How Will COVID-19 Impact Clinical Trials and Health Care?

You're watching Coronavirus in Context. I'm Dr. John Whyte, chief medical officer at WebMD. At some point, the COVID pandemic will end. But how will it impact and change health care? To help provide some insights, I've asked my good friend, Craig Lipset, to join us. He's the former head of clinical innovation at Pfizer, as well as the founder of Clinical Innovation Partners. Craig, thanks for joining me.

John, it is a pleasure to be here. And thank you for doing this show. It's so important to so many people.

Well, let's get right at it. What do you think are the three most important changes that we'll see in health care, post-COVID? And I'm not going to let you say telehealth, because everyone-- because everyone is saying that.

I would say that the three changes that I expect to see on the other side of the curve, first off, everything in our lives going forward is going to be hybrid. We already see that in our lives today. The spirit of hybrid means we're not necessarily going to rush always back into the clinic. And we're not always going to be staying home.

Yeah.

I think the second area, to me, is around how technology is catalyzing that. And yes, there is the story of telemedicine in video, but I'll double down on, uh-- on a different technology and how digital endpoints and our ability to measure how patients are performing, how they are feeling-- we are doing this today in our clinical trials and clinical research st-- studies in earnest. Leveraging wearables and sensors, applying artificial intelligence and other diverse data so that we can measure things in new ways.

The third area that I would call out, John, is personalization and choice. In clinical research studies today, we're not really patient-centric. We're protocol-centric. Our study protocol defines when you're going to go to a clinic, when you're going to stay home. If Whole Foods operated that way and told me that I had to stay home for delivery on certain months and had to go to the store on others, I wouldn't really consider them, particularly, consumer-centric.

And likewise, I think what we'll start to see on the other side of this curve is more emphasis on giving patients more flexibility and choice.

Well, let's dig a little deeper. You talk about endpoints. How are those endpoints going to change? Because I could argue with you with all these wearables, and sensors, and trackers, we have all this unstructured data, which is very hard to figure out what to do. So how are endpoints going to be different?

You know, John, to your point, the reason we do these studies, clinical trials for new medicine or any research studies, are to measure something, whether it's efficacy or safety. And what we're measuring is powered by the endpoints that we choose. Very often, we're relying on legacy, older endpoints, that we'll call the gold standard. But they often don't deserve to be considered cast in gold.

Give me an example. Is it 81C? Diabetes? What-- what's a--

I think a great example that many have been struggling with this year is something we call the six minute walk test. A six minute walk test requires a patient to get themselves into a clinic, where the investigators who research staff will often place cones in the hallway about 20 meters apart and have the patient walk for six minutes, hence the name.

And in the year of coronavirus, it proved to be very challenging. Patients who would have to leave their home and travel to a site-- sites that very often were closed. But we know that there are better ways to measure this. All too often, that patient who's walking one hour to get to the clinic visit has a smartphone in their pocket. And we know that there is data that they're collecting during that walk that is the same as or better than what we may be able to collect by having them in the clinic.

The investment in these types of new ways to measure are one of the most exciting things that's happening this year and accelerating during coronavirus.

Now, you can't search Craig Lipset and not find this concept of digital twin, which you have been teaching me about, and which I find fascinating. And I want you to explain it to our viewers. In terms of research, what's this concept?

John, the idea of a digital twin actually started outside of research with humans and actually can be traced back to a lot of mechanical engineering and a lot of other technology applications. When you look at an airplane or a car today, there are so many sensors on those machines that technicians are able to essentially reproduce that machine on their computers.

Now, if we apply that to humans, and we think about all of the diverse data that you, and I, and all of us are creating every day-- now, when we're in a position to have that type of rich data about an individual, just like with a car or an airplane, we can start to realize the potential of creating a digital twin of me-- a way to have, in your computer code and in your information databases, almost the same embodiment of me physiologically, biologically, that you would have if I were sitting right there, in front of you.

Let's-- let's be real practical, Craig, to explain it to viewers. I can look at your pharmacy data, and I can follow you over time, even digitally, prospectively. And I can use you as a control group, perhaps your digital twin. You've been one to say, do I need informed consent for that? How is that going to change, post-COVID?

Well, I think you're absolutely right. One of the most exciting use cases for a digital twin in research is the idea that you could use my data to replace the burden of having to enroll a person as a control in a clinical trial. Now, most of us know this jargon, a randomized controlled trial. But what that often means is that half of the patients being enrolled are not getting the active new drug. They're getting a control. But that's not very motivating for patients. Why would they choose to participate in a trial if there's a 50% chance of getting the control? Plus, for researchers, it costs a lot of money and creates a lot of overhead to enroll patients just to be in an arm of the study where they're not even getting the new medicine.

And through this idea that you're sharing around digital twins-- and how can you use my data to create a synthetic control arm? Now, I think what's important here is we're living in a world where our data can sometimes travel outside of our span of control. It sometimes can start to wander beyond what we can see. And that, I think, will be a flaw for researchers. I think the opportunity here is to make sure we're including patients, we're engaging them and getting their permission.

Well, that's the key point, that we have to have permission of persons before we really utilize that data. I'm going to give you a multiple choice question. You didn't know it was a quiz today.

Bring it on.

So in terms of clinical trials, post-COVID, are they going to be A, faster, B, cheaper, C, more diverse-- there's no D, all of the above. Which is-- I know. Which is going to be most important, post-COVID?

I'm going to rank order as A, faster, C, more diverse, and then B, cheaper. And the reason being that we're already seeing, in the year 2020, just how much faster we can go. I believe that there are executives inside of pharmaceutical companies that, for years, believed that there had to be a faster way to develop medicines with greater urgency.

Everybody wants faster. But how are--

Everybody wants faster. But we're suddenly seeing that just by removing some of the bureaucracy in governance, without compromising on the science, we can get things going faster. And look at just how much faster the vaccine trials for COVID--

But they're not necessarily more diverse. So how--

And that's why diversity was sort of second on my list.

OK.

I think diversity in our research studies does not come easy. And it is not-- there is no one silver bullet that will just magically overcome the barriers, and the obstacles, the culture, the concern, the fears that have been placed, rightfully so, disenfranchising some communities. For us to fix that, it's going to require a longer term commitment to change. And sometimes, people lose that momentum and lose that focus.

But I think we will be fooling ourselves if we think we could just fix it quickly and then move on to the next problem.

Well, how is po-- the post-COVID world going to look, in terms of clinical trials?

I think they're going to look a lot more flexible. They'll continue to be increasing use of digital in those studies. We're going to see that development organizations realize that they can move with greater speed than ever they imagined. And how does it look when we start to take that same urgency and apply it to Alzheimer's or other catastrophic diseases without meaningful options for patients?

Diversity-- I believe that organizations are working on longer term plays, whether it is how can we improve diverse investigators and drive more, um, access points for patients in diverse communities. How when we're engaging with patients for input and how we design our studies, can we make sure we're including diverse patients, right up front? Because if the input we're getting to design our studies doesn't come from diverse patients, why would we expect it to result in anything different on the back-end?

But I do fear that some of that diversity momentum-- it could wane. Because it takes that long term change that people might start to feel there is another problem that gets their attention.

Well, Craig, I want to thank you for sharing your insights. I want to thank you for always promoting innovation and engaging patients, whether it's in clinical care or clinical trials. And we're going to check in with you to-- to see how your predictions have gone.

John, thank you for keeping us all informed.

And I want to thank you for watching Coronavirus in Context.