it.

(Slide.)

And this is a greenhouse tomato facility which is not important. What is important is this sort of stuff. You can develop judicious use guidelines and produce manuals. And we all have the QA programs which feed into those. But manuals aren't enough because you don't have any evidence anyone has actually read it, let alone done anything about it.

(Slide.)

As this cartoon says, it has, "Our annual ISO 9000 audit is next week. We can pass the audit if we put all of our nonconforming documents in the trunks of our cars and then torch the cars." Doesn't that defeat the purpose of a voluntary audit?

(Slide.)

But one of the things we did with this particular producer group that I think is instructive for implementing prudent use guidelines and communicating with producers and others who have responsibility to manage this risk is we can document changes. For instance, when we ask them, "What are the greatest threats to the food you eat?", in 1998, after imports it was pesticides. By 1999, just after a couple of rounds of meeting and after throwing the manual out, storage and handling and microorganisms were all of a sudden on the list.

(Slide.)

More importantly, we asked them about particular programs they had implemented. And this is for microbial hazards. And in '98, they had barely heard of it. They were talking about reduce pesticides and biological control. By one year later, we are all of a sudden able to show that the number one thing is they have improved their cleanliness. They are starting to think about keeping the place clean. What a concept. But for fresh produce, this is something that is relatively new.

Hand washing and washroom facilities, not even on the list in '98, are suddenly coming in quite high. So we are able to demonstrate that there is at least an awareness. But, you know, people can lie on surveys.

(Slide.)

So you go an additional step. And that is we have a student actually collecting data full-time on end product and on water quality and doing pathogen testing. And that is the data which supports the claims that they are making.

(Slide.)

So as you move forward on implementing, whether it is judicious use principles for initial management because Lester and his group can be doing risk assessments for the next 20 years and they will always be getting better. That is not to slag risk assessments. The alternative I think is astrology. And what Lester said is correct.

But don't put it up on a pedestal because it will get knocked down. It is a useful tool to provide incremental, yet significant improvements in understanding. There are a lot of data gaps at this point that need to be filled to improve that understanding. But we can't wait because you can be -- you can always do a better risk assessment. And that is the point.

In the meantime, you have to demonstrate that you are aware of the risk and are taking actions to reduce risk. And while you are doing that, you need good risk communication. And what we have shown is that, you know, you have a scientific perception of risk. You have a public perception of risk.

And I am not going to go through that today. But in between is the activity of good risk communication, entering into public discussions about levels of risk. And there is a very high level of awareness on this issue from both the medical side and an agricultural side.

(Slide.)

So as you enter into that, just some general lessons that we have learned from previous case studies and some even involving the Center for Veterinary Medicine around BST for example. A risk communication vacuum if allowed to develop is why things end up on the front page. It is exactly what happened in Europe over genetically engineered foods which is another fun topic.

Regulators and industry and academics and producers, everyone is responsible to communicate effectively about risk. And if you are responsible, do it early and often because you won't like the results if you wait. There is always more to a risk issue than what science says. And I think we are going to spend the rest of the meeting talking about what science says.

But just keep in the back of your mind that when you leave here, there will always be something additional that is not necessarily about science. Even though FDA does not have a legal mandate to assess that and that's proper, just in terms of communication, you have to be aware of that.

Educating the public is generally a non-starter. Most people do not want to be educated or they would all be here. Most people want to go shopping, not do homework. They want to go to their grocery store and have a level of confidence so that they can focus on handling the screaming kids, not whether this thing has some sort of problem.

And it is incumbent on the regulatory agencies to generate that level of trust and credibility, that level of confidence in consumers.

I think everyone has agreed that the no risk thing is out the door. You don't hear it very often, at least not in the United States. Risk messages should directly address the contest of opinion. And that is because there are issues that aren't to do with science, yet they are what is going to be out there. For example, Belgium, dioxin. What was it about? The management of the hazard.

We have to address those issues and communicating well because you want to say it is safe has good spin-off benefits for risk management because it may mean you have to change what you do.

(Slide.)

Finally, to use a hockey analogy since we talked about hockey, since we export all our great players here including Wayne Gretzky -- these are my four girls. I had to -- I came in late last night because I coach hockey and had to stay for that because, you know, you've got to have priorities, although Scott and I missed our regular hockey game which to Canadians is somewhat tragic. And I am not sure if I've recovered yet.

You know, the NHL is really upset because Wayne Gretzky quit. You know Wayne Gretzky, right, you Americans? I've just got to check.

(Laughter.)

I know we exported him, but, you know, maybe -- the point is Gretzky was a great player, but he also was a great communicator. Now, if you watch him -- I grew up with him. He lives around the corner, or his parents do in Branford. And if you look at him on TV, he looks pretty goofy. I mean, he is about as unsmooth as it gets, scrawny and he is not too good looking and, you know, I'm not either. Maybe it is a Branford water thing. I don't know.

But the point is he went out of his way to talk to the folks who paid the bills. And that was the fans. The guy never turned down an interview even though he looked goofy. And the reason why people believed him and listened to him is when you score 1,000 goals, that is pretty good data. So get your good data and then go out and talk about it. Thank you.

(Applause.)

DR. BEAULIEU: There may be time for one quick question if there is one?

DR. POWELL: I thought we were all going to be quiet.

(Away from microphone.)

MS. : Well, this is just a general comment. Perhaps there is some insight in the room for us it would help if the ---.

DR. POWELL: Sorry. I wish you had told me earlier. You have to get out and communicate about these things.

(Laughter.)

(Away from microphone.)

MS. : Well, it will be ---.

DR. BEAULIEU: Thank you, Doug. Our next speaker will be Dr. Al Sheldon. Dr. Sheldon has advance degrees in microbiology and genetics. He is a team leader in microbiology in the Office of Drug Evaluation IV in our Center for Drug Evaluation and Research.

He has had 27 years in drug regulatory affairs, experience in drug regulatory affairs including clinical microbiology, quality control associated with drug manufacture, manufacturing and control of both bulk and finished dosage forms.

And let's see if we can't reorganize ourselves a little. I am not quite sure what cords I am running over here. Nothing seems to have unplugged itself yet. Does that help some? Okay.

I think I failed to mention that Dr. Sheldon is going to be talking to us this morning about antibiotic breakpoints, methods for determining those and their use in the medical community.

DR. SHELDON: I will tell you that I have an autograph of Wayne Gretzky, great guy, and it is for sale.

(Laughter.)

There we go. Good morning, ladies and gentlemen, distinguished guests, colleagues from the Center for Veterinary Medicine. It is clearly a pleasure to be here today to discuss with you the establishment of interpretative criteria, i.e. breakpoints for use in human medicine.

(Slide.)

