 Thanks. So it's a little unnerving to stand in front of this group who are more expert in genomic medicine and clinical genomics than I. I have been working on this mostly from a policy and technology assessment perspective with the College of American Pathologists. And also, however, yesterday at 9.50 a.m., my proposal for starting a pilot project in clinical genomics through the hospital laboratories was approved. So I am about to jump into the deep end of the pool, so I may be talking with some of you. So I'd like to talk about just a framework on recommended pathway for omics test evaluation to move information from research into clinical utility assessment very briefly that came out of an Institute of Medicine report. And then mostly focused on the evaluation that the College of American Pathologists did of genomics and genomic technologies. And then a few comments on genomics from a molecular pathologist's perspective. So this report about evolution of translational omics lessons learned in the path forward was just completed in March by an IOM committee. I was a member of that committee. This is very small print. I apologize. Basically it describes how you move from the discovery phase of an omics discovery. And this would include genomics, but it's also proteomics, metabolomics, epigenomics, everything. So there are recommended processes in the discovery phase of how you validate, how you work with your data, which are very large data sets, and how you validate that before it moves into a test validation phase. And that test validation phase, it's recommended be done in a CLIA laboratory setting so that when you move it into the evaluation for clinical utility and use stage, it's already been validated in a CLIA environment with standard operating procedures and another level of independent assessment from the research laboratory that made the discovery. And then various pathways for assessing clinical utility are described, prospective retrospective studies, prospective clinical trials, where the test does not direct patient care. And either of these first two clinical trial pathways do not need the testing to be done in a CLIA environment. So the third pathway, prospective clinical trial, where the test will direct patient care or patient management decisions, that testing needs to be done in a CLIA laboratory environment. Actually that is in the CLIA federal regulations, but very few people understand this. Whenever a test is done for patient management, which means diagnosis, anything, treatment selection, it needs to be done in a CLIA environment. So I recommend this report to those of you who are looking at this translational highway. The rest of my comments until the last slide are based on the College of American Pathologists evaluation of genomics. We called it genomic analysis. I tried to remove that out of this slide set and call it genomic medicine or genomics. But so understanding the human genome, basically the human genome project was completed in 2003, led us to a generic genome. And individual patient genomes will allow us to make decisions about directing patient care, hopefully improving outcomes, but we need data to demonstrate that. And this is what we're calling genomic medicine. So it's made possible by the ability to analyze individual patient genomes or large amounts of patient genome data. Genomic medicine is driving a global molecular diagnostics market with an estimated annual growth rate of about 14 percent annually. And a lot of this, most of this is an infectious disease testing, which I noted is part of what you're doing with periodontal work. But smaller parts and more rapidly growing parts of this growth are in genetics and oncology. Obviously, you know this better than I do, being NHGRI, that the cost for genome sequencing data has dropped precipitously, and this is a logarithmic scale to boot. And now the cost for doing a genome is less than $3,000 and still going down. I will put in a pet peeve. I do not like the terminology whole genome or whole exome sequencing because it basically says that we can do everything now. The technology is advancing such that what we do when we sequence a genome or an exome improves over time, which I think if we're already selling it as complete, we're selling ourselves short. And the advances in the sequencing technology is partly what's driving adoption of clinical genomic analysis in molecular pathology laboratories. So the first genome was done on ABI sequencers, taking hundreds of them. We moved then into the high-seq era of clinical, which is mostly used for clinical research, where you can do 50 gigabases, and it can be used for gene panels, exomes, or genomes. In November of last year, at least at the Molecular Pathology, Association for Molecular Pathology meeting, there was the rollout of the MySeq and the Ion Torrent PGM, in which you can do sequencing. You can buy these instruments at a clinically relevant price, so $75,000 to $125,000, and the turnaround times are 27 hours to 8 hours rather than the week to week and a half of just data generation. So this begins to be clinically relevant cost and turnaround times, and even moving on the Ion proton is coming out in the third quarter that will allow an eight-hour turnaround time for an exome genome transcriptome. And so this is really what we feel is driving clinical genomics to be possible today as this technology continues to advance, and I don't even have PacBio and Oxford and, you know, all the other technologies that are coming on the market. So when we look at current molecular pathology testing, we're looking at a single or few mutations, a single gene or a pathogen or a few genes or a few pathogens, and clinical genomics we feel is really doing gene panels, exome, or genome to analyze exome. There's also genome and transcriptome being done, and these slides, even from when they were developed six months to a year ago, people are now doing genomes, exomes, transcriptomes clinically. So