Dr. Don Sheppard: [0:06] I got hooked on two things. I got hooked on seeing how you could reverse this type of pandemic, but I also got hooked on the power of innovation in medical research where we took a disease that no one had heard of in 1981.

By 1993, we could save lives from it because there was this global effort at the level of people, governments, and at the level of advocacy to drive science forward and bring some solution forward where we could change lives.

Dan Saks: [0:38] This is "Decoding Digital." I'm your host, Daniel Saks. Every episode, we hear from someone who is working to build something new in the digital economy. Each guest has a unique perspective to share. Together, we work to understand or decode a trend that is shaping our digital world.

Announcer: [0:55] People around the globe are fighting a dangerous pandemic, COVID‑19. Even before the virus emerged, infectious diseases were on the march, becoming more resistant to antibiotics and other drugs and threaten the lives of millions of people worldwide.

Dr. Sheppard, our guest on today's show, has been on the front lines of this battle for almost three decades. A doctor and researcher, Don is a world-renowned expert on infectious fungal diseases. He's helped prestigious fellowships at the University of California and has published over 100 research papers today.

He directs the McGill Interdisciplinary Initiative in Infection and Immunity, or MI4 for short, a project that aims to create an ecosystem of experts in medicine, technology, and other fields to fight infections and save lives.

We're honored to hear from someone who's making the discoveries that are helping so many people stay healthy and live longer. Today, Don will discuss the impact of digital transformation on the medical field and speak to innovation that's happening at the frontlines. Let's decode.

Dan: [2:12] Thanks again, Don, for doing this and for being on the show. It's really great to speak with you today.

Dr. Sheppard: [2:16] It's great to be here.

Dan: [2:17] Excellent. The last time we were connecting, the world was quite a different place. You visit us in San Francisco speaking to a group of entrepreneurs and innovators about immunology, innovation, and really the potential threat of infectious diseases on the world. I don't think anyone understood how impactful that potentially could be until 2020 hit. Tell me a little bit about your research and how you evolved to create MI4.

Dr. Sheppard: [2:47] I came into the world of infectious diseases a little bit backwards. I started training in medicine. I trained in the late 1980s and early 1990s. There was a pandemic going on then. Of course, it was the AIDS pandemic.

At the time I trained, it was the battle days of AIDS when we have no drugs, no treatments, young guys that I was seeing every single day were dying of these crazy infections that no one had ever heard of. I got very much addicted to this type of intense medicine, these organisms that no one had ever heard of that were causing disease, taking care of these really sick people.

I thought I was going to be an AIDS doctor. I moved to San Francisco where I started training as an HIV doctor, right when the drugs came on the market. It was the most incredible time in the most incredible city when we converted this death‑sentence disease to a chronic illness like we are now.

I got hooked on two things. I got hooked on seeing how you could reverse this type of pandemic, but I also got hooked on the power of innovation in medical research where we took a disease that no one had heard of in 1981.

By 1993, we could save lives from it because there was this global effort at the level of people, governments, and at the level of advocacy to drive science forward and bring some solution forward where we could change lives.

I really got addicted to that. I went on in infectious diseases, looking at other pandemics other organisms, other outbreaks, and trying to apply what we learned from that to moving forward what we're dealing with now.

Dan: [4:30] Tell me a little bit more about the genesis for MI4 and what the mission is there.

Dr. Sheppard: [4:36] MI4 stands for the McGill Interdisciplinary Initiative in Infection and Immunity. You can see why we call it MI4 because this is only a 45‑minute podcast. Basically, what MI4 was it was an effort to take all of the nodes of excellence of people working in the infectious disease and immunology space, connect them, and reach out to all of the peripheral groups who have their own expertise in allied areas.

Start to look at problems in the infection and immunity arena with different lenses to bring in engineers, to bring in material scientists, social scientists. We've seen the power of social science and how the outbreak has evolved, and to look at things from these multi‑disciplinary teams, to shake things up, get people to work together who never work together, and try and harness the power of innovation through intellectual friction, quite frankly.