Now, before I do, I would like to discuss the regulatory process that is involved in setting up the breakpoints. The establishment of breakpoints really is a multi-step process that occurs in two different stages.

The first of these occurs during the investigational new drug stage which is the stage where the company is investigating the utility, the potential clinical utility of the drug in clinical settings. Therefore, the Agency requires that the company submit experimental preclinical data to help establish the provisional breakpoints that are going to be used in Phase 2 and Phase 3 clinical trials.

As my presentation proceeds, I will go into greater detail about the specifics regarding the requirements that need to be submitted during the investigational new drug stage.

Now, the second stage is really once the sponsor has completed all of the investigational data and they have done the analysis and they feel that the produce now can be submitted to the Agency for evaluation and approval. This is done through the new drug application stage.

In this particular instance, the Agency requires the submission of clinical data to allow evaluation of the correlation of the provisional breakpoints with the clinical outcomes that have been derived during the clinical trials.

(Slide.)

Now, this is -- this slide provides information that is very important. And it is important because it describes the methods that are used and what is required of these methods in doing these kinds of studies. We have to have confidence in the data generated during produce development. That is, it is essential that the susceptibility test method be standardized, reproducible in order to assure precise and accurate results that have been derived during the clinical trials.

It is important in doing any surveillance studies that you have accurate and reproducible methods in order to have confidence in the data that you are evaluating. Therefore, the FDA requires the use of susceptibility test methods established by standard-setting organizations. We use the methods that are established by the National Committee for Clinical Laboratory Standards.

We also determine whether a correlation exists between the MIC and dish diffusion methods that are used by sponsors. We need to understand that if an organism is considered susceptible by an MIC method, it is also considered susceptible by a dish diffusion method, i.e. for resistance.

We also establish quality control ranges. At this point, I would like to describe the fact that not only -- the FDA sets breakpoints. These breakpoints, the quality controls and a listing of this information is included in the package insert that is approved with every NDA. There is also an independent organization, the National Committee for Clinical Laboratory Standards, that also establishes breakpoints.

So we want to make sure that we are not sending mixed messages to our constituents, i.e. the users of these drug products. So the NCCLS actually has invited me to become a member of the Antibody Susceptibility Testing Committee to provide our views on the breakpoints that we have established to try to assure that we are -- that we have the same kinds of breakpoints and that we are not sending confused messages to our constituents.

(Slide.)

Now I would like to discuss the kinds of microbiological studies that are submitted during the investigational new drug stage. The preclinical information required to aid in establishment under the provisional breakpoints is as follows: We require studies on the mechanisms of action. We need to understand the physiological and the morphological effects of the drug.

And, therefore, we need characterization of the targets the drug is likely to be affecting. This includes things like DNA replication, transcription, translation, biochemical pathways because this provides us an understanding of how resistance might emerge by changes in target side.

Now, clearly we know that there are other mechanisms of resistance which are important. And I will discuss those at a later time. We need to have a clear understanding of the antimicrobial spectrum of a compound. This activity that is the spectrum helps us characterize the potential clinical utility of the antimicrobial under investigation.

The susceptibility profiles are presented usually as histograms and population distributions. And these kinds of data help us assess where the breakpoints might be considered.

Now, as I tell you about the kinds of things that need to be submitted, you must understand that it is a compilation of all of these thoughts and all of this data and all of this information that goes into making or describing what would be the most appropriate breakpoint.

(Slide.)

Now, the mechanisms of resistance also aid in the establishment of the resistant breakpoint. Resistance mechanisms can limit the effectiveness of antimicrobials in clinical settings. Thus, we require characterization of their mechanisms and their distributions within targeted clinical populations.

The relationship of the increased susceptibility of these pathogens to the pharmacokinetics and pharmacodynamic parameters of the drug are assessed to determine probable breakpoints. Cross-resistance to drugs of either the same class or different classes mediated by different kinds of resistance mechanisms must be provided, again, to provide insights on the potential utility of the drug.

(Slide.)

Animal model studies are also very important during product development. They are used to assess the potential efficacy of the drug in either prophylactic models or in therapeutic models. They are used to investigate the nature of the disease process and how the product works against the specific diseases that are investigated.

They are also used the characterize the pharmacokinetics of the antimicrobial and to make decisions about the kinds of doses that should be used in humans. They also -- the efficacy aids in characterizing relevant pharmacodynamic parameters, also. These observations, again, provide additional evidence used in setting of the breakpoints.

(Slide.)

Now, pharmacokinetics and pharmacodynamic studies have been elevated to a greater degree of science in that we must have a good understanding of the absorption, distribution and metabolism and elimination of the antimicrobial, the serum protein binding which may affect the utility of the drug, and tissue distributions.

The tissue distributions are important because they allow us to assess whether sufficient drug is present at the site in relationship to the MIC of the organism that is being treated. This information and the animal model studies help us examine the relationship between the efficacy and the pharmacokinetic and pharmacodynamic parameters. These operations, again, provide additional evidence that is used in setting the breakpoint.

(Slide.)

Now, an example of pharmacodynamic parameters that are emerging from animals and limited human clinical studies are as follows: time above the MIC for beta lactim antimicrobials, it seems to be a pharmacodynamic parameter that is important. That is, the time the drug concentration remains above the MIC should be greater than 80 percent of the dosing interval to achieve successful clinical outcome.

For fluoroquinolones, the AUC to MIC ratio is important. If this value is greater than 30 for gram positive bacteria, for example, we have a higher success rate in terms of clinical efficacy or lower mortality.

(Slide.)

In summary, it is a compilation of data derived from different, but very related different types of studies which are used to provide insights into the activity of a drug and its clinical efficacy. This information is used to set the provisional breakpoints that is used in Phase 2 and Phase 3 clinical trials.

(Slide.)

Now I would like to talk about the information that is required for the new drug application. And basically what we want to establish is a correlation between the breakpoints that have been established and the provisional breakpoints that have been established during the investigational new drug stages and their ability to predict what happened in the clinical trials during Phase 2 and Phase 3.

So we are trying to establish a correlation between MIC results and clinical outcome. And that includes both bacteriological and clinical outcome. And this has an important aspect of the evaluation process because it validates what we have set provisionally as the appropriate breakpoints.

Now, the down side of this approach is that in essence we are only validating the susceptibility breakpoint because we only allow for inclusion in the evaluation of efficacy of a product organisms that are considered susceptible by the provisional breakpoint.

We really don't validate the resistance breakpoint. We rely on resistance mechanisms that are available to try to determine where that resistance would occur.

(Slide.)

Now, what is the purpose of susceptibility testing? I will have to leave you with these thoughts. Is susceptibility testing performed to predict clinical utility and outcome or is susceptibility testing performed to monitor changing susceptibility patterns in the emergence or resistance, or is it both?

