So with that said, let me now not take up any more time from you, Sastry. Let me quickly introduce you in the panel. This is a panel on data and digital. We've had this panel each of the past few years. It feels different this year. It feels as Lori Glimcher, for those of you who saw the oncology panel earlier in the day, mentioned, it's happened. We're now not looking when does this happen or what does it look like? We're living it. And for better or for worse, it took a forcing function, which was the COVID-19 pandemic. So Sastry, you have a great panel of experts here and I'll turn it over to you. Great. Thank you so much, Andy. It's been a great set of sessions and the last session was truly outstanding. With this panel, we really hope to dispel the myth that digital and data science is something new that we're trying to do and something novel. I always like to remind people that we moved out of the analog era many years ago. And throughout the day, we've heard these stories from the frontline, be it through the oncology panel or through the rare disease panel or around COVID around the role that digital and data science are playing. So we do have an all-star panel assembled here to talk about how they're meaningfully moving the needle across both their teams as well as the broader organization. So let me introduce them in alphabetical order. So first up is Ann Hetherington. Ann is the head of Data Science Institute within R&D at Takeda and she focuses on statistics, epidemiology, real-world digital and data. And she's most recently been leading the industry effort around data sharing for COVID as part of the COVID R&D annoyance. Next up is Arpaugare. She currently leads the global pharmaceutical business for Merck and she also leads data analytics, digital, and partnerships with a commercial organization where she's building the next generation commercial models and organizations. Third is Maya Said. She's the founder and CEO of Outcomes For Me, a Boston based digital health company that's focused on improving outcomes for oncology patients. And prior to that, she spent several years in senior executive roles at both Novartis and Sanofi. We also have Najat Khan. Najat is the chief data science officer and global head of R&D strategy at Janssen and she focuses on maximizing the impact of data science across the pipeline. And she's also a co-chair of the broader J&J Data Science Council. And then finally we have Nina Shelson. Nina is an early-stage investor at Canon, a U.S. venture capital focused both on health technology as well as healthcare. And she's been supporting biotech and digital health startups for more than two decades. We're really excited to have this panel and we'll talk about this more but for the first time in 14-year history of USAIC we have an all-star all-woman panel. So it's something all of us have been hugely excited about. So diving right in, let me get us to the first question and maybe we can go through in the order in which I introduced you. So there's a tremendous amount of hype in this space and there's a lot of investment money flowing in. Where do you see the greatest opportunities across the board? What are some of the successes that you've experienced but then more importantly what do you see as the tipping point so that when we come back here next year we can talk about here is what I called at last year's USAIC. And then where is COVID also serving as an accelerant because there are a lot of things happening be it around telemedicine or use of real-world data that that are dramatically accelerated because of the pandemic globally. So Anne why don't we start with you? Yes thank you and thank you to the USAIC for asking me to participate here today with all of my co-female leaders it's wonderful. And to the exact question like actually I think everybody around this virtual table as someone who's worked on data since my PhD days and continues to rely on data every single day on my job I actually don't really see this drive to data and digital as hype. I actually just see it as the rest of the world catching up with us and what we've been wanting to do and trying to do for many many years. But that's not to say that with advances in computing power and analytics we can't do more. As demonstrated by Wea Takira we've an alliance a collaboration with MIT at the intersection of AI and health so we can definitely do more. But I don't see it as hype and we should definitely not lose sight of the fact that actually data and algorithms and digital tools aren't the end game for us. A pharma getting medicines to patients faster is the end game and everything is an enabler for that. And with regard to the question about the current pandemic of course we have seen so many ways that flood gates have opened and for someone like me it has been magnificent. But the one example I'd like to focus on is actually what you alluded to in my introduction which is to do with the COVID R&D Alliance where we have had at least 20 pharma representatives around the table and talking about data sharing and what we're moving to is a world where we will rapidly share data both at a study level and at a patient level as trials read out. And at the same time we've had a group working on collaboratively working on real world data for COVID developing methods and protocols together. So the world has definitely changed with COVID and I for one am excited by what we can do with it moving forward. Harpa. Yeah so just to build on Anne and again thank you also for inviting me to this panel. To build on what Anne said around data and analytics being the core of R&D for you know decades in the industry I think from a commercial perspective we have been focused on how do we get our medicines and vaccines to as many people as possible as quickly as possible and I think we have been slower to adopt data and technology in that in that sort of journey. So from a commercial perspective I think the opportunities are huge everything across the value chain from getting broader access across countries around the world based on the data that we have around the patients who could benefit and pricing and market access to patient identification better understanding of which patients could benefit from which therapies leveraging data that we have around clinical decision support in terms of when different therapies may be most beneficial you can see a huge value even in supply chain on how to deliver differently to different countries and different populations to reduce some of the disparities and care around the world and then last but not least improve the broader outcomes right help leverage technology and data to help supplement the medicines and the vaccines to make sure that patients are getting the best outcomes that they have been promised so the opportunities are significant across the value chain I'd say where we have focused in the past on a commercial side has been more around looking at it more from an efficiency play and I think what sort of the tipping point or the news sort of way to look at it is to think about what are all the opportunities to actually improve care and improve outcomes and the more payers and consumers around the world start demanding more of sort of this outcomes-based approach I think the more we will see better leveraging of analytics as well as technology including partnerships right I think that's the other sort of tipping point that I'm seeing is not everything has to be done by a single company it's really around working through the ecosystem to find the players that can partner with us to get to those best outcomes. From a COVID perspective I can give just one example so I'm sure there is many more I think COVID has really accelerated a lot of the predictive aspects of the work that we do so a specific example is you know when COVID the pandemic first hit we did a lot of predictive modeling to look at at a country level where do we expect increased utilization of some of our anesthesia products just given all the innovations around the world we were able to predict at a country level where we expect a demand to increase and at what time period we were able to increase our supply and manufacturing of those products as well as completely change our supply chain to make sure the countries that would need it at certain times would get it when they need it so I think you know that's just one example of how we are accelerating a lot of our predictive capabilities to get our medicines to the people who need them. So maybe I'll go next Sastri thank you for having me for having me here it's always a great pleasure to participate in this meeting so you know to build up on a few things I may be to take it more from the patient angle so the most exciting you know promise of digital health is really it has the potential to put back the patient at the center of the healthcare ecosystem and and just to provide a bit of context in terms of what we do and hence kind of you know the opportunities I see from that angle our mission at the outcomes for me is to empower patients and improve outcomes and we start with cancer so some of the examples I'll be giving are linked to cancer we do so by engaging cancer patients and enable them to take charge of their care and in doing so our goal is not only to improve patient outcomes even though that's ultimately the goal but also to accelerate research by collecting the data needed to drive innovations so this is where you know data science becomes a very important component but in the past year I think you know I'm most excited about you know five key opportunities COVID being the last one which is the accelerant but I'm getting some echo so the first being the consumerization of healthcare I mean consumerization of everything but we're starting to really see a real pull on the healthcare side from the consumer side patients demanding to be part of the decision part of the information we definitely see it with the people we interact with these are patients that have been diagnosed with cancer the second is really around access to information so as some of you or maybe many of you know the CMS and the ONC the office of the national coordinator issued their final interoperability rule on May 1st of this year this is going to fundamentally this is probably going to be a major tipping point because it will break