 All right. Thank you, Teri. Good morning. So my talk today will focus, as Teri mentioned, on pharmacogenomics at the NIH. Of course, as you can imagine from this title, it's not an easy task to be accomplished in 20 minutes. So I really encourage you to look at two of the resources that were sent to you, background materials that were sent to you with the agenda. There are two files that I encourage you to look at that will complement my presentation. One is named NIH-PGX Resources and Activities. In this file, you will find a list of resources and others. The NIH, in this case, was an institute where I asked to indicate which initiative they were funding that were involving clinical implementation of pharmacogenomics. Maybe there are some resources that are missing there because we didn't receive all the answer from our colleagues, but it's a good place to start. The other file is the file named NIH Grants Over 100K in PGEN. This is a file that includes 160 grants that are above 100K and was obtained by querying the NIH-reported database and that included pharmacogenomics or pharmacogenetics in the abstract or title, and then were selected for grants that had included clinical implementation-based titles. With this, I would like to start my survey of the pharmacogenomic at the NIH to get to this point. What we decided in December last year was to convey a meeting of NIH-IC to get together and talk about what the NIH is funding in this field. It was organized by some of my colleagues and I, and 12 representatives came to present their IC involvement in PGX research. The goal of that meeting was really to survey the landscape of NIH-funded PG research to help coordinate the efforts across the NIH, but also to inform this meeting. We collected several information which included resource development programs, consortium efforts, and award mechanism. I will go briefly go over the resources, some of the clinical trial network efforts, and then I will spend a couple of slides on the outcome and the discussion that we had. Some of these resources, I'm sure the audience know about it, so I will really go briefly over it, just to put the context of this meeting. NCBI supports four main resources, GTR, the Genomic Test Registry, which is a registry of available genetic testing. Right now there are more than 5,000 tests available. GIMVAR, which is a database of clinical significance of genomic sequence variation and their relationship to phenotype. MedGen, which is a phenotype resource for information on condition with a genetic component. And then Medical Genetic Summaries, which are structured reviews about genetic variants and rank responses. And these are really well-tyed with GTR and MedGen. NHGRI also supports some resources in the field of pharmacogenomics. The IGNITE Spark 2, for example, is one of them here. This is covered and updated by the IGNITE consortium. And the goal is to help clinicians to incorporate genomic into practice and also to help a researcher to study the best way to include the genomics into healthcare and in addition to educators to provide genomic training to future F-Care providers. NHGRI supports also Phoenix, which is a web-based tool for exploring data for hypothesis generation, especially around drug response implication of genomic variants across the Emerge-PGX cohort. NIDDK supports the Type 2 Diabetes Knowledge Portal, which was developed as part of accelerating medicine partnership, which is a public-private partnership between NIH, FDA, 10 biopharmaceutical companies, and a non-profit organization, and is managed through the foundation of the NIH. And the goal is to increase the number of new diagnostic tests and therapy for patients while reducing the cost and time for developing them. NIGMS also supports a bunch of resources in this area. You all know about CPIC, which is also funded by NHGRI, FarmGKB. They also supported the PGX IPS cell library and services, which is a first resource of this kind that helps members of the PGRI to basically access and contribute towards the IPS cell library for pharmacogenomics research. They also support the functionalization of variants in clinical actionable pharmacogen resource and the PMT resource, which has the goal to understand the genetic basis of variant in response to drug that interacts with member transporters. Let's move on to the clinical trials. Some of the clinical trials are mainly supported by NCI. NCI has awarded 16 grants with PGX-related aims that identify Marcus Preditti of treatment response and ADR. And most of these grants are related to somatic variation rather than germline variations and drug response. One of the trial is called the alchemist trial. And it's a phase-free clinical trial for early-stage lung cancer patient who have received surgery followed by chemotherapy. And the goal is to evaluate if addition of a target therapy based on patient tumor genetic would help prevent the cancer from returning as well as increase their overall survival. Lung map, it's another trial. It's a phase-2, phase-3 