The approach that you take -- or the philosophical approach that you take can influence the breakpoint that you establish. The debate certainly will not be settled in the near future because I can remember from microbiology back in my old days that this kind of question was continuously being asked. That concludes my presentation. Are there any questions?

(Applause.)

DR. BEAULIEU: Thanks, Al. Our next speaker is Dr. Tom Shryock. Dr. Shryock has an advance degree from my alma mater, Ohio State University, which is unchallenged in its academic excellence, at least by anyone I am willing to listen to.

(Laughter.)

However, they have fallen on hard times on the football field lately and we won't go there. Dr. Shryock also has two post-docs in cystic fibrosis and pulmonary infections. He is currently the technical advisor in microbiology for Elanco Animal Health.

He has previously had experience in research and development of animal drugs at Pfizer Animal Health and he was an Assistant Professor at Indiana State University. He is also currently a chair-holder I think at -- on the NCCLS. And he is here this morning to talk to us about antibiotic breakpoints, methods for determining those and their use in the veterinary medical community.

Does anyone in the audience happen to have a laser pointer or know where there is one in the room? Thanks.

DR. SHRYOCK: Thank you very much for that kind introduction, Andy. I appreciate being up here with fellow alumni. It is my great pleasure on behalf of the NCCLS to address you today on the Veterinary Antimicrobial Susceptibility Testing Subcommittee.

(Slide.)

And since time is limited, I am going to run through this fairly quickly as far as organization. If you want to check out the website, NCCLS.org, there is much more information about the organization. It is a standards and guidelines writing organization. Microbiology is just one of several components in clinical laboratories that this organization encompasses.

The NCCLS process itself revolves around a tripartite process of participation from the professions, government and industry. And it uses a consensus process to derive the documents that it produces.

With respect to the development of the AST, or antimicrobial susceptibility test methods, I would like to point out that the current methods are adequate for testing rapid growing organisms. And the list includes Enterobacteriaceae, Staph., Strep., some miscellaneous pathogens.

What is obvious by its omission and germane for this particular meeting is Campylobacter. There are documents that are available for human pathogens as well as for veterinary pathogens. In all of these documents, there are really two components as Al had outlined. There is a lot to do with quality control and methods including standardized procedures, QC. And these deal specifically with the MIC test and the auger dish diffusion test.

(Audio missing due to technical malfunction.)

And you can see here in this example of a single dose, there is clinical cures ---

(Audio missing due to technical malfunction.)

And the red line here would be the intended breakpoint for susceptible organisms. So what we would like to do is look at time after dosing to see if, in fact, we can achieve a concentration greater than that MIC. You can see in this example here an eight microgram per ml can be achieved for susceptible.

(Slide.)

Now, when we come to the scatter gram data set, MIC is listed on the left. Zone and inhibition diameters on the top side here. At this eight or less microgram per ml level, which was indication of a clinical success, you can see there is a large cluster.

So that would be where we would draw the line and say, okay, everything eight or less is susceptible. We go up one dilution for intermediate buffer zone. And then anything above that at 32 or greater would be termed resistant.

You will note also that in this susceptible population, there is a range of MICs from eight, four, two and one and so on. There is really no way to distinguish between differences in clinical outcome of those isolates with lower MICs versus those that maybe are a little higher. They are all susceptible in the eyes of the NCCLS as far as clinical outcome.

So in this particular example, this is what you would see in the document as far as how those breakpoints would be reported.

(Slide.)

Obviously, the establishment of the interpretive criteria are not without difficulties and there is lots of debates usually revolving around the correlation of these data points. The decreased susceptibility aspects here really have not been established for any agent at this point in time.

(Slide.)

There is lots of demographic discussions, controlled clinical trials versus community and animal disease models. Those all get factored in at some point or another. As Al mentioned, there are some ethical issues of treating patients, be they animal or human, with high MICs since you would expect clinical failure to result.

(Slide.)

With regard to Campylobacter testing on the methodology issues, Bob Walker at Michigan State is heading up a working group that has members from both the AST and VAST. And the objective here is to standardize the methodology, to define appropriate quality control strains, identify test media, etcetera.

The interpretive criteria ultimately to be set for treatment of Campylobacteriosis would have to fall into that AST realm since there are no veterinary antimicrobials that have a claim against Campylobacter. This would entail a specific sponsor presentation as it would for any other antibiotic or disease-causing agent to establish those interpretative criteria. Once the methods are available, they can be applied to epidemiologic purposes.

(Slide.)

So just to sum up here and get us out to the break, let me say that the interpretive criteria then are basically set on three different parameters: the efficacy, pharmacology and scattered gram or epidemiology data. There is as yet in the eyes of the NCCLS no approved methodology available for Campylobacter testing. It is being developed at this point.

And finally, the interpretive criteria which was validated for Campylobacter will need to be set by the NCCLS AST group, as well as the FDA upon appropriate presentations of data and determinations. So that concludes the remarks that I wish to make this morning. And I will open it up for questions.

(Applause.)

DR. BEAULIEU: Any questions for Dr. Shryock?

(Away from microphone.)

MR. : Doctor, how do you know where the issue is species-specific MIC ---?

DR. SHRYOCK: The question was how do we deal with species-specific issues given the fact that there is different parameters of absorption and metabolism, etcetera. Each sponsor brings forward that specific kind of data for the pharmacology in the target animal species for which interpretive criteria are being requested. And that is what makes this a real challenge and really sets the basis for the need to do this on an animal-specific basis.

For example, when we have a particular antibiotic that is used in two different food animal species, say beef and poultry, the sponsor needs to bring forward the relevant information for each one of those species. And the break points could be different between those different species because of the pharmacologic behavior of those -- of that agent in the two different species. They are different.

DR. BEAULIEU: Any other questions? We are running a little behind this morning. We got a late start. I would beg your indulgence in getting back here within 15 minutes. If that doesn't suffice, I would remind you that a long break equals a short lunch. I will see you in 15 minutes, folks.

(Whereupon, a brief recess was taken.)

DR. BEAULIEU: Take your seats, folks, so we can get started. Hopefully folks will join us almost immediately. Our next speaker is Dr. Kirk Smith. Dr. Smith has a D.V.M. from Iowa State, Ph.D. from the University of Georgia. He is currently Supervisor of the Food-borne, Vector Borne and Zoonotic Diseases Unit of the Minnesota Department of Health.

He was formerly with the Epidemic Intelligence Service at CDC. Dr. Smith is going to speak to us today about epidemiology of Campylobacter in humans.

DR. SMITH: Thank you. And good morning. This is kind of a daunting task to cover this topic in ten minutes. So bear with me if I speed through some things.

(Slide.)

Well, Campylobacter is the most commonly recognized cause of bacterial gastroenteritis in the United States. It is estimated that there are about two million symptomatic infections per year which is a figure you will see in the risk assessment. And this corresponds to roughly one percent of the United States population.

