 Okay, we're going to get started. Make sure I have the go-ahead from everyone that we're good to go. All right. Excellent. Well, hello, and welcome, everyone, both here and on our Facebook live feed to NHGRI and NIH's annual celebration of DNA Day. Today is the day that we stop to celebrate the completion of the Human Genome Project in 2003 and the publication of DNA's helical structure in 1953. And I'm very happy to share with you all that it's not just the scientists or even just the geneticists and genomicists that stopped to celebrate this day, but that others thought it was so extraordinary that in 2003 both Houses of Congress passed a concurrent resolution to make April 25th every year National DNA Day. For those of you who are quick with your math, you'll also note that this year is an extra special anniversary as we celebrate the 15th year of life in the genome era and the 15th National DNA Day. I hope to celebrate this, you've all been following along with our 15 for 15 celebration the last few weeks, but if not, it's not too late. I encourage you to head to our webpage on genome.gov or our Facebook pages and look at all of the materials and exciting information that is there about the amazing advances that have happened in the past 15 years and what they are meaning and will mean for our everyday life. This effort to bring DNA Day to the nation was led in the House of Representatives by Congresswoman Louise Slaughter from New York. Mrs. Slaughter, who sadly passed away last month, was an avid supporter of science and of genomics in particular and we are delighted today to welcome two members of her staff, Mr. Liam Fitzsimmons and Dr. Nikki Meadows. And also, I am particularly honored that while I'll talk, I'll begin to share with you some of our favorite photos with Mrs. Slaughter from over the years. Mrs. Slaughter was a trained microbiologist and during her barrier-breaking career in Congress, she dedicated herself tirelessly to both public service and to making sure that science was used in the service of the public. She was one of the earliest champions on the hill for genomics and a steadfast advocate for policies that had allowed research, including genomics research, to advance to where they are today. Importantly, Congresswoman Slaughter's policy acumen and passion for research also translated into her unparalleled passion for promoting the fair use of genomic information. Her leadership in Congress over the course of more than a dozen years led to the passage of the Genomic Information Nondiscrimination Act and its eventual codification into law prohibiting the use of genetic information in most healthcare and employment decisions. This law, which is commonly known by its fans as GINA, now enables patients and research participants to undergo genetic and genomic testing without the fear that their results will be used to negatively impact their job and future access to health insurance. Obviously, something that is very important to anyone who is considering using this information and vital to the success and integration of genomics into healthcare as we go forward. In recognition of her steadfast commitment to genomics issues and her legacy for genomic privacy, NHGRI is henceforth dedicating this annual national DNA lecture to Congresswoman Slaughter and renaming it the Louise M. Slaughter National DNA Day Lecture. While we continue watching some of the photos, I'd like to go ahead and introduce to you our speaker and it is thanks in at least part to Representative Slaughter's work on GINA that the public can now rest assured that the privacy of their information is protected, which we know has been helpful to many researchers in their work, but we also suspect to our current speaker's work that he's been launching recently. It is my special honor and pleasure to welcome to NIH and to introduce to you today our speaker Dr. Olivier Noelle. Dr. Noelle is the founder and CEO of a company called DNA Simple, which he's going to tell you about today, and it's designed to be a matchmaker service of sorts to connect researchers with participants in genomic studies who are willing to participate in these genomic studies. Among the many details that Dr. Noelle has brought together in forming this company has been careful attention to the privacy protections and other interests of participants who are willing to volunteer their samples and their personal information for the good of genomics research. Growing up in Haiti and moving to the United States at age 18, Dr. Noelle attended Queens College and graduated in 2011 with a bachelor's degree in chemistry. He then moved to Penn State to begin his studies as an MD-PhD student and he completed his PhD in 2017 and will continue his medical training going forward. It was during this PhD work that Olivier became interested and inspired to start his company because you know life as a grad student is pretty boring and there's just not much else going on. But he's going to talk to us today about this journey and as some of you may already know he's been working quite hard on launching it. He was featured recently in ABC's popular show Shark Tank and has already appeared on Forbes list of 30 under 30 influential people in science. So again we are very honored and excited to hear from him today and thank you very much for coming to speak with us. Well thank you very much for the kind introduction. I think I have to put up my presentation now. All right. Well thank you again. It's really an honor and a pleasure to be here and to be the speaker for DNA Day which obviously plays a special, holds a special place in my heart as scientist. What I'm hoping to do here is to share a little bit about my journey which which already mentioned and go a little bit in detail and also show Alma I went from bench to bedside to business my career so far and and I understand there are a lot of trainees here who are also thinking about potentially launching companies if they do get board of graduate school I suppose. And so you know the overall idea for me here is to show that there are a number of opportunities in the sciences for us to be entrepreneurs and to develop new tools that can push our mission forward and really impact patients in the ways that would be beneficial to them. And so we really want to make this a conversation a little bit so we're discussing the format earlier. So you have a microphone in front of you as well and so if you'd like to ask a question throughout the talk feel free to do so actually I encourage you to do so instead of perhaps saving it to the end. You just raise your hand and you could press the button and fire away. So keep that in mind and I'll remind you again to I think that will be beneficial in that regard particularly with the trainees here as I've mentioned to be able to make this a conversation and really share some of my experiences with you. So in terms of talk outline so I'll start talking a little bit about the bench to bedside background and jump into my entrepreneurial journey and really how I went from again bench to bedside to to business is really a term that I think summarizes really well my journey so far and what I think has a lot for a scientist at different stages again to be able to take advantage of our knowledge of the science and really develop new tools that could be beneficial for all of us. I'll touch upon the lesson some of the lesson learned and ultimately I want to present a framework for bench to bedside to business which can work for all of us again whether we are faculty member interested in studying company or a post back as many of you in the room are medical student graduate school student as well. So we'll get started. So we are very familiar with the bench to bedside process. Typically we start with an idea as a scientist and the majority in an hypothesis that we go ahead and want to test in the lab. The majority of the basic research work at the time at this point is mainly done at colleges and universities and very little involvement with Pharma and bigger in the private sector. This process can take a very long time as you can imagine and depending on the field of work we all know that basic science could really take a lifetime just to uncover a single protein or target molecule in a pathway. If we are fortunate enough for the to find a clinical relevance or develop our target drug then it'll move to clinical trials. And again another long process which will start with a small number of patients in a phase one to determine sort of the safety of the drug. Then if the drug moves to the next round then the phase two use a slightly larger cohort of patients to test the efficacy. And again if the drug moves to the phase three then a larger cohort will be used to again further look for evidence for efficacy of the drug. And as you can imagine this also is a process that takes a long time and as you can imagine as well a number of drug actually fall out of this process at any point. Phase one, phase two and very little considering the large pool at the beginning barely make it there. Once the drug passes phase three then we go into the regulatory approval which is another fun part looking to get to be FDA approved which is obviously an important step. So this is typically when private companies and pharma will step in post work being done in a lab and validated sort of in animal models and other ways to start funding these potential drugs to make it out. And some at some point after the regulatory approval we have what we really call the phase four which is scientists also gathering additional information that you couldn't get at the earlier stages such as long-term adverse effect of the drugs and other long-term effects that were not anticipated positive or negative that will cause the drug to be reviewed again and go back to the process of regulatory approval. So this process is really quite a long process that could take up to 14 years before you really go from that exciting idea that you have in the lab to Olivier sitting at home and using that drug. And so if you think about it another way a lot of the things that we are working on right now and some of the knowledge that we're developing are really not going to touch patients for another 10 to 15 years. And so we're really working with sort of knowledge of 10-15 years back and there's been a lot of work to fasten that process but again it's as I'll show in future slides could be very costly up to 2.6 billion dollars to go through the entire process and an average of 14 years which could be even longer depending on how long it took at the basic research stage. So if you go at PubMed and look up the term bench to bedside really when the term study being tossed around it goes back really all the way to the 1970s in fact. So when I looked up actually the first paper I could find that comes the term bench to bedside was in 1974 published in the New England Journal of Medicine by Wolf S talking about the gap and at the time the idea was that scientists and clinicians needed to take another step to work together and find new ways to incorporate the science into their work. And so the tendency obviously which still holds