 Well, thank you very much for the invitation to come talk with you. I think one of the reasons that I was invited was to tell you the story of what we've actually been doing at the Mayo Clinic related to pharmacogenomic testing in the Department of Psychiatry. I have some relationships you should know about. I'm primarily a full-time employee of the Mayo Clinic. However, the Mayo Clinic has a small equity interest in a company that is named AssureRx Health, and AssureRx Health has licensed intellectual property that's owned by the Mayo Clinic. I'm one of the inventors of this intellectual property. And what AssureRx Health has done is built a web-based electronic interface to support pharmacogenomic decision-making and clinical practice of psychiatry. My objectives today are pretty straightforward. I want to tell you about what has been happening at the Mayo Clinic and what we are doing now. I want to talk a little bit about this question of clinical utility and put forward my own thoughts about how to move forward. Well, the story of psychiatric pharmacogenomic testing really begins in about 2001 when we started a series of clinical studies. And at that time, we focused on Zetachrom P450-2D6, that was our only informative gene, and we found many associations between psychiatric medication response and metabolic capacity. So in February of 2003, the clinical laboratory of Mayo Clinic decided to make this test available, and we worked for a year to see how it settled in our practice. And by that time, there was a sense that other Zetachrom P450 genes were also important, so 2C19 arrived and 2C9 arrived. In April 2004, the Mayo Medical Laboratories made these tests available to clinicians everywhere, anywhere who had really contracted with Mayo Medical Laboratories to be a reference lab. So that was a very important change. Now, as you've heard from many different perspectives, implementation is a slow process. And it took a couple of years before the faculty in the department, before the residents in the department, became comfortable with this new approach to adding information into the process of making a decision. But by 2006, the practice of ordering individual genes had really begun, and I'll show you a little bit of information about that. However, there's another shift which occurred in 2009, and that was the point where we stopped ordering individual genotypes and started ordering an algorithmic profile of genes. I'll tell you more about that. Now, I'm grateful to the organizers to have done some polling ahead of this meeting. And again, you'll remember this particular scenario, consider a CYP450 profile, 43-year-old Caucasian woman is being considered for an SSRI, should this variant be routinely used? Well, this did catch me a little off guard, I must admit. First off, I was surprised that more people didn't know. Only 31% claimed not to know, so a very definitive, intelligent, well-prepared group. But there were 16% who had a strong opinion it would definitely not to be routinely used. So what does that mean? Well, let's deconstruct the question. Any questions? What is a CYP450 profile? I'd argue that there really is none today, that you could create one, but that's not what we do. Important question, why is the woman receiving an SSRI? Is she depressed? Does she have hot flashes? If we consider depression, does she have a treatment-resistant depression or a new depression that has just begun? And then the question, what variant singular is being considered? Well, we'll see about that. And then what does routinely mean? Does that mean that every single patient has the test? Or does it only mean that patients where it's clinically indicated would have the test? Well, again, it's a little ambiguous. Well, this is what we do now. We have an algorithmic profile, and we don't do 2D6 testing. We do these seven genes. And of course, we don't do one variant. We do more than 30 variants. And that's an important concept, because we're back in the mode of, well, one gene variant influence clinical practice. You're not thinking about what we have available to us today to guide treatment. But let's make it a little more interesting. What about just 2D6? Let's go turn the clock back in time. It's a different question than it's a profile useful, but is 2D6 information actionable? Well, Dr. Winschelbaum, in 2003, put forward some information in the New England Journal that would argue at least that there were strong pharmacokinetic relationships. And this famous pharmacokinetic profile, looking at different levels of metabolic capacity, which was really compiled 18 years ago, shows a lot of difference in the area under the curve of nortriptyline, depending on how many active 2D6 drugs one has. Again, there are also adverse effects. Patient died taking doxopin. Again, unknown metabolic capacity. Originally, it was thought to be a cardiac death. It was only that autopsy that it was a toxicology problem. You can argue doxopin is a pretty dangerous drug. What about a safe drug like fluoxetine? Well, again, it's a rare event. But in the case of this child, it was a needless