down the barriers that impede patients ease of access to their information in a digital format and so it will accelerate the empowerment of patients and enabling to leverage that information to drive outcomes the third opportunity also happened this year or continuing to build this you know experiments it's along the lines of value-based cares and experiments that we see regulators starting to take so starting with you know the CMS innovation center has been doing in the past five years a number of experiments on new innovative payment models but the recent model so the oncology care first model which will launch next year which is in succession to the oncology care model which they had for the last five years has two major changes in it and in particular on the patient side so it actually provides the potential to reimburse and to create value based on quality of life impact on patients which I see as a as a great opportunity and potential accelerant for digital health and then the FDA has recently actually just last month launched a program to communicate patient reported outcomes from cancer clinical trials and so this project they call it project patient voice which you start seeing regulators really moving to really put the patient back at the center of the healthcare system and then just on the science side so here maybe I'll share some of the data we've seen recently Laurie mentioned earlier that you know some of the greatest potential here is also around you know early screening inherited cancers but also genomic profiling and liquid biopsies so just to give a sense of what we've seen recently only 50% of patients are tested either for genetic profiling or inherited cancer among the ones that should be tested and so if we can really move that needle empower people to have a better conversation with their physician which we've shown to be able to do that could really drive more impact just to give one example in breast cancer which is a disease we're very present and there's been a recent approval for a PIC3CA mutation where 40% of patients with hormone positive herd to negative breast cancer advanced breast cancer have that mutation but our data shows that only a third of those people are even being screened for the mutation so this is where we can see opportunity to quick you know enabling outcomes so finally in terms of COVID-19 I mean a lot of it has been said but I'll just you know highlight a couple telehealth you know the movement to telehealth has an impact that not only providers are pretty much have really gotten into digital health but also now they're embracing tools that help empower patients and manage them at a distance and here I'm thinking about asynchronous patient reported outcomes we see that in the context of clinical trials also we're doing a clinical trial with MGH where the entire consenting system went online and remote a fundamental shift for the organization and then finally where Laurie mentioned that unfortunately there's been a huge backlog of screening now when it comes to cancer and potentially impacting the outcomes in the short term in terms of overall survival here digital health could play a huge role a huge role in terms of getting people the information they need access much quicker when they need it quicker so with that maybe just to finish on the tipping point you know if I were to pick one it would be patient access to their own data would be the real tipping point right Nina so you can tell from the introductions that I'm not the at the health IT genius on the panel and the venture capitalist who is a broker and a backer of genius so maybe I'll attempt to summarize a little bit of the great comments that have been been made which I think the reason that there is hype about that big data or digital and in the ecosystem is because there's a sense that data science has been slow to come to the biopharma industry and I think that's a real misnomerized as Anne had said we've been using data science and and computational tools in our industry for a long long time and it's just staggering the pace at which we are accelerating discovery of new chemical entities using transcriptional and translational omic data on the target side and then fantastic in silicon computational screening and structural information on on the drug discovery side on our portfolio at Canaan where we do a significant amount of biopharma investing you know we're going from new biology new pathway to a candidate going into iind enabling in faster pace than than we have seen in the 20 years that I've been in this business it's really exciting whether that's a company like vivace that's driving the hippo yeah pathway which has been previously undruggable and they've gone to a candidate going into iind enabling work in less than three years or tyra going after gatekeeper mutations in an entire shin kinase inhibitors and following that path and targeting oncology going into a candidate development within six months of of investment so data science science is data science I think in drug drug discovery I think sitting in a diversified fund at Canaan where I have the privilege of two-thirds of our investments being on the tech side I think they're they sort of scratch their head at why is there not more sort of consumer and mobile and empowerment and ready or access to that that data because they see that disrupt every other industry much more readily and that of course is because our industry is a heavily regulated one and we have to deal with that and that was our first points about the challenges on the commercial side and go to market and why it's more difficult because of liability reasons privacy and security reasons to access those data sets and then also our industry whether you're on the pair side or on the farmer side is also a paranoid data hoarding very protectionist at times paternalistic industry and so we haven't opened up and and created large data sets I think Hal baron has pointed out that what we do in the pharma industry is you know sophisticated multivariate analysis because we're dealing with data sets that are so small because they're not side likes to laugh at us and say you're not doing big data you're doing small data with some statistics so I think that's another reason why there's some thought about about hyping and so I think what we are facing little bit is an existential question as an industry you know are we really going to democratize data are we going to open up and how are we going to work in a regulated environment to really bring consumer insights to bring open source to really liberate the data for better for better insights are we going to publish and make access to failed studies are we going to open up all the data so that we can learn and accelerate for the interest of public health and and global human health I think that's something that that we're going to have to wrestle with because consumers want better public health needs better and we as a society can't get to 50% of GDP going to going to healthcare and the industry I think can really solve solve for that aside from incredible acceleration of drug discovery and that being a huge benefit of data science and computational power the other places of course that we're seeing incredible opportunity generally is through large data allowing us to make more consumer insight and customization personalization of products and services in healthcare that will come increasingly I think to Biopharma as well and the wraparounds around products for adherence and for a preferred side of care and for better better sort of precision prescribing for the right drive to the right patients precision medicine we have a cellular therapy we're doing you know really deeply personalized neoantigen T cells for solid tumors we think that has a real opportunity to eradicate solid solid tumors and then of course in development really adapting clinical trials for a better diversity of enrollment diversity of site and inclusion virtual clinical trials have synthetic control arms and the like using all sorts of data riches and alternate site and remote and mobility to to better better better execute the development of drugs and generating real-world evidence as well. I'll go next you know I think there's a lot of good ideas that have already been shared just to go back to the hype piece I mean I think I take a slightly different perspective on that in the sense that the last six months both the internal and the external ecosystem I think we've started to see convergence of real problems and when I think about real problems like just to echo what Anne said it's how do we build and make better medicines for patients really start to happen you know and as Roy Vagelis said I think there has been for some time a lot of chatter so it's exciting to see that the chatter is coming down with a lot of these data sets with exactly like specific problems that we're solving for so I think that's that's at least my perspective in terms of the opportunities I won't recap everything that's said but I would say that there is a opportunity for connectivity right so if you think about a lot of these real-world data sets across broader populations but also more niche data sets that are coming through I think about how do we use that and it's happening actively not just for approval purposes but also for access that connects to what ARPO is saying as well but doing it much much earlier in the in the development time frame right because a lot of the data sets the models even the partnerships that we do there is commonality across the board so if we really think about scale at an enterprise at a cross-value chain perspective that is something that's is going to be more more and more important and I think it's going to be critical for how we create scale so if I had to think about the tipping point as you mentioned I think it's really going to be how do we have endpoints that are more based on or at least reflective in some way of the real world data that we see and you know that will help us not just with our regulatory approval but also access I think that integration is going to become more and more tighter especially when we think about oncology or also rare diseases with that integration already happens more today and also this ties to other things like external control arms and you know Shastri