already with thanks everybody and I'm here as representative of the IMPC I've been on their advisory board for for several years and it it's it's been a labor of love and so just to to baseline us we have a goal for 2021 to 2030 and part of that goal is to advance the the number of nulls and phenotypes which which we have now it is well as to make the data integrate with other data sets and not evolve away but to a durable impact so the slides I have there's there's no projector and so with that we had a slide here that Chris Austin showed about some ideas that we might consider for our next phase and we all think about mice as mammals and humans as mammals too so with that I would like to thank the folks here that bring to us a human perspective and for us to use this this hour to talk about the commonalities of our shared goals of mammalian phenotyping whether it's mouse or a human so with that we'll we'll start the panel and I had some slides which would help to baseline us we'll wing it and we'll just just use the microphones so thanks well I mean so there are two things that I think about that I've been thinking about over the last year given the context that we're entering year three of the Comprogram we have two and a half years to go we have about a two-year typical planning process unlike a CGE miraculously came to life in one year we're not going to try and do that we're going to take our time and plan things so on one side it's the scientific issues on the other side it's the political issues it's aligning program goals with I see interests and understanding funding mechanisms and mechanisms of doing diverse support for large programs which is essentially I'm saying common fund so for I think for the NIH side all of our thinking is colored by those practical issues probably from the science side you can just think about the scientific issues so maybe we should start there start with our success stories which is a CMG collaboration and a null phenotype resource it seems to be working really well are there things we need to do now immediately in the next two years to improve that resource to make it more accessible to the clinic to make it more relevant and more efficient so we've heard the success stories would you like to say some would you like to scare us with the things that keep you up at night that you worry about that are problems that you know we need better solutions for well I must say that I think I found this I only was here for this one day but I thought the science and the opportunities that we heard about throughout the day were really quite astounding so I would think that we should all go home one enthusiastic and two invigorated from today's meeting Chris laid out several challenges at the beginning of his at the beginning of the day Chris and I were just talking at break and I was saying that I am recently become much more enthusiastic about the prospects of developing therapies and part of that enthusiasm stems from the big success of CF but there are other examples as well and but more I suppose a more profound sense of optimism comes from the at least on the Mendelian diseases frankly from the progress and Mendelian disease identification and that effort I did I didn't make it clear my talk but the numbers that I gave you the numbers for the CMGs but obviously the communities lots of people in the community doing the same activity so overall the number of new disease genes has gone up dramatically and so your chances of developing a biologically rational cure are much better if you know what the molecular basis is to start with and so we're making tremendous progress there the path of physiology is always the more slower activity but the work of the mouse geneticists in terms of making models which are not only helpful for disease gene identification but also provide the resources that are necessary for studying pathophysiology and understanding the functional derangements that go along with defects in genes that we never heard about before Nico mentioned a couple of them in his talk that are just eminently forgettable except they're very important biologically and so just a lot of things that we wished we could have had as as little time as five years ago we have now the other thing I must say is we're hearing about some funded work from NIH I get the sense that there for good creative projects there's money available and that we haven't been able to say that until just recently so we need all to make hay while the sun shines I think and so I found that very all of that very positive in terms of the collaboration I must say based on the work between the CMGs and the comp program comp PIs that I think both groups are eager to collaborate and there's a sort of an energy of activation I know Bob and I talked about collaborations for a couple years before we actually got it rolling but like many of these things once you get it rolling it it gathers momentum and I think both Steve and I feel like once we begin to see mice with phenotypes the momentum will build quite rapidly and that momentum will be generated not only by the CMG centers but also by their submitters the people that are remember I said they're supposed to be the ones right in the papers and and they will love having this data from the comp project as well as and I didn't make this opportunity if you know you want the mouse model there's an opportunity when the live mice are still on the counter on the available on the shelf I guess you guys say that there's an opportunity to give those again that shortens the whole process and moves things along much more quickly so so question for you Dave and rest of the panel is when you want the the information or need the information and I had a slide on that but to speaking mouse or speaking human the the ontologies can be so so different at times in the accessibility of the flat files the accessibility are you going in by gene or phenotype and what's the phenotype called so what would be most helpful to you and to others in the human in the clinical in the patient centric of facing fields because we have our own jargon right and we would like to make ourselves useful or data useful to to your needs well I'm not the most facile informaticists in the room that's for sure and but I take what I find is that the bedrock at least for me are the gene names and so one can go back I find that one can go back and forth pretty easily that gene symbols the universal gene gene symbols right and I think the the databases for both species are also not too complicated omem and related human catalogs and then the mouse databases are also quite I think easy to use so I don't find that much for problem I do think that as the CMG comp collaboration moves forward we're gonna as I said we'll we'll build better more transparent informatic tools to help with that that very problem that you mentioned when I say we'll build it won't be me somebody will build it I mean so we heard about the situation in the UK where they have the National Health Service they seem to have ready access to the full medical record we heard about the UDN where they bring the patient in they do their own in-house phenotyping and genotyping is there an issue trying to reach out to these X01 these more loosely connected collaborators how do we make contact with the bench researchers to do follow-up stuff and make our resource available to them it seems to me that's a challenge they know their phenotypes at every CMG there's some clinical experts and then at every CMG there's some clinical experts that can talk to you at length about the phenotype and they can refer you to the submitter who's actually sitting there in front of the patient and examining them and I think so yeah I was just going to say it was a year ago that Dr. Kent Lloyd approached us and sent us an email saying we are comp to here we are not UDN and we are not CMG either so if you are what I call grass root clinical geneticist working in the clinic you just heard a beautiful presentation by Dr. Rowan as we are doing almost the same things and finding a lot of variants we are unable to do gene discovery as such because you have to look for means to find collaborators I feel like we were very fortunate Kent Lloyd approached us and said here's what we have this facility and availability of the comp to project so the way we started off is what are all our variants of unknown significance that we have found and do we have any genes of unknown significance then we also came up with another another I guess category where the genes were already identified but are they phenotypically going to add more which we also heard in the last couple of days which would be our gene of interest so interestingly for one of the patients the mouse model was already there and the phenotype was slightly different where there was cardiomyopathy so we were able to take that back to our patient and say can you go do an echocardiogram for this patient so we make sure that there is no cardiology issues going on for our patients so I think it was it's a very good way of back and forth and gene name would be a great way of looking for mouse models can you give us a rough idea of what your demand would be for number of variants in a clinical year that you would be seeing and have that the level of questions around does it vary have you found that it's pretty steady state but I would say that just over the past I guess six months we find it like up to 30 variants from my clinic alone and that's only like a small percentage so we would be finding tons of variants which brings us to the next question how are we going to prioritize what genes we are going to be working on and what which ones to choose because maybe I have like 20 genes that you know like they're willing to model so are we going to look at the most common ones or the ones maybe are going to find the max maximum possibly possibility of identifying it in your mouse phenotype or the ones that are most severely affected or the ones that affects most individuals so that's kind of a question I so so so in our six part strategy for a decade for phase three and four that there really covers a lot of the first half of it and beginning the dialogue now for what type of alleles is the black six background or timelines compatible with your need for information to clinic would this be used as a diagnostic tool to help understand the treatment which would be a more immediate concern with a patient that's coming to see you or is this something that you have as an academic purpose that the timeline wouldn't be as critical because you know for us to understand to put ourselves in your shoes is is really important today so when you are academically is very different than being a clinician in front of a patient because most clinicians would experience that on the one hand you feel the excitement of finding a diagnosis on the other hand when you're giving the diagnosis the next question the immediate next question is so we have found the answer what can you do for my child what's secure is that a cure or what's the next step treatment and yeah go ahead I just I wanted to touch on the variants of unknown significance first so just for in the human exome we usually get about 20 to 25,000 variants coding variants and so the whole trick is to late to win or down that number to get as close to one as you can simply by frequency known functional facts model organism databases essentially reaching out to every little bit of information you can find available and doing that it often is possible