2020 National Paediatric Bioethics Conference — Let no good pandemic go to waste

John Massie

Welcome to Essential Ethics and the first of our series of highlights from the 2020 National Children's Bioethics Conference. I'm John Massey, Clinical Director of the Royal Children's Hospital Children's Bioethics Centre. In the first plenary session of the 2020 conference, we were fortunate to be joined by one of the world's leading bioethicists, Professor John Lantos from Mercy Children's Hospital, Kansas City, Missouri. Professor Lantos presented an in-depth and far-ranging lecture about the role of bioethics in the COVID-19 pandemic. In his lecture, entitled Let No Good Pandemic Go to Waste, Prof Lantos highlighted the many opportunities opened up by the pandemic and perhaps a few missed opportunities. Join me now as we listen to Professor John Lantos address our conference.

Dr. John Lantos

But I'd talk a little bit about some of the changes that are coming about as a result of the COVID pandemic and where they might be taking us, what some of the ethical considerations are, both societally and in terms of clinical care and research. The way I'm going to do this, start with some general thoughts and some speculation about how COVID's changing society, how COVID might change lead to fundamental changes in the way we organize health care, transportation, and many other things, and then sort of drill down and focus in on some of the challenges for research ethics and pediatric research ethics in particular. So the title comes from Rahm Emanuel, who, when he was Barack Obama's chief of staff and President Obama had just taken office in the midst of a huge financial crisis. Rahm Emanuel said, you never want to let a serious crisis go to waste. The crisis provides us the opportunity to do things that you could not do before. Crises often shake up the world in ways that nobody foresaw and lead to fundamental realignments. This was something that A famous community organizer, Saul Alinsky, also noted when he was trying to change things like bank lending in

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predominantly African-American communities, he said, in the arena of action, a threat or a crisis becomes almost a precondition to communication, and went on to say communication is what leads to change. So how will COVID-19 change the world? There's been a lot of speculation about the ways that this is leading us to rethink the organization of vast swaths of society. Yuval Noah Harari, best-selling author of two sort of global history of humanity books, Sapiens and Homo Deus, wrote, we could choose to deal with the crisis by imposing totalitarian surveillance regimes or by empowering citizens and ensuring security. greater government transparency. Humanity could decide to rebuild its transport system and

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energy

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sector on much greener foundations or focus on narrow economic recovery. Former Prime Minister of Denmark, Heli Thorning-Schmidt, said, we know what's needed, properly resourced health care, smart and compassionate social security, well-regulated markets where businesses serve societies rather than the other way around. governments and multilateral institutions working together for the common good. But he, like Harari, also asked the question, will we take this opportunity? Will we not let the pandemic go to waste? There are some things we know or anticipate. Human relationships will probably change at least for years or maybe decades, if not forever. The sorts of casual crowding that had been the norm in sports and entertainment or public transportation may never come back, certainly will not come back in the foreseeable future. In doctor-patient relationships, we're seeing more telemedicine and finding that telemedicine is superior to face-to-face interactions in some cases and in many ways. In pediatrics, many parents report that they far prefer to stay at home. They don't have to travel. They don't have to find child care for their other kids. They don't have to expose their kids to risks in waiting rooms, exposure to other kids with infectious diseases. Doctors say that visiting people in their home is a little like making a house call, and they can learn much more. How much telemedicine will stay and how How it will change the world permanently post-COVID, we will have to wait and see. Similarly, for inpatients, the notion of family-centered care, where we have families in the rooms and they participate in rounds, has been a casualty of the pandemic. That seems unfortunate. It would be nice if we could go back to a more family-centered care,

John Massie

but

Dr. John Lantos

we don't know if we will or not. Professional meetings are changing too with advantages and disadvantages. It is sad that I can't be here to deliver this talk in person, but my carbon footprint is much lower. There's much less travel. And in many meetings, the attendance is greater and the participation from people around the world who can visit virtually. increases. So it may be that we find advantages in professional interactions as we do in telemedicine. I give all those as background for the kinds of global changes that may be happening that we are starting to see and can anticipate debates about as things go forward, but want to spend the rest of the talk looking at some of the issues that have arisen as we've started to do research and tried to figure out the epidemiology, the natural history treatments and prevention for COVID-19.