we felt at the time that the genome and transcriptome data would mostly feedback in our understanding of the clinical use of variants into clinically targeted testing with genome panels or exomes. So for me as a molecular pathologist, next-gen sequencing is just the next new technology. I live through PCR, capillary electrophoresis, microarrays. Next-gen is just the new cool tool that we have in the molecular pathology laboratory, and it's being used by many labs today. In the setting of the molecular pathology laboratory, next-gen is not going to replace everything that we do. So some things that we do, deafness, genetic testing, many of the cancer mutations, can be done on next-gen sequencing technology into gene panels, exome, genome transcriptome. But other things that we do, viral loads, bone marrow and grafts, there are many tests that will stay on their current platforms because that's the only way they can be done, and that's the most cost-effective way to do the testing. So I won't go through all of this, but there are these various stages when you think about clinical testing of the pre-analytical phases, generating the sequence data, doing the data interpretation, which Heidi talked about, reporting and billing, and then clinical consultations. So we feel that molecular pathologists, molecular geneticists, industry, others will, with a strong molecular biology or genetics knowledge base, will be able to do this sequence data generation and sequence data interpretation. And I think it's interesting to hear Heidi saying that the sequence data generation is being outsourced from partners because it's very complicated. But we see all pathologists being involved in this pre-analytical test selection phase, helping with proper consenting of patients or documenting of proper consenting, the reporting, billing, clinical consultations around how you use this information. So we look at sequence data generation and sequence data interpretation. The data generation has many quality issues from a laboratory perspective, but it's really the sequence data interpretation that is the pain point. And Heidi, better than this, described that clinical-grade database and bioinformatics tools are a high priority need in the clinical laboratory. So both the clinical databases, where we know that the data generation was done in a high quality manner and not in a research laboratory, not to denigrate research laboratories, but there are different standards for operations and research settings and clinical settings. And then the software tools for interpretation and clinical usefulness are needed. And we think that pathologists should be at the table in the development of bioinformatics tools and these databases. And pathologists should be learning how to use these tools since we are the diagnostic testers along with molecular geneticists that will be doing this. So when we think about all pathologists, we also need clinical decision support tools. So this is different. So when people talk about databases, there are many different things that they're talking about and that's why we describe the clinical database repositories, the interpretive tools, and then when you get into using this information clinically, the clinical decision support tools that are needed. And it's these clinical decision support tools that will help all physicians understand the clinical usefulness. So the speed of clinical adoption, we felt hinged on several factors. The decreasing costs of doing the testing are driving this into molecular pathology, molecular genetics laboratories, as well as the increasing turn, the decreasing turnaround time, the increasing speed of this testing. The bioinformatics is the pain point. We need clinical quality databases and software tools. And the clinical usefulness is also a pain point. What is clinically useful? Clinical analysis is used now with very targeted testing. We're hopeful that research and discovery, such as what you guys are doing, and clinical use will increase the clinical applications. There is a lot of payment uncertainty. Currently, there are no specific CPT codes. I know we're talking about these new molecular codes that will be test specific, but those test specific codes aren't going to deal with a cancer gene panel. Or they are not going to work for this next-gen sequencing technology, especially a genome or an exome. And it was already brought up, the reinterpretation of already generated sequencing data. How are we going to pay for that? And from talking with colleagues of mine who are already doing this, one colleague is doing a 28-gene panel and talked to a payer to get it paid for, and the payer said, but only three of those genes is relevant to the cancer type that this patient has. And so we'll only pay three-twenty-eighths of that test. Yet, if you did those three genes individually, it would be more costly than doing the 28-gene panel. So we have to get them thinking in terms of chemistry testing, you know, where you do the panels because that's the most effective way, cost-effective way to do the test, and you use the parts of it that are relevant to that patient. But that's maybe the payers here understand that, but many of the payers do not understand that. And then there is a great deal of regulatory uncertainty. It is not clear what the FDA is going to do with next-gen sequencing technology in clinical laboratories. Quality standards development is being led by the CAP in collaboration with AMP and ACMG. We now have checklist questions. So when you are a clinical laboratory, there are a series of questions that you have or standards, if you will, that you have to meet in the clinical laboratory. Well, the CAP accredits laboratories under CLEA with deemed status under CLEA. And we were accrediting laboratories that were doing next-gen sequencing technology and had no standards or checklist questions. We have now generated a starting point, trying not to be too restrictive in the standards