to get it depends on the mode of inheritance but it's also often possible to get down to a rather small number of reasonably strong candidates then a tool like gene matcher is very powerful because it's just you just put the gene name in there and then you just don't have to do anything until you get emails and finding other cases with similar phenotypes with the rare variants in your favorite gene or one of your five top candidate genes set you off in the right direction right away and can help prioritize the variants but these are very much research questions they're not the in the clinic I think it's fair to say that if you if you get a result in a known disease gene and your variant looks like it's functionally significant then you begin to have some traction in terms of what you're going to be able to say to the parents to the patients even even if the variant has not itself been described before okay so so that could you just so Karen had talked about that previously can you expand a little bit on that I mean it must be such a changing situation from years ago when you took your boards and there were three known genetic diseases and they were well described and when you said to me to the patient you knew the prognosis you knew the extent of the phenotype you knew every now you're overwhelmed with new diseases where that patient may be patient zero what do you say to them in that situation because you it must be difficult we say exactly that that you know like it's so rare we don't have much data on this and there are probably you know like if it is a really known disease causing gene which is what we are dealing with right now but that there are only 30 other individuals and then you know like I think most parents grasp the enormity of oh oh my child is has got such a rare disease but it depends on the situation some people are like feel the sense of relief to have known what to know what the child has and there is a reason for it and then though there are others who immediately get on so what can be done what do you know about it and where can we go in that instance we do look into like who is working on it and so we may find a researcher who is very interested in that particular gene that we are looking at and look to see what's being done so there may there could be a natural history study going on so we'll send them for that there is one particular gene where there is brain ion accumulation so we look to the mouse models to see is there anything you know like in the mouse model and if there is and if there is brain accumulation then there is ion kilators available and some are penetrant blood you know like they they cross the blood brain barrier so that's where we are beginning to look to prioritize as to is there something we can take back to the patients if we do develop a mouse model and if there are phenotypes that could for which we could do either drug screening or some therapy where we could see tangible results at least quantify something I think that's how I'm beginning to look at things and if I could just add one comment when I was seeing patients in the clinical setting I used to joke that if I was one internet search ahead of the families that were seeing me I would probably be okay in the clinic setting but you know really and families are sometimes their own best advocates and I feel that it really becomes a therapeutic alliance so to speak in terms of encouraging them to find other families and to be empowered by being able to connect with investigators I think the internet and the the availability of these tools on the matchmaker exchange and some of those that have been described at this meeting I think is really quite remarkable and you know some some families will take their child's care sort of into their own hands and we'll reach out to researchers and find ways to you know advance a therapeutic development which is quite remarkable yeah I mean we saw the UDN reported on in the New York Times recently as a medical mystery case right a couple weeks ago purposely to attract the attention I mean I thought maybe they were disappointed with matchmaker that wasn't good enough they had to go to New York Times but it was kind of an interesting story but yeah so we're kind of wondering is there any is there any outreach we should be doing into the patient advocacy community that would be useful I think this one thing that this makes the point of is that as we heard earlier today geneticists currently do a lot of education so when you send let's say a whole exome a clinical whole exam and a patient you if you want things to turn out as best as possible you need to explain to the family what kinds of data you will get you may find an answer that answers the problem right flat out out of the bat out of the box you may find a lot of data that you're not able or you will find a lot of data that you're not able to explain perfectly and you'll be able to rule certain things out also and so I find at least that when you educate the patients before the test and then you come back with the result that you're not clear currently how to interpret they they say okay I got it you said that might be a possibility and how can we move move forward and understand that result more clearly as we go go along so but it does take a lot more I would say counseling of the patients and their families in the clinic both before the test and after the test comes back to to provide the best possible outcome and I think the patients in general understand that the pace of research these days is moving along very quickly and so a result that we're not able to interpret today we may be able to interpret much better a month from now or two months from now or three months from now because the pace of discovery is going so quickly that one of the first reports of the Baylor clinical genetics lab made the point that the solution the diagnostic rate was about 25% but of those cases that were for which a diagnosis was made the diagnosis involved a gene that was shown to be a disease gene sometime in the two years prior to the time the paper was published so if you've done that test two years earlier you wouldn't have known what to make of that result at all so the pace of discovery is really moving along quickly so one thing that we've started to do or have been doing on on the mouse side and this is the comp and I'm PC it's it's in frontiers in the EU is is getting involved in the care for rare in the rare disease networks and I know next year is the campaign for European year for for rare disease in 2019 and we're part of that how can we leverage what we already have for enthusiasm for activities to reach the clinicians to reach the clinical investigators if you will to what what meetings who are our customers and stakeholders here can you help us to to understand that around the rare and how can we better explain ourselves position ourselves and work for for your benefit I was going to say I think most clinicians at least the geneticists are well aware of mouse phenotypes being available they probably you know like don't know how to reach out to somebody maybe that's one of the things where you know going to while having sessions at major meetings at ACMG and the other group that we are kind of living out here are the genetic counselors the NSGC our genetic counselors do a lot of counseling and they're also very involved in figuring out things for our patients so NSGC may be a good place to also advertise on you know like there are these phenotypes available and there is such facilities available yes so I just wanted to sort of revisit this idea of outreach and and ontologies and wondering be there are so many different human ontologies being out there and I know Damien and his team have been doing some really good work trying and the Monarch Consortium have been doing a really good job trying to to crosslink these and and to make our data more accessible to to clinicians and you know as well to patients because what they hear is they hear the human terms of that their clinicians and their genetic counselors use I'm just wondering if there you can see a role in how how how willing do you think the general community beyond the consortia are to get involved in sort of actively helping us to sort of get our data out into the purview and make it more accessible to genetic counselors and patient groups and and others who could potentially benefit because as you mentioned before patients can be their own best advocates so in a digestible way though because I think often what what we put up there is digestible for us but not for someone who hasn't spent their life their professional life doing this sort of thing you know I think I have no data on this so just just my opinion I think if you went around Johns Hopkins and you said what are your thoughts about comp just my random colleagues in the hall most of them would have never heard of comp they would know nothing about it so the genetics people do know about it but the rest of the clinical service even in the Department of Pediatrics doesn't know about it but what they will know is when you publish papers I think going to meetings is great talking at meetings is great but I think all I hope all physicians are aware of PubMed and use it widely and and so I think you had we we were all admonished to publish and and it's just really important to get the data out there and the PubMed makes it really accessible no matter where you publish so just getting it out there is important and kids first so I was sent a lovely slide which which you can't see but but I can and because I was asking at the break who has helped to break the ice here and for speaking mouse and speaking human and kids first has done some a wonderful work to start that monarch has done some I did a screenshot from some of the monarch initiatives where they're breaking through to the anthologies and if somebody from the panel the audience can speak to those efforts because if they already have a headway then we probably best to to follow that if those are accepted ontologies from the collective here may offer an answer to the question about data dissemination on feeds into the ontology issue as well a Google launch an experiment three weeks ago called Google data set search some of you may have heard about it some of you hearing from first time but I believe in few years this will be the place where either your data is seen or resources or not and this is actually linked to the data technologies in action that will allow one to actually annotate one's resource whether data patient etc using metadata ontologies and such so it can be searched in intelligent way this is kind of inverting what Google was really originally about which is searching unstructured text html and the evolution actually was gradual until this point in the sense that Google asked webmasters to contribute more and more structured content using link data technologies but now with Google data search they actually flip it completely they say we will index whatever you tell us to index but you give us metadata in this link data format and the searches will actually show show you show your research so anyway this is my projection that this will be actually transformative and it gets the stuff where it's a publicly used resource I mean I Terry talked about this what the hit rate of PubMed is a thousand times higher than our hit rated a million times higher I mean it's the holy grail you can get into PubMed people will find it so hence you have to publish hi I have a question slash comment