today I think is that a lot of the great work get lost if you will in grants and lab and in nature papers and science papers and don't ultimately make it to the day leaving and infecting patients the way we would like to. This is sort of a little bit of excerpt from the paper at the time which again is very true today that the implication of the basic scientist have turned a lot of information that's not available to promote health of mankind and actually more speed and simplified exchange biomedical information is needed. And so I'll go back to this slide of the process again. So I think where as scientists where there's an opportunity again is to work on this process and trying to shorten it as much as possible while maintaining safety for patients of course. But again what I want to emphasize is that there are other ways to go from our ideas as scientists to affect patient care. Some of us do it to policy changes. Some of us do it to education and my area of interest now is to do it to entrepreneurship. And so that will be a little bit of the theme here about the opportunities I think there are in the field for us as scientists to make an impact to develop companies new tools that could beneficial for a patient. So I'll take a step back here and talk a little bit about my journey and again how I went from the idea of bench to bedside to business ultimately to business. And the hope is that some of you could find yourself at the different stages and maybe we could exchange with some questions there and see how some of my experiences could potentially apply to you. So as mentioned earlier I was born in Haiti for those who don't know it's smack right in the Caribbean. The best weather in the world especially in the winter if you're interested. Right next to the Dominican Republic. So I was born in ways there actually completed high school before I moved to New York 18 and I ultimately attended Queens College where I majored in chemistry and biochemistry. So even from me from high school I think I always had the desire to be involved in science. I think it's probably since the ninth grade after my first basic chemistry experiment I thought I wanted to be a chemist. And later on got involved with, got exposed to the medical world and also wanted to be a doctor. So this is sort of a path that I think subconsciously and consciously I was on from an early age and I think a lot of you could share that experience as well. At Queens I actually worked in the lab of Dr. Natalia Holtzman and I think that experience was very instrumental to me even going into an MD-PhD program. This is where I really got my first experience being a scientist in the lab where I worked for three years in the same project really looking at the endocardial cell migration requirement for proper heart morphology and zebrafish models. And so I think and so this was a key step again as I mentioned in terms of wanting a career into the scientist. So she was really the push and the mentor on the science and the PhD side of things. I also had another mentor that was key there, Miss Pierce Anion, and she was more of an all-purpose mentor and really more so on the medical side. So she was the one really nurturing my desire and quest to go to medical school and wanting to care for patients. And so really grateful to these two really to, you know, responsible for pushing me to both degrees, I guess. And so from Queens, having worked with these two, I knew I wanted to both work on developing new knowledge and also applying the current knowledge that we have to care for patients. Ultimately enrolled in the Penn State College of Medicine, MSDP, MD-PhD program, which is probably one of the best decisions in my life. And at Penn State, I worked at COPI's, Dr. Gerhardt, who's now the chair of the Biochemistry and Medical Genetics Department at Temple University, and Dr. Jim's Broach, who's the chair of the Biochemistry Department at Penn State Hershey. And so I think my experience is there not only, you know, confirm the desire to work in science as a career, but also, you know, Dr. Gerhardt really pushed innovation. And I think that's where sort of the need idea for starting a company and being entrepreneur started. You know, I got that question a few times today and probably we'll get it here. You can't really start a company as a graduate student if you don't have the support of your PI and graduate students know what I'm talking about. And so I was really grateful that I was able to work on my PhD work and do what was needed, and also in parallel be able to allow the opportunity to work on a company and watch a company while I was in graduate school. And I'll be happy to talk a little bit more about that. In fact, to go back, with the end of simple, I think the idea came about right around my second year of my PhD. I was actually working out of the Institute of Personalized Medicine in Hershey. And one of the key problems that I saw there is that, you know, there was the proper infrastructure, there was sequencing ability, there was enough funding for really amazing research projects, but ended up being a little bit of a chasing game where we couldn't build enough, strong enough court at first to be able to do some of the studies we wanted some of the patients we were looking for. It was taking a very long time for them to come. And every day would be sort of going down in the, talking to the United Councilors and ask, you know, did we have patients with this background today? Did we have patients? How many patients for that particular genetic background that we had this month? And so I ended up going to a genetics conference at Penn, actually. And the keynote speaker there was alluding to a similar problem. And they were working on rare disease. That's not really prevalent in the Western world. And one of the ways they were able to contact patients was through Facebook. And so through Facebook, they were able to connect with a number of patients all the way in India and organize the logistics to be able to get the sample. So the joke at the time at the conference was that, you know, Facebook is the new way of doing genetics. And really that stuck with me and really when the sort of the light bulb went on. And I realized that it worked really well in one case. And that's something that we could use and leverage to be able to recruit patients differently. And so that's where sort of the idea for DNA sample came about. So I wanted to sort of leverage the internet and particularly leverage social media to be able to build a national database where somebody did not need to be a patient of a particular investigator or go to the same hospital or be in the same region to be able to participate in this research study and properly provide samples for research. And so that's what DNA sample is about. And I'll obviously go into more detail about that. So things went really well. And eventually I was lucky enough to be a Forbes 30 and the 30 last year. And some of you may have seen me on Shark Tank really trying to get the best deal possible between Cuban and and Brinson really worked out. And so and I'm here today. So again, I would love to make this conversational. And it's really a pleasure to break down each of these steps and tell you particularly about my experience going from a graduate student and building a company. And where I think there are a number of opportunities for us all, whether you are post back a graduate student, a medical student or even faculty member to be able to leverage these technologies that are available to build companies. So as I mentioned, I went through the traditional route to start. I was at the Penn State College medicine still at the Penn State College medicine, their MD PhD program, I went through the first year of medical school and second year of medical school and ultimately took my step one board. Then I went on to graduate school after the first year took the qual exam. Pretty standard. And after during the second year is when the idea for DNA sample came about. And so as many of you, perhaps, I was in the sort of in the same shoes where I really had no business training to start. I joked around that barely could spell start off about three years ago. And I'm all over it and, you know, inciting people and talking about it and really being really excited. So a lot of it was catching up to what was available. So again, learning on the fly and making mistakes and learning and starting assessing the market and feasibility. And ultimately, we launched a minimal viable product to test it out and see how things would work. And if this was even possible. One thing that was really helpful for me was going to the Y Combinator Accelerator in Fellowship in Silicon Valley, where we had a tremendous mentors that really got me up to speed in terms of starting a company, learning different details of lunch, what's important to use your metrics and so on and so on. Following the Y Combinator Fellowship, so that's actually where we officially launched the company out of Silicon Valley. And we went through the Dribbit Accelerator, which is the venture branch of the University of Pennsylvania. And so they were the first actually to make an investment into DNA Simple. And things really started growing from there. We launched the full products. We built a small team. So I have another scientist on board. We actually was my lab mate in graduate school. So you probably want to be nice to people you work in lab. They might be your colleague in the future. And so that worked out really well. So eventually I took a leave of absence from graduate school because things were really becoming difficult to balance the two. And luckily I was at a point where most of my thesis work was actually done. And I was sort of in the tail end of things. Defending my thesis last December. So and the plan is to eventually go back to medical school to finish the last two years and continue with the training. Any questions so far? There we go. I think you could just press the mic. Hi. Hi. My name is Michael. I apologize for not having done my homework. But could you explain exactly what DNA Simple is? Is it a broker? It sounds like a DNA brokerage. Yeah. I actually have a few slides coming up. Is that the next? Yep. Well, I think the next four slides will actually answer that how we are. So go ahead. We may get to this later. But I was wondering at what point in this journey did you feel like this was something that you could do? Like it went from an idea to something that could actually happen. Yeah. So I'm an idea junkie. I was joking earlier that my biggest fear was my phone and lose all the 10, 15 ideas that I have for companies. And so not really the contact list. But so I always have had ideas before. And so I think for this one it really answered the basic questions that you want to answer when you have an idea. Is it solving a need? Is it solving a real problem and will people be using this? And so I think it answered these questions. And you just do it. I mean, sometime is now, is really what I was thinking about. And so typically my personal preference is when I have an idea, I'm trying to find the most pessimistic friend