Invention to Impact - A Webinar about NSF Innovation Programs

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Hello to everyone i wanted to say good morning  because i'm here in Southern California it's   my pleasure to welcome you to our Wireside Chat  this is a series where we invite the public to   listen in on some of the things that we're  thinking about at the National Science Foundation   my name is Andrea Belz i serve as Division  Director for Industrial Innovation and   Partnerships the IIP Division here at NSF i'm here  with my colleague Steve Konsek. Steve hi everyone   i'm Steve Konsek i'm a Program Director in the  NSF Small Business Innovation Research Program   and Steve will be here to help moderate the Q&A  session which will take place at the end of this   i as you can imagine you may not have the  chance to have all of our questions answered the   participant count is in the 600s so i'd like to  welcome you all to this session and to talk to you   a little bit about our programs in translational  research and we think of this as going from   Invention to Impact this transition has been of  interest to scientists for a long time this is   a clipping from meeting minutes of 1917 comments  by J.J Thompson who discovered the electron   and my favorite quote from here is this one that  says that people would have been very skeptical   if they had been told 20 years later that  they would be listening to another discourse   on the commercial applications of electrons  and so that tells us a little bit about the   surprises that can come from basic  research and the applications therein   so what i'd like to do first is give you a  little bit of inspiration and tell you why it is   that we care about translational research  at NSF and how we think about it i'll tell   you a little bit about the agency for some of  you who are less familiar with the foundation   implementation i'll tell you how our programs work  and then i'd like to spend a little bit of time   on our inclusion initiatives and then finally an  invitation for you to engage with us so the first   thing i'd like to point out is some data from  the Kauffman Foundation from several years ago   and these data speak to where jobs are created  the blue line at the top represents firms that   are less than five years old the red is six to  ten years old and the yellow is over 11 years old   and what you see is that consistently the newest  firms are the ones creating more jobs and in fact   this is consistent even in the financial crisis  from a decade ago so we know that new companies   create new jobs and this has been validated  in the economics literature in the years since   so startups serve as engines of growth they  can contribute disproportionately and the   reason we're concerned about this is that we see  a steady decline in the rate of startup formation   over the years this chart begins in 1977  and you can see a fairly consistent decline   as of 2014. i'll show you more recent data in a  moment but what makes this really striking is if  

you think about all of the other forces that have  acted to make startup formation even easier the   fact that you can register a company online all  the new mechanisms and corporate entities and yet   the rate of startup formation is declining  since 2010 you can see additional data that   demonstrate the same phenomenon so the  blue line at the top is global numbers   and the red is in the United States the yellow  is Europe so the last chart ended in 2014   and you can see the ongoing decline since then so  startup creation has been declining for 40 years   we also know that the venture capital world has  really changed dramatically even over the last   25 years since the dot-com boom so let's see  what these data are telling us this orange peak   is the data and internet boom of the early dot-com  era and you can see the bust and then you can see   how that sector really has recovered the blue is  the healthcare ventures which had less of a boom   less of a bust and then has been growing fairly  steadily and consistently in the years since   these engineering companies basically are  hardware and what you see here is the same   lag in the boom but really not much recovery from  the bust and so it's interesting that 30 years ago   it was considered riskier to invest in software  versus hardware because of the sense that you   didn't have anything to hold on to at the end  and now the perception of risk has really changed   and we see very dramatic increase in the software  space this struggle to attract capital has been   documented extensively in the economics literature  as well so venture capital has really changed in   the last 25 years this is another view of the same  data and i know it's a little bit of an eye chart   so let me draw your attention to just a couple  of data points which is that if you look at the   electronics sector over the course of 20 years the  number of deals grew by 40 percent and the funding   by roughly 3x but in software the deal volume  grew by 4x and the funding by a factor of 20.   