you're very close to this work how do we see that go beyond oncology and rare disease to other areas where the standard of care is something that becomes important also for access perspective and then I would say just going downstream how we recruit patients how do we match patients the whole feasibility process and monitoring I think that there has been flickers of how we can do it differently but I think more and more the right data sets are being pulled together I would say more in the US X us is still going to be not at the tipping point right now but it's getting there how do we do that in a completely different way and we have had some success in that and then the last thing I'll say which is a challenge I'd love to see more progress in that is when we build all these models and we have great data a lot of it is around validation making it explainable and then the validation this is again something that I think Barbara was saying which is make ensuring you have consistent high performance not just a one-off because that's really going to drive traction with the clinicians with commercial leaders across the world right if you think about the change management perspective as critical here and there I think not just validation in our programs but the deployment of some of these algorithms through health systems that we partner with so this goes beyond just by a pharma through other organizations that we partner with that is going to be a really big tipping point if we can make a difference I think we've talked about it but if we have specific areas we can focus on that can have a clear shift in how we do our work but also get it embedded in the broader ecosystem to have impact last thing you know you mentioned in terms of COVID-19 completely agree on telehealth one thing I would say you know J&J we've been working really hard on our COVID-19 vaccine as many of others in the in the space have in the biopharma space and it really has catalyzed how we not just embed the use of real-world data and I don't mean just claims or lab results but social media mobility data many many different types of data sets that I would detect companies and consumer companies are much more active at using but then actually do that early on in a program right today a lot of the times it's an add-on is to check the box but you know we should do something with data science versus actually using it in a meaningful way to understand the disease itself given there's so many unknowns we would love to see traction of that even going forward post in the post-COVID era and we've used that and I think Ann mentioned a little bit as well to understand the severity distribution it's a really hard problem right and really important for her for our vaccine program and our case endpoints to say who's going to get more steak and how do we detect who are we going to detect more in the clinical trials why is that important if you get to events faster as a faster trial it's deployed quickly then the other thing I'd also say in terms of which countries to go to setting up are you are mentioning understanding the utilization and certain products in the space in in anesthetics and others in in the commercial space but also from our vaccine trial perspective where do we expect the incidence to be high where should we target in terms of our trials and we've taken a very global perspective of that but I can imagine that such predictions would also be helpful and we're not to go for other programs and then also how to use it for other infectious diseases other different modeling that they'll use so those are just some of some ideas where I think we can really leverage what we've already done the good work already done today great so I'm looking at the clock here and I think we have about eight minutes left so maybe I'll call on you for the next few questions so Arpa if you compare the tech leaders like amazon and facebook to a typical biopharma company the e-bit per fde is something like 5x higher for a tech company I know the business models are different but for me it's more a measure of agility and speed the organizations move faster they kill they make decisions faster and this came up a little bit in the investment panel as well so as you think of these large big pharma companies what do you see as the biggest barriers or challenges to the broad-based adoption of digital and data science yeah so I think it's a multi-factorial sort of set of issues I'd say I think the easy answer that a lot of people lean back on is around regulation privacy sort of where we're constrained and how we can operate directly with consumers or with payers or with customers based on world-wide restrictions that's certainly one issue but from my perspective I think the bigger issue is a culture a cultural bias almost at least that I see sometimes in terms of a risk aversion when it comes to healthcare to experiment in a way that maybe a tech company will experiment on at risk aversion to trying new technologies or new you know adopting new methodologies that are directly impacting a population or a patient's life right so I think there's a cultural sort of bias towards sticking with what we have done partly because what what we've done over the last couple of decades has been successful for the industry right so I think there's a little bit of we have been successful until now and I think I think you know there's also been as I mentioned the regulation there's also been in different countries around the world just significant fragmentation of data where we haven't been able to actually get the full value of what's possible so I think it's multiple different things that's where I see you know this tipping point I think Maya and others mentioned the consumers really getting empowered and taking charge will be a tipping point I think the other tipping point is clearly going to be sort of governments and payers mandating more of a value-based or an outcome-based approach to healthcare and as soon as we get there we're not going to be able to get there without fully leveraging the power of data analytics and digital technologies so I do see this changing and I see it changing quickly but it's going to require a lot of shifts in terms of culture in terms of talent and in terms of our business model so I mentioned at the beginning of this meeting that it took us 14 years to have an all-women panel and it would be a missed opportunity if we don't talk about the broader opportunities for women and STEM as well as in the biopharm industry so maybe we go in the reverse order and I don't start with you on what advice do you have for women who want to enter and more importantly thrive and grow and lead in this space Yeah I know I'm so glad we're having this conversation you know we have this I'm sure all of us want this panel on a one-on-one basis you know when I stopped the question I was reflecting a little bit on what was important for me and I said two things one now I always say if you want to go into a space especially when I think about all different fields not just data science it is becoming more and more interdisciplinary right and you have a team of epidemiologists stats data scientists data engineers I mean a lot of us do it's really important to know a lot of different areas and skills as well as the science so what I always say is start with yourself to really be honest is this an area I'm interested in and if so you will always be leaning in one field more from a trained perspective and then another field more from a self-trained perspective right if I look at my own background it's the same thing so how be proactive first to really make sure you sweat the details to be the best you can be in the space you want to thrive in so that's number one I always say focus on yourself and for that it actually it's super helpful to have a community of folks you can reach out to you know not all great ideas are in one's head or in a book and the space is constantly evolving so I don't like to use the word network because it sounds a little I don't know it's overused but to actually have folks in your community that you just know you can reach out to so that's one how do you make the best of what you do and then then I think there's another aspect that gets less talked about it's talked about more in the headlines that we should have diversity inclusion we should have more women we should but really think about investing your time in a company biotech startup wherever with a group of people that share that same vision share the vision in terms of what's the overall mission to help patients better medicines but then also really just not just talk the talk or walk the talk in terms of will support and ensure that there's diversity on those teams that there's a plan in terms of how do you actually promote women and I don't mean promote just from a job perspective but promote in terms of ensuring that's the right opportunities just right and you know that's something that requires a lot of conversations and it's the worst thing to be in the wrong place where there's a lot of hype in terms of we do this and then get to the job and it doesn't really happen it isn't that day-to-day support that's needed so I think both those aspects are so critical to be successful once inherent and intrinsic to yourself and the other is I always say being a good detective and really keeping your ears open to understand how is that place where you're going to invest the time going to support you back so it's a cool investment Nina I would echo that I would say to the girls or the women go for it that advice is really simple you go for it and hang in there you deserve to thrive in an amazing field biopharma and digital health health sciences health IT is a fantastic career path it is the most rewarding to be making decisions for patient and public good and excel at it and enjoy go for it and the advice is really to the organizations and to the managers out there it is more than time for diversity equity and inclusion it is more than time for that girl and that woman not to have to do the work and do the heavy lifting look at your policies look at your organization look at your culture and have zero excuses for why a woman an lgbtq a black or brown person would not want to or be able to go all the way and thrive at your place of work this is fantastic that