I have. Because your friends will always say, yes, it's a good idea. And I run it by hand. So you want to do that. I constantly do that. And so once I'm able to answer some of the basic questions, then I thought it was worthwhile. So I think if you have an idea and the answer to, is there a real need, will people use it? And is it better than what's available for potential users? If the answer is yes, then you should totally go with it. Yes. Yeah. So we did sort of our internal studies and see what the ballpark was in terms of donating. So we ultimately provide a minimum of $50 every time somebody provides a saliva sample, which they could keep for themselves or donate it to a charity of their choice. No, no, no. Actually, we're not working with blood just yet. We're doing saliva. We started with saliva. And again, I'll show you in a couple of slides and slightly ahead of us, which is good. We've done saliva for a year and then we expanded to urine and microbiome. So stool microbiomes. So we've not done blood because it's a little bit more, no pun intended, messy. But, and so there are different regulations around that. And, and, you know, typically you'll need to go to a laboratory and have a nurse or somewhere that's properly trained to be able to. So saliva and urine are extremely noninvasive in stool. And so that, that strategically made more sense to do that perhaps after another round of investment. That's where we'll get to it. So the blood is a little more complicated. That's what we stayed away from. Yes. So after the, eventually in your business model, most of the time after we do DNA testing, we generally want samples for other, for other tissue types or, or to look into things more specifically, is DNA simple going ahead in that same direction? Yeah. So I mean, the tissue type again, any invasive procedure, we obviously not, we're not doing right now. But down the line, that's a possibility. So if we know, for example, I mean, some of the ideas that we tossed around is that if we know we have, you know, 500 folks in this area that have a specific condition where an important research study is undergoing nearby, then this is something that we're thinking of, you know, small ways to be able to leverage that, those samples to be able to get. But in terms of actually getting tissues, that's really not something that you're going to be doing at home. So the only way for us, I mean, this is something we thinking about, but it'll have to involve a third party for their sake of safety and following the rules. All right. We have an hour and a half. So I think some of the questions alluded to that. So what, how did I go about starting things? So for me, the first question is, you start with a real problem. So again, as I alluded to, this is not how patient recruitment works. You don't just start a study and then you get people knocking on your door and say, I want to participate and you have too many people and you're declining. Typically, it's quite the opposite. And so this is the main problem that I saw in the field that I wanted to do something about. So typically we have a significant geographic barrier. And if you're a researcher in one location, obviously you're looking for 5000 samples of people age 18 to 45 of a particular condition in one area, you essentially have to wait for 5000 folks to be sick and come to an institution and be consented to get those samples. Unless, of course, you could leverage other medical centers and have a consortium to be able to decrease the length of time. But it's generally a process that's inherently have a geographic barrier into it because labs are in one place and people are everywhere. It's quite time consuming again, as I've explained. It's essentially a weight gain. And the thing about it is if you have a $1 million grant or a $10 million grant, you're not essentially doing something better when you have more money. You're actually putting more money into a less efficient system where you'll hire more people to go around the hospital and really trying to find folks around. So before studying things, I talked to a lot of folks investigators and people with grants who've done court studies before. And that was really one of their main complaints, the complaints. And the process is expensive and often you get limited clinical information from your patient, especially if using a third party where you are not a participant in terms of the collection of the samples. And those are samples that are collected and stored for years. You're really limited in terms of the clinical information that you can get from those. Whatever is there, typically what you have to deal with. So again, it says a little bit about some of the big problems, some of the boxes that were checked, yes, before I pulled the trigger and decided to go on with this. It takes a long time. Institutions are really restricted to one area where they are. And if you're in a small town or small, you can imagine now the local population may not be enough to sustain your study. And so most often you'll have to go outside and find other collaborators or other consortium to be able to get those samples. When you do do it in-house, it could be quite expensive and involving third parties, it's always a difficulty getting the full clinical information. So one of the things we really wanted to do at the end of the sample is to allow for the possibility of doing longitudinal study so that you keep track, you could continue keeping contact anonymously, obviously with a particular donor. And so if you're doing a study, for example, and you have the ability to collect samples now, collect samples in three months, collect samples in six months, and see how that varies, which is very difficult to do if you're going to be in contact with a patient once. And so that was another key factor that we wanted to add. In traditional biobanks, you often lose contact with the donors. Again, what you have is what you have. In terms of our advantages, how it compares, so that falls again within, are we doing something that's better than what's available. In standard biobanks, you will recruit donors during hospital visits. Perhaps the advantage here is, depending on what the visit was for, you may be able to get tissues. But otherwise, for us, we try to recruit online and leveraging social media primarily, and also underground campaign. But what we found is that it's worked really well doing it. And this is really an area that's not been used. Traditionally, patient recruitment has always been done at the hospital setting and really involving a physician or a third party, getting their patients and getting the sample. So that was the key difference. Again, the fact that the samples are being collected at home make it very easy and painless for the donor. So a lot of times, you could talk to folks that are interested in participating research study, but they won't drive two hours just to fill out a questionnaire or give us a lot of sample or stool sample, for example. So that was another area that we wanted to change. And again, because we eliminate the physical burden, then we have the ability to expand quickly and reach folks in really everywhere. Our process is a few easy steps. So from an investigator perspective, so essentially what we have is a marketplace, right? So it's a place where researchers are looking for patients and donors for their research study. And research and donors are matched to or on the other side are matched to research study. So from a researcher's perspective, when somebody contact us, they specify the population and this is of interest, essentially letting us know all the inclusion, exclusion criteria. And what we do is our algorithms automatically find that people do match these studies and sort of submit them as potential donors. A key thing is that following this, the researcher is going to be the one determining what the proof of concept is and determine what would be needed to be submitted, what other evidence they would need to confirm that this patient fits what they need. So we do all of that in the back end. We collect minimal information that's necessary for our algorithms to match to a research studies. And following that, the researcher and investigator determine whether what needs to be submitted in terms of documentation to confirm the case. And then in three easy steps, once you sign up and create an account to do this. From the donor perspective, they'll work slightly more, but it's still a two to four-minute process again. Donors sign up on the website once the researchers submit a request and they get matched to the particular study. They dig out a notification and at that point, they find out all they need to know, all the information. So we try to recreate exactly the process that happens in the hospital. So you find out about as much information as possible about the study, according to your IRB and informed consent. And then you get to make your decision whether you want to participate and once you're in, you have the ability to leave at any point. So again, we're trying to reinvent the wheel but really digitalize and take an advantage of really the internet in a way and leverage technology to use a process and really do the same thing that's being done in hospital online. And once the donor has been confirmed, then we would send them a collection kit or a UN collection kit or whatever, which they'll come back to us with the mask, they identify again and the donors will be compensated every time they participate in the research study. In terms of timeline and progress, so this is really sort of what the business plan was before we launched exactly. So we put it in three phases. The first really was to build the first site in marketplace, right? We needed to prove to everyone that we have the ability to actually, can we, we have to answer the question, can we build a place where people could trust to go and provide their information to be able to match and help a research study? Again, so that's what's not available at the time that we wanted to build and show first that you can build that and that it works. And so building the first site, the site A that we call the marketplace, which is the donor acquisition and show and de-risk the whole process and show that in fact, this is working. So again, it wouldn't make sense for us to have 100 people in the database and looking to do a study with 50,000 and knock on an investigator's door and say, we could complete this study for you. So the idea for us again was to build the database to a critical mass and figure out what the formula is for donor acquisition and then match the research studies and try to help in that process. So we explored a small number of studies and show that it actually, the process worked and validated. In terms of phase two, so we slightly ahead of schedule because we've actually started including urine and microbiome simple options. We have a company called Simplify in Boston actually works with us closely to design all the kits, which has been really great. So, and so, yep, was there a question? No, sorry. And so we've been shifting our focus a little bit now to working directly