 So it's a great privilege now to introduce our next panel and our next moderator. So this is another panel that at the USAIC during our summit we have every year, which is around industry and academic partnerships and something that we're doing again this year that we've done each of the last several years that we do this virtually is we don't give you any time for lunch, which means that I don't get any time for lunch. We have such rich content and we're using every minute of this day to bring that content to you. So let me introduce please the moderator of this panel and then she'll introduce the panelists. And the moderator, we're so lucky to have Susan Hockfield joining us. Susan is an amazing leader, an academician, a neurobiologist, who spent most of her career at Yale as a professor, ultimately in an administration going to become the provost at Yale and then spending almost a decade at MIT as its 10th president. And I'll say something about Susan, but let me fast forward to just this past Monday where I had a chance to spend time at the Inauguration event for Sally Ann Cornbluth, who's the 18th president of MIT. And Sally Ann is the second female president and the second life sciences, the second president with a life sciences background, which is amazing, but it means there had to have been a first female president and a first president with a life science background and that happens to be our very own Susan Hockfield. So Susan, thank you very much, Dr. Hockfield, for joining us and I will hand it over to you. Thanks very much. It's a real pleasure to be here and the Inauguration was a trip. It is always very exciting when the piton gets passed and I am delighted that Sally Cornbluth is taking over as MIT's president, delighted and proud and second woman and second biologist, more destructive than being a woman. I can tell you, I've experienced that. So listen, I am so delighted to moderate today's panel of really superstars to help us think together about the current state of and more importantly, the as yet untapped potential of academic industry partnerships, which is really at the core of this industry. And one of the things that was exciting about joining MIT is to jump into this world, this incredibly vibrant rich world of the ability to make great discoveries and then translate those discoveries from the bench to the bedside. So I'm really delighted to be here. And the panelists, I say, could not be more stellar. I will briefly introduce them now, starting at the end of the alphabet with Ilya Zerhouni, vice chairman and president of APCO Health, Marcus Schindler, executive vice president and chief scientific officer at Nova Nordisk, Matai Mammon, CEO designate of Fog Pharma. My colleague at MIT, Phil Sharpe, institute professor at the Koch Institute, or integrative cancer research at MIT, and Priya Singa, executive vice president and head of development and interim head of research and global safety and regulatory sciences at Biogen. So I'm gonna just give a very brief introduction because I want the panelists to have as much time as possible to share their views, but I have to tell you, I mean, I think we all know that the rate of change over the last 15 years or so in terms of new therapies, new drugs has been absolutely breathtaking. There is still unmet patient and industry demand for new therapies. And it's clear that we must increasingly depend on academic institutions for industry innovation. The structured approach that's in use today started in 2007, which is almost 16 years ago. And so today in our panel, we're gonna consider how these alliances have fared so far. What are we doing to enhance the relationships and make them more productive? What are the key performance indicators to measure success? And the big question is, where do we go from here? How do we accelerate what's gonna be a robust activity? How do we make it even more impactful? So let's get started. I'm gonna start with what I call the inside scoop. And I think just it would be fabulous to hear from each of you. We'd like to know about your experience with these alliances. And if each of you relatively rapidly could share with us one story, either a great success or a horror story about these alliances and what was the cause of that success or failure? And I'm just gonna go through the hosted stamps on my screen and calling you one by one. So Marcus, would you mind starting this off? Not at all. Thank you so much, Susan. And I actually wanted to start with my own career, which happened to start at the Glaxo Institute of Applied Pharmacology. So an industry sponsored research institute, led by an industry veteran, but also embedded in an academic environment. And for me, that has been really formative and being there throughout the career that you need to be scientifically excellent but translated to pharmaceutical research. And I think understanding along the way that we have distinct roles to play in this has been super important for me. And one great example actually, not far from here, I'm sitting right now overseeing candle square here, happened at the Whitehead Institute where we actually worked with Hudo Viennese and Rick Young and others with an embedded scientist from Novo Nordus for a couple of years. And they really genuinely opened their doors to that person that didn't participate in everything they did. And we worked together on molecular condensates in diabetes, right? And as they said, well, they wouldn't have never thought of diabetes, they would have worked on cancer or something else. So we brought something unique to the table. And they did, of course. And out of that came sort of a biotech spin, our dew point, which we also know now collaborating with. And for me, that is a piece really of transparency and openness and generosity to let people participate, but then also over the years, let these things take their course and develop into something that I think is of mutual benefit. That's fabulous. And it's a wonderful example