Dr. John Lantos

As you all know, COVID is so new, we don't know very much. How does it spread? How is spread prevented? What is the natural history? How does it differ in different subpopulations by age, race, gender? underlying disease, and then which therapies or combinations of therapies work the best. People have talked about chloroquine, hydroxychloroquine, steroids, immunoglobulin, combinations, antiviral, antibiotics, and ultimately hope that a vaccine will

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ultimately curtail the spread of this terrible disease. Many of these drugs are available Now they're not innovative or unapproved drugs, so there's plenty of off-label use, which raises questions about the best way to capture and analyze data to find out how drugs being used, not as part of a formal research protocol, but based on the clinical judgment of physicians, anecdotal data, retrospective studies, etc., how we can mine that data to better understand what works and what doesn't and figure out when we need prospective randomized trials or when pragmatic trials or the activities of a learning healthcare system can generate the sort of data that will help us better guide treatment. So the question really is how to quickly and effectively do research and do the kind of research that's rigorous enough to give reliable answers, but maybe not quite as

Dr. John Lantos

formal or restricted in its design as to take more time and maybe not give answers that are relevant to the real world.

Dr. John Lantos

As a lumper rather than a splitter, there are two views about how we should do research on COVID. One is, given the crisis, we must do things differently. The other is, no, no, no, we must avoid COVID exceptionalism. Good research is good research, and we have rules for doing that and rules for overseeing it, and we should stick to those rules. Alex John London and Jonathan Kimmelman wrote this paper in Science. against pandemic research exceptionalism, in which they said things like,

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some people suggest that some evidence now, even if flawed, seems preferable to expending greater resources on more demanding studies whose benefits will only materialize later. And these people say, according to London and Kimmelman, we need to balance scientific rigor against speed. And their response is that bad data is worse than no data if we believe it to be good data. And I'll give some examples of how this may have already played out in some of the studies on treatments for COVID. They say key features of rigorous research like randomization or placebo comparators conflict with clinicians' care obligations. Again, this is their perception of what COVID exceptionalists, pandemic exceptionalists are saying. And the response is when clinicians are uncertain, they have an obligation to be honest about uncertainty and figure out ways to do studies to answer important questions. That is not, in my view, COVID exceptionalism. That's what doctors always have an obligation to do or should always have an obligation to do, although they have not always done met that obligation. If

John Massie

you look at

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examples of bad data, they are multiplying very quickly. One of the most striking was a study that appeared in the British journal The Lancet, a study of chloroquine and hydroxychloroquine with or without a macrolide antibiotic for the treatment of COVID-19. This was a multinational registry analysis that is Many hospitals in many countries reported their data into this multinational registry. The registry was run by a for-profit corporation. Researchers then contracted with the corporation to get access to the data and looked retrospectively to see how patients did on a variety of different treatments, including hydroxychloroquine alone with a macrolide, chloroquine alone or chloroquine alone, with a macrolide, and they found that all of these, every combination of chloroquine, hydroxychloroquine, with or without the macrolide, was associated with an increased risk of in-hospital mortality. The control group, that is the group that historically had not received these drugs, had a 9.3% mortality rate, and the groups that got the drugs had mortality rates ranging from 16 to 22%.

Dr. John Lantos

and all of those looking at a hazard ratio were statistically significant. So the authors concluded that using these drugs was dangerous. They also found other factors that were associated with high mortality that I've listed at the bottom here. None of them particularly surprising, although the finding about the drugs was surprising. The only problem with it was it was probably wrong. when peer reviewers or readers of the paper looked at the data, they pointed out some quirky features of the data, like an unbelievable uniformity in the rates of treatment and the rates of mortality at 600 different hospitals around the world, and requested to see the raw data in order to