with investigators and targeting those donors specifically as opposed to our first approach, which was to generally recruit anyone and say, hey, sign up on the NSF poll, you never know, which study you may help in the future. And so phase three, ultimately, it goes back to a little bit of the question I heard, one of the questions I heard earlier, what's the next logical step for us? So for us, ultimately, what we want to become is the place where you think of for patient interaction. So we actually want to be the place to build a court for you. So independent of what you're looking for, whether you're looking to, through our surveys around to find out social economic information, whether you want actual samples, whether you want somebody to show up at a place to do a study, we ultimately see this as a cohort building where we have willing participants. So a number of people who say, we'd like to help science, come get us and tell us what to do. And so we want to be the place to get that. So ultimately, we could get into the clinical trial space and expend services to include blood, which will likely require a third party. Yeah. So two questions. The researcher receives the actual DNA sample. You don't sequence it, you just give them the actual, what do they get? That's correct, right? So we don't do, so yes. Because we don't want to exome sequence it enough and then you need to hold genome sequence. And so it would make sense for us to, on the front end, especially as a startup, maybe Merck and Regeneron can do that. But yeah, so you would get the extracted DNA or the sample itself, depending on what your IRB says and what you need it for. So some folks find it more helpful for them to do the extraction because they've already extracted other samples and would like to keep everything homogeneous, so yeah. And then the other question, it was not clear to me, if I am a patient and I donate my sample for one study and then I receive my $50 and then another investigator also investigating that same disease or is interested in my sample, do I get another $50? Yeah, every time. Every time you sign for another. Correct. Yeah, the idea is to involve everyone in it. So the main point is to facilitate a research study and whatever that was gonna happen anyways and take three years to do, we'd like to be able to say we can make it happen in one year. So the primary focus, and that's one of the good things when you have scientists being the founders, as opposed to maybe straight business people doing the being founders, our interest lies in that, just that. So every time they would get it, they participate in the study, yep. Even if the same researcher wants it a second time. We're going to back first. Hi, I was just wondering when donors are gonna register to be on the registry, they're filling that out themselves, right? And sort of self reporting their medical records or things like that. Is there any check on that or do you have plans to sort of have that sort of be validated by a physician or anything like that? I feel like a lot of genetic sequencing data has to do with accurate phenotyping and do you think that if something's not accurately phenotyped it can throw up studies in the future? Yep, absolutely, quick question. I mean, that's the first thing we thought about actually or this other company, right? So if I want a sample with someone with diabetes who's 52 years old, how do I make sure it is a sample from someone who has diabetes and who's 52 years old? And so the natural inclination is to try to get as much as possible from the patient, right? So give me everything you have so that the investigator will feel comfortable. If you do that, you can have a signup process that's about two hours long and somebody may not be participating in the study. So that's logistically and from a startup organization perspective, it's not ideal, although in the perfect world that's what you'd want. So what we have is have the minimal information needed for our algorithms to be able to match to basic inclusion and common inclusion, exclusion criteria, age, sex, condition, carrier, and so on. And you as the investigator, tell us what it is that you'd like to see or submitted to confirm what the patient has. So if you wanted somebody with a rare disease, most likely you would like them to submit their genetic testing report. Again, and that would be the determining factor. So we leave that up to the investigator. So two investigators actually need the same sample. They need two different proof of burden, we call it, depending on what you're doing and what you're interested in. So I may want to see the pathology report of a cancer patient and you may just want to see the BRCA-1 confirmation. So we leave it up to them with the ideas to not get everything in front load, sort of how we do in traditional biobank and not have overhead costs and have to store all of that and risk potentially other things happening. So we do that on the back end. And so if an investigator does want the entire EMR, we do work with a couple of third parties actually. That's what their business model is. So there are a ton of companies out there where the business model is to actually go back and see and collect all your doctor's note from birth and put it in one place for your electronically. So we work with some of these companies. Obviously, if the patient consents to it, then we have the ability to get that as well. Yes. Sorry, I think she was... I'll go with her first, yeah. So my question is actually related to that one. In the literature and when we look at these big cohort studies, we do see this phenomenon of the same individuals being enrolled in multiple studies. And you're essentially artificially increasing that probability because you're kind of pushing individuals into this. Are you at all worried or do you have any safeguards to deal with that? Yeah, that's something we've totally considered. It's probably gonna be a problem when we get bigger. The bigger we get, the more we have to be careful with that. I mean, there's a series of the identification and systemic ways that we characterize that we basically rename them as a DNA person so that we don't have to deal with the name. So there's a way for us, we're thinking to leverage some of these key combination to name them to identify someone. We can't identify someone who's already participated in the research that you're not. But if someone had participated physically at a research study that was happening here and then an investigator next door here went to us and we provided the same sample, that would be difficult to assess. But in terms of our own samples going into different studies, we're able to track that. Yeah. Hi, this is Nass. I essentially question to follow-up question, the earlier question. Have you ever thought about, to make sure that you're getting the right sample from the right person, rather than giving them $50, have you ever thought that maybe you can provide them a service like ancestor.com like to get their genetic information so that you would do that? Were you sitting at our meetings? No, it's just, I just couldn't go over it. Yeah, no, that's a good idea. Actually, well, that's the thing. So the first start, we wanna provide as many options because not everyone cares. Actually, most people have said, oh, this is a great idea. My son has this, this, this. We would love to participate. There's not enough studies out there because oftentimes investigators don't even touch it because they don't think they'll get enough of a court. It's gonna be a pain. They'll start the study for three years and he dies off. So people volunteer and say, they'd like to participate regardless of the $50, even though everyone has taken it so far. But I don't know how that works. But so we do give the option to donate it to a charity of your choice. And we work in different other areas where you could get some data back or something like this. So we've explored that and that's something we're hoping to bring about in terms of multiple options. Those are things that additional incentive for people to participate. So if you could be incentivized a little more and get some data that's helpful to you, why not? I think, sorry, we'll go with that first. Do you see a role for DNA simple in turning participants into partners in research? Into you? Turning participants in research to partners in research? Like, do you see a role for your company as being involved in that process? That's a great idea. I actually did not think of that, but that's a great idea. Thank you. I'm gonna write that down. 0.1%. Now that's actually a great idea, yeah. Well, I mean, the danger for us is that if an investigator is doing some work, right, typically you'll put an NDA out. You don't want people to find out about some of the things you're doing. And so it's very difficult for me to reach out to someone else and say, hey, this guy's working on the same protein you're doing, this is what he's doing. So it's a fine line. Maybe we could put a certain level of, maybe we could have a form that each investigator fills out and then that's the information they're willing to put out to potentially find a collaborator. So, but it's a little tricky because you don't want to put other people's out. This is you and your NDA when you're working. Yes. Well, now that you brought up the NDA and I imagine you'll get to this soon, could you tell us about privacy? Yes. I thought it would never come. No, no. So we, again, we're trying to emulate everything that the exact way that things are being done in the hospital setting. So the idea for us, we're not creating anything, we're not allowing, we're not providing IRBs, we're not doing anything new, but connecting willing donors to patients. So we take every potential, every possible encryption method, the identification method, and that's one of the reasons when the samples come back, they don't go back to the researcher to come back to us, first to de-identify it again before providing it. So we mask the identifiers. And so the investigators themselves never get the name to start. So there's not a possibility for you as an investigator to make a mistake and leak the names. To begin with, yep, cut. And if you're subpoenaed, and are your servers outside the US? If you're subpoenaed. We are not outside of US yet. So the thing, the tricky, yeah, so we're just the North right now, but it's tricky going international because the rules are different in different countries. So we've actually, we're exploring that, but we don't have to deal with that problem just yet. The question was if your information is subpoenaed. Okay. If it is. If eventually it gets, I'm not sure what you're getting at. If the current. So if you have your information on the server in the US. Yep. You are subject to US subpoena. That's correct. For criminal or discovery purposes. Yes, yes, yes. If it's not in the US, then it may be less discoverable. Okay. Get that point. Another point, 1%. I think, yeah, I think we have the back here. We're doing great on time, guys. So my question was actually related to that too with regards to confidentiality and like medical records. You