that's for Melissa but for the panel as a whole and it seems to me especially after hearing Melissa that there are certain areas of human disease and disability that are really being underrepresented by the comp phenotyping pipeline in a particular how do we evaluate intellectual disabilities and mice who won't take IQ tests and I'm I'm just wondering why not take a bunch of genes and some of them must have already gone through the pipeline why not take a bunch of genes that are known to cause intellectual disabilities in humans and then just ask what are the pleotropic effects or what's the brain pathophysiology or what are the behavioral assays in the mouse that might actually reveal a relationship to human intellectual disabilities it may not be as hopeless as it appeared I think that's a terrific idea and what Nora what Nora would counter with I'm sure Nora would say do imaging right yeah yeah no I actually I think that's a really very nice idea and I you know none of us is not even thinking that we're gonna have a single IQ test that's going to be useful for mice to help us understand their level of cognition most people would even argue it for human beings that the standard IQ tests are flawed so you know let's get out of this mindset of we're gonna have one test I think what we have to look at is functional domains and I think the folks at NIMH have a very interesting approach to this are you all familiar with our doc is anyone I know that NIMH is probably not as well represented here at this meeting but they're really trying to take these really complex behavioral phenotypes such as you know anxiety and depression really break them down into their components and not relying so much on the diagnostic and statistical manual for mental health conditions the DSM 5 which has been sort of the standard for diagnosis of mental health conditions but essentially what I'm suggesting is that there may be some sort of parsable entities that are domains of say executive function that you could find something comparable in the mouse or attention that you could find comparable in the mouse that might actually map on some of these complex human cognitive and behavioral phenotypes and could actually give you some traction in trying to sort out which genes and which phenotypes are linked to those genes and really start to make some progress in the intellectual disability field to use the genetics to help understand the phenotype in this case to do it by I guess so I'm new to this discussion so but for me it sounds like the question is what is the question so I think that I understand the utility of oh I found a patient in somewhere in the world can somebody please make a mouse or I can diagnose them but from my perspective I'm sorry to be I mean you know I use multiple organisms the mouse is not the correct roots because it will never scale ever every exon will derive a minimal of after day's point from very high quality bioinformatic analysis we're going to still end up with two to five can the genes and that number will stay plateaued for a very very long time especially for the denovers that will keep hoping up so I what I'm thinking though is that there is amazing opportunities to actually prioritize sets of alleles that will be useful to the community not necessarily for diagnosis but for biology so you will never compete with the zebrafish model where it costs 1500 bucks to test an allele you know it's just never going to happen but the zebrafish model sucks at consistency it sucks at looking at progressive disease states it sucks at generating enough biological material to do transcriptomics to do metabolomics to do other interesting things and I'm speaking of the zebrafish because this is what I know but I think the same the my my fly colleagues and my worm colleagues will say the same thing so I think it's not you know I think it would be I mean you know the the knockout project was amazing because it answered also biological questions and you know questions of tolerance and genome plasticity it might be useful to think about in terms of what is the next really big question impact it's going to be right so I heard earlier on today about the variable effect of nonsense mutations on transcriptional regulation splicing this and that this is a fantastically important question that we're going to have a very hard time asking in humans not least because we don't even know where the nonsense allele in a fibroblast which is all going to get from a from a human or maybe blood will have the same misplacing effect in the nervous system which is what we really want to know well I think this group is is is supremely positioned to answer this question I also think that there was mentioned about laminin right and the spectacular you know disease on this well these are some of the alleles that might well be made because there's a very deep biology that could be gleaned from that and so on and so forth the last thing to say is against this sort of proselytize you to sort of my view of the world a little bit is that there's two other questions that I think comp should consider answering then I'll shut up I promise the first one is the species specific activity this we've got to face it's a major bias both positive and negative depending what our starting point is and again I think you have the setup of the tools to actually answer this question in an absolutely comprehensive fashion we should be making some of this is symbol double mutants and asking the question the second thing is is a little footnote that somebody said early on remember seven percent of of children of individuals are going to go clinical exome sequencing at the moment are two first but we do not understand truly whether these are two independent events or whether additive or they were multiplicative I think these are areas of of I'm gonna call it clinical biology that we really need to understand so these perhaps are some of the big questions that you might want to consider anchoring your next activity as opposed to more in which I live in our house yeah I mean we're sort of talking about finishing because we're halfway through the null allele on a single background and it's very doable in the end point is in sight and then the opportunity once we since we have this platform to pursue other angles but I think you're right we're going to take a clean slate look at things we're going to look at alleles variants complex genetic interactions we have to consider all the model systems all the experimental systems when we look at that but I think comp comp or you know mega mosque is what I'm thinking but could I ask a Nico question yeah just Nico many mis-sense mutations in fact I would say that the vast majority of mis-sense mutations actually have their negative effect if they are deleterious have their negative effect by disrupting protein folding and so the zebrafish of course lives at a different temperature than mammals so our alleles that disrupt protein folding in mammals do they also disrupt protein folding and to a similar extent when introduced into the zebrafish the only answer I can give you in that context is that when we look at specificity data as in we take mis-sense alleles that we know a detrimental to function in humans and we test in the fish we see the same level deleteriousness so I guess I'm not asking the question fully but all I can tell you that if they if they're acting as deleterious in a human because they're folding they're still acting as deleterious in in that system but I do not know whether it's because of folding or not but the false positive rate is essentially zero so a question for for the clinical folks here and but but for the human phenotyping where are you seeing the best place for that data to go so then we could be a fast follower if you will with the mouse data and instead of us looking for our own database to for for you to go to where do do you think the collective knowledge should reside is the one that you use now is it omen is it something else I mean where should we be looking yeah all right so I think I have a one kind of a very general question which is you know phenotyping is the bottleneck in terms of imbalance right genotype phenotype with whole genome sequencing we have much less phenotypic information second is we have problem matching in our model phenotype with human phenotype shouldn't this bottleneck be addressed by now turning to molecular phenotypes as possible solution and let me well of course you guess my answer right my answer is yes and I'll suggest to you know one is epigenome which may give us a clue about effects of regulatory variance in terms of inducing allelic imbalances in the same way in the model and human which is a kind of ideal control experiment where we have locals in a heterozygous state within the same nuclear environment right in the same cell and we can observe whether we can recapitulate say effects of variants on changing local methylation in cis as a signature of transcription factor binding effects and such the other molecular phenotype maybe metabolom right because it's the first one that has entered clinic it's now in wide use by major projects so if you could match metabolic perturbations so multi metabolite perturbations in humans to those in mice we can actually maybe arrive at a conclusion that some of the phenotypes that are not recapitulated sufficiently at the whole organism level may in fact be recapitulated at the molecular phenotype level and in that way validate our models and gain insights also in the mechanisms you know the molecules that mediate the effect on the ultimate phenotype this this is very important also for complex diseases that are quite heterogeneous at the organism phenotype level and may allow us also the side effect to dissect these more complex phenotypes yeah I mean I think if we had the money and technical support to be able to do RNA seek on our knockouts it would be fabulous I mean to wreck links to the links program that it's just a fungible digital Bitcoin can take you a lot of different places I think cost is an issue but they are now as they say metabolism and son and maybe targeted epigenomics which actually are becoming quite affordable actually one can argue cheaper than complex phenotyping of humans so that the first all let me say that I love the idea about using the metabolomics profile as a broad and sort of one stop biochemical data for each patient there are published data showing that the closer you get to the gene the more penetrant variants are and the more easier it is to see the genetic effects so that would be all to the good there's a lot of biochemical data already out there but it's not organized into one single test so you have to pull it together from all different places and and that takes time and money and so forth the thing about phenotyping is that it's very it it's it's important in my view this just a personal bias to do it in a uniform way in a way that's searchable and recallable and that way is not the medical chart as the medical chart currently exists if there was a and if there was a program that would go to it let's say epic and pull out the data in an organized epic is the electronic patient record at most of the it's currently the number one one in the country it's completely opaque to many users but if if there was some way to go in and interrogate what's in the epic chart and put it into a very straightforward accounting of the phenotypic features that would be extremely useful we in phenode B we record the phenotypic information