because people imagine that they transfer it down by throwing things over the fence. And you've just illustrated the incredible importance of a really intimate and integrated approach. Matai, how about you? Do you have a success story or a horror story or maybe both you want to share with us? No, it's a great question. And I'll talk about a success story in a moment, but just to contextualize the answer, as you said right at the beginning, Susan, like the unmet needs are all around us. Like in most areas of medicine, they're inadequate. In most areas of treatment health, there's inadequate medicines. And so it's a hugely difficult task that's collaborative even outside of academia industry. These are so many other kinds of collaborations with government and manufacturers and pharma service groups and dirt data purveyors and all these like groups. And so this specific interface is absolutely critical, as you said, and one really good thing, one really a feature of our industry, feature of our world is there's so many different models being tried. If it wasn't for that, I don't know what the best way is of collaborating. A really good example that's worked out really well in my previous job at J&J is the collaboration with Remnick Xavier's group. And it's been at the Broad and MGH. And it's been a really good example because I think right up front, years back, some of the barriers to collaboration were addressed head-on. Like how best to handle differences in mission sometimes, like we're advancing knowledge through somewhat undirected work is often historically what has given rise to like incredible breakthroughs. That's a different mission than translating science to a product that is meant to serve patients. And the other big area that just needs alignment and pre-discussion, and this is what makes collaboration successful, is how to handle knowledge and intellectual property. I've seen like lots of, I've seen in fact the majority of academic industry relationships sour at some point because of that. Like when you publish, when there's patents versus peer-reviewed publications, when you talk about something, when you don't. So, Remnick and the team at Janssen did a really amazing job over many years bringing forward biology that was only really discoverable in academia and married it well to the translational machinery and the excellence in all sorts of downstream activities within J&J. So that's a great example. But it needs to be handled. Some of these barriers are very real, they're to be understood and managed right at the beginning, not halfway through. Thanks, Matat. That's really great insight. Maybe we can come back to this at the end in terms of how do we really accelerate things? Phil, sharp, my colleague. My first collaboration with industry was in 78 and interacting and starting Biogen because we were a bunch of academic scientists and we formed an advisory board. And then we worked with management to start a company and I was chair of the advisory board for over 25 years. So it became part of the collaboration. Since then at MIT, I've been head of many collaborations with industry. I'm sorry to say, and we've avoided horror stories, but and the reason for that is that the two parties had a full understanding of what both parties can bring to the collaboration. And I'll take the example of Merck. Ed Skolnick was head of research at Merck. He wanted to actually build relationships in Cambridge at MIT. We started a collaboration. He learned about faculty, he learned about what we were doing, we use the resources to stimulate a lot of young faculty to get involved. We started programs training engineers and biology because Merck wanted more people in that space and we supported very excellent research which they learned about. But Ed knew and I knew that we weren't developing products at MIT. We were developing people and science and that's what they wanted. And we had a very effective collaboration. Now you can be more oriented towards particular disciplines now, but that was a very successful collaboration. Great, thank you. Shared understanding of everyone's roles. Yeah, please. Priya. Oh, you're on AQ. Oh, there you are, great. Yes, thank you. First of all, excellent to be on the panel with all of you. And I'll just start by saying that, I think I believe and I know at Biogen, this is true, Phil led by you that many years ago that it's really a team sport, everything that we do. So we see this interface and we see the collaboration between industry and academia as an absolute prerequisite. We also see it, I think, Matai, to your point, we see it across the chain. So we explore it for CMC, targets, human biology, building medicines and more. I think we've had many, many successful collaborations, but one that stands out for me is a collaboration that we had with the university in the Netherlands. And the reason that I think this was very unique is about the clarity at the outset, which was also mentioned about setting expectations, about being very clear what the incentives were on both sides, what the goals and objectives were. And as part of this collaboration, what we ended up doing is we were looking at early biology and targets, but we hosted each other scientists for a six month period. And that made a very big difference because it was sort of walking two moons in someone else's shoes and being on the other side. And we had that end point and objective of delivering on the publications and the science. So I think that that was one that stands out in my memory, but we've had many. And I agree that some of these expectations need to be set at the outset and not midway because it's already too late if you do that. The other point I'll make is sometimes we have very large umbrella agreements with not as much clarity. And I found it to be much better in the reverse, which is you start off with a very focused collaboration and depending on milestones, expectations and success, you expand it. That works much better in my