so there are more deals they're bigger that  is where venture capital is largely going   there are other perspectives on how the  investor appetite for risk has changed   so these data are from a 2020 paper that shows  roughly the same phenomenon i just showed you but   going back further in time so the blue box here is  software and you can see how that has grown in the   30 years in between these two samples the next box  the light blue is consumer and business products   and services and you can see the explosive growth  there and in some ways it has come at the cost of   venture capital investment in telecommunications  networking etc now this is normalized to 100   percent so it doesn't tell you about the total  number of dollars going in but you can see how   the proportions have really changed the top box  is biopharmaceuticals and medical devices so it   supports the idea that we have less investment  in some kinds of hardware than we used to   these data speak to the number of companies  that generate revenue at the time that they   raise venture financing so venture financing  comes in in multiple stages the earliest stage   is the seed stage and that's the red line here  series A typically follows and then series B after   that and of course there are more letters in the  alphabet as needed so 10 years ago only 10 percent   roughly 9 of the companies had revenues when they  were attracting series a financing today at 67   two-thirds of the companies are generating  revenues at the time that they get seed funding   series A has gone from 17 percent 10 years ago to  77 percent, that's three quarters of the companies   getting series A financing are already having  revenue and with series B it's gone from 47 percent   to 92 percent so that's a really dramatic  shift in where risk lies in the private markets   the investors effectively are  transferring risk to the customers   and the reason we care about this is that while  both angel and venture groups contribute to   innovation we know that venture capital funded  firms experience faster commercialization and   so what this suggests is that there's an even  greater need for support during the early stage   funding gap because the private markets have been  evolving we have another view into the markets   this time in the public markets when we look at  the lifespan of companies on the S&P500 index   what you see here is the life span the average  lifespan as a function of time going back to   1965. so the ups and downs are effectively the  business cycle the economic cycle but you can see   that there's a general downward trend for how long  companies last on the S&P500 and the most extreme   case of course is to look at companies that were  there 100 years ago only two of them remain today   so we see that the pace of refreshing  in the public markets has really changed   another view of the public markets is to think  about intellectual property and intellectual   property is part of a class of intangible assets  that includes branding goodwill and other assets   this study was done by an investment bank  that focuses on the role of intangible assets   in estimating company value so in 1975 17 percent of the  S&P500 market value represented intangible assets   the vast majority 83 percent or five parts out  of six were captured by tangible assets property   plans equipment things that you can touch and  what you see is that over the ensuing 45 years   that ratio flipped and today  roughly 90 of the S&P market value   represents intangible assets and that includes  all kinds of intellectual property so that's a   stunning statement about the importance of  intellectual property in the public markets   another interesting statement is the idea that  roughly 30 percent of the Nasdaq exchange's value   stemmed from university-based research and this  is from congressional testimony 10 years ago   so we see that intellectual property and  universities are connected to the public markets   we know a little bit more about intellectual  property when we consider how it relates to   research and development investment and the output  and so what we see here is that if we invest   roughly 270 billion these numbers are a couple of  years old so you could say 3 billion 300 billion   dollars in R&D and we have an output related  to IP of six trillion dollars and that again   is all kinds of output now you can say well  the output that we're getting today is not   related to this R&D expenditure today because it  stems from investments that we made 20 years ago   and that's absolutely correct which is why our  investment in R&D today is so important because   it can be captured in output in the future  we also know that wages associated with   jobs in firms that create intellectual  property are typically a little bit higher than   they are in the other companies and that it's not  just the people generating intellectual property   it's everyone benefits from this so intellectual  property has a multiplier in economic output   these data relate to federally funded research  and they come from a study i did for the national   academies a couple of years ago and what  you see here is three different levels of   investment of federal research dollars so  the blue data are basic research the red   is applied and the green is development these  data go back to 1955 and what you see is that   basic research in universities has really  grown over that period as you would expect   whereas there is less federally funded research in  industry that's not to say that industry doesn't   do basic research because this doesn't capture  what industry is investing in its own research   we then see the applied research which is  the intermediate stage and then of course the   development research is highest in industry as you  would expect what makes these charts interesting   is that they have the same y-axis and so we can  ask ourselves these questions we know that basic   research happens in universities and development  research happens in industries what does the   handoff look like between these two groups and  so that's a question of great interest to us   so i know