in a very standardized way it's very quick to score it means that we score every patient using the same queer set of data queries and it's very it's a very robust way of evaluating the phenotype of not evaluating but of scoring all the phenotypic data but we don't have we have not built a tool that will let's say go to epic and extract those data out of epic those those data are coded though right as opposed to a DB term it was just clarify I was not actually referring to phenotypic or EHR date I was referring to actually measurements that can be done comprehensively on hundreds of metabolites and so on that may be a compliment to what you're saying but it's actually a different approach yeah pulling data out of epic is probably illegal anyway the only comment I have to say about the molecular genotyping is finding a gene or when you do a molecular analysis is going to be effective only if your phenotyping is good because of the unknowns in the genome let me just add one additional advantage of molecular phenotyping is that in fact phenotypic information can be exchanged freely without danger of the identification right so you can publish all the phenotypes and have a matchmaker right on molecular phenotypes without any concerns because metabolic profile is not identifiable now by chemical perturbations you know by chemical testing lab will tell you that you know they can read these metabolomic perturbations and find all kinds of things about nutrition disease and so on so I think that it depends maybe on the domain if you're too far away from biochemistry then maybe this may be a not familiar territory I think I know that Baylor is probably moving fastest with metabolomics and I see art behind you there art are you using artificial intelligence to it to score the metabolomic profile that's a seems to me to be a perfect opportunity not to my knowledge well I should disclose I do have a research project with Baylor genetics where we're doing exactly that you know detecting perturbations at multi metabolite levels so it's five o'clock and some people have to plane so if you need to leave feel free to I just had a quick comment about the use of electronic medical records and one of the mechanisms that has allowed Stephen Kingsmore to have these 56 hour turnaround times in some cases for his rapid whole genome sequencing of ill newborns in the NICU has been an approach that uses natural language processing and AI approaches artificial intelligence to extract meaningful data from the medical record it's not just looking at HBO terminology but it's actually a fairly complex algorithm which I know I couldn't begin to explain to you but has shown to have some remarkable efficacy for actually being able to home in on what are the relevant genetic variants that might explain this newborns medical problems and phenotype so I think there is some emerging work in this field and I'm sure there are others who are doing similar sort of approaches because the the MR systems are as you say opaque heterogeneous and bulky to work with so we have some other strategies we think we have to use so I have a question just on common fund synergy is there an effort to combine the data sets from the different common fund you know just as thinking just common fund efforts because one advantage of that is for all the money invested by common fund over these years at least it's protecting and integrating those combined efforts there are a lot or related there's rare there's personalized there's I am PC comp is there a common fund ideal on how to preserve and retain for durable impact these collective efforts well do we have anybody from data commons I don't you mean here today no I think so we might have a PI anybody involved in the data commons we do have an effort within the common fund called the data commons and it has a new name now which I'm not even going to remember but it is to basically provide a place for not only the common fund data sets but other data sets and allow integrable searches across them and and also for them to be used on the cloud and my understanding is that the the first three sort of pilot data sets are the model organism databases top med from NHL BI GTXO thank you which actually used to be one of my programs so and also kids first is sort of latching on to that and my understanding as you again is a little bit further down in the pipeline so we're trying and also the microbiome project is is you know is poised to go in so it's something we've been trying to address for a number of years I think now we're just just actually starting to make progress and doing it because we've made a recommendation at least the advisory board did that the IMPC comp effort have a dedicated working group to looking towards that to meet your needs while we're still in phase two and because we want this effort whether we are at 8,000 20,000 genes to detect datasets to be able to integrate and have impact for all the common fund efforts for for 20 years right and I guess one way that I'm thinking about is if you're if you're already working with kids first and UDN and some of the other programs you know you can all sort of go together at least have some some things and some strategies in common but the other thing to say is that our office is hiring somebody to a person a full-time person to actually work at reaching out to the programs that aren't in the in the first three datasets so again it's something we haven't hired that person yet but it should be happening within the next few months while we're on this topic I think everybody in the room recognizes that exact and Nomad have been a tremendous resource for interpreting genetic data and we need a similar resource for whole genome data we have really quite puny whole genome data we heard today I think 125,000 genomes in top med are those accessible in an exact like Nomad like database sorry thank you thank you for reminding me to use the mic the data itself is available through DB gap for 55,000 of those the rest are accessible within the program and the informatics research center has done joint calling but I don't know just how much of an answer I can give you today as to how grand I was going to say I mean Gonzalo Abba cases group is creating a Bravo server and the Bravo server really is equivalent to Nomad in terms of being a variant level server for that whole genome data so in addition to the things you were just describing that is one of the efforts that's coming out of top med and do we have a timeline on it so Bravo is currently publicly available now you can just search Bravo top med I mean just need a Gmail login you can log in and and search variants there's a lot of really great data in there can't not not really recalling up to off the top of my head but I would encourage you to explore that we're also it's turned out to be a little more complicated than we would like but there is also an imputation server with all of the top med data there are a lot of policy issues with sharing that publicly but we're also working to hopefully get that made publicly available within the next year or so and I'll also mention that the data commons has a portion of it dedicated to top med that we actually call data stage and that is meant to provide both cloud resources and storage but also tools and analytics publicly on the cloud in a way that would make this sort of thing more available to researchers that don't have the really heavy infrastructure that you would need to do some of this really high throughput whole genome analysis it's coming yeah so concerning the data integration for at least in Europe for the IMPC data there are two possibilities that I'm aware of so one of them is to have the IMPC database as one of the core data resources for the bioinformatic research infrastructure called elixir right and the other one which I'm aware of is that there is a project called the European Open Science Cloud Life which is a collaboration of different research infrastructures in life sciences and it would be possible to nominate IMPC into incorporating into this project to have a yeah to preserve the data there sure no problem I can do that well I think we've had a full day so so one last question or going back on on data set so as a clinician when you try to find data do you go to Omen or what's your gold standard because if we want to take a look at the ontologies and how that's being staged then that would help us go to where you like to go I think any practicing clinical geneticist has a computer open to Omen in the clinic constantly okay they can't they cannot really do their work very well without that also any practicing clinical geneticist is reasonably facile with exact and nomad because they they get a report on the sequence from somebody there'll be some you know they go through the first they don't look at the first three pages they go to the bottom line and there's some variants listed there and they want to know how frequent those variants are and they know they can get those data from nomad or exact you know immediately and and they for the most part the residents the fellows the clinicians know how to use those databases without any problem so for common fund data sets if we looked at those and tried to break our mountain to do that now for a five-year plan at least we're combining some of the key the key foundations so if we consolidate on one side in the translational model and and there's consolidation on the human end then that may be a smarter way to go than all the bits and pieces trying to be be formed in separate spheres right and the other site that's open is PubMed in the clinic all the time and you because in a genetic a typical genetics clinic you never know what's going to walk in the door and you practicing geneticists is someone who is comfortable taking out a patient that they have never seen a patient with that problem before in their life and so in the minute or two before they go in to see the patient or the day before when they learn that that's what is coming they're doing a quick study to see what's known about that okay so that's where they go in their deep dive and then just specifically for Omen on some of the known phenotypes or associations yeah yeah and yet I mean the other thing is gene report what is that our gene gene reviews right excuse me if I can just interrupt I didn't hear you say anything about that the clinic clinician uses Clinjan is that a useful resource they do they do I'm dating myself a little bit here okay yeah because the that's that's another potential interaction to work with that consortium find out what functional data they need to complete a review right yeah I only see follow-ups now so all right so what I'm hearing is kind of recommendations about how to build these systems and son I would like that you know the recommendations be what the clinicians are experienced with is interfaces right the web interfaces they're enormously important actually but we have a different layer design is underneath it using API is linked data technologies and such so whenever recommendations are made they should take into account both the technical perspective and user perspective if we go off balance will be building silos we'll be using approaches that are 50 years old since the era of you know airline reservation systems but times are changing rapidly on the web and so we should be thinking about how to employ the latest technologies so that layer underneath it right actually scales to the diversity and volume of data and accommodates a multiplicity of contributors