experience. Thank you. Thanks very much for your great insights. Ilyas, please. Yeah, that's a great question, Susan. So I'll just share with you what didn't work and then share with you what worked. And I think some of the points have already been made. The one thing that didn't work my life in academia as an executive vice dean. And when I remember the tendency at the time was to do institution partnerships. So the university X would work with company Y and then they would work together, have a common committee and try to make something happen. That was an utter failure. It didn't work and you can, I won't name names, but there are examples we all know of great programs with multimillion dollars that just didn't happen because of what Priya and Matai already said. It's almost like academia, the product of academia is knowledge and train scientists and engineers. The product of industries is products. And those two don't match. It's almost like oil and water. So what did work? You need an emulsifier. To mix oil and water, you need an intermediate. And I think that the intermediate are either things that can work like separate institutes that are funded by industry, closed by academic ecosystems like the Novartis Institute in Boston and many, many of the R&D organizations that are now coming to Boston seek to benefit from an informal network. What did work for me was something that actually Andy knows well, was the notion that the pharma company would reach out to academic teams with the following characteristics. Number one, it had to be a great scientific idea with really great science and great scientists. It's not enough to have an idea. You have to have the originators of the idea on board. The second is the company itself had to understand the constraints on each side that the academic team really needed to have support but you could not provide support without creating an intermediary, which is a biotech company, which is the model that most people follow today. But to do that, you need an assembler. And this is something that I don't think we put a lot of attention because you need someone who's trusted by all parties who is the super connector and assembles the components. And so we work with Third Rock Venture and with Cricket Seidman and her husband because they knew the genetics. We worked with Sputich on Yale because he had figured out the structure of myosin and acting. And with Andy's insight, he told me, he said, this is really something we need to support. And we made a common endeavor called myocardia. And the idea there that was that everybody thought would be a wild goose chase was that we had a genetically driven science with a biophysically understood mechanism and the capacity of a third party put together of actually a credit Charles Humsey for being the assembler in this case. And so I think this is my experience. Institution to institution doesn't work. Specific idea, specific team, assembled by an intelligent super connector who is really connecting capital sources, knowledge sources, skill sets, academia, industry. That works. And I've seen examples of that. I think flagship pioneering essentially is a super connector, super assembler. So I will stop there. Thanks. It's really interesting to have articulated that particular role, the, you know, mixing the, I wanna call it the whisk. It brings all the parts together. Thanks. Shiv, let give us your thoughts, please. Well, it was very educative and I echo what Elias has said, especially in a country like India at the Cinder U.S. Forum. The academia wants to work with industry, but the government has a feeling that any scientist who works with industry is probably has some vested interest. And the vested interest is that he may be funded or he may have, you know, some other kind of, you know, support. So the best way is to have a biotech, you know, incubator. And very recently we have tried to explore this. The government has set up in India, at least several biotech such innovator things in the medical institutes. Till a few years ago, they were only done in the engineering colleges or in a management colleges. So all these collaboration of academia and the industry was not happening in the medical schools. So I think it has started just this year or a year before. There are now incubators and this collaboration is coming. However, I still remember long, long ago that in many institutes, the industry was supporting the several positions for faculty, but the positions for faculty were at the choice of the investigator. This thing has not come to India. My feeling is with you, Suzan and all the other people, there should be a mechanism by which we can have people with overseas who could come and work and they're supported. So you have a, not only US based or India based, but we have a bilateral relation. If people like you or Andrew or someone or Philip can come and the industry supports without vested interest and you spend three months or maybe not three months, three weeks and set up the ball rolling for the country, I think it will do a lot good for India. So we need a very transparent system where we can have you as the industry leaders come to academia, maybe work, maybe stimulate and use. And I work at the Institute for Liver and Billiardy Sciences, which is the only dedicated liver university globally. We see close to 1,020,000 liver patients in a year. With all that, we still do not have products and we still do not have a platform. So it would be encouraged if you people join hands on this. Thank you, really interesting. Sanjeev, do you wanna wrap with your own experiences? Sure, please. I'm afraid you're on mute. You could unmute, we'll hear you. Thank you. Thank you very much and excellent discussion and pleasure to be here. My experience with the industry is good. We have done recently a nasal trial for COVID vaccine and it was very successful nowadays and we are using it as a booster dose. And I said by professor in that in India, we have collaboration with