The most commonly identified species of Campylobacter among clinical isolates from humans is C. jejuni which accounts for 95 to 99 percent of the isolates. Most of the rest are Campylobacter coli which is clinically indistinguishable. So when you talk about the epidemiology of human Campylobacter infections, we are talking primarily about C. jejuni.

(Slide.)

Campylobacter jejuni is found worldwide. As in the United States, it is very common in other industrialized countries. It is actually hyper-endemic in developing countries. And most children will experience multiple infections by the time are a few years of age. And so it is not common that Campylobacter is a commonly identified cause of traveler's diarrhea.

(Slide.)

We will get more into the clinical signs and symptoms later. But Campylobacter causes diarrhea, often with fever and cramps and often with bloody stools. The incubation period can range anywhere from one to eight days. But it is typically three to four days. It is usually a self-limited illness. But it can cause serious invasive illness, particularly in the elderly, infants and the immunocompromised.

(Slide.)

Just to mention FoodNet briefly. Some of you I am sure are familiar with it. It is a collaborative agreement between these federal agencies and certain state health departments.

(Slide.)

And these are the FoodNet sites currently that cover a population of about 20 million people.

(Slide.)

And FoodNet does active surveillance for a number of bacterial pathogens including Campylobacter. And it does surveillance for parasitic organisms, syndromes related to food-borne disease and also food-borne disease outbreaks.

(Slide.)

Well, based on FoodNet data, again, Campylobacter is the most commonly recognized bacterial cause of gastroenteritis among the FoodNet sites. And you can see it is consistently so each year.

(Slide.)

And this graph shows the seasonality of Campylobacter infections in this country. And typically what you will see is a marked upswing in cases during May or June and then a peak in July and August and a steady decrease throughout the rest of the year.

(Slide.)

And this graph is Minnesota data, just a little different way of showing the same thing, the summer seasonality of Campylobacter infections.

(Slide.)

Well, this graph shows the age distribution of Campylobacter cases. By far the highest incidence is in infants where we will see an incidence of greater than 50 cases per 100,000 people. Children less than five years of ago also suffer a fairly high incidence, not really demarcated on this graph.

We see a second peak in incidence amongst young adults 20 to 30 years of age and to a lesser extent 30 to 40 years of age.

(Slide.)

Well, almost all human Campylobacter infections are accounted for by these sources, poultry, unpasteurized milk, inadequately treated surface water, pets and foreign travel. The specific sources of infection during foreign travel aren't really known, but are very likely to be the other sources on this list.

(Slide.)

Well, poultry is by far the most important source of Campylobacter for humans. In most surveys, you will find that 50 to 80 percent of retail products are contaminated. And poultry accounts for roughly 50 to 70 percent of sporadic human infections with Campylobacter. And this is a figure that you would also see in the risk assessment.

In evidence from throughout the world including some work we have done in Minnesota, it is apparently that poultry is a source for fluoroquinolone-resistant Campylobacter for humans, as well.

(Slide.)

This table shows outbreaks of Campylobacter that have occurred in the United States from 1978 to 1996. And first let me say that outbreaks due to Campylobacter are rare. You can see an average of about six per year in the whole country. And when they do occur, you can see they are food-borne or water-borne. The specific source for many of the food-borne ones is actually unpasteurized milk.

You can see poultry isn't implicated specifically in many outbreaks, but many of the other food items that are linked to the outbreaks have actually been cross-contaminated with poultry in the kitchen.

(Slide.)

The seasonality of outbreaks due to Campylobacter is different than the seasonality of sporadic cases. Again, sporadic cases, seasonality in the summer outbreaks. The seasonality tends to be in the spring and in the fall. And this is due to largely to the seasonality in outbreaks due to unpasteurized milk shown in yellow and due to inadequately treated water in blue.

(Slide.)

Okay. So just a brief summary. Summer seasonality. Sporadic cases are -- account for the vast majority of cases, are far more common than outbreak-associated cases. Sporadic cases occur for 99 percent of all Campylobacter cases.

Poultry is the primary source of Campylobacter for humans in the sporadic cases at least. And person-to-person transmission of this organism is rare. For some reason, we -- it just doesn't appear to be very efficient. We don't see the institutional outbreaks. We don't see the day care outbreaks that we do with some other pathogens such as Shigella and E. coli 0157:H7.

(Slide.)

Okay. Back to clinical features. Infection with Campylobacter can range from no signs whatsoever, it can be asymptomatic, or it can cause death. Diarrhea is a hallmark, of course, and it is often severe, often producing bloody stools. Fever can occur. Abdominal pain, severe abdominal pain is another hallmark of Campylobacter infection. And the nausea and malaise occur commonly, as well.

(Slide.)

Now, Campylobacter gastroenteritis is usually self-limiting. The duration is usually less than a week, although it is a pretty miserable existence for a week. It is a debilitating illness.

The duration can be up to three weeks in 20 percent of cases. Systemic infections are rare. Most isolates are from stool. Only about 0.5 percent of isolates are from blood. And the hospitalization rate for confirmed Campylobacter infections is about ten percent, ten or 11 percent. And that is really a fairly high figure when you think about it.

(Slide.)

The case fatality ratio from a couple of outbreaks is three to 24 per 10,000 cases. And it is estimated that there are 100 to 150 deaths per year in the United States. And Campylobacter not only causes gastroenteritis, but it does cause some chronic sequelae including reactive arthritis and Guillain Baret syndrome.

(Slide.)

So antibiotic treatment for Campylobacter gastroenteritis is not needed in most cases. It is beneficial to patients with prolonged or worsening symptoms, high fevers or bloody stools. And it is definitely indicated for patients who are immunocompromised or pregnant. This is very important. Our immunocompromised population is going to do nothing but grow as the baby boomers age.

(Slide.)

So the drugs of choice for Campylobacter when treatment is indicated are either erythromycin or a fluoroquinolone such as Ciprofloxacin. And fluoroquinolones are used widely for the empiric treatment of gram negative bacterial enteritis. And it is also a treatment of choice for traveler's diarrhea.

And so where as both will work fine on Campylobacter, erythromycin actually is not effective for the other causes of bacterial gastroenteritis. And that is what causes a problem for physicians, is Campylobacter needs to be treated early. And so treatment needs to be started before culture results are back.

(Slide.)

Just quickly, a little bit about NARMS on the human side. Just quickly, Ciprofloxacin resistance was documented in 13 percent of Campylobacter infections both in 1997 and '98.

(Slide.)

I just quickly want to tell -- this is the work that we had published in May. I do have reprints of this article for anybody that is interested in catching me during the next two days. But quickly, in that we show -- and these are the data -- the data from 1998 are what is in the paper. These are the percentage of Campylobacter isolates submitted to the Minnesota Department of Health that were resistant to quinolones.