that we're asking for, mostly focusing on documentation of what is being done, what databases are being used, how things are functioning. And those will be in the 2012 checklist. So we do have standards, and that same group is now beginning to work on proficiency testing around next-gen sequencing of anywhere from a gene panel to genome transcriptome. So when we think about this, there are no IT standards for reporting in the LIS, the EHR, and the personal health record. Many things flow directly into the personal health record, interoperability standards are needed, terminology standards that Heidi already mentioned. The molecular CPT codes are under revision, but won't address the issues. And there aren't next-gen sequencing codes available today or even planned. Early adopters are finding that they're negotiating coverage and reimbursement with each payer for each patient. This is the early adopter setting. I apologize, I redid these and was not able to update my slide, so sorry. And the regulatory environment, the FDA held a meeting to understand the early clinical user's needs and concerns, but there is no FDA position or guidance available on next-gen sequencing technology. There are no CLEA standards for genomic analysis. We have introduced those into the CAP's checklist, as I already said. So pathologists feel that they have an opportunity to lead in the medical community in genomic medicine. There is no single medical specialty, unless perhaps genetics, but that leaves out cancer that is well-informed about genomic medicine as a specialty group. Pathologists have an opportunity to be leaders in genomic medicine, considering that it is another diagnostic testing modality, and that's what we do. While genomic technology is rapidly advancing, the discovery process for clinical genomics applications will be an evolution rather than a revolution, because we're going to be discovering one gene, one disease process at a time. So we don't want to ring alarm bells with pathologists, but they need to keep up with the changing genomics landscape. So I'm just going to say here thoughts on genomics, and I'm not going to show you all my bullet points, because I've re-thunk what I wanted to say, based on listening to a few things, but also my own thoughts. This testing, if it's used for patient care, has to be done in a CLEA laboratory setting. And it's interesting, because when I walked in the room, someone said to me, we're trying to figure out how to get the lab's CLEA certified. And I said, oh, that's interesting, because I'm thinking about how to get the CLEA labs to do next-gen sequencing, and it's two different processes. So I think one of the aspects of moving this into clinical care is really understanding the business aspects of next-gen sequencing technology and what it provides, and how you justify the cost. So I spent four years intensely the last six months working with various hospital administrators to get my plan for a pilot, it's going to be a colorectal cancer genomics project approved to be able to buy the sequencers, because we weren't a genomics sequencing institution. So we have to buy the sequencers, how you justify that. So I think business plans that include the clinical significance, and starting with a pilot project is an interesting approach for those people who don't already have huge access, and so business plans are needed. Also when we talk about standards, I see that there's a series of talks below, you know, further on in the meeting that are titled standards. I see what they're going to be talking about, I think, as evidence generation. But I think of standards more as the laboratory standards, the SOPs, the best practices, how you know that the data that you're generating is accurate, what alignment protocols to use, what variant callers to use, all of those technical aspects, as well as I think we have to have discussions around what are laboratory aspects that are regulated under CLIA versus what is the practice of medicine in the interpretation of the sequences. And I think that that's a very blurry line. I don't think, I think you have to regulate the quality of the technical aspects, but I think you also have to develop guidelines for that interpretive aspect, but I see that more as the practice of medicine. This is just the next technology for molecular pathologists, and I'm, I can't tell you, I was practically jumping up and down yesterday to be able to move from a talking head to a molecular pathologist who will be doing this. So I think I'll, and my comments there, I'll just thank the IOM committee that I worked on and the CAP committee and the CAP for letting me use their slides. David. And then John. I had a comment for Heidi, but it's also related to your representing CAP and the opinion on this. Going back to data sharing, I'd like to suggest it's not only about altruism versus proprietary databases. One of the unexpected surprises with our ISCA databases, NCBI wrote some pretty simple automated quality data checks for it so that when I submit my data to NCBI they immediately send me back a notice saying that I've classified the same variant two different ways, and would I like to look at those and reconcile the discrepancy in my own data. And then they do a second check where they compare my classification of variant to all the other labs that have submitted that same variant. And the proportion of discrepancies within a lab and between labs was shocking to me since we had all spent a huge amount of time on conference calls developing the guidelines of how to classify pathogenic, uncertain, benign variants. And we thought we all understood that we were doing it the same way. But lab directors within the same lab had different interpretations and between labs was even more significant. So I see this as a quality control measure, and I see it's something that CAP, CLIA, the ACMG can all deal with as a quality control recommendation or requirement to share data so that you get