it's an old woman panel it's fantastic that there were women and people of color all over this agenda so hats off to andy and perun for that it's time it's more than time maya yeah so maybe i mean i agree with everything that has been said maybe just so a lot of two things well i'll add one thing and i'll reiterate another one so to the to the person kind of looking to enter the space i would or kind of you know like um early in her career my biggest advice is don't undersell yourself and the reason i really say that is as a as an early stage company we've been recruiting a lot and most recently since covet and now i see it systematically where women tend to undersell themselves and not even apply for a role because they don't have all the parts of that role so that would be my advice and then up to the organization i mean i just i agree i agree with what nina said but i will emphasize something that nina said which is culture culture gets said very early on and especially in the pure tech or digital health health tech you know the engineering culture and how you want that to be pay attention to it because that's essentially going to be how diverse the company is going to end up once as it's growing all right arpa and then so i i completely agree with everything that's been said i might just take a slightly different uh twist on the question that's i think about um i'm a parent i have three children one of them is a daughter and um the other sort of call to action i would throw out there as we think about the longer term is um there's a tremendous amount of evidence that early exposure to stem and to these types of careers is really um the tipping point right so um i think i would encourage all the viewers to also think about the younger generation and making sure that we're supporting them and exposing them to stem as early as possible um because there's a lot of evidence to show by the age of 10 or 12 if you haven't seen or been exposed to or um had interest in or been inspired by others um in the field it's very very difficult to change that going forward so um from a long-term perspective i think there's a lot we can do whether it's as mentors sponsors uh or as companies um to help from a long-term perspective as well and i have four very very simple things to add one is get educated get out there get your education and frankly phd is international it goes everywhere with you number two say yes opportunities are exactly that not extra work number three and i think it goes back to the community solid foundation family friends and people that challenge you and make you push yourself and lastly actually particularly in this data and digital space don't be put off by all these differing terminologies of data architects and data engineer and exposure of data it's all just data and mathematics and if you know that you're fine fantastic i think we're out of time here so my apologies to Anil Sawant and Peter Muller who had amazing questions around the role of regulators in terms of uh software as a medical device as well as uh thinking around uh how do you start to break the silos between the various uh parts of the organization within pharma companies and i'm sure we can keep this conversation going on for a much longer time than what we have here so i'd like to thank the panel a lot for giving us their time and their advice and insights it has been truly exciting and we look forward to getting together again next year hopefully in person


The mayor and councillors of the Castery City Council conducted a tour of the facilities and areas that are the responsibility of the Castery City Council. The tour spanned a period of two weeks and provided the council an opportunity to assess and identify key areas that require immediate attention. The final leg of the facilities assessment tour was conducted in Castery South. The Minister for Tourism, Investment, Creative Industries, Culture and Information and the Parliamentary Representative for Castery South, honourable Dr Ernest Helaire, joined the CCC team in touring the community. He commended the mayor and the councillors for undertaking the initiative. The playing fields that they have to maintain, the community centres that they have to maintain, the clearing of certain drains that they have to maintain. So we visited a number of products. We started by the Old Cemetery Hospital Road, about the clearing of that Old Cemetery, removing a lot of debris that have accumulated over the years. We did four shows of the drains, burn and play in field. We did a few other areas, ended up in passages. We have to look at the incompleted community centre, Marigo, the playing field and different areas throughout the constituency. We stopped them to take a look at it. The hope is that the Castery City Council will have an assessment of the work that they need to do in the constituency. They can then prepare their work programme, they can do their budget and they can seek the financing from central government to fulfil their mandate. The Mayor of Castery's her worship Geraldine Lendor Gabriel indicated that an important component of the tour was consultation with various community groups. This she said ensures that the CCC's addressing the needs of the community. She lauded the communities in the Castery's area for their positive response. We found that generally the communities were very welcoming, the persons in the communities were welcoming and not very demanding. I think the things that they were asking for are very basic things that need to happen and so it requires that we address those needs quite quickly. Some of them are a little more challenging than others but there are some, what I would call, some very low-hanging fruits that we can actually address quite quickly and we are committed to ensuring that we do so. The Mayor further outlined the way forward now that the problem areas have been identified. As we speak, when we went in last week we've actually gone into the Human Resource Development Centre at Entrypo. We've already begun discussions with the group so we have a meeting quite soon. As I've indicated, we're not going to just go in there. We need to know what is happening, we need to speak to the people who have had oversight for some of those facilities and work with them. So we are going to be rolling out, the next four weeks would be meeting with those groups and for us to identify what is considered to be the most important to them because again it requires budget allocations, allocating the resources in the best way because we do not have everything. But once we do that I think it's going to allow us to be very strategic about closing those various gaps over time. The final leg of the Castery City Council's Facilities Assessment Tour took place on Sunday 16 January 2022. From the Government Information Service, Lisa Joseph reporting.


Question is from DSA Inc. 213, what are the differences between a front and behind-the-head overhead press? Is one more beneficial than the other? Okay, so they both have unique benefits, but before we get into those, one is more risky. Yeah, way more.  A behind-the-head overhead press requires a lot of good mobility control. You have to explain. It wouldn't be if we all had healthy posture. Yeah, if you could just, it's not the case. Yeah, I mean if, and that's why we weren't taught it in any of our certifications. Like if every national cert that I have, every single one of them, none of them advocate for it. Oh, they avoid it like the plague. Yeah, it's a do not do type of deal. And so that's why I didn't teach it and I didn't do it myself for many years, which actually probably did more harm than good for me. And the truth is, if it hurts you or you can't do it with good form. Don't do it. Yeah, don't do it till you can, but that's a great sign that there's an area you need to work on. Totally, yeah. And it's the lack of shoulder mobility and probably thoracic mobility that is limiting you from being able to do that, which is an obvious thing since I think the percentage is somewhere between, I wanna say 65 and 80% of the population suffers from upper cross syndrome. So if a majority of the population have the rounded shoulders and the forward head, well, yeah, trying to take a bar behind your head.  Yeah, but if you can do it, it's gonna promote good shoulder mobility and thoracic mobility. Totally. So it's kinda like the, think of it the same way of like doing a deep squat. Most people shouldn't do an astagrass squat because they don't have the capabilities to do it because their form is gonna break down, they're gonna fill it in their low back, they're gonna fall way forward, but that's a sign that you should work on that. So I was this person. Now what's cool, now that I've done all the work of working on my mobility for a solid year and a half or so to get into a deep squat, now the only thing I need to do to keep mobility in my ankles and my hips is deep squat. That's what's awesome is that, so if you can't do behind the neck presses right now, the real benefits of being able to do them is it promotes good shoulder and thoracic mobility and that's an excellent thing. No, totally. Now an overhead press is hard to do for the average person anyway. It still requires work and mobility and you take that behind the neck and you've just exponentially made the exercise far more difficult. Now that all being said, just like Adam said, if you can do them properly, if you have good control, good stability, I love behind the neck presses. It's a completely different type of form. I feel it in different parts of my shoulder. I go lighter because of the position that I'm maintaining, the pumps I get in my shoulder phenomenal. I feel like I get less of the front part of my shoulder and a little more of the side of my shoulder when I'm pressing up, mainly because of the position that I'm trying to hold myself in. It was a favorite among bodybuilders back in the day. Back in the 70s, 80s and 90s, bodybuilders favored behind the neck press over traditional overhead press. The overhead press didn't get popular in bodybuilding. It was popular originally in the 40s and 50s, maybe 60s. It didn't get popular again until relatively recently because you had bodybuilders like Jay Cutler who did standing overhead presses and of course whatever the top guy does, everybody else does. But