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check out whether It seemed to be reliable. The company that had the data did not release it, claiming that it would have violated their confidentiality agreements with the hospitals. And based on that, the Lancet retracted the paper within a few days of publication. We still don't know whether chloroquine or hydroxychloroquine are beneficial, harmful, or have no effect on mortality. Similar thing was found in one of the first studies published about remdesivir, an antiviral agent. This was published in the New England Journal and showed on the y-axis the cumulative incidence of clinical improvement in patients who received remdesivir compared to those who didn't. They stratified it by age, but showed that in every age group there was significant improvement problem with this, as was quickly pointed out by some readers, is that their analysis was flawed and somehow in what probably represents a form of COVID exceptionalism, that is hasty peer review in an effort to get important data out to the public more quickly than might have been the case in the absence of a pandemic. The New England Journal

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reviewers, statistical reviewers, missed that the Kaplan-Meier analysis was erroneous. They censored data on the deceased patients at the time of death, a serious methodological error, and when that was corrected, showed that survival rates were much lower with remdesivir, still better, but much lower than had been reported in the initial study. Interestingly, these Corrective analyses were sent to the New England Journal again within days. So although COVID exceptionalism may lead to the publication of flawed data, the publication and open review may offer a remedy for hasty publication. One last example,

Dr. John Lantos

which in some ways is the most amusing example, Can smoking protect against COVID-19? A study supports the claim. This was a meta-analysis of mortality rates in hospitalized patients, 13 observational studies, thousands of patients. And their conclusion was based on the fact that among hospitalized patients, the number of current smokers was much lower than in the general population. And from this association, they suggested a conclusion that maybe smoking protects prevented hospitalization with COVID-19. Again, reviewers quickly pointed out that association is not causation and that this is a common error. Further studies showed that smoking is in fact a risk factor for severe disease. Smokers with COVID have worse outcomes, but it may be, and this is speculation, that people with lung disease are more likely to quit smoking and therefore less likely to be hospitalized with COVID-19.

Dr. John Lantos

In any case, this was published and again quickly debunked. My own view of COVID exceptionalism is that research on COVID highlights problems with the existing system that we have of research oversight and of data generation. And those problems can be described like this. Much clinical practice, not just related to COVID, but across generations. Every domain of clinical practice is not evidence-based. In much clinical practice, there are widespread and idiosyncratic practice variations. These practice variations lead to similar patients being treated differently by different doctors with likely different outcomes, and those outcomes are not well studied. In such situations, we don't know what works best, and usually our uncertainty about what works best is neither acknowledged nor disclosed to patients. Part of the reason is because evidence is expensive. Research is difficult. It's rigorously regulated. It's hard to do the kind of rigorous research that will give answers to specific research questions. And so only a small number of clinical dilemmas are actually rigorously studied in a way that generates the evidence to allow us to have certainty about what works or what doesn't. The problems of doing research on COVID are not new or different from these other problems. It's just because COVID is so dramatic an example of our lack of knowledge, the problems are highlighted and easy to see in stark relief against the background of lack of knowledge. The problems with doing clinical research are the same problems that arise in heart disease or cancer. We have what I consider to be a broken system in which research is considered more risky than it actually is, and non-evidence-based clinical care is considered less risky than it actually is. So the COVID-19 pandemic gives us basic options to reshape what Rob Califf has called the evidence generation ecosystem. And he proposes that we have a fork in the road One is to maybe make some changes to deal with the emergency and then revert back to the good old days. That would be against COVID exceptionalism. The other would be to learn from the innovation that is happening as a result of the crisis to figure out as with, say, telemedicine or as with, say, doing virtual meetings, what works, what doesn't, and maybe implement changes to in the system that will carry forward even after the pandemic has started to wane. So what is the fundamental problem with the current system of regulation? I think it's that