Dan: [5:30] Can you share an example of that?

Dr. Sheppard: [5:32] The great example I used was the one that we applied here in the COVID outbreak. Early on, every single country had the same problem. They all wanted to test as many people as possible. None of the countries had capacity.

There was a huge run on buying the ingredients to do testing from the swabs to the plastics, to what was the rarest of all, the enzymes that went in the actual test, these little proteins that did the business of finding the virus.

When South Korea put in their huge test, the entire country strategy, they sucked up the entire world supply of enzymes. Canada, the US Europe, none of us could buy this stuff to do the testing. Our governments would say, "Oh, we're going to roll 10,000 tests by tomorrow. We can do 10,000 swabs," but they sat in the labs because they didn't have the enzymes to test.

We ended up putting together a team of people that had absolutely nothing to do with designing testing. What it was, was a group of scientists who worked on studying enzymes as their day‑to‑day work. They never heard of COVID. They never heard of viral testing.

What they did was they made these types of enzymes on a daily basis because they couldn't do any of their work unless they were really good at making enzymes. They linked up with people who worked in supply chains, with people who worked in clinical testing laboratories.

What they did was they built essentially what is a generic solution to this proprietary problem. They linked with bioresources in federal and provincial governments these large-scale bioreactor companies that make proteins but have no idea how to make tests.

When you link those two together with the testing labs, you made a homemade built by McGill Solution to roll out the enzymes necessary to support testing. Within 30 days, these guys had built, optimized, and delivered on the prototype. By day, 60, they have rolled out enough to test our entire province.

Now, they've built and rolled out enough to test all of Canada and are going to start exporting these protocols worldwide so that every country has a safety net of being able to make their own testing reagents and fixing these global supply chain breaks with homemade solutions. That really was innovation. None of these people knew how to make a COVID test.

Dan: [8:05] Let's decode that because there's a lot there. Culturally, you're bringing together people across different disciplines, industries, educational backgrounds, public private. Did you see a culture clash? How did you align everyone on a vision under such a strict timeline?

Dr. Sheppard: [8:26] It was an extreme challenge. There's absolutely no question. Academics do not have a clue how business works, neither really understood how government agencies work. In Canada, of course, with a single‑payer health care system, we had to try and work around the Leviathan that is our health care system. Nobody understood how to do this.

By leveraging the energy, the frustration, and the pressures that were coming top‑down with the willingness and flexibility to go bottom‑up, that was the magic, that was the secret sauce. If you hadn't had this simultaneous public pressure to, "Oh, my gosh. We need to fix the fact that we're not testing," with a bunch of people that didn't know what the rules were supposed to be, that allowed people to meet in the middle and find ways to do things that were not the way they had been doing them before.

Dan: [9:20] What were some of the communication challenges you encountered in bringing these groups together?

Dr. Sheppard: [9:25] The first and biggest challenge was they didn't speak the same language.

When you start talking about large scale manufacturing companies and making things that are going to be used that have to be precise because you're using them for human medicine, and you compare that with a boutique scientist who's used to essentially cookbook and chef‑like recipes where you add a dish of this and a dab of that to twist it to your own devices, those are two completely different cultures.

They don't even use the same language. They don't understand the priorities of how you take something that you make work perfectly for you into something that can roll out across an entire country and that's going to work the same on Tuesday at four o'clock as it works on Wednesday at three o'clock in Saskatchewan and in California. Those are completely different cultures.

Dan: [10:13] We had recently Eric Ries on the show, who is the author of "Lean Startup" methodology, and talking about agile cycles. To me, this is a perfect example of taking something really quickly, testing it, having a hypothesis, and iterating. What happened in that 60‑day timeframe? Was the first answer the right one, or how did you address the cycles of learning to get to an outcome that could ultimately result in success?

Dr. Sheppard: [10:39] There were a few key elements. We had to identify what the major barriers were right away. As you might guess, the first barrier was simple dollars and cents.