industry and I'm working at All India Institute of Medical Science in New Delhi, where we have collaboration with many industry partners and doing successful research. Thank you. Thank you very much. I have to tell you, I'm just gonna make an observation. So many of you highlighted something that surprises me, which is the real physical cohabitation. There is a sense that there's a piece of the work that gets done in the academy and a different piece of the work that gets done in the industry and this idea that actually having people, real humans, from the other entity, living and breathing and working together, I think is really powerful and you've all articulated just how much that helps move things along. So I wanna ask you a question more of perception, but I think it's an important one, which is that for reasons I don't understand because the successes have been so numerous and so unbelievable that we've been able to develop drugs and that ideas from the academy have made their way into industry products. When you talk to people about, there's a huge amount of negativity and the general kind of receive knowledge is that these academic industry collaborations are not productive, but they're unproductive and is that just a question of numbers? I ask any of you to speak to this is why has this reputation evolved? Is it well-deserved? And if so, what should we be doing if not, what can we do to change the storyline about it? But I would say that the general public view of these collaborations are, don't reflect the optimism and the productivity that all of you have just talked about. So how do we either or both make more of these happen, but also change the storyline? And I'm not gonna call on people. So you just speak up please. I can start, this is Priya. And maybe what I can offer is that without that initial setting of expectations, trust, respect and clear goals of the common collaboration, I think it's very hard to even define success. So I think one thing I have noted is that when we're not clear in our contracts about exactly what we're attempting to do, then the story is lost and there's dissatisfaction on both sides. So I do think that that's important. The other aspect that was mentioned is absolute and total clarity on publication strategy, timing and intellectual property because these have huge impacts both to industry and academia. And we need to be very vigilant and trusting and transparent. So I think transparency and trust to me can set the stage but currently we may be suffering from some of the maybe not so great stories being out there in the public that are driving the dialogue. I do think there's a lot of success but I think that the ones that get the attention are the negative stories. And so I do think we need to turn that tide and trust and transparency is the only way to drive it forward. Maybe I can build on I think Priya's excellent points which I think is a super important baseline but maybe there's a thought also to redefine what productivity actually looks like we internally did an analysis on how many tangible targets and molecules actually enter the pipeline or progress to the pipeline out of academic collaborations. Now that number wasn't large. So if you look at that the productivity might have been seen as low but out of many of the collaborations have we gotten joint publications we have grown our network we've really deepened the understanding of the biology and the technology we were working on. And I think to Priya's point if we don't see that as a success also in industry then of course we might be disappointed. So that's number one. The other piece I think is important is the element of time. To work on fundamental biology some process that it might take years, decades until some of those things as IRNA, MRNA actually turn into something that the world sees as useful. And often we have moved on then in that space and forgotten sort of the founding academic contributions at that time. So I think it's really to pause maybe and redefine and be very clear about that. Also publications, understanding of biology is a product and a valuable product also for us in pharma. So both of you Priya and Marcus you've illustrated something that when you're on one side of the divide do you think if we just had this one magic thing from the other side, everything would be solved. And it's kind of a mutual set of wrong expectations. And I love the idea that you're both talking about is setting out very clear expectations based on experience. I mean, obviously this was new, frankly, not so long ago, but 16, 17 years seems like a long time or 20 years. But I don't know that we have a good formulation of again, how you set expectations in ways that have greater chance. Yeah, go ahead. Just based on what you just said. Yeah. The excellent comments of both Marcus and Priya here. Like so one principle that I, maybe it's wrong to overindex on it, but one principle that does seem to have held to define success to me is the degree to which work is directed. And so there's a spectrum there. I think if work is very undirected like if it's curiosity driven to the extreme, then the government industry interface is often best. And those, sometimes I get worried if those become too applied and too directed and too goal oriented. In industry academia, in academic collaborations where it sometimes fails or falls apart is when there's an attempt to be too far one way or the other. If it's very undirected, then the timeframe for any kind of tangible success might be literally decades. So it might be one of those things where in retrospect you rationalize talent and knowledge being infused into the system. But on any normal measure of success, like within the company, it'll be seen even 10 years out as, oh, it didn't yield anything. So then on the other hand, I've seen it fail also where it's very frustrating to the academic partner if it's so directed that the academic partner feels like a CRO. And that also is bad because there's no