for a long time, it was all about behind the neck presses, behind the neck pull downs. You see Arnold Schwarzenegger and Franco Colombo doing them like crazy. I love them. I have to go much lighter. So if I do an overhead press, I'm gonna go, the lightest I'll go with a barbell is 100 pounds. As I'll go as heavy as 130 to 140 pounds. When I'm behind the neck, I go 50, 60 pounds and maybe 100 pounds at the absolute heaviest. Yeah, I would definitely put that as an advanced exercise to where it is something that is achievable and attainable and it does provide value. Like it definitely promotes a different stimulus for your muscles to respond to and it does help your shoulders build in a different way but it's gonna require a lot of work, a lot of prerequisites to even get close to be able to have access and also to control it properly. This is why I love the Z-Press. The Z-Press. I fell in love with this exercise for this exact reason. It was around the time that I was working on this. Yeah, cause when you first, it wasn't long ago you first started doing behind the neck presses. Right, cause I couldn't. Like many people, I couldn't take the bar behind the back of my head without forcing my head forward and what I loved about that. Now, some of the, obviously the prerequisites that Justin's talking about, your wall circles, your thread, the needle, your even doing a PVC pipe, your handcuff to rotation, these are all great mobility exercises to do to start with getting in the right position. Then the exercise that I love to do to help me get to a place where I can do behind the neck presses is the Z-Press. And the two main reasons why that. One, when you're in the Z-Press position and you press, which for those that don't know what that is, it's when you're, and I like to do it inside the squat rack where I'm sitting on my butt and I use the- And your legs are straight out. Yeah, my legs are straight out and I use the guards on the squat rack, like you with safety guards to start the bar on there to where it's resting by my chest.  And the key to this is the stabilization at the top. So I, when I'm teaching this to a client that I'm working on this with is we'll start really light and we start in the Z-Press, we press and it completely extend all the way up and stabilize up there. That stabilization with the bar completely extended above your head, your head pulled through the window, we say. And that right there is a great place to start. This is also why I would do those like one-arm carries and stabilizing like weight overhead carries. And then also, because you need to learn that mechanism, that mechanism on packing the shoulder. So not just reaching out, but you have to anchor that too with your shoulder blade. And so to be able to stabilize properly in your full lockout, being able to control the load, be able to decelerate it properly, bring it down nice and slow. And all these things involved, it takes some time and effort but you definitely can build your way towards a nice solid behind the neck press. And the beauty of the Z-Press is that you can't cheat it. And that's why I like it better than single-arm exercises or machine or anything else that you're trying. It's great for teaching. It's almost cheaper. It is because in order for you to stay upright and fully extend to where the bar is above, or behind your head and your arms in line with your ears, that's the only way it works without you falling backwards.  And so it's a great way to teach those good mechanics. This is like to Sal's big argument on Instagram in the last few days about, here's a good example of like, this is where coaching comes into play for a really long time. If you were to show somebody the research on a Z-Press compared to a standing overhead press, which builds the most muscle in your shoulders, like Z-Press is gonna lose. It's not a better movement in comparison to a standing overhead press where I can generate more force and I have more. But its value is not in building muscle in comparison to it. Exactly. And so that's just something that you've learned from years of coaching people and knowing that trying to- And application of it. Right, getting clients to cue them the correct way to do the movement properly. It's one of those little trainer tricks I love. You know who does a version of that exercise that I've seen done over and over again of that is Olympic lifters. You ever seen Olympic lifters? They'll put the bar across the traps.  That's a move, what does that call, Justin? That's a move, isn't it?  But it's off the traps. And it's in a seated position. No, no, standing. No, standing. It's explosive. Oh, you're saying standing.  They can't be forward an inch or back an inch or they're gonna lose the lift. So that's one of their lifts. I saw a video on YouTube of Mario Pudzanowski. He was the world's strongest man doing that with like 300 pounds. And that encouraged me to do a full range of motion behind the neck press. When you get really good mobility and control bring the bar all the way down to your traps and press all the way up. The pump you get from that, but again, you gotta do it right.  But the pump you get from that is insane. It's one of the number one exercises that'll give me the best shoulder pump by far.


Evil people are characterized by being very ego-driven and vain are traits that the God of the Bible, the Torah and the Quran has in a huge abundance. We see that the first three commandments out of the ten commandments illustrate this. We see that he commands that there will be no other gods before me. There will be no graven images and you will not take my name in vain. That's correct. God of the Bible set these three commandments in motion. He had ten, but he wanted to make damn sure that the first three edified him and placed you in a position where you would always be trying to seek brownie points from him, where you would always be in a position of subservience to him. Hey man, can I share something with you?  I've seen other people accuse him of being self-centered and prideful. But let's think about that for a second. When you're prideful, egotistical, narcissistic, self-centered, why is that a bad thing? One aspect is the attention and praise you're trying to garner for yourself is not deserved. You are not the most important thing in the universe, therefore the attention you're trying to get for yourself is not justified. But think about God. He is literally the most important being in the whole universe. He is the Alpha, Omega, all-powerful, all-knowing God. Therefore, when God tries to get our attention, it's not only right because he is the most important being in the whole universe, but it's also good and loving of him to point the attention onto himself. After all, he's the best, his beauty, his glory. When we try to get all the attention for ourselves, we're revealed as a fraud when our flaws are exposed. However, when God demands our attention, we are met with an all-consuming love that does not disappoint. That's good news.


What's up everybody jason from jatsby's case breaks calm We are giving away the last six spots in the threes company football mixer with this 2018 panini prestige football One fat pack break random teams number 16 and again guys first We do the break we randomize the customer names and teams distribute the hits out and we know veteran common shit But everything else does then at the end of the break will randomize all 32 customer names top six names win a spot in the threes company break Good luck Here's a dice roller customer names teams. Let's do it Four and three seven times One two three four five six seven Adam done a quarry one two three four five six Seven, which are lions down to the Cardinals. All right again guys take to what you got. It's a quick little pack filler So something super crazy. All right, so quickly. Let's you see your teams really quick right there What up Aaron? How's it going buddy? How it goes? How it goes? All right, let's quickly do this. All right, so let's quickly go through the base We got Don trout in man. We got Joshua Jackson. That's a rookie there. We got Baker Mayfield last one right there Mike Gasecchi Treyquan and There you go. I'm doing all right, man. Happy Father's Day. By the way, man. All right, so Here we go threes company coming up filler time randomize the time So here we go again the last six spots Are we giving away here top six get in guys roll? Three to six nine times. Good luck one two three four five six seven eight nine All right, so you got top six Scott Corey Natalie Greg Jason and Aaron at the top after nine times It was top six Boom So congratulations guys you guys are now in The break itself coming up next is the Jatsby's threes company football make sure that includes three boxes to select Three boxes of containers and three boxes of one football. Appreciate you guys