right who contribute their own pieces of the puzzle and I think fairness you know FAIR is a new set of principles that's been promulgated by the NIH it's been enormously useful actually as a way of bringing up the technical aspect of the actual implementation of systems so fairness actually talks about that layer underneath the user interface and says you not only need to build a silo you need to build an interoperable system which means it needs to talk to other systems to computer programs who can have their own interfaces so-called API's so you can share your data through that and findability actually is the key one which means you need to use certain dignifiers you need to have metadata about identifiers and expose it for search by search engines such as you know BioCADD data med index built in NIH for example a fair share but now things are really changing with Google data search why because Google data search if you follow these principles in the past few years you're ready for Google data search why because they're asking for the same thing and all of a sudden this ecosystem is growing so what I'm saying is we should be careful about the actual implementation right and take into account these trends and so build interoperable systems that interoperate not only with each other and within the small biomedical research world and I'm saying by small because I'm having data search in mind where there's all kinds of additional information there but also interoperable with these broader trends which actually will dictate technologies going forward yeah I mean the IMPC data is on OMIM but it's buried in a sidebar in a pull-down menu where you get a link out and that's not effective I mean what should be there is a synopsis of our findings right boom right in front of you speaking of that you know this design principle makes it possible for multiple parties to build user interfaces on top of the same underlying infrastructure so the benefit for the end user is that there could be multiple interfaces catering to different audiences right so that their needs are maximally met and there isn't a single portal or single interface because it's very hard to meet the needs of all users right of OMIM and SON so this design will actually in in the end benefit all the audiences as well I have minimal influence on OMIM but some and I will do my best okay on that note Dave's gonna solve all our problems for us we're good we can leave and we have a volunteer so I don't want to take up any more of your time we're over time I think we've had a very full day we've got a lot of work we're ready to do this coming year supplements are in place plans are in place excitement is in place we'll meet again here next year and hear about a lot of progress that's been accomplished so thanks for your time


Okay, sorry for the technical hitch there. Right, I was supposed to be doing this talk with a colleague who works with G on JFR. Unfortunately, he wasn't able to come, so I'm going to cover the material he's provided for the talk. This is a talk about our attempts to add some new functionality to Graal VM. So what I'll do is I'll start by providing some background of what Graal is, just to give an overview of how it works and what we're actually trying to achieve. Talk about the things we wanted to do, explain how that went, some of the problems that we had, what we actually succeeded in doing, some of the things we learned from the process, and I suspect we probably won't have time for questions, but I'd be happy to talk with them outside. So Graal is not just one thing. It's actually a whole series of components all written in Java. The core of that is a compiler which is used for various different purposes. It can function as a JIT compiler as an ahead-of-time compiler. There's an interpreter framework called truffle, which can be used to provide support for a whole lot of interpreted languages that the compiler can then be optimized by compiling. There's a native image generator that can take a Java program and finds a closed world of all the code that's called from the program and will generate a small executable from that code. That can run independent from OpenJDK, doesn't need a JVM, because it's got its own little JVM inside there called substrate, which replicates all the functionality you need from OpenJDK to run a small native Java image as a self-contained binary. You can also generate shared libraries with it as well. It's just a binary with multiple entry points essentially. So what Graal looks like at the core of it all is this compiler, and you can use it in OpenJDK as a JIT compiler. So if you were to plug it in by the JVM-CI compiler plug-in interface, OpenJDK will create some compiler threads and start handing methods to it to compile and get compiled code back, and that will be used as the compiled code for OpenJDK. In order to do that, it has a front-end, which parses byte code and generates a graph structure. There's the usual high, middle, and low tiers that massage that graph into a shape that you can spit code out and a back-end that generates code buffers, and there they are. You've got compiled methods. A slightly different configuration of the compiler, most specifically with a very different back-end for linking in a different way, can be used in the ahead-of-time compilation for Java and OpenJDK, and that can be used to populate the class data sharing segment, application class data sharing with predefined methods so when you bootstrap, you've already got compiled code for Java runtime methods or application methods. So the same compiler has been repurposed by reconfiguring all the components in the compiler. Another use for it from Truffle, Truffle allows you to build interpreters that parse a language and there's various Truffle language implementations and execute by walking the abstract syntax tree for the parsed language program. The Truffle interpreter framework knows how to take a node in that graph, that syntax tree, and maybe some of its subnodes push the graph straight into the compiler, bypassing any bytecode parsing front-end because you've already got a different representation of the program. It pushes it through the stages in the compiler, out pops code at the back-end, and you can install that as an execute method for the interpreted language to call directly rather than interpreting the graph, running on OpenJDK. You can also use it in native images where you've compiled things to native compiler and the gral compiler can run inside a self-contained binary as part of a program running some Truffle language. The native image generator itself makes two uses of the compiler. You start from a method in a particular class or a set of entry methods for a library and it takes that method and the class is associated with with JVMCI descriptions of them, eats the bytecode, and instead of compiling it down to machine code, in the first pass it analyzes the method and at the bottom of the transformation stage in the graph processing comes a transform method and a list of methods and types that that method refers to. They're put into a pool, into a universe which is built up recursively processed, finding all the references from classes to other classes, methods to other methods, until you build up a closed world of all the code that can be reached from your initial entry points. You can then take all the type information you've derived and the methods that you've found and compile them to a completely self-contained executable image that has a closed world model. You found all the code that you could reach from that entry point for that library or that application. It's not quite as simple as that because this closed world executable image is at some point when you call into the JDK runtime methods is going to expect to call out and have a JVM under there under normal operation, have open JDK. Of course, this program has to run its own without open JDK and it can't reuse all the JVM functionality from open JDK because that expects to do class loading and keep track of classes and it's all meant to be compiled into the image self-contained. What this translation process at the first stage does is it also substitutes invocations of JDK runtime code at certain cut points and side steps into substrate which provides an equivalent thing to the same sort of job as open JDK in this delivered image or delivered shared library. It used to be that all the functionality that was provided to emulate the open JDK VM was implemented as Java code. That became a bit of a burden when they realized they would have to keep porting that for 11 and all the later releases. So, from a lot of the native code that's implemented as C code in native libraries like the zip library, the libnet code, that's been put in and linked underneath the substrate image and it's used directly to avoid having to maintain so much Java code. So, it obviously has to emulate some of the things that normally go on inside the VM code and provide an alternative because you've got a different model for execution. So, there's this set of things that started arriving a few years back and we were looking at this about two and a half years ago and thought, well, the ARM port isn't really properly supported. It's a sort of second-class citizen. So, our first idea was we do some work with ARM, back-end, be on a par with x86 and our goal there was architecture parity. More recently, we've been interested in the native image generation because of our middleware product Quarkus. So, we looked at adding JFR support into the substrate and VM and into the native application. All the monitoring capabilities you have along with JDK are not currently present in these native generated images and really for usability users are going to need to understand what's going on in the application and also have some of the way of identifying things when it goes wrong. So, JFR was what we decided we wanted to port. Oracle already had plans to have that in their enterprise edition of Grail. We wanted to add it as a community feature and that's really critical, we think, for usability for the community edition, the open source edition. With debug info for debuggers this is a different story. A program that runs on OpenGDK if you get a native image compiled version of it and in any way diverges from OpenGDK behavior, that'll be because the compiler is compiled code into this heavily optimized executable program that is doing the wrong thing. So, you've got to be able to work what happens if ever something like that should arise. So, we wanted to put debug info in that would allow you to take the executable image and refer back execution of the instructions there to the original Java source code in a debugger like GDB Visual Studio. So, you could actually deal with that problem should it ever arise and understand what's gone wrong and then go and fix Grail probably. So, this is more a supportability goal. So, for the the ARM64 code, what we wanted to do was just add very basic stuff. Two and a half years ago there was very minimal things like addressing, there were no displacements embedded in addressing. They were actually loaded as independent values into registers. There's no prefetching things like merging an abstract shift and a mask operation using one of the bit fetch instructions in ARM that we wanted to optimize issues like that. And the most important was using load acquire store release for volatile operations rather than having memory barriers for efficiency. So, there was a lot of stuff that really