Although the federal government, the provincial government, everybody wants to see this happen, for those gears to move, for funds to get liberated, and pathways to open up that someone could send just the actual dollars necessary to buy the first round ingredients, that was almost three quarters of the 60‑day time period.

That's where our strategic initiative fund from MI4 jumped in and our emergency coronavirus research fund. We paid for the first 60 days of the research just to get it moving. The other thing we learned was the problems on day 1 and the problems on day 60 were not the same. There's two sets of enzymes that are required in this test.

The first set is to pull the RNA out of the virus. When you have a swab, you want to convert that swab into some isolated RNA. The second set of enzymes are the ones that do the test itself. Initially, we were very short on the first set of enzymes, but we had enough of the second. Somewhere around day 30, it pivoted. We had plenty of the first one, and we were short of the second one.

We had to completely shift our emphasis from one set of products to a second, literally halfway through the initial ramp up. What it really took was an iterative process with constant input from the end users who were part of the design process from the beginning. I guess in your world, this is probably something that's much more familiar to you.

In developing tests in medicine and science, end users don't usually come in early in the design process. We have beta testers way out at the end, but nobody really talks about input of end users at the early design stage. That was absolutely critical here, or we would have invested six months in building something that there was absolutely no need for.

Dan: [12:40] This methodology of, for example, identifying and user testing early, is that something that could become pervasive throughout the medical field, or is it more the iterative process that you're uncovering around each problem is unique, we have to bring together different disciplines, and then figure out the right methodology and innovation strategy in that specific case?

Dr. Sheppard: [13:00] It's absolutely necessary for us to be getting end users in much, much earlier. We learned that not only from this project, but some other projects as we started to roll out telemedicine. That's the other big digital innovation that we're seeing here. We've got locked down like many places did for three months.

Our hospital system shut down because all we were dealing with was COVID. We weren't allowed to see patients face to face as physicians. That's when telemedicine was born. It was born out of necessity instead of design.

What we've seen is that it's really being driven by the user experience. The patient experience is driving how telemedicine works. As a result, it's turning into a much better product than had we done it with the classical development of getting companies to launch products and look at them.

We're really seeing that 98 percent of what we thought we wanted in telemedicine is a waste of time, but that there is a huge amount of stuff that's incredibly useful if we listen to the patient population and get a feel for what they want out of medicine. It's being really co‑created between physicians and patients as this moves forward. Of course, it's not just physicians. It's all caregivers. This co‑creation model where you really have early and iterative incorporation of end‑user feedback, it's not new to the world of app design, in the world of computers, I'm sure.

In the world of health care, this is really new. We usually get a completely designed product if it's, for example, an electronic medical record or a telemedicine unit that somebody else somewhere thinks that they have done a perfect job in designing every single possible need we can have. As users, we can't figure out how to turn it on its head to do the one thing we want to. The things that are being developed are really stripped down. They're purpose‑built. They work really well.

Dan: [14:52] Did you wake up one morning and say, "I'm going to apply tech innovation and user experience testing to the medicine"? How did you come about this methodology and method of experimentation?

Dr. Sheppard: [15:04] Absolutely not. I cannot take credit for having had any vision whatsoever. This is simply the use of a disrupter event to make us reassess the way that we're working. There has never been in our recent history as big a disrupter event to the medical profession as the coronavirus pandemic.

Not just because of the impact on the health care system from the illness point of view, but the effects that the shutdown has had and the supply chain shifts have had to make us relook at the way we do our business. There's been a forced integration of industry with the health care system because of these very in‑your‑face supply chain issues.

When you can't get swabs to do the test, suddenly, you realize that you have to pay attention to the way industry works. When you start interacting with them, you realize they have a lot better ways to do things than the way that you have been doing them.

There's a real silver lining to this pandemic in how it's going to be disrupting our processes moving forward in the way that we innovate within the medical profession. There's going to be a lot more public‑private partnerships.

Dan: [16:13] When you think about big data in context to solving the problems that you're focused on, what evolution would you think you'll see due to bigger data sets and bigger computational power?