movement of knowledge. So I think you have to get it right within this spectrum on the degree of freedom that the investigations or the research has and both sides need to bend a little bit. And then out from that can flow the alignment on the intellectual property and publications, et cetera. But this degree of directiveness, I think it is somewhat relevant. Can I add? Well, just another dimension. I think all the comments are extremely correct in terms of analyzing the inside value of the relationship between the partners. But I think the perception may also be related to a much larger issue which is that there is a not enormous frustration in the American public for the performance of our healthcare system and the fact that we spend twice as much as anybody else and we have the worst statistics. That's really running in people's mind. And then when we say, well, one of the great things we can do for you is work, academia and industry to develop new products and then the products are costing an enormous amount of money which makes the people feel gouged. And then what you understand and what you hear is the public advocacy groups who say, we're being really taken to the cleaners twice. One, we pay all this research with taxpayer funded NIH funds and others and all the benefits and the profits go to the pharma companies. Who by the way are just working on rare diseases and cancer and have forgotten all the major diseases that we suffer from. So I think there is a political policy perception aspect out there that relates to the fact that the deal is wrong between academia and pharma and industry in the eyes of policymakers, Congress is always asking NIH, why is it that you don't get a larger return? After all, it's your inventions that the industry raise and makes profits from that gouges the American public. I think the industry, the pharma industry is right now. The last word, when you have something that doesn't work as complex as healthcare, you need a villain. And I think the villain is pharma and it has become pharma to protect others who may be more responsible actually for the malfunction of the system. So I'd just like to bring that angle in addition to what was really well said by the other speakers. Thanks, Oyes. Phil did I see you? No, I was just trying to make a traditional point. And that was when in striking these relationships, there's two sides to being transparent and able to value. And there are organizations that are basically basic science, curiosity driven, makes new discoveries. And there's organizations that are structured to be more impactful with large data, which is becoming a major issue in how we do science now. And the Brode here at MIT is an example of a letter who has platforms that can do things that are absolutely unique in terms of the scale that you can probe data and gather it and analyze it. So striking these relationships are, it's important that both parties understand the capacity of the other and what drives the nature of the other's activities. Thank you. Sheva Versanje, thoughts on this. Yeah, go ahead, please, Sheva. Well, I was just wondering and recalling my work, there are three or four types of academia and industry partnership. The industry develops something and the academia uses as Professor Sena said, we do the clinical trials. The second is that a academic person discovers a molecule and takes it to the industry rather self-sat or they now have a partnership, which is rather rare. But if it does, it takes huge amount of time to make a large quantity of a protein or maybe convert it into a bio design. It's a huge challenge because there is no facility. But the first one is very easy. The industry does and you do the trial. But if an academic person does, there is no repository, there is no support system and the industry always looks at what will I gain out of it. So there is sometimes a vested kind of motive that whether we should support or we should not and all that. I mean, it's not bad, but for the academic partner, it is challenging. The third is that we could develop something which very rarely occurs. Like in the COVID time, there were things which could be developed by some universities and taken up for vaccine, so code development. But to me, the best model is cohabitation, where cohabitation in the sense that you probably spend time, think, it's an exchange of ideas, which is free. And that is very, very rare. And if you can provide a platform for cohabitation, this probably would be a way of developing things. I recall my days at Yale, we wanted to develop something and the industry guy would come. He would even know what, where is the liver is, but the guy would tell you, look, this is the way you can develop it. And this was an MR guy. So the idea of having a collateral and literal thinking word, to us, it doesn't exist. You go and see patients come back and teach and go to the lab, but there is no incentive. So what I feel, the fourth matter is where the minds can be put together into a soup and churn to get a new product, cohabitation. Thank you. Thank you. Sanjeev, do you want to add in or when you're on mute? I'm sorry. I have one question with panel if you vomit. Please. So my question is how can industry, academia, partnership better collaborate with research and development and innovation by bringing together industry and universities, partners in application and infrastructure, including artificial intelligence for the students and scientists who are planning their future in the industry. Thank you. I have to say, I love that question. And I love that question because what I've seen around the labs at MIT is the faculty are they're interested, they're eager, but their trainees are lunatics. And they are the glue. We think about the hybridizer as some upper level person, but actually the true hybridizer has ended up being these young colleagues. And as I say, I just love this question is how do we bring them into the mix? How do we expose them? Because they are going to