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guidelines make a clear distinction between research and practice that doesn't acknowledge that the boundary between these two activities is actually quite fuzzy. This comes from the Belmont Report to Clinical Practice. The purpose is to provide diagnosis, preventive treatment, or therapy to enhance the well-being of an individual patient with a reasonable expectation of success. Research, by contrast, is an activity designed to test a hypothesis, permit conclusions to be drawn, and thereby develop or contribute to generalizable knowledge. The obligations of the clinician, the moral obligations then, and the moral obligations of the researcher are quite different. The researcher has an obligation to science. The clinician, by this view, has an obligation to the patient. This was a letter from the Office of Human Research Protections to investigators of a study of oxygen therapy for tiny babies. They said a fundamental difference between the obligations of clinicians and those of Researchers exist. Doctors are required, even in the face of uncertainty, to do what they view as best for their patients. Researchers do not have that same obligation. Not everybody who wrote these regulations or pioneered the field of research ethics saw that distinction as clear-cut. Jay Katz, a lawyer and psychoanalyst who taught and wrote for many years at Yale University, and was a pioneer in medical ethics, wrote about this as far back as 1969. And he said, the multiple purposes of medical practice, caring for patients, advancing science, improving the health of community, nations, and future generations cannot be separated clearly. Research and therapy, pursuit of knowledge and treatment are not separate but are intertwined. This was a visionary, almost prophetic statement that anticipated many of the discussions that we're having today about learning healthcare systems and about how the guidelines that were written about a few years after Jay Katz wrote this and have been governing research ever since may be outdated or even obsolete.

Dr. John Lantos

Keith Barrington, who's a neonatologist in Montreal, spoke about this and talked about his fiduciary obligations both as a clinician and a researcher and about how they're intertwined. He said, I have a fiduciary obligation to provide optimal treatment, the clinical practice obligation. I also have a moral obligation to know what the optimal treatment is, that is, to acknowledge when I have uncertainty. And when I do, he went on, I have a moral obligation to keep trying to find out what the best treatments may be, and he speculated about different ways that data generation and analysis could take place to fulfill this moral obligation that he feels as a clinician to do what is best for his patients that leads to a moral obligation to understand and analyze what is in fact best rather than assuming that what he learned in school is necessarily correct. COVID, as I say, highlights these problems. Doctors are treating sick, very sick, dying patients. But at the outset, there's no good research on which to base that treatment. So when doctors are making clinical decisions in this time of radical uncertainty, are they doing research? Are they doing clinical practice? If they treat patients and analyze the results of their treatment to figure out what works best, it's something both in between or overlapping. both domains. So what we're seeing is this warp speed science on different domains, and let me just focus on a couple of these. One is the epidemiology and the risk factors for transmission. The other is treatment and prevention. And finally, I'll talk a little bit about how these issues may play out in studies of vaccines.

Dr. John Lantos

So there are three questions. There are many more, but one could imagine these as crucial to the public health efforts to control the spread. How common is asymptomatic infection? How transmissible is the infection from someone who has no symptoms? And what percentage of the population, attributable fraction of transmission, comes from these people? The answers to these questions have implications for who we screen, who we test for, infection, how we do contact tracing, and who should be quarantined. The problem is it's really hard to get answers to these questions without doing large observational studies. People have started to do that in many different venues where there's been an outbreak, people have been exposed to someone with the disease, so they can be observed and tested and estimates can be made of how many of the people who test positive show symptoms and how many do not. The problem is that the answers are all over the map. They range from about 30 percent to about 90 percent of people who are positive but asymptomatic. Those answers, as wide as the range is in that study, other studies show even a wider range. Some have showed 5% up to 41%, which at this point leads us to the unsatisfying conclusion that somewhere between 5% and 90% of people who get infected are asymptomatic. That may be knowledge, but it's not very helpful knowledge in deciding how to do population screening, testing, or contact tracing and

Dr. John Lantos

Part of the reason is because there's a distinction being drawn between what people have called asymptomatic infections and what people call pre-symptomatic infections. And this got the World Health Organization into trouble when one of their top officials said that asymptomatic people cannot transmit the virus, but pre-symptomatic people can. The problem with the distinction... is that the only way to know who is asymptomatic and who is pre-symptomatic is to see who goes on to develop disease so that at the time someone is asymptomatic, that is, doesn't have symptoms and tests positive, we don't know which category to assign them to. Further research may help with this, but it will have to be through much larger and, I think, more rigorous studies than the sort of small and observational studies that have generated the data that we have so far.

Dr. John Lantos

When you look at what's happening with treatment and prophylactic prevention trials, we see some interesting phenomena in this world of combination of new different ways of doing research and attempts to harness data generated through routine clinical practice. In the United States, the Patient-Centered Outcome Research Institute, or PCORI, launched a study called the HERO study, where the goal of this was to see whether hydroxychloroquine or chloroquine works as prophylaxis for people at high risk for infection. So the goal was to enroll 15,000 healthcare workers or people who are working in healthcare settings and therefore are thought to be at higher risk of disease. randomized them to either chloroquine or placebo, and then see whether the rate of infection in the two groups is similar or whether there's a difference.