obviously, it's private because like health insurance companies can't get a hold of that information. Just the ways that you can like be insured to the person who wants to join the study that they will not be subject to any of this in the future because we never know how our genetic information could potentially be used against us one day. Yeah. Yeah, no, that's that's again, we take that's clear. We clearly state that that's what we do. We again, whatever's available in terms of technology and what they do at the hospital, we want to do the exact same thing. And so, you know, we work with folks where do you have informed consent in IRBs, stuff that's clearly determined, clearly set how things are going to be done. We're not in the business of consent in IRBs specifically. We just post that once that's correct and set. This is how this is supposed to be collected. This is how we said we were collecting. Then that's when we come in. Because that's obviously the most important thing when you're dealing in that, that generally takes, yeah. So it's a little unclear to me, are you holding genetic test results in your databases or are the investigators holding the genetic results? So if the investigator can, if they requested that as part of the participation in the study. So if you're doing for example, you know, drug response study and you want participants who are fast metabolizers of ex-drug. So that's both like the evidence that you're gonna require from them showing that you have this variant that makes you a fast metabolizer. So at that point they would have it. And I think. So I'd be interested to hear how you do your outreach to identify potential donors because that's a real issue of the, when it comes to diversity of participants. So how do you, what's the process that you use identifying donors? So we do, we have, we do it in multiple ways. So we try to put it in two categories where we try to collect, we try to get as many people as we can and say, you never know which study you may participate in and sometimes we know exactly what we're looking for. Then we target different organization and such. So we do it underground, but the most, probably our most effective way has been online through social media actually. So that's been the much more effective than the traditional method that we also do. Okay, so, yes. So I have, can you hear me? Yes. So my question is in term of patient identifiers. Before the data is de-identified, where do you store it? What kind of system do you have and is it safe against hackers? Because nowadays, as we know, this is what people do. So how do you guarantee protecting that information? Yeah, absolutely. I mean, it always goes back to sort of the same answer before. We do what everyone else can do. So I don't know if you could ever, I mean, it's always a tricky question to say. It's 100% proof against hackers, you know? So every single step that's being taken at other places is what we're just trying to emulate. And in terms of the technicality and servers, I probably could talk to you in more detail after that. You mean by this that the information is encrypted somewhere? Yes, absolutely. Okay, thank you. Yes, 100%. Okay. Okay, so timeline, and I'll run through this a little bit and insert this through the questions. So we launched out of the Y Combinator Fellowship and ultimately did the Jumit Fellowship that with the University of Pennsylvania were our first investors. And ultimately, we did a round with venture capitalists. So these are a couple of examples of some of the studies that we've done. So we've done a rare study, apatrophic cardiomyopathy, and the database growing from zero to 5K and progressively moving on. So we've done the drug response and risk answer. So a little bit of variety in terms of the studies that we've able to help. And 2017, as I mentioned earlier, we were unchecked and obviously got a nice boost that's sustained now. So the range of studies, even at this size, has been quite interesting and we've been pretty pleased about it as a range from different cancers to a common condition to more rare conditions. So in terms of the journey itself, there are quite a number of lessons that I've learned obviously and this is probably one of the most common questions that I've gotten today. So I try to put it together into four big lessons that I've learned that I think could be helpful, especially if I were to go back, you know, second year of graduate school when I was starting. So there is more to drug development as entrepreneur options for scientists and I've shown that graph earlier and how it's a process that takes such a long time and typically that's what's thought of as entrepreneurship for a scientist. Typically from the target molecule in the clinical trials, that will take an average of 14 years and obviously it could take a lot more and there's an 85% failure rate could cost us up to 2.6 billion, assuming you passed to that set. So this is a substantial process with very low rate of success. And frankly, part of the reason this is 2.6 billion is not so much that the one drug that made it cost 2.6 million, this has to cover, you know, the 85% other drugs that didn't make it. So if in the perfect world, it'll cost a lot less if the rate was a lot higher. So if I put in 10 drugs in the market and nine fail and each cost me a billion dollars, the one that made, and that's just how economics work, the one that made it is gonna have to cost and cover the $9 billion. So, and there are really a number of areas in that we can make an impact as a scientist, really. And the biotechs, the software, hardware, particularly diagnostic in R&D and even clinical labs. And so I talked to a few graduates the other day and it said, well, I don't have time to do this, to do that, but he knows how to code and he has great ideas. That's entrepreneurship too, being able to use and leverage some of these basic technological tools that we have and create an app that makes patients do X, Y and Z much better. And so that's also an area of great opportunity for us. And again, when you talk about hot areas and stuff that could, you know, probably each of us could create a company tomorrow and when you talk about the elderly care with productive healthcare, beauty tech, food product, these areas seem to never be saturated. Sorry, yeah. Thank you for coming today. I was wondering if you could please comment on the population distribution of the 130,000 donors who are currently in your database. Yeah, absolutely. So it actually mirrors the US population fairly well, except for, and I wish I had the data here. Yeah, so it's in terms of ethnic background, it does. In terms of age distribution. Yep, it goes across the board. Obviously we need parents, so going in to sign minors, but we see quite a range. Probably the most common would be maybe the 30 to 55 range, I'd say, but we see quite a nice graph. That's actually one of the, you know, first graph that I'd like to show the investors and quickly to point out that just because we do, there's a compensation or we use social media heavily, we don't see a concentration in the age that would be a bias due to that. So that's actually one of the pretty cool things that we've been able to see. How about racial or ethnic distribution? I'm sorry? Racial or ethnic distribution? Yeah, yeah, so we probably- System economic? Social economic, we don't have, so we don't collect all of that data at first sight because frankly, most genomics investigators would not need that. I mean, it depends. It depends what you're doing. I should rephrase that. So it's part of what I would talk earlier about, do you put a questionnaire of 100 pages to find out about some socioeconomics at first or do you ask it once you find an investigator that really has specific questions that they're looking for and then you use, because we have the ability to upload questionnaires also as investigators, so it's really nicely put in for that. So I don't have quite as much data that I have on ethnicity and the age distribution and such as clean as I have it for, yeah. Okay, thank you. Yeah, that was a great, terrific question. All right, I'm kind of piggybacking on the last few, especially the partnership and science. Yep. Is there something in your business model that really speaks to the question of health disparities and ways that, because I can envision investors having their ideas about where they want the science to go before they give you the money. So if they have ideas on where they want you to go, unless you have that bedrock in your business model, then how are you assisting or how are you not in danger or risk of affecting health disparities by virtue of, for instance, I'm gonna just use an anecdotal, although a very powerful historic piece, which is, if you mentioned Tuskegee to black people of a certain age in this country, that's why probably anecdotally speaking, there's not a lot of participation in science as much as maybe there should be. Yeah, no, that's... So how did your model address making sure that the money doesn't affect what you're doing? It's a great question. It's funny you said that, because I think in the next couple of slides, there's gonna be something about healthcare disparity. It's actually one of my big focus in terms of initiatives and things that I wanna do in the future as well. So one of the things I thought about when I started the anti-simple was the ability to involve a side of the population that has not been involved, for example, and that's one of the things I'm thinking about in the clinical trials down the line, otherwise in science. So we constantly think of thought about how to recruit under-recruited folks. And so you will hear that all the time from investigators, I tried to do this study, but I couldn't get enough of these samples. I never get participants from here, participants from there. So that's one of the things we clearly focused on. And thankfully, we've not had really pressure in terms of where to go with the company from investors. They've been pretty hands-off in letting us run it as scientists. So I actually have a few slides on there and how I think we can help tackle this problem. So one of the first things I thought we could do is recruit in the residency space, which is difficult to do at an institution in one place and also involved segment of the population that's been severely underrepresented in studies. Yep. Just, so until now, what I understand here as your business model is to actually speed up the progress for the part, for the data collection, which is mostly the basic research. And I'm still having a hard time to understand how is this gonna speed up the clinical trial part because are you gonna send them a drug and are they gonna use the drug? If you are gonna do it, how are you gonna control the side effects or if something goes wrong? No, no, no, no. So the clinical trials, I mentioned it as part of a next transition for us. So we have the ability to, we wouldn't be, we have the ability to do a non-invasive one at home, obviously. But in terms of the drugs, they would have to go to a center or a third party. So what I'm saying is that we have the