trial for patients with advanced squamous cell lung cancer that has responded to, has not responded to, or stopped responding to the standard of care. And patients are assigned to new treatment that is best matched to their tumor genetics profile if that's available. NCI match is another clinical trial that analyses patient tumors determining whether they contain any gene abnormalities for which a target therapy is available. And assigned that if it's available. The trial has 24 treatment arms so far and 17 agents. Supported by NIMH, there are two clinical trials. One is focusing on the mood stabilizer response in bipolar disorders and another one on the neurobiology of treatment response in major depressive disorders. In terms of research effort, we have NIDDK, for example, that has, is supporting drug-induced liver injury network. This is an effort that has the goal of creating a registry of these cases and to identify clinical, immunological, environmental risk factor for drug and CNM mediated epatotoxicity. GMS and IGMS, primarily, but a lot, a lot of other IC are contributing to this. It's supporting PGRN and I'm sure you know all about this resource. But also, the NIDH is supporting two initiatives. We have the Precision Medicine Initiative, which hosts the All of Us research program, which is a landmark longitudinal research effort that aims to engage one million or more US participants to improve the ability to prevent and treat diseases based on individual differences. And All of Us gathers information on medication through the EHR data and the participant provided information. And they are still developing their genomic roadmap and plans. But also, we have the NIH clinical center, which has a PGX subcommittee that makes recommendation for clinical implementation that are submitted for approval to the Pharmacy or Therapeutic Committee. And their division, their decision to implement a test, it's really based on CPIC guidelines. More efforts supported by NHGRI are the IGNITE program, which has the goal of sharing and disseminate data from multiple sites, implementing PGX testing to contribute to the evidence base of metrics and health-related outcomes gained from using PGX information in clinical care. We also support CleanGen, PGX working group, which has the goal of evaluating and annotating genes in the field of pharmacogenomics and develop systematic methods for representing and depositing knowledge into CleanVar and reconcile nomenclature for pharmacogenomic variants. The PGX working group has proposed four categories of PGX variant to facilitate the reconciliation of PGX nomenclature. Last, we support the Emerge PGX project, which had the goal of validate actionable variant in a clear certified environment and to integrate PGX variant into the EHR for using clinical treatment. This group recruited more than 9,000 patients in over three years. Now, I will briefly summarize the challenges that we identify and potential synergies and collaboration that we came out from that meeting. First of all, a major issue to identify is the standardization of PGX nomenclature and drug metabolist phenotypes across all data type and resources. Specifically, we felt that the allylic nomenclature across data sets, it's really not standardized. And there is disagreement on defining drug metabolism phenotype, for example, ultra metabolizers, poor metabolizer, and so forth. And association are very often gene by gene specific or disease specific. The other thing that we came across was that there are a number of existing PGX resources available to the community. And there is concern that many of the aspects of each resource are being really maybe duplicated in the effort to enhance the PGX knowledge for the scientific community. And so, by definitely reducing unproductive duplication overlap would be definitely something that we need to focus on. Also, another aspect that we discussed was that, as in many other genomic programs, population diversity remains a challenge. And representation of non-European population is not as balanced as we would like to be and adequate. And there is really a need to move away from the five overarching census defined USA population groups that we use right now. Another aspect was the adverse drug reactions that we felt was very often not adequately studied. And there are only small sample sizes studies and therefore not established predictor of responses or not enough evidence of irritability of drug response. And also, we discussed briefly how epigenetics changes affected by drugs are another knowledge gap that we may need to tackle. Last, we felt that effectiveness of preemptive genotypes should be assess PGX wide rather than gene by gene, as I mentioned before, or disease by disease. Also, we need tests that have been really prove reliable from an analytical standpoint and clinical valid that are low cost and can be incorporated, as Dan was saying, in routine medical care in which the turnaround time it's proven to be fast. And we felt that preemptive testing might be