 Okay. So being the policy breakout group, is that better? Okay. Being the policy breakout group, I'm a little bit hesitant to get up here because of course we don't have a lot of concrete things where some of the things that have come out of the discussions are very concrete and I'm always jealous of that when we talk about policy because there's a lot of really important discussions but how we get at them sometimes can be a bit challenging. So like Howard, I'd like to thank the group. We had actually nine different countries represented and so we had a lot of experience both in terms of what the individuals had done but also the cultures within which they are working which is of course also very important to the policy discussions and also we had about a third of our members that were responsible for health care delivery systems and for thinking about how to integrate research into health and they weren't all from the genomics field and so I think that also gave us a broad perspective and I wanted to be able to say that before I put up the first slide which we can now show because one of our early discussions was to come out and make a clear statement with very broad agreement that genomics was not unique in some of the questions that we were thinking about and in terms of the policy solutions that we would need and that it would be very helpful if we were to think about it and think about the kinds of solutions or pathways to solutions that we need to get to by thinking about genomics as another tool for health and that it's one element that needs to be considered in moving towards personalized medicine that we can look to past examples of how other new technologies have moved into health care and learn from them and think about them as we're trying to put together our own next steps. Also I think one of the strong recommendations from the group is that we needed to think about what genomic medicine has to offer with regard to the comparator of what our current care pathways are and where do we see the differences to make to enhance the current care and move from that standpoint in what we're doing. So in terms of the priorities that we did talk about we were talked about in the beginning all of the various issues that the many speakers raised through their talks and the challenges but I think this list while it might be a bit simplified and certainly doesn't cover everything that came up or that everything that we discussed I think these were the key things that we acknowledged as being major issues. Several of them are addressed or have components that are addressed from other working groups and so we didn't spend time on them but of course engaging the stakeholders the issues around funding who's going to support the work and the research that's needed as well as the technology assessments etc to move the work forward who are the right decision makers for the health care in different countries it varies it's different in every case that of course complicates trying to think about moving things forward in one nation let alone as we're trying to look internationally and then of course also the patients are the stakeholders and that as we can engage patients and this has already come up in the breakout reports then they will also push for this the benefits from genomic medicine as part of personalized care personalized medicine to come forward data sharing obviously it never fails to come up as a key issue privacy informed consent the morass of legal issues again within one country and particularly then we start talking internationally about how to harmonize or find common principles around privacy and informed consent so that we can promote better data aggregation to enable the research and the science and to promote sharing as well from from the ethics standpoint the regulatory oversight that came up this morning in particular around FDA and the situation that we're facing but also in others and then the cost benefits the cost and the benefits of adding genomics to the care systems again thinking about it from a systematic our systems perspective I think among these the engaging the stakeholders issue we didn't really talk about in terms of opportunities and next steps I think some of that has been addressed by Bruce's group and others it just didn't really make it to our strongest priority where we actually spent most of the time and pretty quickly got to a focus on was this issue of how do we determine the cost and the benefits of adding genomics to our care systems and so that's where most of our recommendations or detail of the opportunities will focus so first with the data sharing and the regulatory issues the primary point that our group really wanted to bring forward in terms of what are what are should our next steps be is that there are many different groups and different alliances that are out there working on this in an international perspective we've heard a lot about Erdick in rare diseases there is a global alliance there's a genomic medicine alliance that was talked about this morning there are just a lot of people out there already working on these and also some of the issues around privacy and informed consent that enable data sharing for the research to go forward are also focused on the research end of the spectrum and not the implementation end in terms of integrating genomics into care and so that this might not be the best place for our group to form to do a lot of additional work but where it could be very useful in the future for people from this group to think about is trying to to map what the different activities are from all of these different groups and alliances and what are the issues that they're working on so that we can both know who is working on what and how they're approaching it so that we can all learn from it but also to do the gap analysis of and see is there a unique place that we can get to where we can make a contribution that is not already being addressed by some other group with perhaps better expertise than we might be able to bring to it and so there were also talked about whether or not we might encourage a network of networks to form again around those you know all of the different groups working on informed consent or all of the different groups looking at particularly engaging different sets of stakeholders and we put this up here but acknowledging that network of networks is a great policy phrase that sounds good but is really questionable as to what it might actually mean so but we did think that it could be a way to share information and to try and articulate a more more clearly what the responsibilities are and who has ownership of trying to push different issues forward because we thought that would be helpful again just so that we don't all try to duplicate in the same the same problem area so moving back over then to the cost and the benefits and trying to think about that in terms of what will genomics add to care in a delivery system and we talked a lot about trying to define what is it that we would need to have in order to go forward and so there is of course the technology assessment that evidence but there was a working group that that's we've already heard from talking a lot about that so we didn't dwell on how do you determine what the evidence is but of course in addition to the scientific evidence we need to have demonstrated clinical utility and we need to be able to articulate what the costs are they could be small costs or they could be large costs but those costs need to be known so that they can be weighed in balance to the clinical advantages etc so again this is a place where one thing that could be done would be to to look at and do some analyses on different successes in