Dr. John Lantos

To do this and to do it quickly, they harnessed the PCORnet sites, which have patient registries. People are screened through registries, and then if they are eligible for the study, referred to a local site. randomized and provided a one-month supply of the studied drug. They do web-based check-in with self-reports of symptoms, side effects, and exposure. And then at the end of the study, there are cheek swabs and serum tests to see how many people in each group have, in fact, seroconverted. This would give data both on chloroquine, hydroxychloroquine's efficacy, as well as data on the number of people with symptoms who actually zero convert and have COVID, or the number of people who zero convert have COVID but didn't have symptoms, so that if 15,000 people could in fact be enrolled, this would be a very valuable, pragmatic clinical trial. That is, patients are reporting their own symptoms, taking their own medication. This study illustrates what warp speed science is like.

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ordinarily designing and launching a study like this would take months or even years. In this case, it was first proposed to the PCORI Advisory Committee on March 25th. There was a planning meeting on March 27th. A few days later, the PCORI board approved the protocol. A week later, the IRB approved it. Contracts were signed, and in less than a month from the first meeting to talk about the importance of doing this study, the trial was This is an example of the sort of thing that shows what's possible and may, in fact, be an improvement over current ways of doing things. Another example of warp speed science, a study of chloroquine and hydroxychloroquine for post-exposure prophylaxis, so rather than just recruiting health care workers who were high risk because of the nature of their job, In this study, they enrolled people who were exposed without adequate protective equipment to a patient known to have COVID, and then shortly after the exposure, randomized to either hydroxychloroquine or placebo. There were 820 asymptomatic participants who'd had this sort of exposure, and the outcome was how many got COVID-19 in the hydroxychloroquine group or the placebo group. These were their results in the hydroxychloroquine group. 11.8% had confirmed or probable COVID-19 in the placebo group. 14.3% did. This was not statistically significant, although it is interesting to note that there was a 20% difference between hydroxychloroquine and placebo. And so the conclusion that it didn't prevent COVID-19 when used as prophylaxis may be a true finding, although it may be the result of an underpowered study, and raises the question, what should count as a significant difference? Maybe a 20% reduction is good enough, or at least enough to justify further studies of whether hydroxychloroquine is effective. The HERO study, the 15,000 worker study, had to consider these results in deciding whether to continue the work that they were doing, or whether this sort of data, or for that matter, the data from the Lancet study when it first appeared and was later retracted, whether that should lead to stopping ongoing studies of hydroxychloroquine. In this case, the HERO study decided to continue,

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and those results may be forthcoming soon. Another example of warp speed science, the recovery trial in the UK in which every COVID-19 patient in the country was invited to participate and, if they agreed, randomly assigned to five different arms, illustrated on this slide with the main outcomes being death, discharge, need for ventilation, and need for renal replacement therapy. Patients were given a simple two-page information sheet and a one-page consent form. It illustrated the

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basic outline of the study and the potential risks and benefits. Again, like the HERO study, but even more dramatically, this went from the first draft protocol on March 10th to the first thousand patients being enrolled in just about three weeks. So this can be done. The study has an adaptive design, so if things seem to work, more patients will be assigned to those arms. If things seem not to work, fewer patients will be assigned to those arms. There were data linkage agreements that were worked out over a weekend. These, too, often take weeks or months in the pre-COVID days. The data will be regularly reviewed in an ongoing basis. Effective treatments will be identified and made available to all patients. And the team will constantly review information on new drugs that may be added to the protocol, including investigational drugs that are not currently available. So the trial will be constantly evolving with ongoing data collection, data analysis, and protocol redesign. So conclusions about these sorts of pragmatic trials are the most effective way to quickly get preliminary answers. Like all studies, they raise as many questions. as they answer. And the process shows that we can design and implement studies far more quickly than we have in the past. But the question for the future is whether this will be the new normal or whether these simply represent something we might call crisis standards of care for research that, if you go back to the slide about the fork in the road, we will then revert back to business as usual once the pandemic wanes. The final thing I'm going to talk about is some of the issues that are likely to arise or are starting to arise in the study of vaccines for COVID. There are unique ethical complexities to vaccine studies. You need large numbers of healthy people, particularly ideally people who are at somewhat higher risk than the general population