Dr. Sheppard: [16:25] The interesting thing, I think, and this is where I may be a little bit countercultural, is the failure of big data to really seize the opportunity of the pandemic. Right out of the box, we had this signal, that BlueDot, that company using its AI algorithms, had been the ones that predicted this was going to be a pandemic, had identified the new emergence of the coronavirus.

Everybody saw this incredible potential for AI to really lead how we've managed this outbreak. I would defy you to come up with some superb examples of success since that initial signal. We've had AI algorithms to diagnose the disease. It turns out that most of those are based on looking at CAT scan signals of people's lungs because we don't do CAT scan signals to diagnose coronavirus in the community. The only time you get a CAT scan is if you're sick enough to be admitted and go to the ICU. By then, all those people have been diagnosed anyhow. That turned out to be a bit of a tempest in a teapot.

When we look at our modeling data and our predictions, the AI algorithms haven't really taken over from standardized hardcore modeling. I don't know if that's just because we're in a growth phase and the algorithms haven't had a chance to play with the data and mature enough, or if there really is an issue with the fact that this is such a fast‑moving outbreak, getting the large data sets to the people working with machine learning and AI has had so much of a lag that by the time things come out, the disease has moved on.

It hasn't really lived up to its promise yet, at least. I think there are some important lessons about big data though. We have to look at them from more of a cultural and societal issue. The big data and the data flow and information issues that I think we've seen are ones of access and transparency.

The analogy I like to use is that in the Vietnam War, it was considered a very different war because television brought it to the living room of Americans. They had a personal interaction with the visual and the facts of the Vietnam War at a level that had never been seen before. That changed how society developed its relationship with its perspectives and its opinions about that particular war. I would suggest to you that this pandemic has a similar relationship but with the Internet, social media, and non‑traditional media channels.

You know just as much as I do about the case numbers in the United States today. You are accessing the exact same data I am as a researcher. It's online. You can get it in 30 seconds. Research is now being released in open‑access preprints.

Before, it's even peer reviewed by scientists. People are reading it. It's on the news. Decisions are being made, and it's becoming politicized. We've seen the politicization of data. We've seen the manipulation of data for other agendas. We have this new open‑access society where data is accessible, but I don't think that our critical thinking algorithms or filters have caught up with it.

I think that's something we need to be asking ourselves, how do we deal with this deluge of data? How do we deal with it responsibly in a way that allows us to incorporate it, think about it, recognize its limitations, and move on but without reacting from the hip and creating things like we saw with hydroxychloroquine or the current mask debate?

Dan: [20:10] Let's double‑click on that. People obviously have an abundance of information. This would apply today more than ever due to media, but I think it applies in many sectors beyond just medicine. You talked about the need for critical thinking. How would you break that down, and what framework would you apply to give people the ability to filter information in this world of abundance of misinformation and abundance of media?

Dr. Sheppard: [20:36] It's the biggest challenge I think we're facing, and I would not claim to have any great answers to it. The traditional model has always been that information is filtered through essentially what are key opinion leaders.

Whether those were the mainstream media, whether those were scientific leaders and medical leaders, government, and policy leaders, that's the traditional way of it. For most of our society, we've received our information. You had to wait for it in measured doses where it had been pre‑digested and analyzed. Our parents watch the 6‑o'clock and 11‑o'clock news. That's it. That's all they got during the day. That came to them in a filtered, analyzed, organized, and boxed way, whereas you and I have a 24/7, every minute of the day, unfiltered, unorganized influx of data.

We're not going to be able to rely on this top‑down analytical approach anymore. One of the things we're going to have to do is reform the way we educate people so that it becomes a bottom‑up fundamental. It's not just about learning your ABCs, your 123s. It's about learning your ABCs, 123s, and how to think critically about information that people are giving you every day of your life because this deluge is just going to get better or worse depending on your perspective. There's no sign that we're going to have any other framework to access data.