ability to tell, hey, we have, there are 3,000 donors in this region that are willing to participate and show up at a center. So in terms of, there's no way, it's kind of just like the blood. There's no way it's gonna be able to be done at home. These would be helping third parties and direct them towards a clinical center because we've identified them as being within 10 miles or something like that. So it was more presented as a next logical step for us in terms of growth. And my second point I wanted to bring about is that there are a lot of opportunities outside of the normal route. So in terms of postdocs, assistant professors, et cetera, that we can do. And so this is a nice graph that I actually got from the NIH, the report NIH website. And without going through the entire thing, really, wanna direct your attention down here. So you could see most of us, again, in training or sort of geared towards or aspire to go into academia and becoming assistant professors, and up the ladder. But what you see is that the field doesn't have, cannot accommodate all of us, really. I mean, only 43% go into academic research and teaching. And even more importantly, this number, 23% tenured. I mean, you're talking about almost 80% for fifth of the workforce, essentially training to go into this process and not going into tenure. So there is more than half of us will actually not end up in academia. And I think it will be a terrific idea to really take a step back early on during the training and not just go through the pipeline and really take a step back and see where it is that you think you're gonna make an impact and can go. Because the field, there's actually a lot of opportunities for us to, again, be entrepreneurs and do exciting things that can also, not only we'll use our science, but we'll advance and push our mission forward and help patients. So lots of graduate students, lots of postdocs coming out every year, but obviously very little spots for them to come in. And so, pretty interesting piece of data here. In terms of MDs and PhDs, as we'd expect about 82% of them do non-research patient care. Not much industrial research data, but the academic, again, 12%. So this one, this group is a little tricky. It would be nice to break it down between specifically MD-PhDs versus MDs, which are obviously expected to go into that category. But again, less obvious and significant as the straight PhDs. But again, I think a lot of us from the beginning go into a pipeline with the idea that we all gonna do the same thing and do the same process. We're really at the end, more than half of us will not. And so it's a good idea to really think about it now in terms of what really makes you happy and perhaps that is going into academia and being a professor ultimately and writing grants in the research. But for some of us, we will not be doing that either by choice or not. So I think it's a good idea to perhaps think about it early. Yep. So it's interesting that you mentioned that graph. And so I'm trying to phrase this gingerly, but how much, I mean, so how, you know, for graduate students going through the program, I do know there's a lot of pressure from PI. I'm just gonna say it then. I was gonna say, you should just say it the way you wanted to. Yeah, yeah. So there's definitely a lot of pressure. And I've known a lot of people that have great ideas and they thought about other opportunities, but their PI just kept pushing them and pushing them. You know what? Graduate, you'll definitely, you're really smart. You'll get a professorship and so on. They've gone through two or three postdocs and then after a while, you know, they're miserable. They're absolutely miserable. And so, you know, it's great that you're mentioning that you should think about it, but I also feel that there's a culture, especially in academia, and I'm not gonna say that it's one out of negativity, but I think there's some PI's just don't realize that there's other things out there. So I don't know, so, you know, I'm complaining, but I'm also trying to say that, you know, how do you correct this and how do you, and you know, especially since you've sort of gone outside of the academic realm, how do you sort of foster this, you know, encouragement that, you know what, there's other things out there? That is a tremendous point. And actually there's, you know, it's a little bit of a segment segue into one of the initiatives that I'm starting, which I'll talk about at the end. I will answer just that question, but I mean, it's hard to put it nicely, right? I think you did your best. But no, no, but we get the point, right? So it depends on some lab, forget about it. So the reality is, you know, you have PI's and typically, you know, I mean, they're great scientists. So they work till, you know, their 80s, 90s, almost hundreds. But you're pumping three or five graduate students every year. And so you're creating more PhDs, but you're not creating more jobs. And so it's a fact. And it could be a very difficult competition to have. And again, it'll be, I think, I mean, the only way to do it is to be aware of this from the very beginning. So you may be interested in studying companies, you may be interested in working with pharma, you may be interested, I mean, ultimately the end is to, you know, bring about changes to patients. And so there's different ways to do it. And so I think it, again, I'll touch upon an initiative that I'm looking forward to, to relaunch that, we'll address just that. But I think starting it as early as possible and have that honest conversation is what you, you just have to do that. If you don't mind, so you actually finished your PhD, but you're still starting your company, right? So why didn't you leave your PhD? I'm sorry to make, I'm sorry to make it personal, but no, no, I love that. This is, this, that's why I'm here. And this is, this is great. Can't wait for the, the follow-up. So we're like, oh, we can ask these questions now. Okay, no, that's a great point. So, so I, I personally know a few friends of mine who are MD PhDs will call it quit at different levels. So I have a friend who started a company third year. So first year of PhD out just doing companies. I know somebody who was in the third year of ortho who left the residency. So, I mean, he's not struggling, but you know, so, so when you're passionate about something, you're just passionate about it. So I know people personally who's, who've done it at different spectrum. I think for me, I quote it at the right time. It may be a little bit more difficult if I did this first year of graduate school. And now it's really difficult. So I think being able to do it, you know, essentially a third year of graduate school and really spending that year analyzing the market, looking to launch a minimal viable product before going full blown launch, give me, I mean, it was obviously very difficult. And you know, you have to sacrifice to be able to balance the two. And it's been a tremendous pressure. But particularly when I started, I felt like I had to work harder in life to be honest, just for the sake of not, you know, showing others an excuse of what. So if anything, I worked harder when I started the company in lab. So I think, yeah, it's just a timeline for me, the way that timing works. Obviously I took a leave of absence from medical school, but I think depending on where it started, and I know actual friends of mine who've, you know, somebody studied his company in G4. And so he just finished school and now he's not doing the residency. So it varies depending on the timing. I would just add to this conversation that it's a little PI dependent. There are some who are very good about starting companies. Okay. And it's also very institution dependent. And some institutions have a real, we're academic and that's what we do. And other institutions are like, where's your company? And so I think the onus to some degree is on those graduate students to pick the places they wanna go carefully. Even though I agree, I remember it was a long time ago, coming out of college, do you know to do that? It's tough to do. Terrific point. And that's what I have to give credit to Penn State also for being really on the innovation side and not as an institution, it's a great place to be if you're interested in being an entrepreneur. So in a year you'll have your MD and be a MD PhD. Was that? In a year you'll finish your MD program and be a MD PhD following that you plan on doing postdoc, residency, or the company. I know it was getting personal. Well, I mean, the goal is that, right? The goal is to go back. So I still have the two years. So I've done the first two years of medical school, not three, so two and then five PhD. So yeah, that's the goal, to go back and, well, you know, to have a frank conversation, I know what I have a clear picture of what I wanna do in the future, even post residency. So I know that I came in into the MD PhD program wanting to do 20% clinical and 80% research after I was done. So now that I've got this additional experience, I think I still wanna see patient 20% of the time, but the 80% now I know exactly I wanna spend it. And this, you know, I know I'm not gonna be a traditional, you know, member of the academic, you know, sort of the academic way and, you know, postdoc and such. I know I wanna get involved in certain companies. I wanna get involved in pharma and finding ways to leverage really doing what translational research is about, right? I'm very interested in actually translating what the research means. So what we find, I wanna think of multiple ways to leverage it into companies that people will use it and they'll have the positive effect that we think it's gonna do. So this molecule has this potential to do this. I'm interested in finding new companies who are doing that. So I think that 80% of changes in terms of straight research and writing grants in the standard way, it's gonna vary. But I'm still overall interested into seeing patients using that as sort of material for research to drive back to the patient and again, bench to bedside the business is where I'm gonna go for it. How critical was in your trajectory the incubator where you sort of learned and should scientists early on in their careers have some kind of a rotation or kind of an exposure to incubators to foster that kind of... Yeah, I mean, I probably shouldn't say that but I personally think every grad student should start a company but maybe we'll have to edit that part in the video. But seriously, we could all write grants. I mean, we all do the qualifications, the quals that those are serious grants that a lot of us end up submitting. It's not harder to start a company. I mean, to find a way to force yourself to leverage something into finding solutions to problems. I mean, we don't like problems in the world. So I think, yeah. Yeah, I guess that my point was since so many people are not gonna be in your track, if they had an opportunity to explore incubators early on in their careers, it would make it easier because you don't know what you don't know. So you just go through there and I can do this. No question, exactly. And actually, there's