we've touched on many different topics  and different sorts of data but what do we really   have what we see is the following if we care about  jobs in young companies we know that the venture   capital community views risk differently than it  used to we know also that there's a faster pace of   market disruption than we have seen historically  there's a strong multiplier from intellectual   property and universities have a role to play  and what we see is that if you combine these   factors you discover that it's very meaningful  for us to help launch technology startups   and so i'll talk a little bit about the programs  that we have in order to help execute that vision   if you're not familiar with NSF our mission is  to promote the progress of science to advance   the national health prosperity and welfare and to  secure the national defense our new director not   so new anymore Sethuraman Panchanathan  Dr. Panchanathan has spoken extensively   about the need to accomplish our vision at  strength i'm pardon me at speed and scale   and so i'm going to talk a little bit  about how we try to execute on this   these are some numbers that describe NSF many  of you may be familiar with this already but in   general more than 90 percent of our budget goes to  funding research education and related activities   we are of course very proud of our 248 nobel  prize winners we invest a billion and a half   roughly in STEM education and so out of this  budget you can see that we try to support   basic research across just about every discipline  and so this chart tells us the fraction of   total federal support that we provide for basic  research in a number of different fields and this   is very important for us to think about in the  translational world because we are really working   to translate all of these different technologies  to the marketplace writ large meaning deployment   at scale so if you look at our budget we have a  Division of Industrial Innovation and Partnerships   focused on translational research and we're really  working to generate impact with these programs   so if we ask ourselves well what do we actually  do we think we have several different roles one   is that we educate nsf invests extensively in stem  education of all kinds and we participate in that   we accelerate the transition of  technologies to practice to use at scale   we demonstrate through technological  feasibility studies and then we translate   and those were the risks that i was speaking  to in the first part of this presentation   so people think that when you're interested  in startups that you really love risk and the   truth is that we don't love risk but we are  obsessed with it and being in a startup is   really an exercise in learning how to manage many  different kinds of risk so we worry about skills   gaps that's what we're addressing through  education we worry a lot about market risk   and making sure that we're building things that  are meaningful in the marketplace and that people   want of course we worry about technical risk and  whether technologies will work and then finally we   worry about financial risk and then we can map our  programs onto this list of risks and discuss how   we can address each of them and so i'll talk about  the programs that are described here in brief this   is an example of the kinds of things that we  can do when we think about it this way Marinus   Analytics is a spin-off from Carnegie Mellon and  by integrating facial recognition with analysis of   with text analysis they can identify victims  of human trafficking and are working closely   with law enforcement in order to do that this is  another example Ginkgo Bioworks is a bio factory   and their early funding came from the NSF when we  were first launching a larger effort in in life   sciences most recently their valuation is on the  order of 15 billion dollars and so we're really   excited about this company and how they were  able to contribute to solutions to the pandemic i'll talk for a few minutes  about the SBIR and STTR programs as i mentioned earlier we fund technologies that  the agency funds as a whole we don't fund clinical   trials but we fund just about everything else and  so this chart shows you that in fiscal year '20   we invested more than 200 million  dollars in technologies of all kinds   i know the font is tiny here and that in itself is  an indicator of the breadth of technology topics   that we fund and if a technology of interest  to you doesn't appear we also have other topics   we really are working to make sure that we're  funding relevant technologies and companies that   are on the cutting edge of all of these so what  is America's Seed Fund we are working to transform   discovery into commercial and societal benefit  we have a simple pitch process which enables you   to submit the equivalent of an executive summary  to see if it's a good fit for our program and   it's an efficient way that you can get feedback  from us to make sure that it's a proposal that is   consistent with the goals of our program there's  roughly two million dollars available per company   the first stage is a six to twelve month grant of  a quarter million dollars for feasibility research   then a million dollars for prototype development  and then this is where we try to realize the   promise of partnering with private markets  by matching third-party investment in a   one-to-two match so 50 cents on the dollar a  note on the differences between these programs   the companies in both programs  must have fewer than 500 employees   the STTR awards involve an academic partner and  so there's