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of

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exposure and therefore of contracting the disease. There's need for relatively long-term follow-up. You want to see whether the vaccine prevents disease acutely, but also whether it has any lasting immunity. You also want to know whether it has any late side effects. With COVID, there are many, many candidate vaccines working their way through the pipeline. So if each of them is going to need to be tested, In large studies with large numbers of people with long follow-up, that will require an infrastructure to enroll hundreds of thousands of patients in many multiple studies with lots of competition to get to market first and lots of financial rewards for the winner, which creates all sorts of temptations to cut corners scientifically or ethically. One way to speed up the process of vaccine development would be to use what have been called human challenge trials, that is, studies in which you don't just take a population at risk of being exposed to the disease, but instead deliberately expose people to disease. And here's what a hypothetical study design would look like for a human challenge trial. Take volunteers who have never had COVID-19

Dr. John Lantos

Most people propose that they be healthy young people who are at lower risk of certainly mortality, but even complications or symptoms from COVID. Some people have suggested that we should preferentially recruit for these trials people living in areas with high rates of COVID, that is, people who already are at relatively higher risk of being exposed to the disease, so the relative risk of being exposed in the study versus in real life may be higher. lower than people in lower risk settings. There has to be meticulous informed consent about the risks and benefits. The studies would have to take place in special biosafety facilities so that the virus that's being used to deliberately infect them would be contained. They'd be randomized. They'd be challenged with COVID. And it would be a much quicker way to see whether the vaccine works. It would also be a way that deliberately exposed people to the risk of disease. And there's where the ethical controversy lies. There is a history here. When Walter Reed did the first yellow fever studies, people were enrolled and then exposed to mosquitoes. And they had a consent form that said the undersigned understands perfectly well that in the case of development of yellow fever in him, that he endangers his life to a certain extent. And people who agreed were given $100 to enroll, $100 if they got yellow fever, and another $100 to the family if they died. If we just adjusted for inflation, that would probably come to something like $10,000 for each of these. The question is whether compensation mitigates the ethical complexities or whether instead it becomes a source of coercion. There are ethicists on both sides of the debates about the ethical acceptability of human challenge trials. Ruth Macklin says they are not acceptable in COVID and only acceptable if there's an accepted treatment for study participants who develop severe disease. If it's a vaccine to prevent malaria, say, where there's a treatment, then human challenge trials would be ethically acceptable. With COVID, where there is no treatment and where people might get very sick and die, Macklin says these studies should not be done. Jeff Kahn

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shares a similar view to Risky, and he makes the further point that informed consent is not really possible because we don't have the information to know either what the risk is for these people

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because the natural history of the disease is not understood well enough. or what the risks are of the experimental vaccines, and therefore, without informed consent, the studies should not be done. Ferguson and Kaplan say, that's not quite true. We're getting a better understanding of what the risks are. The risks are manageable, and we could explain them in a way that would be adequate, and therefore, people could give informed consent, and people who want to sign up for such studies and who understand the risks should be lauded in their altruism. encouraged. Nir Eyal, a proponent of these trials, points out that the risks of being in the study need to be balanced against the risks to everybody of not quickly developing a vaccine, and that delays in studying vaccines will cost many more lives than even the hypothetical risk of somebody in the study who might die. And therefore, if somebody's willing to take those risks, similar to Ferguson and Kaplan. They should be allowed and the studies should be approved. There's a group called One Day Sooner which has enlisted volunteers who say they would sign up for these studies without compensation. They're just eager to serve humanity by allowing the research to go forward and they're willing to be exposed to the risk. Josh Morrison, who's the founder of that group, has said the risks are comparable to other activities that we permit healthy adults