People are going to have to be able to come up with credibility ratings for the source of the data and understand the limitations and become comfortable with shifting information. One of the biggest things we saw in this outbreak that highlighted is people are not comfortable with a lack of absolutes. People are not comfortable with changes in the data. When the outbreak starts out and people say, "Don't use masks," and then suddenly people say, "No, the science now says do use masks," that fails at a broad scale across the population.

It really fails and we're seeing the fallout from it, but that's reality. Knowledge is not a static thing. Knowledge evolves. We have failed as a society to teach the fundamental principles of how knowledge evolves and how to change your own opinions with new knowledge.

What we have to teach people is to have the willingness to reexamine their own personal frameworks with the understanding that their personal frameworks are allowed to change when data changes. We've created a society where people become so invested in their opinions that any change is incorporated and somehow a personal failure because it's a failure in your own personal mindset.

I think that's a very dangerous way that we've taught people to be. We taught people to be dogmatic. That doesn't allow nimbleness. That doesn't allow you to pivot. That doesn't allow you to say, "This is not working. I need to go at 90 degrees. It's orthogonal time here."

That's one of the things, it's the bias of, "I've launched on this path. I'm going to keep on this path. Even though all the signs are telling me this is the wrong path." There is disruptive discussion about thinking about this, getting rid of these inherent biases, and continuing the same path.

We need to integrate this into our educational system at a much earlier stage. We need to be teaching people how to think. We don't need to teach people how to memorize anymore. The data is so accessible. It's a waste of time. You need to focus on the fundamental precepts of critical thinking.

Dan: [24:02] What do you think is the future of education?

Dr. Sheppard: [24:06] That's exactly what it is. I've seen the change just in the past few years. I have my own children. I have four. They all have worked through the education system, and they're all going off to university now. In the last five years, I've seen a much greater emphasis on critical thinking than memorization than data acquisition than fact. It's coming through in the way they approach the data. They want to know what's going on. They want to know why.

It's not an aggressive why. It's not a, "I'm challenging your opinions because I don't respect you. I don't believe," but they want to be convinced. They can be convinced, and they seem to be more nimble. That at the moment is happening in late secondary school. Those precepts have to be inculcated much earlier in our educational stream. We have a lot more heavy lifting to do in that department, not that I am a early stage educator. Obviously, I'm a university professor, and I teach at a much later level of life.

Dan: [25:08] What impact do you think that training for critical thinking will have on mental health and people's ability to ingest information?

Dr. Sheppard: [25:14] It's going to have a huge effect on mental health. If you think about it, one of the biggest causes of stress, anxiety, and depression is cognitive dissonance. When you have your precept, beliefs, what you want to be true, and what you think should be true, and reality is just constantly telling you that that's wrong, but you can't let go of it because you're too wedded to it, that cognitive dissonance is a huge part of the stress in our lives.

Let's look at the COVID outbreak. You're in your house. You have three small kids running around who are trying to do tele‑learning. You're on a Zoom call at work. One of your kids runs through the room. You feel frustrated. You don't want them to you feel somehow it's unprofessional.

Everybody is in exactly the same boat. How hard is it to release that fact that having a kid run across the background of your Zoom call at work is somehow unprofessional? Even though it does nothing, it actually has no ill effect on anything. It's a concept that we just can't get past, and it causes us undue stress.

So many people have found working at home to be one of the most stressful things that they've ever done because they can't seem to keep that division between real life and work separate enough to be comfortable.

Dan: [26:34] I see. Let's touch on disruption. You mentioned this earlier that disruption accelerated the way people think about innovation when it comes to medicine and public‑private partnerships. How would you just find disruption, and how can you use it as a tool for good innovation?

Dr. Sheppard: [26:56] I'm not an expert in this area. In my mind, a disruptive event is an event that requires you to go outside of your daily channels, your standard working arrangements. That can of course be good or bad if it compromises efficiency, if it compromises your delivery of service.

In the case of the COVID outbreak, when we ran out of masks, when we ran out of our supply chain, when we had too many patients and not enough beds or too many patients and not enough respirators, that's the bad side of disruption. We saw that in many places. Milan is a great example and northern Italy.