We will now hear from Dr. Robert Green, by the way, no direct relation. Of course, we're all related, but just happened to both have the same last name. Dr. Robert Green earned his MD from the University of Virginia School of Medicine and completed his residency in neurology at Harvard Medical School's Longwood Neurology program. And afterwards, he completed research fellowships at the Beth Israel Hospital and Children's Hospital in Boston. Now, Dr. Green is an associate professor of medicine in the Division of Genetics at Brigham and Williams Hospital in Harvard Medical School and also associate director for research at the Partners Healthcare Center for Personalized Genetic Medicine. His research interests have evolved from a focus on clinical trials and genetic epidemiology to a focus on translational genomics and health outcomes. He has been continuously funded by the National Institutes of Health for 21 years and has published over 300 articles. His key contributions have included the development of risk estimates based on family history and genetic markers, leadership and analysis of large multi-center treatment and prevention trials, including trials and enriched through family history, and design leadership and future planning of the first large-scale randomized clinical trials in translational genetics. He serves on a number of advisory, editorial, and grant review boards, and he's been invited to participate in NIH planning workshops in the future of genomic medicine, and has been a featured or plenary speaker on translational genomics and personalized medicine at meetings both national and international in scope. So we will please ask Robert Green to please come up and we will hear from him. Well, thank you. Thank you to the organizers of the Smithsonian. Thank you, Eric. Thank you, Professor Wolff. And thank you all for coming out. It's an exciting night. I hope you were as impressed by Professor Wolff's historical review as I was. And I think we can all agree that racism is wrong. The Holocaust was evil. Patients' rights should be respected, including privacy, including the right to refuse treatments and tests. And in your final and stirring ending, that patient privacy, patient rights, and public trust are critically important. So if that is where we're going to go, there is no debate. We totally agree. But as we'll talk more about, I think, in the give and take portion, I believe Professor Wolff has fundamentally misread the nature of the practice of medicine. And I'll go more into that after I make my prepared remarks. My prepared remarks, however, are that genetic information is fundamentally similar to other types of medical information and that we need to beware the FUD. Now those of you with smartphones don't look it up right away. Let me surprise you with it. I'm going to start my talk by disclosing, as I disclose with every talk, that my research is primarily funded by NIH, especially NHGRI, to which I'm grateful, that I have financially unentangled collaborations with some of the direct-to-consumer companies that I occasionally speak. And I'm compensated for speaking from Illumina, a maker of genome sequencing. And I occasionally advise some other companies in this space. But I'd also like to disclose something else. I grew up around here. I went to school in Winchester, Virginia, only a few miles away. And I'm so pleased that some of my friends from Winchester have joined us here tonight. And we all got our start with teachers and mentors. And Laura Rob, my fifth-grade teacher, and John and Marjorie Lewis, my sixth-grade church group mentors, are here in the audience. And just as, before I continue, if you just give them a round of applause for me as I stand up, stick your hand up for me. And I don't know if it was fifth-grade or sixth-grade or seventh-grade, but somewhere along the way, I and most of you probably learned about Gregor Mendel and his peas and plants. And this fundamental and early historical example reinforced in your mind that genetics was somehow deterministic, that if you put the right traits together, you always got this trait. Or if you had that funny recessive thing going on, you had that probabilistic situation with the traits. But that fundamentally, genetics was destiny. The genetics meant that if you had this particular gene, you had the particular pea color or the particular disease. But with the Human Genome Project, with the extraordinary knowledge that Eric outlined and that we've learned, and with what has happened since 2003, we've actually learned that genetics is very rarely deterministic. Sure, genetic variation is responsible for everything, what we look like, what we perhaps some degree to our temperament, or at least partly responsible for some of these things. And Eric mentioned to you that we've got these, most of our DNA is exactly the same, but we've got these variants throughout the genome that make us slightly different. And most of the diseases that we have, especially all the common diseases, are not the products of one variant or two variants. They're the products of hundreds of variants. That deck is shuffled and it's like throwing a deck every time, it's like throwing a new paradise every time you're born.  But they actually turn out to be the exception. So determinism in genetics and genomics is the exception, not the rule. Now this principle, determinism, has somehow embedded itself, whether it's early, whether it's being an elementary student and studying about Mendel, or it's a number of other things that I'll tell you about, this principle has embedded itself deeply in our psyche and it is really hard to dislodge. We've all got it. And it's certainly that this principle has been abused, just like other principles have been abused. But in fact, there's a bunch of historical antecedents to genomic medicine that have stressed determinism and stressed caution. Some of these are justified, some are less justified, but it has been an insistent drumbeat of determinism and caution, caution and determinism as we have moved forward with genetics. Some for very good reasons. We learned about Mendel and his peas early. Pre-conception and pre-natal testing around the birth of a baby are highly charged. If a woman is gonna terminate a pregnancy, she has to do so in a limited amount of time with tremendous emotional distress. Caution is warranted there and those were some of the first examples of applying genetics and genomics. Newborn screening is one of the greatest public health successes of all time and newborn screening involves testing for some very, very rare deterministic mutations. Misattributed paternity.  And that's throughout most societies around the world. And guess what? Genetics reveals that pretty easily. That's a sensitive subject. Talk about patient partnership. The current caution attributed to this in genetics. I was shocked to find actually has geneticists and genetic counselors being advocating to misrepresent the truth to families on whom they stumble across this. I'm troubled by that. It's an unhappy truth perhaps, but it's still the truth. Huntington disease was the first disease for which we had a reputable genetic test and for many years it was the only disease for which we had a test, a predictive test. And it is by far the exception. It is a horrible disease that comes on in adult life is always fatal and there's absolutely nothing you can do about it. That example colored our perception until today. The complexity that Eric referred to is pretty daunting and it colors our view toward the entire field of genetics and genomics, even in situations where things are pretty straightforward. We've had a certain amount of optimism about genetics. I've shared in it, Susan says she shares in it. We've even probably used it to sell genetics to the Congress and to the public. Maybe we've oversold it, part of that overselling at times or at least oversold the timeframe. Some of that is a reflection of determinism. Hey, we can tell you everything about yourself because genetics is so deterministic. And as Susan said, the budget of the human genome project had a set aside earmarked, millions of dollars earmarked for ethicists to study the ethics of genetics. Now listen, that's a good thing, don't get me wrong. I've benefited from this, Susan's benefited from this, the world has benefited from this. But if you're an ethicist coming into a field searching for funds, are you gonna say everything's fine? Go ahead, no. You're gonna say this is bad, this is dangerous. Be careful about that, watch out for that. So there has been, I would propose, all of the historical antecedents have created a bias toward FUD. What is FUD? Fear, uncertainty, and doubt. And so I lay this groundwork because I really believe that in the long run, I believe that some of these early examples have created certain sensitivities that we absolutely need to respect. But in the long run, as genomics becomes part of medicine and part of our everyday life, fear, uncertainty, and doubt will do more harm than it will do good. FUD number one, genetic information is different because it's gonna frighten people. Well, 14 years ago, every Alzheimer's specialist in the world said you should not disclose their genetic risk for Alzheimer's disease because it will terrify people, there will be catastrophic psychological reactions. There's a gene called APOE, and if one in four of you actually carry that, the allele that puts you at increased risk for Alzheimer's disease. That's maybe, I don't know, 25 of you, 30 of you. So 30 of the people sitting in this audience are at increased risk for Alzheimer's disease, about three times the risk of other people. How many of you would like to know if you're going to be at that increased risk? How many of you would like to know the answer? Okay, well, it's usually higher, but then usually Susan isn't speaking in front of me. I don't think you should have to know either, actually, but I think you should have the right to know. And pretty much every ethicist of the day, 14 years ago, said under no circumstance should this even be offered. We put that to the test in a series of randomized controlled trials over 10 years in which we enrolled over 1,000 people in something called the Reveal Study and people who wanted this information did very well. I'll refer you to all the papers if you'd like, but that's the bottom line. FUD number two, genetic information is different because it's too complicated to be understandable. You heard themes of this. We didn't get to see each other's slides before this, by the way, but I kind of thought she'd touch on some of these. It's just too complicated. People are going to misunderstand. There's going to be errors. Well, it's not like there's no errors in the rest of medical testing, right? I mean, really. And it's not like your doctor understands all the complications of every technology that he or she is using. It's not like every patient understands everything that the doctor is saying. In fact, we have hands-on evidence from the Coriel Institute's Personalized Medicine Initiative where they're giving thousands of common complex snips back to doctors and patients together. From the radically progressive personal genome project where George Church is sequencing hundreds of individuals and putting their entire sequence on the internet for anyone in the world to use. From the multiplex study, an NHGRI study that has given SNP information that's common risk information to hundreds of individuals about common diseases. And from the incredible ClinSeq project, another internal NHGRI project led by Les Beesiker, where nearly 1,000 people have been sequenced and make no bones about it. He's maybe sequencing them for some cardiac risk issues. But he's telling them whatever he finds. And he's found some fascinating