the past those that had a great deal of evidence to support them such as pet scans was an example that we talked about as well as those new techniques or methods that that are put into care very rapidly sometimes without a lot of evidence and what's what is it about those that that have them move in and then of course the difficulties with getting them out of care when they are when there is evidence to say that they're not helpful another potential opportunity where a group could come together to look at this and this was something that we thought we needed to take a look at the literature and see what might already have been done in this area what but would be taking the perspective of the health care delivery system trying to walk through that in a pipeline fashion and think about where would genomics make a difference again to help us get to the point of being able to define where the economic costs would be and where the clinical advantages would be we thought about this along the lines of different disease models that could be done there's also talk about really if we wanted to make a difference for health care and in a large scale would be looking at what is genomics going to do for chronic diseases and there seemed that maybe because the science may not quite be there yet there hasn't been as much work in looking at or having models or pilots to think about how genomics might be able to improve care for hypertension or diabetes or mental health etc and but that what we really needed to get to was where is genomics going to make the biggest impact on care and that's how we're going to engage the state engage the decision-makers and provide them with information and evidence to get them to be willing to try and integrate this into care there we go so I think this is about my last slide so again thinking about what will we need the economic issues and the need for more economic analyses better economic analyses inputs to have into the system for helping us to determine evidence came up we talked a lot about who else is already doing this again thinking about the fact that genomics is just one tool this has been done in other places and we should look to places like the health technology assessment agencies and in various countries pharmacoeconomic societies that do this all the time to see what we could learn about how would we structure some of these analyses for genomic methodologies in particular they're talked about the fact that in Canada as one example they are requiring in some cases that health health economists now be part of the research team so that those questions are being brought to the table at the time that the research is being designed and all along the way and then also needing to recognize that it's not just about technology assessment in terms of making the decision but that that the technology assessment then becomes an input to those who are making the payment decisions around care for insurance or other health systems and of course again as we've heard over and over again throughout the meeting and in this these breakout reports needing to engage those who are making the payment decisions one recommendation for something that might be worth trying to pursue would be to work in a system other than the US we didn't come up with the ideal system but where there is one or maybe just a few centralized payers so that again we could have conversations with them about what is it that they needed to see where we have hope of trying to get something that's definable again unlike in the US where we get lots of different answers so that we could try and look at a particular case and carry that through for a pilot or demonstration and use that then to move on to other examples so that I think was in this area was our top recommendation for what the opportunity would be in terms of what we might do as a next step and then while this the other issue about trying to integrate economics and economists into our research teams is something that I think there was also a lot of agreement with and that in terms of who can act on that would be funders but I think anyone really and how they're designing the research projects and putting together their research teams could look at it and I will stop and take any questions and also invite the group please and the synthesis of this was all very different from the actual flow of our conversations so if I misaligned anything please please stay up so terrific I I guess I would just following up on your last point and the discussion we had earlier about evidence generation it would seem that if there's already a project pilot project going on in a environment that lends itself like a single payer environment that might lend itself to economic analysis and it's not happening that would be something to really try to embrace that a way to find the resources to make sure that that analysis is done or secondly to consider a an existing pilot project from any of our global communities and making sure that it or selecting an environment where that could be done with the appropriate economic analysis as a demonstration project as you say and the other it seems that the this this whole area it should be a significant interest to industry because it's their their ability to launch a product get it on the market get reimbursed and adopted is going to be predicated on having the economics work in their favor so would be an opportunity I think to partner not just with some of the agencies you mentioned but with industry as well that's a really astute approach I think and this community is in a place such a project or several projects would be easiest to do if there wasn't a lot of population variation in the disease for one of the bed not a geneticist and also if there were a straightforward genetic test that could be applied to identify the target population because that makes the Markov model or whatever economic tool you're going to use to do the economic analysis more straightforward to use so choosing the project wisely would be of high value and this group's probably an ideal group to make that decision yeah I would agree that a focus on economics is important the only point of contention that I might make is that there are actually different ways to look at this that can take into account variability which is to model so that you look at a threshold of effectiveness model so that you can manage to say you know if the prevalence of this particular genomic variant is this level it's above this level in a population it is cost effective to do this if it's below this level it is not cost effective and so in terms of how you define the problem and also define the model you can come up with very useful things that can be applied to an individual country or group once they know what their what the prevalence of that is in their particular population yeah so yeah so the point that was being made is that there's lots of variables and the difference between an economist and the statisticians the statisticians require data right so and so all of these are assumption based and so the doing sensitivity analysis on the models to and that allows identification of what are the most important pieces of data to really understand because they most profoundly affect the performance of the model that is also extremely important information because that can drive the research agenda to say you know we don't know the answer to this but it doesn't matter because if you're at between one and a hundred the model performs exactly the same but if this if we're off by a factor of two in this one the model completely works differently so right so just the point that she was making was that defines the prioritization of the evidence collection