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and his prime example is kidney donation, particularly kidney donation to a stranger, which used to be prohibited, then got to be tolerated, and now in many medical centers is actually encouraged. Carl Elliott, who's frequently a critic of biomedical research and particularly of its tendency to exploit medical poor and vulnerable people who sign up for dangerous studies in order to get compensation, says, yeah, that's true, but this is an important problem, and there are ways that we could make a vaccine trial, a human challenge trial, ethically acceptable. Its first criteria is no payment, no compensation, only unpaid volunteers, so there's no coercion and no risk for that exploitation of the poor and the vulnerable. But he says we should provide compensation for research related injuries, something that does not happen today in most studies in the United States. Further, he says we should provide lifetime financial support for permanent injuries and presumably for the families of anybody who would die. He says companies doing the studies should guarantee that the vaccine would be priced fairly and made available to everyone who needs it. So the altruism of the volunteers should be matched by a sort of altruism by the companies who make this. That is a promise not to seek the highest possible price, but to seek universal distribution. Study data needs to be made public. A particular concern in the United States is that some volunteers don't have health insurance. So Elliot says that would be a precondition to doing these studies in an ethical manner. And of course he says meticulous attention to informed consent. These seem like good guidelines for doing such studies, and it would be nice to see some of these changes enacted into law. Again, not just for COVID, but as Dr. Elliott himself says in the paper, these are changes in the way we do clinical trials that ought to be applied to all research. studies and should change the way we think about and regulate human subjects research.

Dr. John Lantos

The long term impact that I would like to see come out of this is a change in the way we think about using real world evidence and the way we think about the evidence generating ecosystem, which is a term that I prefer to this distinction between research and practice.

Dr. John Lantos

As I say, I think that distinction is unhelpful and obsolete. Evidence is constantly accumulating, being analyzed, and should change practice. And such activities protect patients and lead to generalizable knowledge in the way that Keith Barrington described his fiduciary obligation to do both activities simultaneously. An analogy that might help, if you think about the distinction between research and practice, the way we used to think about the distinction between a telephone and a computer. There was a time when we knew what a telephone was. Its purpose was to call other people. We knew what a computer was. Its purpose was to manipulate data. Today, our phones are all computers, and our computers are communication devices, and the distinction between the two no longer exists and therefore is irrelevant. In a similar way, I think the distinction between clinical practice and research no longer exists or should not exist, although it still exists as a bright line and a huge barrier in the way we oversee both activities. This is the traditional way compared to the phone and computer. We thought about randomized trials. This is an illustration of the new way of thinking about evidence generation systems where it's... not two arms of a trial, but a circular and iterative process that's constantly

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gathering data, analyzing the data, and changing practice. In a robust learning healthcare system, nothing is purely treatment, nothing purely research, and everything is constantly being analyzed. So the take-home message for this talk would be we don't yet know the answers. We need to keep gathering and analyzing data. that are ongoing in different populations using different methodologies and that are embedded in public health programs and programs for screening and treatment and ultimately in programs for vaccine prevention. These data are then used to inform the design of clinical trials and to decide whether we need pragmatic clinical trials, formal prospective randomized trials, or ongoing analysis of constantly accumulating data. Rob Califf, again, who was former chief of the FDA, now professor at Duke, says here are the essential steps. Evaluate what has and has not worked in the changes made in response to the crisis, and then allocate funding to transition issues and evidence generation at the interface of medicine and public health, and increase purposefulness by creating methods for deciding what are the most important questions, and then rewarding the behavior of that gets answers to those questions quickly, safely, and with respect for the dignity of participants and their rights to know

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what the results show and what is being done with their data. Thank you very much. This is our hospital in Kansas City, Children's Mercy, a beautiful place. I hope to visit Melbourne and I hope that many of you can someday get to Children's Mercy and we can talk about more of these issues at that time. Thanks so much.

John Massie

That was Professor John Lantos opening address at the 2020 National Children's Bioethics Conference. The National Children's Bioethics Conference is brought to you by the Royal Children's Hospital Children's Bioethics Centre. The conference was supported by the generous donations of the Friends of the Children's Bioethics Centre. If you enjoyed the podcast or the conference, please support our work by joining the Friends. The podcast was produced by Creative Services at Royal Children's Hospital. If you would like to know more about the Children's Bioethics Centre or join us in 2021 for our 13th National Children's Bioethics Conference,

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