things, including making diagnoses on people who had problems and never knew they had the problems. Sequencing has allowed us to peer inside previously completely unsuspected diagnoses. In our own NHGRI-funded Impact of Personal Genomics study where we've questioned thousands of people who took these online direct-to-consumer genetic tests and have all done pretty well. You know how many people have taken these tests? Well, people don't know. A couple hundred, a couple thousand, 10,000, 100,000, 700,000. Do you not think we would have heard of terrifically tragic anecdotes, or there wouldn't have been lawsuits if there had been? FUD2A, genetic information is different because people won't act upon it. Or if you want to turn that around, people will act on it. But they'll do so inappropriately. They won't take their doctor's input. Well, in that very same PGN study, we found that people are acting all right. Most of the things they learn are encouraging to do basic public health improvements. And 30% of the people who get direct-to-consumer genetic testing, something that's been pretty roundly criticized by many ethicists, make improvements in their diet or exercise. And you know what else? Only about 1% of these direct-to-consumer customers actually changed their prescription medicine without consulting their doctor. That was another concern. So fear, uncertainty, and doubt raises these questions persistently over and over and over again. But like the mist, evidence dispels them. FUD number three, genetic information is dangerous because it's going to confuse regular doctors. And sure enough, there is a lot of information in the genome. And it's a pretty big challenge to figure out how to condense it, collapse it, distill it. And you've got to think about a lot of things, where are their eras, what's been proven, what hasn't. We've been funded by NHGRI to do something called the MedSeq project, which is a study in which we're giving genome information back to doctors before we could even get started in that way. We're going to hand them a hard drive with 3 billion bits of information? No. Before we do that, we created a one-page summary report that a primary care doctor can understand and work with that has a segments on the more deterministic mutations, the more risk mutations, the pharmacogenomic variants. And we're testing that right now. It's not perfect. But you know what? Our primary care doctors, after only six hours of orientation, are getting it and working with it and talking to it about their patients. You don't have to be a nuclear physicist to get an MRI report. You don't have to be a radiologist to get an X-ray report. All you have to do is put the report in a format that a doctor can understand and work with. FUD number four, genetic information is particularly different for children. There's all sorts of hypotheses about bonding problems. If we tell the parent of a child that the child is at risk for an adult onset genetic disease, we're somehow changing the nature of the child in the eyes of the parent. Well, that's a reasonable hypothesis. There's only one problem. The evidence doesn't support it. What the evidence does support is that a parent dying is really bad for a child. So if you sequence a child and you find out something about an adult onset risk, say of cancer, one of those parents passed on that mutation. You've just given that parent a chance to save their life and be around for that child. Do parents want this? You bet they do. I went on to the newborn unit where parents have just given birth and I said, would you be interested in genome screening for your baby? And over 80% were somewhat very or extremely interested. Now my friends in ethics would say to me, yeah, but they're at a vulnerable moment. They've just given birth. They don't know what they're saying, right? I repeated it three months later and nothing changed. My friends in ethics would say, oh yeah, but you haven't really educated them about what this is. I went through a whole process of telling the worst things they could possibly find out. And not just the worst in terms of medical outcome, but the most uncertain, exactly the same number still wanted the information. And so we've been funded to do something called the Baby Seek Project where we will be sequencing newborn children because if you believe as I do that some predictive information is good as an adult, then perhaps it's even better as a child. I think that's a testable question. I'm not sure that's right, but we're gathering evidence. And as Susan pointed out, there's a lot of information in your genome and one of the key questions of the day is about incidental findings. And Susan and others would have you believe that a standardized process for seeking and reporting incidental findings should be different in genomic medicine than for the rest of medicine. And I would argue that's simply not true. That doesn't do you any good, that doesn't do me any good. And by the way, it has nothing to do with the Holocaust. It's about the practice of medicine and doing well for the patient. And possibly, just possibly, saving that patient's life. What is the right analogy?  In fact, they'd get sued for malpractice if they didn't. Susan and I actually agree on a lot of things, but one thing she said is, I believe, fundamentally wrong. It is not stumbling across this nodule. It is not noticing this nodule. If you look in radiology textbooks, radiologists are required to systematically review the information in front of them. They are required to go down the ribs one by one. They are required to look at the shape and size of the heart, and they are required to look at the lung fields and tell your doctor in their professional report that there's something there, whether it's related to the reason that the x-ray was put up in front of them or not. Period, fast and simple, no questions asked. I admit, there's a real question here. Is the proper analogy a chest x-ray or is the proper analogy a total body scan? Critics have argued that the point we're making is more like a total body scan when you only needed a chest x-ray, but I reject that. Total body scans aren't bad because of incidental findings. Total body scans are bad because they're overly expensive and they expose you to unnecessary radiation. It's apples and oranges. Yes, we came out after a 14 month process with 16 experts plus 20 outside experts plus the entire board of the American College of Medical Genetics and Genomics in an exercise of imagining a future in which not 5,000 people, not 10,000 people, but 20 million people are getting sequenced weekend and week out. How should you think about managing incidental findings?  No, no, no. And do you make that easy? It's not a question of whether they have a right to refuse as we'll see in a minute. They have a right to refuse, but do you make it easy for the frightened patient or the lazy doctor to avoid all that? Don't look for those incidental findings. No, you don't make it easy. You make it hard. They should have a right to refuse, but they should have to be thoughtful about it. This is a minimum list. It's basically standardizes the search and reporting of a very few variants. It's consistent with the practice of medicine and this is what it really is about. You've got about 45,000 exome variants in this bar on the left. And if you take just the ones that are associated with diseases, you've got about 015,000. And if you take just the variants that are in the 56 genes, you've got that little purple line at the top. And if you take only the variants that were pretty darn sure are really bad, the very pathogenic variants, you've got a tiny, tiny, tiny fraction of the genome. That's all. It's the tiniest fraction of the genome that we think actually means something. You know what the criteria we used in this group working group?  We sat around thinking, if we did a genome on our patient and they had a mutation in one of these variants of this kind and we didn't tell them, what would keep us up at night? What would make it so we could not sleep? That was the criteria. We rejected lots of nominations. So again, if there's, let's say, 100 people in this audience, two of you are carrying one of these 56 variants, a pathogenic variant. Two of you are carrying that. Now, I'm not going to take a poll, but the situation you have to ask yourself is this. You go in for a genome sequence for, let's say, a heart issue or your child goes in for one. And the genome is done and a cancer predisposition that could affect you and your entire family is uncovered. How easy do you want to make that for us to bury that information? And how problematic is it? Well, Baylor, which is the most advanced laboratory in the world for doing clinical sequencing today, not research, but this is a real patient. They've got a real problem. Send it to Baylor to get sequenced. They have all this information.  If you get your genome here, you get these back. Or your doctor gets these back in their report. And by the way, we'll get into this in the talking, but your doctor doesn't actually have to follow the recommendations. And your doctor doesn't actually have to tell you if you make it that important for him or her not to tell you. We'll get into that. It's hard. We wanted to make it hard, but it's possible. So to conclude, I urge you to reject the FUD, reject the fear, the uncertainty, and doubt. Certainly there have been abuses of genetics in the past. Certainly there are sensitivities. I don't think those abuses are specific to genetics and genomics. I don't think those sensitivities are specific to genomic medicine. HIV testing, life and death decisions of all type. But I'll tell you what Susan has been polite enough not to use this term, but other critics of these recommendations have used the term mandatory, have used the term coercive. I'll tell you that when you look up this term, FUD, fear, uncertainty, and doubt, its origin was in companies trying to get a competitive advantage over each other and people reviewing business ethicists considered fear, uncertainty, and doubt to be coercive. Think about that. It's kind of a weird way to think of it, but think about that. I want to thank all of you for being here. I want to thank NHGRI and all my colleagues for supporting the research that we've done and that we're doing. Thank you.