a lot of people who actually, well, not a lot, but there's a number of people who would do that and reserve a summer to do an internship as a consultant or as an intern in different places. I actually have a slide where I talk about a framework where you could do at different stages and I actually have that on there. I think it's an excellent idea to be able to spend a summer or a month or even prior to, to get some experience in there. You may end up doing it, not doing it, but at least you're not starting from scratch when you're doing a PhD and kind of lost. Yeah, excellent point. Yep. Thank you. Who do you see as your major competitors? Where do you see yourself in five years? Wow. Are you being mentored? Do you think you're gonna sell your business in the next three to five years? Well, we do have lunch after this, so there's gonna be more of a Q&A for other questions. But generally speaking, I think, I don't think I remember the order of the questions, but in terms of mentoring, yeah, I mean, I mentioned a couple of them actually. My PhD advisor, I mean, he's still a mentor to me. So my undergraduate advisor is still a mentor to me. So these two, I mean, they actually one of the two smartest people I've ever met. So I think even in five, 10 years post PhD, I'll always go back and say, hey, what do you think about this? What do you think about that? So I think one of the questions was, oh, we're gonna sell. Who are your major competitors? Major competitor, yeah. So our model, there's not like another company that is exactly the same way. But in terms of competitors, why would say research match is probably something that's the closest to us, right? They provide a platform where people can provide basic information. That's free advertisement. And they could get together with researchers. So their model is slightly different, but they're probably the closest thing to what we do. And actually, data people we refer to as for a quick comparator to folks. So research match would be a DNA sample competitor. Yes. Just curious. So do you have, as part of your business model, entrepreneurial internships? Well, we'll be raising funding. So I think as part of that, as of right now, not really. But that's part of the plan. I think for us, the more brains the more scientists we have on board, like the better we are. It's just one of the things I really enjoy about startups is to be in a room, five, six of us just tossing up ideas on a white board and just back and forth, back and forth. And then at some point it's out and people are using it. So I think for now, the answer would be no. But in terms of, I mean, we hoping to go for, prepping to go for some more funding. Just to throw in here, I wanted to point out really and specify that I didn't say scientific entrepreneurial interns. Yeah. There is, I think, I've worked at a startup during the dot com days. So to me, you know. Yeah, no, we're not just, we're not just science. I mean, you could argue we're less science and more tech if you want. So it's not, I know I said science, but not necessarily that. I mean, we market, I mean, you could see, an MBA person, you could see it fit with us. I mean, every field really, marketing, social media marketing, business development, and it's really a team. So I know I said science, but I meant generally speaking, but it's not, it really, it's less science in terms of development, to be honest. Okay. So we'll go a little more, a little faster. So the third point is most of what we work on as scientists still really has not made it to the patients or the general population and that there's still a bottleneck. So, and the example I like to use for this is that if you think about some of the basic tools that we use in the lab, if we just pull it real quick and say, what are some technique or tool or just basic term that you use all the time? We get gene editing, microbiome, whole genome sequencing, CRISPR, and if we go into streets right now and ask Average Joe, do you know what these are? I'm pretty sure most of the time, unless they have some type of scientific background, they will say no. And those are really basic tools that we've been using for a number of years. And so what I think we could do as scientists is to, and another example is the genetic variant genotyping. I'm pretty sure if you also go around and ask Average Joe, do you know what a genetic variant is? You may get yeses, you may get no, not really, you know. But companies like 23andMe and NSDNA, if you ask them about these companies, they'll say, oh yeah, I know that, that's the ancestry, that tells me about my background. So what these companies are doing is really leveraging some really basic tools that we're using. I mean genotyping, we've been genotyping for ever now. And so I think one of the things that, I don't wanna say low hanging fruit, one of the things that if you wanna think out of the blue, what are some opportunities in the field? I think there's a number of opportunities and I think almost each of us could really draw up a list of the top 10 basic techniques that we use in the lab and really think of simple way of leveraging it to the general population. So it doesn't have to be a big drug every time that cures a massive condition to be able to be worthwhile and see that as entrepreneurship. Those take a long time and those are important too, but there are very much lower hanging fruit and much, a lot of opportunities to be able to leverage really some basic things that we've been able to do for years for folks to use. And the last one is, goes back to your point. Entrepreneurship should not be taboo within graduate schools. And I'm sure if you go to a lot of institutions, I've talked to a lot of folks, you should never say pharma, you should never say company. You have to only say grant and paper. So I mean, frankly. So and I think that could be a mistake. Obviously we're being trained properly, being trained to be scientists and doing that. But again, there are other ways, multiple ways of skin and cat in a way. And so if you look currently, there's minimal if at all entrepreneurship classes and training in medical school and graduate school and postdocs and residencies really, most places does not a money class, entrepreneurship class. Folks now have been doing the MD MBA, but in many places, but it's on their own. It's them taking initiative and doing that extra year. So I think that could be or should be a point of emphasis in graduate school and it should really be a taboo. And what we ought to do is perhaps teach our students to think like business people, businessmen and women, actually. And the goal originally would bench the bedside. Again, what's to teach doctors to think like scientists. And now I think we should shift that. And now the goal should be really to teach our doctors, scientists to really think like entrepreneurs and put some of the stuff that they're working on. So it doesn't really just dies in grants and papers, but also makes it to the home. And really it sounds like what I'm advocating is an MD PhD MBA. I think my parents would not appreciate that. And we're approaching the telling now. And ultimately what I wanted to put forward, and it goes back to what you were saying earlier too. A little bit of a framework in terms of how do you go and internalize that concept of bench the bedside to business approach. And typically the route is undergraduate, do a post back or medical, graduate school, postdocs, residency, faculty and move on. And it's okay to perhaps deviate. And if you have an idea, and again this is not to be exhaustive, this is sort of what's been really common. And from talking to folks and what I've seen out there happened most times. So this is assuming that you still wanna do this and not just sort of incorporate both the way I did it. Starting with an idea, at this level I think it's a very good idea to do an incubator and accelerator. Those are not MBAs where it goes forever, it's an intensive a couple months or depending on the size of it. Well you get the basic tools that you need to start a company and get to a team. And I think that could be really helpful. And obviously the school innovation office, Penn State I know I was a really active innovation office that can help with folks who have ideas and looking to translate into companies, yes. Just a question. Given that you've gone through incubators and accelerators and some other public settings like Shark Tank, do you worry that someone might copy your idea? How do you manage your intellectual property? Yeah, I mean that's frankly a classic investor question. And typically you go into a patent and such. Really the best patent, the best way to do that is to be ahead of the competition. There's a lot of things, algorithms that you can't patent anymore and the rules have to be changed. The best way is to stay ahead and really get to a point where you make it not worthwhile for somebody to start. In theory all of us could start Uber tonight if we wanted to. There's no rule against that. But you would never do it because there's no way you're gonna pull up the team, the marketing team to be able to promote it and go out there. But you can, you can do Facebook, but folks I've tried for many times. So the best protection honestly is to be able to push it. There's a very fine line, limited time that you have to really push it to a certain point where you really discourage that. But there's loopholes around some patents. The more solid ones obviously are the drug ones. Those are the ones that you have for 15 years and you can't really copy it and get in trouble. So by the start-up's ideas, that's when you have to bootstrap and get it going as fast as possible. So as postdocs and a resident, and obviously time is limited there, from an idea again, what's typical is to sort of co-found a company with your API. So that's assuming your API also has this innovative spirit. And I've seen that happen quite often actually at a number of institutions where the research material became so translational and had so much power in terms of clinical data. I've seen the PI and the graduate student leave, period, and just start a company. Oftentimes they'll remain and then they'll work together. And there are ways to actually incorporate that into your thesis. Different schools will allow different things, but you can't actually do that. But obviously as a postdocs, you're already done. So often what you work on, if you work on a two-year postdoc, it's really the research and development part of the company that you're working on, and it's developing the R&D as your postdoc. And you'll be extremely, whether it fails or not, you'll be extremely valuable for pharma or stay in academic if you want. And obviously, with my care, there's the SBIR and SDTR that we're hoping to take advantage of that it's really terrific at the NIH. It's the small business innovation grant, research grant that you can use, then those are probably some of the best monies you can get because getting $200,000 from a VC and getting $200,000 from an angel and getting $200,000 from the NIH, it's the same amount, but it's really not. And so there's pressure and other