some fraction of the budget that is   dedicated to that academic partner typically a  university the PI the principal investigator must   be employed principally by the small business  and we work on a quarterly window system   not a deadline system so you can submit  a pitch anytime and a proposal anytime   some information about the kinds of awardees that  we're funding 95 have fewer than 10 employees and   so this is a reflection of our goal of funding  very young companies 81 founded   in the last five years more than 50 percent are  new applicants to us and if we look at how our   portfolio has evolved it's gratifying to see that  these companies have gone on to raise over nine   billion dollars in follow-on equity financing and  we've seen over 150 successful exits remember we   are trying to take on the risk that the private  market really cannot and so this is gratifying   for us to see that we can do that this is not  the only indicator of the impact that we have   we funded the company that ultimately developed  LASIK surgery we funded Qualcomm so there have   been many great success stories in the past that  indicate value far beyond the financial markets   this is our stakeholder subcommittee and  i encourage you to look on our website to   learn more about them but we maintain very  close connections both to the philanthropic   and private investor communities as well as the  corporate venture communities and they have been   particularly helpful to us in understanding  the impact of the pandemic on our community a moment about I-Corps so I-Corps  is really designed to answer these   questions questions like what problem does  this solve do customers want something   efficient or cheaper these are questions that you  really cannot answer in the lab you can't even   answer them on campus and so the I-Corps program  requires that you are commercializing a deep   technology and it's a seven-week course which  focuses on teaching the business model canvas   and conducting 100 interviews of industry experts  it's really gratifying to teach this because we   find that graduate students stand up and say  things like i've never talked to anyone outside   my research group before so it's a wonderful  experience from that perspective the team has   three or four people typically an entrepreneurial  lead a graduate student or a postdoc a technical   lead who's the faculty member or senior  research staff and then an industry mentor   the award is 50,000 dollars it used to pay for travel to  shows today it pays primarily for salary support   and registration in conferences and we've  had roughly 2,000 teams about half of them   form companies and the follow-on funding that they  report is over 500 million dollars here's a great   example of the kinds of technologies that we see  it in I-Corps and so this is a team that has been   developing socially assistive robotics pardon  me so robotics to support health care services   and you can see that this stemmed initially from  a basic research grant 10 years ago after doing   I-Corps they were able to go on and get a phase one  and phase two award from us and we're happy to   distribute links to their video and to their press  page i'll talk for a moment about the Industry-   University Cooperative Research Centers program  so these are centers that are really designed   for us to help catalyze partnerships between  university and industry we do this through   this sustained engagement model where the  industry members pay membership fees and vote   together on the models of the kinds of research  questions they'd like to address and so today   we have over 70 centers 800 members these are  distributed across the country they typically   have multiple universities who are participating  and students have great opportunities to   learn about industry research and for that  reason they're often hired by these members   this is a little bit of a list of the  kinds of technologies that we fund   again we are technology agnostic we're looking  to support technologies at large throughout the   nation here's an example of a center that we fund  the Center for Health Organization Transformation (CHOT) and CHOT was up and running before  the pandemic you might remember a year ago   when there was a very interesting Wednesday when  we learned that we were actually in a pandemic   and the following Monday we at NSF transitioned  to 100 telework as many of your organizations may   have done a well as well what was remarkable was  how fast we were able to respond to the needs that   were clearly emerging and so you can see that two  weeks later we were making awards like this one   developing modeling and analysis tools to  track coronavirus and infectious disease spread   so this is an example of how responsive  we hope to be in addressing national needs   Partnerships for Innovation so these are  prototyping awards for NSF-funded principal   investigators again open to any technology there  are two different tracks depending on whether a   partner is engaged or not and the teams are  required to participate in I-Corps so that they   have marketplace insight while they're doing their  prototyping recently we released a notice a Dear   Colleague Letter about how there is an opportunity  to support patent expenses in the universities   and i'd like to thank the LinkedIn community for  distributing this information very rapidly it was   amazing to see that within a couple of days  it had gotten hundreds of views so thank you   this is an example of a PFI team from UT Austin  where they've developed a system that provides   data-driven