Hi everyone, I'm Joe for jaspyscasebrakes.com coming at you with 2022 Leaf Stitches and Slabs Baseball. Three box, random hit break number three. So what we're going to do is we're going to open up all the boxes, randomize the names and the hits and match you up with whatever. But Steve Birch is saving us that trouble of randomizing because he got all the spots. It's a personal break. Thank you. Good luck. Here it is. Stitches and slabs. Three boxes in each of these cases right here. I am going to turn off the top camera right there because with the jerseys we'll do a quick round of who am I. We're going to give you some clues. You're going to tell me who's on the jersey. These will all go to Steve so I'm rooting for him and I'm hoping that all of these are monsters. I think this is nice. I recognize that face on the back of the card. It's Ken Griffey, Jr. PSA 10, 1989 score traded Ken Griffey, Jr. All right, so look how young he looks there. Who am I? I am a shortstop in Major League Baseball, wears number 23, has a lifetime 292 batting average, 82 home runs and 199 runs batted in. In my short career I've been an all-star, two-time MLE first team, two-time Silver Slugger award winner and an NL home run leader. Who am I? I also like to ride motorcycles. Fernando Tetease, Jr., the motorcycle rider, busting up his wrists, hasn't played a single inning this season because of that. Come on, Fernando. But when he's healthy, when he's healthy, he's pretty amazing. There's his auto right there. These are custom jerseys, so I'm going to leave them nicely folded in here, Steve. Yeah, definitely a good start. Little old with the Ken Griffey, Jr., a little new with the Tetease, Jr., a couple of juniors. Next up is Christian Yelich, rookie Christian Yelich from 2013 Topps Update, PSA 10. Nice. All right, who am I? First base, DH, number 27, active in Major League Baseball, O'Reidy, bats right, throws right. Lifetime 285, 89 home runs, and 254 runs batted in. A one-time all-star, an all-MBA first teamer, an AL Hank Aaron award winner, a Silver Slugger award winner, and an MLB home run leader, another junior, but in the AL. Who am I? Si, Chris Vladito, Vlad, David, yep, Vlad, another junior. Yeah, representing, you always see Vlad and Acunha in these cases. You're right, Rex, right on this one. All right, Steve, so far so good. Let's see what the third box has. I feel like, even if we just stop there, I feel like this would be pretty nice. Now let's see what we got in the final box. This, this, I think worth staying up late for, that's pretty cool, okay. Another graded card, it's gonna be Bryce Harper, nice, 2011 Bowman Prospects autograph, centering a nine, edges, nine-five, corners, nine-five, for a card grade of nine-five, the auto grade? A nine, yeah, I was gonna say auto kind of starts to run off the card here a little bit, but still nice. Bryce Harper, two-time MVP award winner. I remember when Bryce first signed with the, this is a great card, I remember when he first signed with Philadelphia, I was asking the chat, asking our community, hey, does Bryce Harper win another MVP at some point in his career? Overwhelmingly, the answer was no, but shows that he is a pretty good baseball player, he's pretty good at baseball. This jersey right here, this guy was also pretty good at baseball. Let me hit you with some stats, let me hit you with a stat gun. He's a righty, throws right, bats right, and a Hall of Famer, a 12-time All-Star, a World Series Champion, a 7-time Gold Glover, 6-time Silver Slugger, Roberto Clemente award winner, an NL RBI leader, and first ballot Hall of Famer, 84.5% of the vote, lifetime 283 batting average, 3,110 hits, 465 home runs, and a little over 1,800 runs batted in. I was also drafted as a pitcher with the fourth overall pick in the MLB draft, and the Atlanta Hawks and the Utah Stars, the NBA and ABA Utah Stars also drafted me, and though I never played college football, the Vikings drafted me in the 17th round. I am one of the six players ever to be drafted by three professional sports, the others being George Carter, Jojo White, Noelle Yankee, Mickey McCarthy, and Dave Logan. He ended up playing baseball. The slab was really nice Rex, 2011 Bryce Harper. No guesses on this? Played for the Padres, the Yankees, the Angels, Blue Jays, Twins, Indians. Not Al K. Line. I thought that being drafted by all these major sports would give it away pretty easily, I guess not. I think once you see it, you're gonna be like, right, that guy. Dave Winfield. Oh, David, you had no idea, yeah, I feel like that's like a cool trivia question for Dave Winfield, like what other sports was he drafted, you know, by, I mean not even Bo Jackson was drafted by the NBA. It's pretty nice. And there you go, ladies and gentlemen, that's it. Steve Birch bought all the spots, get all these wonderful heads. Steve, thanks for buying into it. Thanks for watching. Thanks for breaking with us. Thanks for your supporting jaspeyscasebreaks.com and our team here. Appreciate it. I'll see you next time for the next break. Bye-bye.


Another piece of good news just occurred to me. This is out of all places, you'll be surprised, but good news out of California. California, the good news out of California is that they were going to pass a bill to institute single-payer universal healthcare in California. In other words, California was gonna unilaterally socialize medicine in an entire state. And this is a state where the governor is democratic, where they have supermajorities in both the house and the Senate in the California legislature. So, you know, if the Democrats were serious, if the Democrats were committed to single-payer healthcare, if the Democrats were committed to the general agenda, if they were committed to socializing everything in our lives, it could have passed, it would have passed. But they're not.  They're actually just more practical than that. And they know, they're trying to socialize healthcare in California with bankrupt the state. They know they're trying to socialize healthcare with California would probably be the single thing that turned California Republican. That and just opening up the California border would probably be those two things. It would piss off California so much that it would turn the state into a Republican state.  They have a supermajority. They won't even bring it to a vote on the floor of the House of Representatives in the state of California. Basically single payer, socialized healthcare, universal healthcare in California is dead. So a victory, not for free markets, not for reason, not for individualism, just for political practicality. Even the Democrats realize that their position on healthcare is not a winning position. It is a losing position.  You know, maybe at some point in the future, they're not quite yet willing to commit suicide. Thank you for listening or watching the Iran Book Show. If you'd like to support the show, we make it as easy as possible for you to trade with me. You get value from listening, you get value from watching, show your appreciation. You can do that by going to iranbrookshow.com slash support by going to Patreon, subscribe star locals, and just making a appropriate contribution on any one of those, any one of those channels. Also, if you'd like to see the Iran Book Show grow, please consider sharing our content and of course, subscribe. Press that little bell button right down there on YouTube so that you get an announcement when we go live. And for those of you who are already subscribers and those of you who are already supporters of the show, thank you. I very much appreciate it.