just wasn't there we needed to put in. With JFR we really just wanted to get JFR working. So, we wanted this low overhead profiling method mechanism because it's really critical. We needed to have as many of the VM events, we wanted the equivalent sorts of things that made sense to come out of the substrate VM so you can see what the virtual machine and the native runtime code is doing. We'd also want to have support for user events and we'd also like if there's something about the way substrate works that isn't really a correlative open JDK, we were thinking of adding new events for that. We mostly just wanted to reuse the existing code as much as possible so we didn't have to reinvent the wheel. The debug support, we had a fairly simple set of capabilities we thought would be enough to debug problems. Break points by method name break points by file and line number and the ability to step when you hear a break point line by line, stepping into a row of functions, back traces. We'd like to print objects field by field if we can and we'd like to use path expressions to dereference through objects and pick values out using a sort of field axis so on. So, that's the sort of capability we really wanted to add. So, what happened? What were the things we encountered when we did that? Well, with the ARM code, two and a half years ago we started this. It's actually still ongoing. We've been slowly adding things. We met in real problems because of the complexity of the compiler. It was very difficult to get things into the code base. But actually there were problems with the development process in that that was organized and there was also problems with our understanding of where GRAL was going, what the roadmap was for GRAL. I'll talk quite a bit about the compiler complex because this is really quite important. Any compiler is going to be complex. You've got usually a high, middle and low tier of transformation stages in a graph model. And so there's a whole load of different operations happen in various stages. Some of them are rigid, some of them are nested. What happens with workflow controllers is really quite a difficult thing to do. And you're massaging a graph and transforming its shape all the time. Nodes come and go. So a line of the life cycles of the graph and the life cycles of the phases is always a problem. When you have a very deep node hierarchy, you may have a phase that operates on a generic node type. But which actual types of node does it really operate on? Same view as a lot of interfaces. These are generic problems. The problems that GRAL faces, but I think it's particularly difficult with GRAL because of the questions of scale. But there's also the configurability issue. GRAL is used by many clients for many different purposes. So all those phases that apply in each suite and all the different back ends are different for different uses. And that makes it, that means there's a lot of possible combinations of choices of what might be going on in the graph transformation process particularly. They also use a plugin model which allows you to take a particular method operation or a family of method operations or a particular code operation and to have some special handling via a plugin. And each different client plugs in different phases to do these different operations. There's another indirection mechanism for where things happen. Annotations are used on the code to guide these operations, to guide how the phases operate, how the plugins operate. So you need to understand how the annotations actually side effect this. And what makes it really complicated is that some of the annotations are defined in substrate classes and they affect the way that JDK classes are modified and compiled. There's an indirect mechanism. So you can see there's lots of hooks and lots of indirections that make the complexity of this really, really difficult to follow. And a lot of the configuration is done with a layered hierarchical overriding model. So you have a basic suite provider that provides the phases. You have a hotspot suite provider and then you have an AOT hotspot suite provider. So there are these nodes in one place. It's distributed. So it's really, really very complex. Some of the numbers involved there are 150 subclasses of class phase. This is a thing that does a single graph transformation. There are 200 different types of graph node in the code base. Access, which is an interface that's used to encapsulate all the memory nodes has 21 different types of read or write nodes or in one case a read write node. The graph builder plugin that does special case side particular transformations. 200 different graph builder plugins. 9 different types of plugins doing different types of transformations. And there are 200 annotations that direct these operations, these transformation operations in different paths. And of course the other problem we had was when we started this the ARM port was relatively new so there were problems with the code and the shifting code base. The ARM64 code was the least stable part of the compiler. But actually there were problems with some of the generic code so when we tried to fix what we thought were back in problems in the ARM64 port and improve code quality we actually ran up against things that were problems in generic code that didn't quite do what was needed so there were generic fixes needed and we weren't really in a position to do that. And actually that generic code was also still in flux a bit at that point. It's got better since and we've managed to make some of the generic changes but it really meant that we had to either rework things or withdraw some of the things because they were just too fragile. But the really biggest problem was the development process the Graal engineers at that stage were working on their own on their own repo with their own management system and they put up a github repo with PRs for us to try and push things in but they were really focused somewhere else and they weren't ready to be receiving things from us. They weren't even really looking at what we were doing because they were actually looking internally to their own group so getting them to actually be prepared and understand the implications of trying to build a community and to work with that was actually quite a long slow process. It didn't help also that the final testing stage, this is an old story though from JDK, was done behind the scenes in Oracle and so when we put changes in and did get them through we would sometimes get a cryptic message saying you've gone wrong but we couldn't see what had gone wrong because we couldn't see the tests and we couldn't see what changes Oracle were putting into the code base that might have broken our tests until they could see. So it was really done at a distance, it was quite hard. Sorry, can I just? Yeah. The other problem was that what this product was and where it was going was quite difficult for us to see. Graal has got a very long history, relates back to Maxine, I think before that, Jikes. This idea of Java and Java and all the sort of generalizations that Graal was doing, all the capabilities was something we gradually began to understand. It wasn't just a JIT compiler and an AOT compiler, it was actually not just an interpretive framework, it had all these other uses as well. Part of that was us not really knowing enough about it and not reading the right things, we just went in to do a job and fix some code. Part of it, I think, was that the roadmap that Oracle Labs had for the product was not clear anyway, they had different ideas about what they would do with Graal, what would be the key thing, the key value proposition and so on. It wasn't all our fault but that was to a great degree or there was no public roadmap, it wasn't really because it was a private project that was trying to become an open source project and none of the things were in place there. With JFR support, Josh had real problems understanding he had to go through much the same learning process I had with the compiler with Substrate VM, understand some of the limits of how it operates. He was trying to link in JFR code, there's native code and there's real issues with linking things in. This substitution mechanism that replaces things I think this thing was going to happen because that's the way it works in the JDK runtime but actually it's different in Substrate and just putting the whole thing together required a lot of understanding and since it was more new than the compiler even though we did this more recently it was still a bit of a moving target. One of the things that you have to really deal with is the fact that you can't use reflection and you can't load classes dynamically so you've got to make sure that any class you want to the image is notified to the Graal code analysis the points to analysis so that it will get linked in and compiled ahead of time. So you've got to actually go about getting code that relies on these features to work in a different way and you have to understand how to do that and similarly J&R you can't just load a library and have native methods, there's a registration mechanism for registering foreign code. That was actually quite tricky to do and this actually changed part way through as I said all the Java codes were placed with callouts to the Java libraries so LibNet, LibZip and so on. The one library that wasn't included was LibJVM and of course the JFR code that we wanted to use is in LibJVM so Josh is still working on getting that factored out and actually linking that as a separate static library and that means the other alternative would have been rewriting it all in Java and that's really not interactive proposition so that's been the biggest stumbling block yet. As I said, if you're looking at the way that the JDK runtime code works, Josh is looking at system load library trying to get a library loaded to get some foreign code in and system load library never got called because they'd cut above that point so he spent a long time trying to work out why his code wasn't being run and eventually found this out. There's another thing that Substrate does for optimization generate in the native image that you produce, you can pre-populate a heap with static class field data including objects that are computed at build time or else you can run class initializers at run time now you've got to get those two things consistent across all the classes that might be side affected by computing and evaluating something in the build time context versus what you might generate if you compute things in the runtime context you get those wrong, you get these really subtle bugs so that was another thing that was really hard to decide what should be initialized at build time what should be initialized at run time whether any existing decisions that were made about that might snooker you, so Josh spent a lot of time working through that. So he's had a really difficult time of it actually and again this code was in flux there were things changing particularly the library the way that the JNI and the library stuff was changed really meant he had to redo a whole lot of work. The debugging work is something I've done much more recently than Josh and it's been probably the easiest thing but I think by this stage we understand a lot more. It's actually also a relatively self-contained thing which is if you've got code in your code base or types in your type base for this analysis universe how do you tell a debugger about it? So one of the problems he had was to put this in a way