that kind of feedback. And I'm curious your response to that. I think that's great. I don't know what Heidi's thoughts are since it was for both of us, but I think that would be extremely useful quality check. I didn't have time to go into some of the depth, but Dave and I talked about this before. And I think it's a terrific concept that if we could get some leverage within the standards communities and the regulatory communities to leverage that fact, it would be useful. Do you have training sets and sort of examples that you make people go through to sort of understand how to do that classification? Not so much training sets, but series of algorithms about what kinds of data allow you to interpret something as pathogenic. We could provide people with a set of sequence data and say how would you classify this and that would be a way to making sure that everybody's doing it the same way. John Harley. Can I just make one comment because there was a point on my previous slide that I didn't use, which is we need to think about how we train the next generation who's going to be expected to be doing this. And I think we talk about how we're practicing it today, but there aren't a whole lot of groups talking about how we're training in residency training programs. Medical school, I mean even pre-med, is it relevant to do organic chemistry anymore or should we be requiring other forces? Sorry, sorry. Or the bones of the foot, right. I'm struck by the comment you just made and the idea that before there were molecular pathologists, people used to look at slides in the old days and make diagnoses on the basis of those slides. They still do. And all the pathologists I know have these huge collections of slides that they've had from all the patients they ever saw, and this whole business of trying to go back and redo the data and reinterpret it has a direct parallel to what those pathologists do. My pathology chairman still has a huge collection of slides and tissues, and he's constantly going back and getting patients from five and ten years ago and reinterpreting those slides. And so I think we have this idea of having a data, a large database that's kind of fluid, we don't know what to do with it, and that that'll be re-inquired over and over again in the same sort of way is just an evolutionary difference of the kind that you're talking about. Well, and in fact, looking at those glass slides is evolving as well with digital pathology, which is kind of internal to pathology practice, but will allow algorithmic analysis of images and comparison of one image to the next. But yes, pathologists do this. We'll soon be doing genomics on those slides too. We already are doing genomics on those slides. Okay, yes. Jonas, I'll make it here. I directed the vision of informatics in the pathology department, so I could hear you singing for the past 20 minutes. It was wonderful. What I want to say is that the same way that we use annotated images to train our statistical models, we need to capture this variability in the reporting. It's important that there is no sort of forcing of the classification. We need this variability to be preserved in the reporting. Otherwise, we'll miss a lot of information we need in the statistical modeling. And yes, pathology departments are including... We have informatics faculty within our department, and we collaborate very closely with the Institute for Computational Biology. So it's an aspect of the training of having people trained in genomics and computational biology or bioinformatics, and that combination of experts is going to be needed as we move forward with genomic medicine. Jeff, last comment, and then we'll have a break. You got me into this. Don't blame me. The FDA uncertainty is somewhat stressful. I don't know... Is there anybody from the FDA here? Yes. Okay. Oh, great. Oh, well, welcome. All right, well, I was going to add... I was going to ask... I was going to ask Deborah to speculate where the FDA might put its stake in the ground in this area because it seems that it could be at the level of the data generation, but it could equally be at the level of interpretation and analysis or the entire spectrum. We're talking about next-gen sequencing. So it might just speculate when there's an FDA person in the room. So the FDA did hold a meeting and looked at both the data generation phase as well as the bioinformatics phase to hear from people doing this about what is needed. And I think what came across at that meeting, although I only heard secondary reports, was that regulation of the instrumentation would be helpful to clinical laboratories in that when you have the Wild Wild West and everything is changing every month or three months, it's very hard to lock things down. And research instruments aren't required to do pre-notifications. They can change their chemistries. They can do anything they want to us in a clinical laboratory setting that messes us up. So I think that's one of the aspects. And I don't know what the FDA heard around the bioinformatics aspect. So maybe you can comment. Yes. So could you introduce yourself and then talk to Mike? So I'm from Office of Invitro Diagnostics and I was one of the organizers of that meeting last summer. And we asked a lot of questions and many answers that we got back, as you all know, is this is all in development. It's changing all the time and we don't know that that was the answers for a lot of stuff. So we are working with the other government agencies. We are working with CAP and CDC and NIST and trying to get input from everybody to try to figure out how to go ahead. Because obviously we don't want to stop developing technologies, but also we want to make sure that the results people get back are correct. So that's in a nutshell, but I can talk about it. I think that this has been a really great start to the two days and we'll break for coffee. We'll be back at 11 o'clock. So instead of a half hour break, we're going to have a 15 minute break.