really the answer and might represent the low-engined fruit for PGX. Another aspect is the possibility of engaging payers for reimbursement, which needs really consideration. However, this might be a challenge because of the evidence that they might need to do what we need them to do. So, another aspect that we observed that we felt was interesting to point out is that translating PGX data into cancer treatment and precision oncology presents a challenge. This is mainly due to the fact that by the time we have a test available for a drug that is treating a tumor, that drug is already obsolete. So, the need of maybe come up with a companion diagnostic would be probably the answer to this challenge that is presented in cancer. Immunotherapy has been discussed, especially in the context of cancer, because it's the next thing that the field is doing. However, we felt that immunopharmacology should be really explored beyond cancer and infectious diseases. Also, a major issue, which is especially evident in psychiatry, is the lack of biological markers. And defining psychiatric phenotype is particularly challenging and essential to measuring and defining response to treatment. So, many studies in psychiatry, especially, are done on candidate gene and cannot be replicated in large cohorts. And the basically getting sufficient number of participants is a challenge and especially for study replication. What we felt was that basically collecting data from the EHR might be the answer to this challenge. Lastly, NIH, I see colleagues felt that we really need to collaborate more and on several levels. First of all, the first step could be really to look at the different project in clinical implementation and identify those that we could call them gold standards. Examples for the community to look at. Also, it's important that we keep on sharing samples and databases, especially because many times an institute is focusing on their own disease but collecting information that might be relevant for other ICs. And also, it's important that we keep an eye on collaborating on animal and iPS cells model for toxicology studies and epi or genomics studies of drug response. With this, I would like to say thank you to my colleagues. These are the NIH IC that participated in this one-day meeting for coming and for sharing the information. And in addition, I want to say thank you to Melpy who helped me organize that meeting, summarize the meeting, and getting this presentation done. And with this, I open the floor for discussion. Great. Thank you very much, Simona. That was a whirlwind tour through what's going on in NIH Pharmacogenomics. And I would remind everyone that we will be making slides available to everyone in the conference as well as eventually on our website. Howard, Jacob's going to take over the discussion shortly, but if there are specific questions for Simona first, we can certainly entertain those. Simona, do you have a glimpse into what other members of DHHS are doing in terms of... I know FDA has some research going on in Pharmacogenomics and a lot of activity in that area of obviously non-research. You know, Mary and her introductory slides talked about taking out the R word. I shouldn't say it that way, but basically at some point removing the word research and just implementing. So CMS really should be somewhat interested and there's other components. So any glimpse there? Yeah, VA, of course. Thank you. No, I didn't survey the landscape of the entire HHS, but definitely something that we might want to do and see what other big programs are funded from HHS. And I know, as you said, that FDA has started some of the initiative in this area. How about antihypertensive pharmacogenomics? I didn't notice on your list, but I would suggest like you kindly mentioned oncology, immunotherapy, psychiatry. But I'm just curious. There is no activity in antihypertensive pharmacogenomics. It's a huge problem. You know, almost half of the population suffers from hypertension and we actually don't know how many do not respond, excluding those who do not adhere to that. But I think it's not a low hanging fruit, but I think it's extremely important for the population. There's no activity currently? Not that I heard, but maybe. Yeah, so we were funded for 12 years including our no cost extension in PGRN. And so, I mean, we've done a lot of work and we've published, I think, 55 original papers from PAIR on hypertension pharmacogenomics. The challenge probably is not that dissimilar from the challenge in hypertension as a disease, which is there are unlike sort of the drug metabolism pharmacogenomics. There are many, many sort of smaller influence variants. And so, I mean, we're working really to try to figure out if we can sort of put those together and collectively they are predictive enough, but it's not as straightforward. It's a common complex disease and the drug response follows that common complex disease nature because we really don't have strong variants on the pharmacokinetic side for the antihypertensive drugs.