treatment for neurological  disorders and after their PFI award they   were able to start doing demos with rehab and  research programs and are now successfully   raising money and so this is an example of  the kind of transition to practice that we see i want to transition for a moment to  talking about broadening participation   it has been a focus at NSF for many  years we're very committed to this   if you were to go to this page i could not list  the programs because the screenshot didn't make   it past the letter A they're listed alphabetically  i strongly encourage you to check them out   i will talk for a moment about our focus in the  Division in the Inclusion in Innovation Initiative (i4) and i4 has three key components one is affinity  two is community and three is opportunity so what   does that mean affinity is that we identify  a partner who is interested in targeting the   same groups that we are and then we co-design new  activities the community is that we really form a   joint mentoring team and then work to conduct  outreach at scale and opportunity is that we   introduce industry discovery to these students and  then help them transition to funding opportunities   so we have partnered with the National GEM Consortium in the i4 initiative and what's   beautiful is that they decided i4 was  to inspire integrate increase and impact   so this has been a great partnership that we've  had now for two years and in terms of the outcomes   these numbers are from a couple of months ago but  20 plus events in the space of nine months with   76 universities participating we had over 200  participants in these outreach events and the   reason we note that they're unique participants is  we find they come multiple times to learn and hear   the information again so that we can reach them  and help them explore the questions that follow   and we see primarily PhD students participating  in some Master's students so the first GEM teams   have been entering national I-Corps cohorts and  this team on the top is led by this young woman   who is a GEM fellow and we were delighted to see  that they won a $100,000 prize competition just   last month so we are excited in particular about  the numbers that we're seeing so that we can help   inspire students to consider translational  research and to pursue some of these other   funding paths in particular by using I-Corps as an on-ramp we also support the ASEE the American   Society for Engineering Education in supporting  underserved post-doctoral researchers they work   in startups and many of them go on to be hired  full-time following their postdocs in the startups   and then NSF has an active effort through its  Science of Science program in understanding   how we can continue to broaden participation  in entrepreneurship and innovation so that   we can really engage all of our nation's  communities in these important activities i will touch on the review criteria for our  proposals we like the rest of the agency   we are committed to high standards on intellectual  merit and broader impacts i'll define those in   a second and then we also look at commercial  potential and the strength of the business model   so that we can help companies be successful so  the profile of a good proposal is as follows   intellectual merit is that we are looking for  differentiated approaches to solving a big problem   and ideally with high technical risk and  methods based in science and engineering   on broader impacts we're looking to  benefit society in many different ways   strengthen competitiveness and enhance  participation these are examples of the broader   impacts obviously in benefit society there are  so many ways that our companies can help and then   finally in commercial potential we are looking  to understand what is the commercialization path   and we want to be a significant catalyst for that  company so companies that are too far along where   we may not provide a catalytic advantage  may not be as central to our focus we are always looking for reviewers so  please consider joining us as a reviewer if   evaluating proposals along those  dimensions is of interest to you and just so you have a sense of who's in IIP this org chart with small font is our team   i am currently on leave from the University of  Southern California Viterbi School of Engineering   we have a couple of people who are also rotators  as they're called from other universities   we have postings in three different programs  in the SBIR and STTR program in I-Corps and   in PFI and so if it's of interest for you to  have this kind of catalytic effect in the nation   we strongly encourage you to apply to one of  these postings and we have the capability to   engage you if you're a university  faculty member or if you're not   so please contact us and look at these  postings if that's of interest to you so in closing i hope that you've seen  that the need to support commercialization   of deep technologies is profound it's profound  and it's challenging and it's challenging in part   because of the way the private markets have  evolved and yet the public markets also tell us   that there's so much opportunity we support basic  research across all disciplines as an agency   and our division mirrors that and works  to translate these technologies to the   marketplace and to deployment at scale we support  training and research in many different ways   and we welcome your participation as a reviewer  as a mentor on an I-Corps team or another supporter   And so I'd like to thank you for your attention

2021-06-22

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