The good part, of course, is when it allows us to recognize that there are new pathways that are more effective, that we've ossified in our way, and that many of the processes that we're used to using are inefficient, ineffective, or getting in the way of what we're trying to accomplish. To me, that's the yin and the yang, the good and the bad of disruption. We certainly saw all of this play out with COVID‑19.

Dan: [27:55] You mentioned the advent of telemedicine and that accelerating. Talk to me about the digital transformation of the medical profession. Where do you think we are on that spectrum?

Dr. Sheppard: [28:06] I think the medical profession is well ahead in some areas and quite far behind in others. The access to information, the move to real‑time access to information in the delivery of medical care and the digitization of technology and medicine is well‑advanced. It's very much at the forefront of some areas.

When I see patients, I literally can perform data searches in the medical literature in front of them. When I look at scans, I can get real‑time results and share them with the patients. We can review them together. I can show them their CAT scans. These are all examples of where we're way ahead.

Some of the other places that frankly we've been very far behind are the use of support infrastructure, things like the electronic medical record, which has been the best and worst thing that has ever happened to medicine. The ability now to access all of the patients' medical records digitally instantly is huge.

The way that this is rolled out and the role that it plays in the patient‑physician interaction has been devastating in two ways. One is the physician efficiency and burnout, and the second is the patient‑provider relationships. The current EMRs we use are incredibly unwieldy, slow, and bogged down the efficiency of us doing our daily work.

They've created a situation where we are spending our entire patient interaction staring at a computer screen and ignoring our patients. The caregiver aspect of medicine has fallen by the wayside as we are now dealing with a computer instead of a patient the vast majority of the time. That has been a very difficult thing for many physicians and many patients to deal with.

The other problem is that constant deluge of data, the real‑time access, and the ability of patients to interact with physicians 24/7 has led to burnout wide scale. You can no longer disconnect because the data is coming at you 24 hours a day.

There's always a sense that you're missing something or that you need to deal with it instantly and disconnecting from this digital world when you're dealing with health care. The desire to deliver health care has become a real problem, and work‑life balance has disappeared for many caregivers because we haven't figured out how to deal with this kind of real‑life access issues in our daily lives.

There's a real yin and yang there that we haven't figured out. The place we're behind is telemedicine. That's the new thing. It's ridiculous that we have not done this. I've consulted with many of my colleagues. It's very clear that at least 50 percent of what we do does not require the physical presence of our patients. I need to see you the first time. I need to do a physical exam. I need to make the diagnosis. When I'm going over the results of a lab test that you had last week, and it's completely normal. I know you're completely fine.

I don't need you to come into my office to spend a half an hour traveling, an hour of trying to deal with parking, another half hour waiting to see me, and then rewinding all of that so that I can tell you, "Yeah, you're great, everything's exactly how I need it to be, thanks and it's nice to see you." That's a complete waste of everybody's time.

Now, you can be at home doing whatever you want and wait until your computer chimes. I'll be in there and out of there in 15 minutes, and you had a normal day.

Dan: [31:30] You talked about burnout in the medical profession. We see this applying everywhere in culture. What are strategies that you'd recommend to manage burnout? From your observations of working with different types of people across different industries, do you feel that certain industries are more susceptible to burnout than others?

Dr. Sheppard: [31:48] Burnout is dependent on a couple of factors. One is the type of industry and service you're delivering, how mission‑critical and how time‑sensitive it is. Obviously, medicine is really never going to feel like something that is not a very important time‑sensitive issue.

I'm sure there are certain things like looking at somebody's toenails and wondering whether they have a fungal infection that really could probably wait until Monday from Friday night and no one's going to get stressed about that.

There's always this huge specter of, "Does that symptom relate to something a little more serious than it does?" The test that I've ordered is going to tell me. I really want to make sure that it's not that serious thing, even though it's only a minor chance that it is that makes the majority of what we do seem very critical to us.