In red are the yearly figures. In blue are the quarterly figures. In 1998 -- that is as far as we got published, the yearly data, the yearly percentage resistant was ten percent. In 1999, now, of course that is not counting December yet, but things won't change much. But not counting December, the yearly percentage resistant is over 17 percent now.

And you can see during the first quarter, 39 percent of isolates were resistant. And even during the trough in the third quarter of this year, over ten percent of isolates were resistant.

(Slide.)

And this is in the paper, so I won't belabor it. But we did show a clinical effect. Quinolone resistance did result in a longer duration of illness for patients that were treated with quinolones.

(Slide.)

And we did isolate Ciprofloxacin-resistant Campylobacter from poultry and -- quite commonly and showed identical DNA fingerprints in resistant isolates from chickens and domestically acquired resistant human cases.

(Slide.)

Okay. And that is my whirlwind tour. And I will stop there. Thank you.

(Applause.)

DR. BEAULIEU: Maybe one question for Dr. Smith. Tom?

(Away from microphone.)

MR. : Yes, I was curious to see if your number graphics supplied --- less --- evidence --- particular segment of the population --- Campylobacter?

DR. SMITH: Well, absolutely. I really don't think a lot of it comes directly from eating raw or undercooked poultry. I think most people know not to eat undercooked chicken.

What I think is happening is I think the vast majority of Campylobacter infections from poultry actually comes from cross-contamination in the kitchen of other food items, food preparation surfaces, utensils and so on and so forth. So that would be my best guest.

DR. BEAULIEU: Thank you. Our next speaker is Dr. Paula Cray. Dr. Cray has a whole series of degrees associated with microbiology, bacteriology, biochemistry, veterinary microbiology. She is currently the Research Leader of the Antimicrobial Resistance Research Unit at USDA's Agricultural Research Service at the Russell Research Center in Athens, Georgia.

She has a great deal of experience dealing with food-borne pathogens, particularly Salmonella and Campylobacter. And she indicates that one of her other interests is she is also proficient in fast foods. And she and Dr. Sundlof might want to compare notes there because I know he is an expert at McDonald's.

DR. FEDORKA-CRAY: My fast food expertise is dependent upon which toy is out.

(Laughter.)

Well, it looks like I have to re-boot the computer. It put itself to sleep. So I will take a moment to say that I will stick with the thought that Andy gave earlier that developing gray hair is a result of a antimicrobial resistance. I keep trying to tell my children now that this is the professional look.

And I caught them on a telephone conversation recently telling my mother that a bottle of her Clairol would fit really well in my stocking this year. I am not sure where that is going to leave me. I hope it is a good color. I guess I could get purple to match my computer, too. I saw a few of those in Paris last week.

(Laughter.)

Well, with this modern technology, I had modern technology glitches in -- this week when I left my power cord on Monday at home and found out that you just can't plug your finger into the socket.

(Slide.)

I will start by saying that some of the production statistics, just to give you a background on where we are coming from, 8.25 billion chickens were -- are estimated to be in production for 1999. And more than 29 billion pounds of ready-to-cook chicken is produced. This results in an economic impact of 22 billion dollars for the wholesale value of these shipments.

We eat it is projected more than 79 pounds of chicken per year per individual. This is increased from 28 pounds per person in 1996. And our estimated expenditure for these products is 40 billion dollars. A retail price for chicken has increased from really a minuscule amount to $1.02 per pound.

However, it is supposed to be 44 percent less than it was many years ago, though I don't seem to think that the IRS has much thought about that. And I know my sons who consume vast quantities of food have no consideration for what anything costs anymore.

(Slide.)

There are top states for producing chickens which sometimes results in a regional analysis. And broiler companies directly employ 300,000 Americans. Now, if we look at Campylobacter itself, I was pleased to see that Kirk really gave a lot of the epidemiologic aspects. So I will concentrate a little bit more on the microbiologic aspects.

It is a fastidious organism. And really, it is fairly fragile compared to something like Salmonella which can survive in the environment for years at a time and survive in many different means and states.

However, it has been demonstrated that Campylobacter can survive for weeks in soil and water. I don't think that it has been clearly demonstrated that Campylobacter can survive for a very long period of time on surfaces. And we don't find that surface survival even in the laboratory is very high. And I can assure you that OSHA doesn't want to come on a daily basis to the lab and check the bench tops.

It is a gram negative organism which makes it one of the more popular organisms. It has a motile nature which helps us in identification. And it has special oxygen requirements in that it requires a low oxygen, a micro-aerobic environment for growth. So this confounds and compounds our problems in the laboratory as we try to propagate it.

It often requires special media including the addition of blood and blood products, iron and other compounds for growth. Over-growth is highly likely, in fact almost -- most often observed on a daily basis regardless of what one puts into the broth media for selection. And this confounds our selection of Campylobacter.

And often it is missed. So I will still comment from Dave Nesbitt who gave a comment at our USDA/FSIS meeting earlier this week when he said that they noticed 80 percent prevalence in swine. And someone said, "Oh, you are doing well. You only missed 20 percent."

So the range for prevalence estimates go anywhere from zero to 100 percent. And I think that a lot of that has to do with selection methods and skill of the lab itself. Antibiotics are often required to minimize the overgrowth in the media.

And this may effect recovery of some of the organisms. And --- gas that is used in media often as a selector. And it may select specifically for jejuni and coli populations which may minimize the prevalence of some of the other serotypes.

(Audio missing due to technical malfunction.)

--- you will find halviticus coming from cattle --- is why don't we see it for three weeks. Okay. Why is it so difficult then if it is there and we have the genetic relationship from the breeders to say that, in fact, it went from the breeders to the chicks but we don't see it for three weeks? What is happening?

And we have a lot of different theories about that, but that is a hot and heavy topic right now for scientific pursuit.

Now, one of the things though that we do observe is that within a single bird, we can see mixed species. And they are often recovered in varying numbers. We can have coli and jejuni, lari, maybe some --- all coming from the same bird. And it is hard to predict in what population it is going to be, although of course most often it will be jejuni or coli predominating over the other lesser species.

Mixed species have also been recovered from human fecal samples. And this then puts the question of our selection criteria for any one colony on a plate. If we are looking on a plate, typically -- because I have my nice new little purple computer, I failed to put all of my nice little pictures on here.

But if we look at a plate of microbiologic media and we have, in fact, the opportunity to pick multiple colonies from a plate, which one are we going to select. And this can be confounded by the culture methods and by the fact that we have this mixed population and it is difficult to predict exactly what is coming from any one individual source.

(Slide.)