that doesn't upset the upstream implementation that already exists so that's one of the constraints we're going to have to go through in the review process the biggest technical challenge was making sure that the stuff that writes the object file doesn't have to know about all the other types in the compiler and the heap management and so on. So there's only one sort of constraint and that just was defining several interfaces to allow these things to happen. That was decoupled fairly easily I haven't looked yet at making this an optional feature using all the sort of mechanisms Graal uses for enabling features. I'm assuming that's going to come out of the review process I hope so but it's been pretty successful So with the JIT we did get some very basic things in about two years ago we had another little round about 18 months ago and got a little bit more in. In the last year Roland Westrelin has managed to make some generic changes with the Graal compiler team and actually ARM have also contributed some of the instruction reduction optimizations quite a lot of stuff there so we have had quite a lot of success eventually it just took several goes to get there Josh is still really struggling getting a working prototype in a native image. He's got the event stuff worked out. He understands what he needs to do we can run that in fullback mode when it runs on OpenJTK and we know it's going to work but he's still got to deal with the library linkage problem so it'll probably be a few more weeks before we get anywhere having something that's a working prototype that we can then polish up and submit so there's still a work in progress there unfortunately. The debug stuff I actually two weeks ago submitted a pull request with the first three features so we now have for Linux and GDB we have working break points working line stepping and working back traces and the type stuff is the next thing I'm going to add in that's just gone in for a review and I got just two days ago a nice big set of review comments from Paul Virgo which is really good so Oracle were really helpful with this they actually gave us a whole lot of hints some of which I already found some of which I haven't when we raised this as an issue and they've actually been very cooperative about getting this into the product so that's been really quite heartening and I think this will probably go in in the next two or three weeks I'll have the core debug functionality and then I'll work on round two next the process has got better the Oracle engineers and labs are much more aware of our existence I mean we've been bombarded in a way with lots of pull requests not just us but the caucus team and many other users of Graal but a lot of them have risen to that and started working with the community more they're still working on their own repo that's the problem but they are more aware and they're more responsive they've always been helpful it's just the time this response has been the biggest problem they're now much quicker and we know who people are and that really helps and they know who we are as well we had a committers workshop we met them we made some good contacts so that's really helped in terms of us actually just getting things to happen because it just makes a difference that you've met face to face and you know people it's just a fact of the world the planning process we understand a lot more where Graal has come from and that was particularly helped by talking to the Graal developers and they also we also have more idea of where the product's going and how we can now fit our work in and the committers workshop was actually very helpful in getting all that to happen and we've got a agreement that the open JDK team and our middleware team who are working on caucus will regularly review and some of the other people contributing outside of Red Hat as well will regularly review things of the Graal team to improve the process and make sure we plan things we've been actually given ownership of the issues for some of the compiler issues and for the debug info and I'm assuming that in the longer term we'll get that with the JFR issue as well so we now actually are responsible for negotiating all that with the community and seeing it through review so there's been a certain devolution of ownership and responsibility as well which I see is one of the most positive things that's happened just in the last week that happened hopefully just to wrap up we had a lot of problems there are still some structural problems we've learned a lot by doing all this and we've also I think we've helped educate the Oracle Lab about how to work with the community and how to build up a community and benefit from having community input the project is now I think stabilizing a lot more it's Oracle are clear where they're going, Oracle Labs are clear where they're going with this and I think we know where we need to go with it the functionality we need in the community and so I'm hoping that this is going to be an up and up rather than something that gets stymied or stagnated here so I'm quite optimistic about this at the moment so how's that doing time for questions? No, not really Alright well I'll take them offline then I'm sure Andrew would be happy to answer any and all of your questions on that corridor track


It gives me great honor at this opening day and opening session to introduce to you Prime Minister Abe, Prime Minister of Japan. And Prime Minister, when we met some months ago, you promised to come to Davos. And I know you are a man who keeps his promises. You mentioned to me there's only one difficulty. It's the opening of the diet, which usually takes place end of January. So what we did, we are slowly advancing the beginning of the annual meeting to make sure that you cannot, that you can be with us not only today, but also in the coming years. And so there's no conflict anymore. Now when we met via video at the last annual meeting in a small group, and you asked to bring together some of the world's best economists to have a dialogue with you, you were just at the beginning of Abenomics. You shot the first and the second ever. Now I can say Japan is back, and we are very eager to listen to you about the third era, which certainly you will develop for us. But I would also like to use this opportunity to congratulate you, because in the last 12 months, you also were awarded the site of the Olympic Games in 2020. Prime Minister, when we talk about Abenomics, it's not just your country which is concerned. We know that we are living in an era where the traditional economic concepts may be not valid anymore. And please all the economists in the room, excuse me, if I say so, we need new bold concepts, and Abenomics is such a bold concept, which may be valid for quite a number of countries in the future. So what you are telling us now is very crucial for all of us. Please join me here on the stage, Prime Minister. Thank you, Professor Shorap for your kind introduction. Mr. President, it's an honor to speak after you. Now I don't know who chose it, who coined it, but they call my economic policy Abenomics. Well, I hesitate to go on calling my own name, but let me use it anyway. So Abenomics has three arrows. The first is bold monetary policy. The second is about flexible fiscal policy. And the third arrow will continue sparking private investment. Japan economy is just about to break free from chronic deflation. This spring, wages will increase. Higher wages, long overdue, will lead to greater consumption. Our fiscal situation has also made steady improvement. Japan is now getting on track for fiscal consolidation. Pandits used to say that Japan was at dusk, or the land of the setting sun. They said that for a country as mature as Japan, growth would be impossible. These arguments were made to sound almost legitimate. You can see what Japan's psyche was like before I took office as Prime Minister. Hardly can you hear any such voices now? Our growth rate has changed dramatically from negative growth to positive. In six years' time, the Olympics and the Paralympics will come to Tokyo. People are now more vibrant and upbeat. It is not a twilight, but a new dawn that is breaking over Japan. May I tell you, ladies and gentlemen, that late last year, we decided to go on major reforms. I have broken through the notion that certain reforms could never be carried out. We will completely liberalize Japan's electricity market. By the time the Olympics compete in Tokyo in 2020, Japan's electricity market will also be completely competitive for both power generation and retail, with power generation split off from power transmission. In Japan, people have long said that such a thing is just impossible. We will also foster medical care as an industry. Japan is on the leading edge in regenerative medicine. We will make it possible to generate sales at private sector factories. In Japan, people have long said that such a thing is just impossible. We are also doing away with the rice production adjustment system. This system has been in place for more than 40 years. Trade companies will be able to engage in farming without barriers and growth crops they want without artificial control over supply and demand. In Japan, people have long said that such a thing is just impossible. And yet, last autumn, we actually decided to make all these changes. In addition, yesterday morning, I gave additional instructions to reform the Japanese system because we also need large-scale healthcare companies in the form of holding companies, much like the Mayo Clinic. I have maintained that I am willing to act like a drill bit strong enough to break through the solid rock of vested interests. Soon, our deregulation package will be set in motion. The designated areas on my own watch will cut through red tape. There, over the next two years, no vested interest will remain immune from my drill. In cities hoping to join the world-class limits on floor-area relations will become a thing of the past. The sky will be the limit. We will soon see high-quality housing or business complexes and zero-emissions towns appearing one after another. The Trans-Pacific Partnership, or TPP, will remain a central pillar of my economic policies. We will push ahead the Japan-EU Economic Partnership Agreement. Those will surely make Japan's economy even more deeply integrated into global flows of knowledge, trade, and investment. Companies and people from abroad will find Japan among the most business-friendly places in the world. Japan's public fund management will also change a great deal. Japan's Government Pension Investment Fund now holds about 1.2 trillion US dollars. We will press ahead with forward-looking reforms, including a review of its portfolio. That GPIF will contribute to investments leading to growth. We must also make the tax system for companies internationally competitive. We will reduce the corporate tax rate by 2.4 percent from April this year. We will also encourage companies to use the tax. They have gathered towards capital investment, R&D, and wages in workers' salaries. To do this, we will put tax incentives into place in a way completely different from before. This year, we will set about further reform on corporate tax. We will reform the labor market that ties workers to old industries. New industries require innovative and creative human resources. We will redirect our subsidies so that workers without meaningful work in old industries can move to new industries that require good human resources. Japan is becoming a super-aging society even