The other issue is when does the information come in, the requests, the data, the test results, whatever it is in that particular industry. Again, in medicine, we're getting 24/7 data coming in. The machines that process blood cultures read them all night long and can issue results all night long. Biochemistry results come in in the middle of the night. X‑rays.

It is the kind of thing that doesn't lend itself to nine to five. People don't get sick on a nine‑to‑five schedule. You almost wonder if we really need to be evolving the equivalent to shift work, where there are people who actually have designated windows to cover not the day to day you're seeing your patients, you're doing your visits, but the data that's coming in.

That there's somebody who's designated to cover that during fixed time periods so that you can truly disconnect, because without truly disconnecting, that low‑grade stress, that low‑grade tension just continues to build, and build, and build. We've seen it. We're seeing it across our system.

Dan: [33:36] What products or services do you think should exist that don't today? We have a lot of listeners that are within large organizations, some entrepreneurs. Everyone would be curious to get your perspective on where's the gap.

Dr. Sheppard: [33:49] There's two ways to address these gaps. One is to follow a patient through a hospital or a medical clinic for 24 hours and watch them navigate the system, because I've done that a few times. We were moving to a patient‑centered care model.

I walked with a patient through the entire setup of our infectious disease clinic, from getting into the parking lot to going home, and just track them to see what we needed to do to innovate. The things that we found had nothing to do with anything that as a caregiver would ever occur to me.

Silly things, like the fact that we had set up our doors so that the patients had to open the doors with their hands to get in. If you're running an infectious disease clinic where you're worried about most of your patients being infected or having unusual infections, you probably don't want them all to touch the exact same spot on the door.

It never occurred to us that maybe putting in an automated door in an infectious disease clinic might be a smart thing to do. We're just following that process. I'll give you one request for all of your designers out there.

Why is it not possible for me to carry around a tablet when I am doing my rounds in the hospital? When I walk into a patient's room, that tablet immediately illuminates with all of that patient's EMR data, secured by whatever type of protocol you like, whether it's face recognition, the patient's RFID, etc.

So that, instantly, when I am discussing with that patient, I have two access without 14 logins, three passwords, and a partridge in a pear tree, and leaving the patient's room and finding another computer, all of the data I need to answer the questions that that patient is going to ask me, and the ability to deal with any of the orders and things that I need to do onsite with the person.

That just doesn't exist in any health care system that I have ever been in. Instead, we have to then go and deal with all of it in a separate place in a separate location, and try and remember it all or disrupt our rounds or whatever else. It seems like this should be the easiest thing in the world to design for people that design these type of apps. Yet, that product doesn't exist.

Dan: [36:06] We definitely see the aggregation challenges when it comes to technology and platforms as being one of the harder ones. As products, services, and software matures, APIs are the new way to connect. For those viewers out there that are familiar, there's a good challenge for you for a great opportunity. Would love to get a sense of what resources you listen to, read, watch that really spur your thinking around innovation.

Dr. Sheppard: [36:34] I tried to read scientific literature in the engineering field. Obviously, that's far away from medicine as I can get, but not directly into things like metallurgy.

I find that reading biomedical engineering literature, I find that looking at material sciences in the biomedical space, and then looking at the programming applications in that area to be the ones that really spark the most interest in me because that's where at least the potential for application technology rears its head.

That's where I see things for the first time, and then reaching out to individuals in our own community to see about applying those principles to the problems that we're facing. I find that to be a really rich source of information. Engineers are smart people.

Dan: [37:28] One of our investors talks about how entrepreneurs aren't solving big enough problems. Do you share that sentiment or do you feel that you're exposed to entrepreneurs and people in business that are tackling the right problems?

Dr. Sheppard: [37:42] I guess the perspective there is a very different one, because when you're in medicine, much of the research and innovation that we see in the classic medical fields is incremental. It is not transformative. When we see the transformative stuff that happens outside of the classic medical space applied to medical problems, we're blown away by how big a transformative change that is.

You're absolutely right. If you compare that to the transformative changes we see outside of the medical space, sure, we're not inventing the microwave here. What we are seeing is that in our own innovation space and timeline, the outside medical people are much more transformative than the inside medical people.