be the future on both sides of this divide. But I think so, we only have a few minutes more. And I think that's kind of at the end of the day what I've been directed to elicit from all of you, which is how do we attract the best people? How do we set up this kind of, not permanent cohabitation, but thinking groups, ways to actually share ideas that the unexpected thing that no one has thought of yet is the thing that really comes out that we can act on. And I mean, how do we establish new alliances and territories that are underappreciated? I guess part of this is if you had your dream target, your dream of future success, first of all, what would it be? And what do you see as the pathway? I mean, how do we draw on the talents of our, from my perspective, our academic communities so that we can build the technologies and the drugs of the future a little bit faster than what we've been able to do? Priya, you're nodding. Tell me what's on your mind. Sure. I can get started. I think it's a great question and it's really important as we look to the future. So I'm gonna raise three points. First is that we believe we've got to go where the science is. So we are going global, we've got collaborations with Japanese universities, with Chinese universities across Europe and America and hopefully more than that. And that's important because I think we have to go beyond because there's good science in different places. And as I said, we're going across the chain. So they are experts in different regions. We're trying to tap that. Number one, number two, we believe that we have to go beyond even the science. We have to kind of tap the underprivileged communities. So we are forging alliances with historically black communities as well as universities to really assess what we might be missing to the point that was made. And number three, I think we've got to enroll the future generation. So we are trying to do more postdocs, internships, fellowships, they're short, they're not all very long or doing the resident exchanges. And finally, I think COVID taught us that with the virtual, a lot of amazing science is possible. So while it's always good to have residents come in and postdocs be with us, what can we do virtually? So we're trying to tackle that. Those would be the three thoughts I'd offer. Well, thank you. Can I, yeah. Please try, go ahead. Yeah. Just in response to one aspect of the question around artificial intelligence, data science very broadly, this is an area that within the regulated atmosphere of biopharmaceutical companies 10 years ago, 15 years ago, still new, brand new. And right now it's coming in strong, but the skill sets don't necessarily exist yet. It's all influx, it's all changing. So one, this is, we don't have to think of academic industry collaborations as always. Like, you know, establish a biology research program, a medical research program, sign a contract to it, it can be more organic. Like in the case, I'd like to highlight an example where in the J&J system, where a data science team was built very expertly internally, absolutely key, first advisors, and then eventually collaborators became Dina Katabi and Regina Varsley. And, you know, even though admittedly, like they wouldn't have had the same degree of seasoning, right? With research and development type activities, as extraordinary MIT professors, they were able to, you know, get up that learning curve incredibly fast and broth such freshness to a team that otherwise it couldn't have been had. And now Regina and Phil Sharp work on J-Clinic and that's an entire entity that many of the listeners know well within MIT. And Dina's running a company on a very important measurement around Emerald. These things I think couldn't have necessarily been all anticipated, all the impact on all sides of the equation here, but they can begin organically as well. So again, the emphasis on different approaches, different models, not everyone should try the same thing, I think is important. And you've pointed out the importance of actually just starting the conversation, because again, I mean, I've seen both Dina and Regina and they've been fabulous, but they're students, as I said, are the lunatics. Yeah, exactly. You know, around 100 yards. I'm running. Well, yeah. All right, I think I'm getting the cue that we're running over time. What a surprise. Thank you all for joining me in this really interesting conversation. And I really trust that all of us together will figure out a way to accelerate progress going forward. Sorry, Andy, over to you. Thank you. Not at all, Susan, thank you very much. And thanks for the hope. So let's turn on the polling question so we can get our audience involved and see how the audience reacts to all that great content. All right, good. So if we could please pull up the polling question. And for all of you, please, if you could chime in, academics have improved their ability to perform reproducible research to industry standards. I love that. We're bringing academicians up to industry standards. A, not at all. B, a small amount. C, a large amount. And D, totally. I really like this question and I'm very interested to see where we land. I think we have more of an industry audience than an academic audience, even though it's mixed. So we'll see where the audience takes this question. So great. So we'll have a minute or two to answer that, Paul. Thank you. And before we introduce our next panel, if I could bring up the results of the polling question. Great, so, oh, interesting. Academics have improved their ability to perform reproducible research to industry standards. And actually we're not feeling very confident about the reproducibility of academic research in this panel. We see the majority of people, 60% actually voted only a small amount. So I remind everybody that I don't have the list of participants, but this is predominantly, I would imagine, an industry audience. So it'd be interesting to ask that same question, Susan, to an academic audience.