as the number of children is falling. You might find yourself asking in such a country where you will find those innovative and creative human resources. Mariana Huffington once said that if layman brothers had been layman brothers and sisters, the farm would have survived. Japan's corporate culture is still one of the pinstripes and bottom-downs. After all, the female labor force in Japan is the most underutilized resource. Japan must become a place where women shine. By 2020, we will make 30 percent of leading positions to be occupied by women. In order to have a large number of women become leading players in the market, we will need a diverse working environment. Support from foreign workers will also be needed for help with the housework, housework care for the elderly and the like. As GDP could grow by 16 percent more if women participated in labor as much as men. That is what Hillary Clinton told me. I was greatly encouraged. Another thing that will be needed is a major impetus for change aimed at corporate boards. We will soon put forward changes in the corporate law to the upcoming parliamentary session. After these changes, external directors will increase. Next month, we will also draw up a stewardship code. It will make it easier for institutional investors to have a greater role in corporate governance. All of these combined, I'm sure we can double or inward direct investment by 2020. All this would reboot the entire country. Trans-economic landscape will change dramatically. On March 11, 2011, the north-eastern part of Japan was hit by the triple disaster of earthquake, tsunami and nuclear power plant failure. Three years will soon have passed. The love and compassion we were given from the world touched us deeply. The recovery is far from over. I'm the one most responsible for the future of the survivors. Yet, it are these very survivors who helped each other with stiff upper lips trying to overcome so many hardships. Their spirit of perseverance moved people all over the world. It is with that same spirit of mutual assistance that Japan is now set to turn into a nation that will contribute even more positively toward world peace. In Cambodia, the hospital Japan built for mothers and newborn babies helped reduce the country's infant mortality rate. In the Philippines, after the devastating typhoon, the relief effort by Japan's self-defense forces was movingly welcomed. Based in Debuchi, over self-sacrifice men and women are still on high alert against poverty, protecting ships from around the world. In our age, no single nation can preserve peace by itself. None of us alone can solve the challenges the world faces without helping each other. And New Japan is now waiving a burner for proactive contribution to peace. I want you to know you can count on us. Asia has become a growth tenter for the world. Japan is surrounded by neighbors with unlimited possibilities, such as China, South Korea, the ASEAN, nations, India and Russia, and across the Pacific, the TPP partner countries in this region, which will be the engine driving the world economy forward. I am always contemplating just how we can achieve peace and prosperity and make them everlasting. The foundation for prosperity comes down to freedom or movement for people and goods. From the sea lanes, in airspace and recently in outer space and cyberspace, freedom or movement must remain secure. The only way to fully keep these indispensable public goods safe and peaceful is to rigorously maintain the rule of law. It is for that purpose that fundamental values like freedom, human rights and democracy must be assured. There is no alternative if peace and stability were shaken in Asia. The knock-on effect for the entire world would be enormous. The dividend of growth in Asia must not be wasted on military expansion. We must use it to invest in innovation and human capital, which will further boost growth in the region. Trust, not tension, is crucial for peace and prosperity in Asia and in the rest of the world. This can only be achieved through dialogue and rule of law and not through force or coercion. Now in order to turn Asia into a region for trust and order and not, when the force and coercion I would like in conclusion to make an appeal to Asia and the world. We must, ladies and gentlemen, restrain military expansion in Asia which could otherwise go unchecked. Military budget should be made completely transparent and there should be public disclosure in a form that can be verified. We should create a mechanism for crisis management as well as a communication channel between our armed forces. We must lay down rules that promote actions based on the international law of the sea. Only then I believe can we achieve growth and prosperity in Asia, where all of us can realize our great potential, Japan has sworn an oath. Here again to wage a war. We have never stopped and will continue to be wishing for the world to be at peace. It is my fervent hope that through a binomics we can create a vibrant Japan that can bring up peace and prosperity in the region and in the world. Thank you very much. Thank you Prime Minister Abe. It was quite a comprehensive program which you presented us in order to regain momentum in the Japanese economy and particularly your very concrete reform proposals I think are very promising. Now Prime Minister allow me maybe a very touchy question. You emphasized at the end the need for stability and peace and trust in the region. With your shrine visit it looks to the world that Japan's regional relations with neighboring countries particularly China and South Korea is getting worse. Can I ask you to elaborate maybe for us how in this let's say very tenacious situation you see the future? Not for a very straightforward question. I believe that there is a major misunderstanding concerning the Yasukuni Shrine so allow me to briefly explain to you what kind of place Yasukuni Shrine is. This year marks the centennial anniversary of the end of the First World War and 50 years before that there was this Meiji Revolution and including the Meiji Revolution and the war that in the First and the Second World War the spirit of those perished in these wars are enshrined in the Yasukuni Shrine. So I paid respect to those people who had perished in war for the nation and I had prayed for the souls of the departed which I believe is something quite natural for a leader of any country in the world. Now in Yasukuni there is this remembrance memorial in which all the war dead throughout the world are enshrined not just limited to the people in Japan and I have won an oath never again to fight war so that nobody would suffer from the sufferings or nobody would suffer from the devastation of the war. I believe many leaders in Japan have the same feeling. I have no intention whatsoever to hurt the feelings of people in China and also in Korea and we believe that Korea and China are very important neighbors and Korea shares the same value system and they are a free democratic country and since we have these challenges I believe it is very critical to have this summit meeting. The door to dialogue is always open on our side and we would like to with great sincerity and with due courtesy try to continue the dialogue. Just following up what you said I think it was very appreciated and in the best Davos spirit when you were sitting in the sessions this morning of President Madam Park listening to her. Now if I take if I go back to Abenomics you have a one of the highest debt ratios in the world and you have an aging society and it's a moment particularly with your first arrows you are adding to your fiscal deficit. Now what is the end game? Could you just enlighten us how at the end I expressed once you are running and we are all running in the world or trying to run our economies with a big backpack on our shoulders the debts. Now is the backpack so big that one day you will break down or can you get rid of the backpack or at least get some weight out of it? Indeed as you said Professor Schwab Japan has various so difficult challenges that it is faced with. On the debt issue for fiscal consolidation first of all we should reduce and do away with waste. At the same time we have to increase tax revenue. There's no other alternative there's no other way. Japan has experienced prolonged deflation and the tax revenue has continued to diminish common GDP has gone down so it's natural that we see this so we have to end deflation to grow the economy and increase tax revenue and at the same time eliminate waste. This is the policy I have introduced and this is indeed the policy of the three arrows. Fortunately at one time tax revenue which has dropped to 38 trillion yen this year will increase or has increased this fiscal year to 50 trillion yen and furthermore in April we'll be hiking the consumption tax from 5% to 8% in reducing the debt. We have to turn the primary balance into a surplus. The primary balance deficit is still very large compared to the GDP in 2010 by 2015 we want to reduce the deficit of the primary balance to one half and achieving this goal is in the horizon. We have made no waste and we will grow the economy and we will move ahead with the structural reform to grow the economy and that we will increase tax revenue and to consolidate our finances fiscal situation. When we met last time we of course I congratulated you for the Olympic Games and we discussed the possibility of conducting in Japan a Davos for the sports to bring together the best minds of and the best spirits and the best people in the sports and community. And to hold this Davos for the sports in 2017 what are your expectations concerning such an event? The 2020 Tokyo Olympic Games and the Paralympic Games will see athletes from all over the world come to Japan and we want to create a situation where they can do their best and they can give their best and at the same time we want to extend hospitality or omotenashi leveraging on Japanese tradition and culture. We want to make these games one which will make its mark in history. Toward the 2020 we hope that Japan will regain vitality so that we want to repay those who have supported us after the disaster by showing how we have recovered and the sports tomorrow, sports for tomorrow is something that we have committed to. This is our contribution to sports. Target is over 10 million people will be ascending sports instructors overseas. This is a plan which is in the making and for we want to provide the support for putting in place the environment conducive to sports. And your proposal on sports for tomorrow and the sports culture Davos conference I would like to definitely extend my cooperation to hold this conference. 2017 the sports Davos so that this is successful I would like to render my fullest cooperation. Thank you very much Prime Minister Rie at the end of our session and I only can tell you all our best wishes accompany you when you are going back now to announce some of those reforms also to push them through the diet and to make them successful and we are sure with your personality with your strengths we will have a new Japan being born under your leadership. Thank you very much Prime Minister.


Hello I'm Howard DeVall, at-large City Council member for the City of Columbia. I'm here to wish you a happy holiday season, a happy Hanukkah, a Merry Christmas and a happy Kwanzaa. This has been a rough year in 2020 for all of us and we're happy to see 2020 leave us. I hope you have a wonderful holiday season and that 2021 will be a wonderful year for all.