things that come with other money. So if you're able to leverage those, obviously they're competitive, just like any other grant is, but if you're able to leverage some of that at the tail end of your R&D, two-year of a postdoc, then that could be the gateway to, that's an employment right there, and that gives you an additional two, three years where you could really take off and see if it's worthwhile. And ultimately, even as a faculty member, you commonly, they'll be your scientific founder, that's assuming you wanna remain a faculty member again. This is not meant to be the full exhaustive list and what you can do, but a common framework of what typically works out there. You could be a scientific founder or you could actually co-found a company with another PI or faculty or with a postdoc, typically, or even a graduate student, and typically they'll also have a board position where you could influence, but it's not full-time. So this is perhaps you're meeting with the company once a month and to use your expertise or a lot of times companies will need those faculty members for connections and knowing where to get the places. So if you have a product and the guys are the god of this part of genetics, so you'll see folks like George Church and several hundred companies, so typical. And again, the SBIR and STDR fits really perfectly, especially at the postdoc and faculty level where you have time and not the pressure of working and get the R&D going and stuff going and then you could apply ultimately for it. That's sort of the framework and I think that could apply. And again, if the earlier you can understand this and notice about yourself and that you're interested into it, the better it is, obviously, because some decisions will make it more difficult, depending on which lab, the institution, and the places to be able to apply this. So as early even undergrad, I didn't put anything here, but almost everything here, just assume undergrad has all the time in the world, so you could do everything. So again, I just wanted to take a minute to, again, remember Congressman Louise Slaughter who passed away last month and then said a little bit of the words, a few words about what she's done, but I just wanted to take a minute to recognize and remember her for some of the work, particularly as an advocate for genomics research, some of the stuff that we talked about with health insurance and other companies not being able to leverage your healthcare information against you, which is extremely big. So that's a big deal. And obviously, her participation in human genome projects and such, so a quick thank you. And to really end with a concrete example, and I wanted to pick a concrete example again with in terms of the, in the genomics field, particularly precision medicine, and show how you could go with the framework to go about studying an initiative. So as we know, precision medicine is trying to do away with the one size fits all therapy. So we're trying to end the days where patients with the same phenotype or the same conditions were giving the same treatment. Obviously there is a reason why we see this numbers right there were anywhere from 38 to 75% of drugs not working for the population. And so the idea is that we should design therapy based on a person's genetic background. And for example, if you're a fast metabolizer, then you would need double. If you're a slow metabolizer, you get half the ratio. And even, and really design therapy best, again based on someone's background. And the idea is that even within this, giving two patients the same therapy, the dose ought to be adjusted again based on their genetics. One of the, I think the gentleman mentioned earlier, unsolved challenge I think is in the healthcare disparity. This is probably one of the most profound statistics I've ever seen. It was less than 2% of more than 10,000 cancer clinical trials, often about the NCI, included underrepresented minority. And so that's African-Americans, Hispanics, Native Americans. So that's an insane number. That is almost ridiculous, right? And so there's a ton of opportunities for us to do something in there. And if we really real about precision medicine, obviously you need to include everyone. So that's gonna be precision medicine for not the 2% because all the data and everything we collect is gonna be based on the specific population. So if we serious about this, this is obviously an area of need, an area where we could easily make a difference in impact and again apply the bench to bedside the business effect. In terms of all clinical trials, the numbers are not that much better. I mean 5% of all clinical trials participants were African-American while they represent 13% of the population. 1% Hispanic, they represent 17%. And 83% what occasion where it's 67% of the population. Again, and this goes back to way since 1993. And so pretty staggering piece of data and I think opens up the flood gate in terms of opportunities for all of us. If we serious about precision medicine, there is a lot to do to get there. And so from that problem, you could think of in terms of bench, we could continue generating knowledge from the court studies, make genome more usable and establish clinical applications for these findings, you know, make sense of junk DNA or so. Need to develop, to continue developing personalized therapy and do away with the one-size-fits-all model. Again, and for everyone obviously. And continue to find new ways to incorporate genomics-driven data into patient care. Ultimately in terms of that transfer into businesses, what we really need is to develop new tools aiming to increase clinical trial participant. And that, I mean if you're looking for an idea for a company, you could start five right now just based on that, because that's really needed. And that answers a question and that would solve an important problem. Also we need to leverage the technology to develop ways to apply current and the new knowledge. And so that, like I said, they don't die in papers and grants. There's a need for new companies to be able to leverage those sequencing data that's coming to the pipeline and ultimately make sequencing even more affordable. I mean it wasn't too long ago that we were talking to Mike earlier that genotyping was $600. And so, and now, and obviously with all our cost of sequencing going down, it's not far-fetched to get to perhaps the $200 for whole genome one night. So again, I wanted to quickly actually mention some of the NIH-funded opportunities. The All of Us program, obviously, it's something that's similar to us in terms of patient recruitment as part of the Precision Medicine. And that's a group that we're actually looking to potentially reach out to when NCI work together. There are a number of other training programs in the NIH and you could feel free to Google some of those where those are small training and business training that's offered and I think are pretty helpful in terms of if you're starting from, I don't wanna say from scratch, but from the way I started, only with the science and the standard curriculum and being able to start getting immersed into the business world. And obviously the SBIR and SCTR are really huge. A lot of, I know a lot of folks with those grants making a significant difference in terms of pushing their business forward. So those are amazing opportunities on top of Angel and another investor. So and this probably is my last slide almost before the thank yous. So, and that answers the question and that's a little bit of a plug for me. One of the things that I'm working on and I'm hoping to launch in the fall is a hub where scientists like ourselves, faculty members, graduate students, medical students, pulse backs could interact with each other and discuss some of their sciences to leverage it to make companies. And so the idea I think we, this is something that's very needed where we, it's there for a lot of the other fields but there's really not a spot where I am working on an important target molecule and someone in San Francisco is working on something similar. There should be a way for me to communicate with them and say, hey, we have this combined, this is, we could leverage this into a company. And also this hub would allow for opportunity for business, straight business folks or even for my company to come in and go through some of the discussions and fund some of these projects. So I think that's something that, we're calling Bench the Bedside to Business Pipeline and if you're interested you can check it out on my website as well. And this is something that we're hoping to launch in the fall and we're building a team together if you're interested in any shape or form to join this initiative. We're writing in the pick up, getting a team together. So we're hoping to be a place where ultimately researchers again, all could gather and leverage a lot of the science and discuss ideas and leverage them into companies. Knowledgement, so I'd like to announce a few folks from the DNA sample team. There's Joel Kobo that we actually started in the same lab and now we're in the same company. So one thing with your co-founders, you would them probably more than your significant other. So you should be with someone you like. And Abeka Bonti is one of our excellent developers in these two members or an hour scientific advisory board. Dr. Eldairi, Dr. Lim, and particularly Dr. Holzman would be who's been very helpful in the design process of a lot of the processes that we have now and continue to help us. And ultimately I wanna thank my co-PIs, particularly Dr. James Brooch and Dr. Gerhardt who's been really extremely supportive, pushing innovation actually in the lab and always pushing us to think of new ways to, I'd like to say not to find ways to make the horse faster and stronger, but to invent the car. And so last but not least, I wanna thank the Penn State College Medicine, MSTPM, DPHD program, the leaders Bob Levinson and Leslie Parent for obviously allowing me the opportunity to be in the program and be able to put all of this together. So thank you and I could take additional questions. So we just want to do the obligatory pictures and handing over of the certificate. But I just wanted to thank Olivier again for an amazing talk and not just a talk of really succeeding in creating a conversation with us here. And I thank you for what you have done and in particular in advance for what you will do because you are clearly full of ideas and energy. And so I know that there are great things to come. And so we'll present again a certificate with our first annual, Louise M. Slaughter National DNA Day Lecture. Thank you to our audience, both here in person and online, on Facebook, those who are watching whether it's right now live or in the future. Thank you to Olivier for the great talk and conversation. Thank you most deeply and humbly to Congresswoman Louise Slaughter for all that she has done for Genomics and for all of us in terms of our genomic privacy. And there will be a reception just outside for those who are in the room. So please join us there and we'll continue questions and discussion with Olivier at that time.