Dan: [38:24] We started this discussion with you giving the example of multiple disciplines coming together. What advice would you have to entrepreneurs or people in business out there to best get to know and understand the ways in which they can work and collaborate with the medical community and engineering community to come up with great solutions?

Dr. Sheppard: [38:47] It is a challenge because the way that our health care system is set up both in Canada and the US right now has not left much space for that type of creativity in the health care providers' lifestyle and day. There really is now a regimented every minute counts type of problem.

Recognizing that time limitation and coming up with creative challenges around it is the first and probably most important step. The second is embedding yourself in the problem. We put together these innovation teams at McGill where we bring together people from our business school with teams of surgeons. They go into the OR together to see what the challenges are in the operating room.

The people from the business side, from the entrepreneur side are blown away because in their minds, they had no idea what happened. They can't understand this space without the hands‑on experience. I guess it's just a fancy way of saying get your hands dirty. Get in there. Don't read about it. Go do it, go see it, go shadow, get physically involved, put your hands on it, try it yourself, because then you really see what the limitations are. You really see what the challenges are.

Dan: [40:04] Got it. What advice would you have for young people out there who want to innovate and who want to really make transformational change in the medical community and beyond?

Dr. Sheppard: [40:15] You should not listen to the medical community when they tell you no. That's the first and most important thing, because that's going to be the standard response. Sadly, we are, as I mentioned, less innovative than the entrepreneur community. We need to be pushed as a group to move to the next step.

That is changing. The younger generation of physicians and physician scientists really are open to it. They're the ones that we're seeing developing their own innovative and entrepreneurial solutions. You need to be pushy. You need to be able to push past the, "Oh, no, that's not going to work stage," which is likely going to be the first response you get.

I don't think that that should discourage you. You should be anticipating it and be ready with your, "Thank you for bringing that challenge my attention. Here's how I'm going to deal with it," type of response.

Dan: [41:02] Incredible. Thanks so much for the innovation you've brought to the profession, the inspiration you have for people. I took away so much in terms of just thinking about new innovative ways to iterate and the similarities between solving problems. So appreciative of your time and passion. Thanks for saving lives and really helping to create meaningful change.

Dr. Sheppard: [41:22] Thank you. The best is yet to come.

Dan: [41:27] Today on Decoding Digital, I had the pleasure of sitting down with Dr. Don Sheppard to speak about innovation and immunology. It's fascinating to see the similarities in the way that people approach innovation in the medical profession, engineering professions, and in entrepreneurship around the business world.

What was abundantly clear is that agile innovation methodologies and critical thinking skills are more important than ever to create transformational change. The disruption that's occurring in the world today has a profound impact on the way that we work and innovate, and will drive new business opportunities for next generation of entrepreneurs.

Taking a step back, COVID‑19 has had a significant scientific and economic effects. I wanted to acknowledge the tremendous human impact the pandemic has had on communities around the world. This reality touched the AppDirect community earlier this year when we lost one of our colleagues, Yves Francis.

Yves was an incredible man who was admired by everyone he worked with. We miss him every day. Though our hearts are heavy, we cherish his memory and keep him and his family in our thoughts. As we work to end this pandemic, we encourage everyone to wear a mask, practice social distancing and, above all, take care of yourselves and each other.

Dan: [42:55] On the next episode of Decoding Digital.

Michelle Zatlyn: [42:58] Go find a meaningful problem. If you find a meaningful problem that will impact people, and this goes back to where we started being a doctor, find a meaningful problem where you're solving a problem for somebody. Ask yourself, is there more than one person in the world that has the problem? If the answer is yes, a lot of people do and it is meaningful, then you should go full force and do it.

Dan: [43:19] Co‑founder and COO of Cloudflare, Michelle Zatlyn.

Thanks for listening to Decoding Digital. Make sure you never miss an episode by subscribing to the show in your favorite podcast player.

To learn more, visit decodingdigital.com. Until next time.