death. Poor metabolizer was not recognized. But what about actionability? Would you give a patient who had very poor 2D6 metabolic capacity, Prozac, Paxil, or Refexor? Well, I would not. Would you give them norpermine or topfranol? No, I don't think so. Would you give this patient halodol or respiradol? Nope. Would you give this patient stratera? I don't think so. Would you give this patient coding? Well, I hope not. Those are actions. What about the reverse? Would you give this patient Cilexolexapro or Luvox? Well, yes. Unless there was another counter-indication. Would you give this patient Symbulta or Pristik? Yes, unless there was another indication. Would you give this patient Refrexor or Giadon? Yes, would you give this patient Conserta? So there are options to choose. Now, I have given all of these drugs to patients with poor 2D6 metabolic capacity, because I didn't know any better before 2000. But I try not to these days. Now, what is this? This is a component of the Algorithmic Pharmacogenomic Report. I'm just going to show you to take a second to try to explain to you that in addition to stating the genotype, in addition to stating the phenotype that we would impute, there's guidance to the clinician and medications in that first group are antidepressants. And you see there are many. There are 18 in that first set of rectangles. And this is a patient that has a very common genotype, not a poor metabolizer, but someone with intermediate metabolism of 2D6 and 2Z19. And again, the three categories are uses directed, use with caution, and use with caution, and with more frequent monitoring. So these medications can be used regardless of the genotype. But the focus of the clinician should differ based on the genotype. And again, there are many choices for this individual, some probably better than others. But now the picture changes when you have a patient. This is another patient that has impairment. But this impairment is really inactivity of both of the key enzymes. And there you see there are many more medications that are likely to be associated with side effects in this patient. And once you have this information, it's quite unlikely to start prescribing a medication that would be in that red rectangle. Well, again, the Pharmacogenomic Research Network group has been thinking about the issue, how do we facilitate clinical implementation of pharmacogenomics? And you heard quite a bit about that from Howard. But one aspect of that is we tried to think through what is the method by which one can establish the right amount of evidence. So this is a commentary that Dr. Laremann and I wrote this summer. And it argues for considering a broadening of the base of evidence. So yes, randomized controlled trials are a wonderful, well-established gold standard for some things. But given the nature of questions that are being addressed related to pharmacogenomic testing, related to specific drugs and a wide range of different gene variants, we would argue that the development of pragmatic clinical trials that are actually embedded within clinical treatment settings is a reasonable alternative to provide additional information that is more feasibly obtainable. Now, again, there's also other methods of finding out information that will help guide a decision about adoption. And well said that if there's something related to safety, that really forecloses the process. So when there was a focus on a risk for Stephen Johnson with carbamazepine, there were no randomized controlled trials. It was much more an issue of let's be sure we know which patients are at risk. Now we've tried to do retrospective studies and during the era before the algorithm, we reviewed 2,390 patients who were seen on just the consultation service. And again, these are patients referred for all sorts of reasons. And 19% were tested with at least one genotype, 58% of those with serious treatment resistance to antidepressant treatment were tested. We have two pragmatic clinical trials that have been conducted. One at the Ham Clinic, a proof of principle trial and there to our surprise, despite the underpowered nature of this preliminary trial, there was a difference in actual decrease in depressive symptoms in patients whose clinicians had the information about their genotype from the algorithm before starting treatment versus those who did not. And then in a somewhat larger sample with a very similar design in, again, in La Crosse, Wisconsin and not particularly sophisticated but a very lovely place. And again, the finding was demonstrated that not only did clinicians and patients find this to be helpful, but there was actually an outcome difference. Again, these are early days and these studies need to be replicated. They need to be replicated in much larger samples. But I think the direction is becoming clear. And my conclusion is that for us to really move forward with implementation, we have to make the reports more understandable and friendly and useful to clinicians. Again, we had experience with reports that were genotypes and phenotypes. They weren't perceived to be particularly helpful. What