Now, although we have this mis-population, it is often confounded by our culture methods, as we said. And if we look to genetic identification to do rapid PCR tests, for example, while it can provide us with information about the mixture, it doesn't provide us with an isolate to do any further characterization. So that's what limitations we would have in using genetics to identify what is in a population.

So then if we finish us looking at slaughtered, all of our populations are, in fact, mixed then in the chill tank in particular. And there is a high probability that, in fact, the carcasses will acquire other strains while mixed in this fecal soup. And we are the premiere lab for ---

(Audio missing due to technical malfunction.)

And these mixed populations that are observed in slaughter samples then, we have to ask ourselves from the scientific standpoint what are these differences between the strains that might be coming from any --- of each individual isolate and with respect to the resistance profiles that may or may not be identified from the selected isolate.

And then we have to ask ourselves then how do we facilitate selecting an isolate. Many members from the laboratory are in the back. To them I owe great deal of thanks. We have had many pizzas over the year, increasing from 1,000 to 5,000 colonies is to integrate my budget there along the pizza lines. So the Pizza Hut will be happy.

So these are some of the questions I think that we have to ask ourselves scientifically. If we look at some of our information, we see that just by random chance, 33 percent of our isolates that we selected over the course of the year were coli as opposed to jejuni which suggests that there is a higher population of coli actually going into the human population.

(Audio missing due to technical malfunction.)

--- associated with jejuni. We do see a much higher resistance with coli compared to jejuni for both the human and poultry isolates. And I will leave you with that.

(Applause.)

DR. BEAULIEU: I quick question for Paula?

MS. : In Europe, we see the same seasonal peaks that you have shown in your material in the U.S. But you also see the same seasonal peaks in the poultry. The thing is that the human peaks ---

(Audio missing due to technical malfunction.)

DR. FEDORKA-CRAY: What we do is seasonal association with Campylobacter also in the poultry production, although this may, in fact, be confounded by region in that we have different climactic areas that we would be dealing with. So the prevalent --- region for any number of reasons.

And then we can -- we have observed some studies which we have been involved with in which there really wasn't much of a seasonal analysis or, in fact, we do find times that it shifts. And those may be due to climactic reasons.

One of the things that Norman Stern has reported on is that when there is a more -- more rain or humid conditions, then the prevalence of Campylobacter increases. So even though you see you may have an off season when you shouldn't be seeing it, say winter, if it a rainy winter that is a little bit warmer, then I would guess that the prevalence of Campylobacter, in fact, may be higher at that point in time. So --

DR. BEAULIEU: One last quick question.

(Away from microphone.)

MR. : A comment. Relative to chillers and in poultry processing plants, the additive of fecal soup, as a veterinarian working in this industry, I feel that that is the thing. That the chillers are mostly after ---, after the food separation of the carcasses, after at least one, two, three --- antimicrobial compounds.

And I might add that there is a zero tolerance for fecal material in chillers established by USIS. And I know of plants --- chillers. If you think this is a small task for simply a chiller that holds thousands of gallons of ice water, let me tell you it is not. So I am taking some exception.

DR. FEDORKA-CRAY: And you are right --- for colony on that. And I should not have mentioned it as fecal soup. I think that when you look into that, you will see a lot of carcasses. And a better description would be that all the carcasses are in close contact with one another and have the ability -- a lot of the Campylobacter contamination does occur on the skin and skin surfaces.

And so the opportunity for mixing and rubbing is there. I meant in no way to imply that they were standing in a lot of fecal soup.

(Away from microphone.)

MR. : Well, even as a --- chiller --- agitated ----.

DR. FEDORKA-CRAY: Yes.

MR. : --- by air. Yes, their contact where there is also separation where the ice and the warmth completely surround the carcasses. But the question I have -- and I saw this in the document that you have just given us. I see here it is referenced where we ---

DR. FEDORKA-CRAY: Right.

MR. : --- as literally an enrichment for growing Campylobacter. Now, when do you do that? Aren't we actually selecting the first stage of development of resistance for ---?

DR. FEDORKA-CRAY: There is a debate about that. And we have talked about that with CDC. We are looking at some of those mechanisms. I think that -- let's see, Nina, do you want to speak to Gerald's -- I think Gerald feels that there is no selection, is that correct, as far as there is no genetic selection ---

(Audio missing due to technical malfunction.)

--- for isolates that are more prone to that first step because they will have to have some resistance to the nalidixic acid to propagate. And there is a disparity in methods in how isolates are selected. And that --- you know, and if that is in fact the case, then all of these graphs and everything have to have a disclaimer associated with it.

We don't use it for our selection purposes. It is an identification tool. But other labs will.

DR. BEAULIEU: Thanks, Dr. Cray. I am sure Dr. Cray will be around for your other questions. I am sure she will be happy to answer those one on one. There is also time set aside this afternoon for additional questions. Go ahead, David.

Our next speaker is David Vose. David is an independent risk analysis consultant currently located in France which I think falls into the category of it is a tough job, but somebody has got to do it. He is an expert in --- risk analysis with ten years experience in simulation modeling. He has applied his expertise to a wide range of problems from oil and gas production to banking to epidemiology all over the world. And David is going to take us through the risk assessment.

DR. VOSE: Thank you. Good morning.

(Slide.)

The CVM risk assessment, what I am going to try and cover in the 40 minutes that I have got is, first of all, what we modeled and why, the logic associated with that model. And I am sure that that appears to something of a black box to at least a few of you.

I am going to talk the results that we have gleaned so far, uncertainty analysis which is a large part of what we have been doing, recognizing the degree to which we do and don't know. And as Wes pointed out in his presentation, that a great deal of the value of risk analysis is to work out what it is you know and don't know. And I am also going to describe how one might use the model in brief form to help make your regulatory decisions.

Well, first of all, of course, I have to recognize the team that I have been working with. First of all, Sharon Thompson who is my boss so she comes at the top of the list. Sharon took over with this project halfway through from Peggy Miller. And I take my hat off to her because that is a tough job to do. It is halfway through and she suddenly has got to understand what we have been doing. And it was a very complicated problem that we had to deal with.

I also have to thank Peggy Miller who was the initiator of this project. And I have to recognize to Peggy that she was the person who originally thought of this approach to assessing this risk, as much as I would have liked it to have been me. I simply executed what was a very clever idea from her.

There is me, the consultant, of course ---. Kathy Hollinger -- just in case you don't know because you will end up in the wrong place if you don't know that, somewhere in Germany.

(Laughter.)

Okay. Kathy Hollinger, as Dr. Sundlof has said in his opening remarks, Kathy put an awful lot of effort in. And she sort of reminds me of a bulldog. I am British. And so she has the tenacity of the bulldog who will go out and just keep collecting information and not be satisfied. She would often come up with a comment to me, "But it is not that simple, David", which gets very irritating because I would like it to be. It's a model. But all power to her. She kept me on line.