I think now we need to do is to make information available to clinicians that they can actually use. So I think my time just ended, so I'll stop. Great. Thank you. I think we have time just for a question or two. It struck me that most of the decisions you're making were already being made for the exact same pathway in the context of drug interactions. So how do you look at the same pathway from those two lenses? Howard, that's a terrific point. And I think it actually does provide some insight into the rate of adoption that psychiatrists were able to demonstrate here because you're entirely correct. We were thinking about the impairment of pathways due to drug-drug interactions. And of course, the correct response is to put both of those features together. You need to know the genotype and you need to know with the drug interaction. And you can create a phenocopy of a poor metabolizer by simply inhibiting that particular enzyme. So my response is that it's additive and perhaps synergistic, that you have a more complete perspective of what are the factors affecting drug response. Jonathan, did you have a question? Yeah, and this sort of gets at a topic that was brought up in the last session about should genetic professionals, genetic counselors and medical geneticists be involved in these discussions? And my feeling, and I was sort of chatting with Howard about this, is thinking, say, a few years from now, whenever the genetic information's already there and resident in some place in the medical record, these types of things almost don't need any genetic counselor involvement. This is decision support matrices. This is embedded in the medical record that is just in time information for physicians that are doing prescribing with information there. And so I think this is a good example of how once the genetic information is already in their medical record, it becomes available when needed, at times in the future, when drugs are being prescribed. I think that's right. So you have mentioned standards of evidence for the use of these tests and looking at it from the clinical pathology perspective, therapeutic drug monitoring is available. It's not as readily available for these drugs as it is as functional testing, for example, for warfarin. But I'm wondering whether you've considered incorporating measurement of drug levels, which is the hypothesized or posited method of a relationship between the genetic metabolic, the genetic change in metabolic enzymes and the outcome. That fundamental link of drug levels in the same patients in whom you're performing studies could be done, and I'm wondering whether you've considered doing it, thanks. Yeah, it's a good question. Grace, will you focus on what is the potential synergistic role between therapeutic drug monitoring, monitoring the level of medication in the patient, versus genetic testing, and I do think that we would benefit in this country by doing more therapeutic drug monitoring, and there are many reasons why. Certainly, it's reassuring to see a correlation between genotype and blood level, but that, again, may not add much value, but there are other circumstances, for example, if a patient has a good metabolic profile and has a bad response to the medication, you raise some hypotheses. It may be a target gene variant, or it may be something as simple as not taking the medication, and therapeutic drug monitoring is a very good way to identify that. We see this fairly regularly in do-do serum levels. Okay, one more quick question. Related to your trials, which I understand are pragmatic. Have you had problems persuading clinicians to randomize at the point of care and problems with IRB approval, for such work? Oh, okay, the question is related to our pragmatic clinical trials, and what are the issues related to IRB and the issues related to potential for randomization? Well, we chose to do, well, first, the IRB has been overseeing hundreds of genetic studies at the Mayo Clinic, so the IRB is very knowledgeable about the risk related to genetic testing, so we did not have a problem with the genetic testing component. The way the studies were both designed, there are two phases, so there is no randomization. Phase one is a period of treatment in the standard practice, so without genetic testing, and monitoring the outcome of those patients. Phase two, the guided phase, clinicians are given the profile that you saw at the onset of treatment and can use that information in any way they choose to care for the patient. One interesting observation that I did not anticipate, and it relates to other topics that were discussed at this meeting, is how valuable is genetic testing to the patient? And we've had some NIH trials where we have worked very hard to recruit 700 patients and have to approach two for every one we get, and in some studies, three for every one that signs up. In these two studies, because everyone eventually got a genomic profile, we had one person that we approached who did not, one patient, one subject who did not decide to participate in this particular trial. Great, thank you. Okay, thank you.