As did Mary Bartholomew who spent a lot of time helping collect the data and analyzed the data that was given to us in forms that weren't necessarily exactly what we needed. In quantitative risk analysis, you need numerators and denominators very often because you want to work out uncertainty.

People will tell you, "Oh, well, we found 30 percent resistance." They don't like to tell you that they only checked five chickens. So we need numerators and denominators if we are to say what that means. And Mary has done a great deal of helping obtain that information.

(Slide.)

Okay. This is the only slide with this much information on it. So I apologize. Why do we model fluoroquinolone-resistant Campylobacter in chickens? Well, this was originally set up as a pilot study to determine the feasibility of doing the risk assessment on antimicrobial, bacterial, blah, blah, blah.

We wanted to look at the data needs that would incur and we wanted to look at the source of information where we may be able to find that data. As others have pointed out, Campylobacter is the most commonly known cause of bacterial food-borne illness in the U.S.

Ninety-nine percent of Campylobacteriosis are sporadic illnesses which makes life a lot easier from a mathematical point of view. If they were these outbreaks, then we would have a more difficult problem.

Chicken is, as others pointed out, the most commonly identified risk factors for Campylobacteriosis in the U.S. It has been -- Campylobacter has been reported to develop resistance quickly to fluoroquinolone which, again, makes our problem much more simple. Fluoroquinolones are important antimicrobials, of course. It is a valuable drug to us and we want to make sure that we guard the value of that drug.

And most importantly, we felt that certainly as we started to move along this part, we felt that there was enough data in order to produce a meaningful quantitative risk analysis. I am a quantitative risk analyst. I am involved in the mathematics of things.

Another option is to go down the qualitative route where you just simply identify the factors and talk descriptively about the problem. And other organizations have done that.

(Slide.)

Okay. Well, this risk assessment modeled direct transfer of resistance because fluoroquinolone resistance is on the chromosome. It is not transferred to other bacteria. This is something I know absolutely nothing about. But because it is not a two-step process, it makes, again, our mathematics a little simpler.

You can see that we have picked out this particular problem for two reasons then, Campylobacter fluoroquinolone resistance in chicken. A) Because it is a big issue. But B) because there is data there. And C) the math makes it feasible.

Now, we are going to try some further analyses on the risk initiatives underway to look at other microbial resistance issues such as indirect transfer. That may or may not be something that we can feasibly do quantitatively. But we are certainly not going to start out saying yet we are going to be able to do everything else quantitatively because we could do this one so.

But -- so the point to take away I suppose here is that if we couldn't have done it quantitatively on this risk issue, we certainly wouldn't be able to do it on the others. But we can, so we have got some feeling of security that we can proceed on.

(Slide.)

Okay. The problem we modeled, imagine you have poultry in a shed. They get some disease, e.g. collibacillosis. I probably said that wrong. They are all treated with a fluoroquinolone. Then that fluoroquinolone-resistant Campylobacter, it proliferates in the drug because -- sorry, proliferates in the poultry gut because all of the other bacteria have been erased.

Then us humans go and eat that chicken and they get contaminated with that Campylobacter. And then they go to the doctor and the doctor says, "Oh, you are ill. Take some fluoroquinolone." And nothing happens. So to how many people would that occur is what we are trying to work out.

Now, there will be a lot of people I think who would criticize this model because it is not a predictive microbiological model. A predictive microbiological model would say, for example, look at the number of pathogenic organisms in the chicken and then flow through, see how many were gotten rid of in chillers that the gentleman in the back was talking about through evisceration, etcetera, etcetera.

How many would be lost through natural attenuation of the numbers from chilling or freezing, and then the cooking. And, oh, it just goes on and on. I mean, you can think of so many things. Even if we just dealt with the one last issue. Here is a quantity of chicken that has fluoroquinolone-resistant Campylobacter on it and you go feed it to someone. Well, who do you feed it to. You know, if I gave all of you out here the same dose with the same pathogenicity, you would have varying reactions.

There would be any number of you who would have light illness. Some would have no effect at all. And it would depend on, for example, what you had -- when you had your cup of tea, did you have some yogurt if there was any out there? Did you -- have you had a full meal? Have you had nothing to eat yet this morning like me, etcetera, etcetera.

So it is an extremely complicated problem if you want to look along the microbial part. And certainly from the point of view of the regulator, the Food and Drug Administration here, it really wasn't relevant to look at all of those parts.

Now, from the point of view of industry, I can quite imagine that they would want to work out ways that they can try to reduce the number of bacteria that actually were loaded in their chickens. Absolutely right. It is fair to say is it fluoroquinolone that should be used or should we try and work out ways of reducing its use; is there any effect on the chicken population. Right.

(Slide.)

So we chose this rather simple model as being the most appropriate. Now, although it is simple, we can make corrections to the original assumptions for changes in the system. For example, if changes in human feeding patterns -- if we eat more chicken or less chicken or if we tend to eat it more cooked or less cooked, things like that. We can probably start making some kind of fudge factors, but reasonable guess fudge factors that will allow us to update our model as the system changes, if it does.

But the essential real benefit of this is it provides a responsive means of continually assessing the risk. By responsive, I mean if we keep monitoring the problem, we can assess month by month or quarterly by quarterly, we can assess the size of the risk.

Now, if we had gone down to a predictive microbiological model with so many changes to the system like they change the number of chillers that they use or the frequency with which they clean them out, well, we would have to go all the way back and do a much more complicated analysis.

So the point of this is it is easy to use. And we can get a quick idea of the size of the risk that we are exposing the U.S. population to.

(Slide.)

Okay. Now, to my mind, this risk analysis -- this microbial risk analysis is unique in that we found data to quantify all the model parameters. I say unique because I have been involved in a number of microbial risk assessments including the United States of America. And almost always -- well, always we have somewhere along the line to make a guess. We have to assume something that we really wouldn't like to have to assume. We have to use a surrogate bug for the dose response, etcetera, etcetera.

Well, in this particular risk assessment, we have thanks largely due to Kathy and Mary found data to quantify every single parameter. And that data has come from a number of sources, from FoodNet surveys, physicians' reports, CDC's attempt at a case control study, NARMS, from poultry industry, data on consumption and production, U.S. population records, etcetera.

Data didn't just have to be collected, but it had to be collected in a form that allowed us to perform uncertainty analyses. So we had to dig out not just the information like prevalences and percentages. But we had to, as I said before, talk about numerators and denominators.

Now, given all of that, 1998 was the first year that we were able to produce a complete set of data. So we had both sides of the equation that I am going to talk about in a minute, we had data for everything. What I had originally imagined doing and I had hoped that we would be able to achieve is to compare several years of data from the past. And we would get a much more firm understanding of what was going on.

So I suppose at this point we are in the first year of what I hope will be several years of data collection that will make us more and more able to understand the connection between Campylobacter-resistant fluoroquinolone in chickens and the effects on the chickens.

(Slide.)

All right. If you read through the risk assessment report that we have done, probably a lot of you will be confused about this quantifying uncertainty. Uncertainty is about the state of our knowledge. There is in theory some parameter value that is out there that could be known. But we will never have perfect data. We will never have perfect information about that parameter.

And if we just take at face value some of the data that we have when we have a very small amount of data, we can be very wrong. We can be overly conservative. We could be overly pessimistic. We don't know. But we would be very wrong if we just take the data at face value.

If I toss a coin three times and I get two heads, you are not going to tell me that the probability of the heads is 66 and two-thirds percent. It wouldn't make sense. Well, that is the same principle.

In this particular problem -- analysis, we used a Bayesian approach. And there were good reasons for that. First of all, it allows us to combine dissimilar data. So we were able in a couple of instances to take a set of information over here with a particular certainty with information involved in both of those two different studies.

A potential criticism of the Bayesian analysis is that we have to introduce something called a prior distribution. And that would introduce a very small bias. And Dr. Cox, who is following me here this morning, will probably mention that being a Bayesian mathematician.

But having said that, the data set sizes mean the results pretty much equate to the classical statistics estimates which is perhaps the things that you remember from university and certainly less controversial, although Bayesian inference is certainly growing in use.

(Slide.)

And so quantifying uncertain analysis not only tells us how much we really know and how good our predictions can be. But it also tells us where we should be able to collect more data and how it would be useful.

(Slide.)

So here is an example. This is a distribution of uncertainty about a particular probability. And you have -- I'll get my laser pen here. You have three distributions here. The first one, which is this broad curve here, is talking about your estimate of a probability.

If you were, say, to take -- go to a population and say -- oh, let's talk about Republicans and Democrats -- ask four people, "Are you going to vote Republican or Democrat?" -- and I can do that because it is 50/50, so I am all right. Two say Republican and two say Democrat.

Well, if I am trying to extrapolate to the true population, I know that I don't really know very much about the proportion of people that are going to vote Democrat or Republican. And so this description here is describing the amount of uncertainty.

Well, it is pretty much somewhere between zero and one, not very sure. But as I accumulate more data, I go through this -- the beta (3,3) is talking about four people, two of each side; a beta (11,11) is 20 people, ten on each side. And you can see my distribution is becoming a bit narrower.

And then here we have got a beta (21,21) which is 20 people of each side. So 40 people are asked and 20 people said Republican, 20 Democrat. And there you have a much narrower level of uncertainty. So the point of it is that if we accumulate more data, so we become progressively more certain about what the truth is out there.

(Slide.)

For those of you who are more technically inclined, here is a little graph to show that although Bayesian inference has a slight bias to it, the classical statistics of an estimate for this particular type of problem, when you had four people, two Republicans and two Democrats, well, the classical statistical estimate will be this thing here, this red line.

It is a binomial distribution. And there is an approximation there in blue which is the normative approximations of the binomial versus this green line which is the Bayesian estimate.

Well, what I am trying to show here is that with this red step line, that is the perfect classical estimate as they call it. And yet they frequently represent that with this blue line. It is a little more helpful for them for a majority of the analyses they do. So if a classical statistician is willing to take this step line here and make it into a blue, then going from blue to the green, that is not a big deal.

(Slide.)

More importantly, as your data sets become bigger, so the difference between this three of them, and you can't see the blue and the green, the classical versus the Bayesian. They just completely overlay on each other. And that is not even for a very large number of data points, just 20 data points.

(Slide.)

So there isn't really any controversy between Bayesian and classical inference in this particular model.

(Slide.)

Okay. Now, I do -- the difficulty that people will have I think in understanding what I have tried to d here is looking at this idea of a nominal expected number of people who will come out with Campylobacteriosis. I say nominal because I wasn't really very interested in the actual number of people.

CDC put a lot of analysis into trying to determine the true number of people out there in the population of America who got ill. Well, I was more interested in something called the intensity of that system because I want to know whether if we were to take that same number -- that same system and one year we note that 30 people became ill. Well, the next year we are not going to note the same 30 even though there was the same risk out there. Maybe it is going to be 35. Maybe it is going to be 25. I want to know that if you were able to repeat that year many, many times, what would the average be which is my much better estimate of the true risk to the human population.

So here is an example of a Poisson distribution which is the appropriate distribution in this circumstance. And you can see, I have got -- this is the probability. And for a given intensity -- this is for a given size of risk if you like. On average risk, two people per year would die, whatever, ill.

Then you would see we could quite easily have zero people one year or we could have one person or two persons or three or four all with the same amount of risk. And yet we can observe different things from one year to another. And that gives you some idea that we should be a little bit cautious about interpreting changes, reasonably small changes from one year to the other in what we observe in the illness out there because it could simply just be a sampling error. It is just that we -- it's just there is so much randomness out there, it is quite possible you will have a small sample one year and a larger one for the other, and yet have the same level of risk.

So I am very keen that when we do this risk assessment, we use it to quantify the risk. But we should be completely cognizant of the randomness that is out there that could if we are not careful sway us from making overly cautious decisions or underlie cautious decisions. And the purpose of doing the uncertainty analysis was to stop us from doing that.

(Slide.)

Okay. Model overview, how I set this model up was, first of all, to look at the number of Campylobacter culture confirmed cases observed in the U.S. population. And this comes entirely from CDC data except that I am interested in the nominal expected number.

So I am interested in that two value if you like from that Poisson distribution versus the actual observed numbers. So I am trying to get a sense of how many people out there are getting those Campylobacter cases.

And from there, this is in Section 2, I am looking at the total number of Campylobacter infections in the U.S. population. So it is the total number of Campylobacter infections in the U.S. rather than those that were culture confirmed cases because culture confirmed cases are the only ones that you actually observe in your health system because they have to be identified. You have to get them, thus, in scooping the poop and doing the microbial analysis.

So we extrapolate from there to work out the total number of people that are ill in the population. In Section 3, I am looking at those -- the number of those people who would have been ill from the fluoroquinolone-resistant Campylobacter because, clearly, those are the people who would be at risk.

And I want to see how many of those who were infected with the fluoroquinolone-resistant Campylobacter then went to the doctor and were prescribed an antibiotic and that antibiotic happened to be fluoroquinolone because, clearly, those are the only people out of everyone that had Campylobacteriosis, those are the only people who are going to have any observable difference in their final outcome.

Over here in Section 4, I am looking at the number of -- the quantity of meat consumed, of chicken meat consumed that is contaminated with fluoroquinolone-resistant Campylobacter. And the idea is to say if