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Smarter Clinical Research: Interview with Dr. Laura Esserman
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Released: June 13, 2024

John Marshall
John Marshall, MD
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Smarter Clinical Research: Interview with Dr. Laura Esserman

[14:40]
As I just promised you, I have found maybe. the smartest person on the planet about how clinical research has to evolve in order to actually cure cancer. Because remember, that's what we're here to do. And Dr. Laura Esserman is a professor of surgery at the beautiful UCSF out in San Francisco. And for the last while she has built this incredible program around breast cancer research, and now other cancers are starting to follow suit. And she's nice enough to take a bit of a break out of her own clinic day to come and join us and talk about this.

Dr. Esserman, Laura, thank you first for joining, but right away, what the heck happened to clinical research? What happened over the evolution of the last 10, 20 years that's got us in this bad state?

Laura Esserman, MD, MBA: In an effort to try and make it more consistent, I think we took a wrong turn. I have two words to sum it up, misplaced precision. We have two systems, one for clinical research and one for clinical medicine. They're both terrible, and, what we need to do is improve both with one better approach. People say clinical data isn't good enough for research. Really? So, it's really only good enough for patient care?

What is that? Right? You know, who would accept that? There are a certain set of facts that you would not forego if you're taking care of a patient with colon cancer. Same way for me with breast cancer. The surgeons want a little bit more detail on this, and the medical oncologists want a little more detail on this, the radiation oncologists might want something else, but all of us know what it is that we need to collect. We need to get to the business of collecting the right data once. And just having a commitment to high-fidelity, high-quality data as we go. And then you've got all the data you need for clinical research. Now we've got these CROs who are coming in and combing through the data, and they make money every time you find a discrepancy. So, our incentives are completely misaligned to make things better. And everything's gotten so bureaucratic that no one wants to do any of this stuff. This is crazy.

John Marshall, MD: I kept thinking that we become highly paid data entry specialists, right? And even then we don't do it correctly, as you say, and they in the CRO thing. I remember the day when a clinical trial might be $2500, $5000 a patient and you could abstract out from the data, and cooperative groups accepted this, the FDA accepted this, this was good enough. And then this CRO thing came in, and what is it, one-third of the total budget of most trials is this data discipline over top of us that's paid, as you say, to find us making mistakes. If we don't make any mistakes, then they don't have a job.

Laura Esserman, MD, MBA: That model, I think needs to go, I've dispensed with it. And you don't need it. And the thing is, there's already data you can extract. We've developed these tools called OneSource. You can pull the data out. I mean, why, why are we having data coordinators extract lab values from one electronic system to another?

One of the things that isn’t going to break the bank is the patient reported outcomes because the patient's only going to report them once. And we only need them once, and, again, the patient should report what they know best. You don't need the clinician or the study coordinator to report what the patient's going to know. They know if they are having aches and pains. And then, the clinicians should focus on grade three and grade four adverse events, adverse events of special interest, and immune related events. And anything that causes a dose delay, reduction, or discontinuation, and that is it. Are we collecting adverse events so we can report them to the FDA? Okay? Are we collecting information so we can get them to the clinician to manage, improve and minimize toxicity? Again, a complete lack of focus on what matters, what's important to patients.

Imagine if you had a trial where you were constantly learning and evolving and figuring out the best sequence of therapies, trying to learn and manage and optimize the management of toxicities as they arrive. Everyone would want to participate in such a trial. And that's what I-SPY is. That's what we've done. 

John Marshall, MD: you brought it up, the I-SPY, and I have watched you. I was your IRB reviewer here at Georgetown for many years, so I know it well. and as you know, I'm really interested in it for us in the GI cancer space. I think it is a great model for us all to follow. Getting back that control over decision-making, simplifying, expediting; all the things you talk about. So maybe, those of us who know, know, but there are a lot of us who don't know about your solutions for this, and so maybe some highlights of that for our audience.

Laura Esserman, MD, MBA: Let me just sort of give you a quick summary. And again, I think there's plenty of complexity in the trial, but it's focused on clinical decision-making, not on, you know, the nitty gritty detail of every last event.

All disease is heterogeneous. And all of us really know that, and we'll say, oh, well, it's a heterogeneous disease, but then we go ahead and treat everybody the same. That makes no sense. And then people are like, oh, well, you can't do subset analysis. I'm like, okay, fine. So let's start. We started, actually, I started in the cooperative groups, and I left the cooperative groups because they weren't moving at a pace that I felt was appropriate. I mean, the cost of drugs and the cost of development is astronomic because we've allowed it to be so.

John Marshall, MD: And time is a factor in that

Laura Esserman, MD, MBA: Time is a factor, and If you think about it, the person sitting across the table from you does not have 10 years for you to get your act together. So, what we started with first was, let's take the fast-growing, molecularly high risk, stage two, three breast cancers, where we showed in I-SPY 1 in the cooperative groups that, you know, if you could actually start with the therapy first, and you could make that tumor go away, you've got your intact biomarker. By the time you operate, you're getting in the course of care. The important information that tells you what to do next. So, if the tumor's gone away, that is strongly associated with event free survival and distant recurrence free survival, which is what kills people, right? So that with a hazard rate of 0.2, that is an amazing early surrogate marker.

So, your goal should be to try and figure out what are the different disease subtypes? How do you start figuring out what the right drugs are for the right patient at the right time and constantly learn and evolve and improve the algorithm so that you can optimize everybody's chance at getting that good outcome. In the first 10 years of the trial, we studied 23 drugs in control and 10 of the arms graduated. And some of them are on the market today or were superseded by other drugs. We had Taxol (paclitaxel) with a novel therapy, plus or minus any one of a number of therapies, followed by ACE, adriamycin, which is a terribly toxic drug, then followed by surgery. The next person coming into the trial would get the benefit of what we learned from that. That's actually not what patients want. They want to know that they're going to be on a trial that is smart, and that will actually give them some agency and some learning.

At the beginning, we couldn't do that because we didn't have the drugs, but now we're running the trial the way I'd envisioned in the first place, which is three blocks of therapy, three shots on goal. Again, everybody starts with the systemic therapy first. I'm a surgeon. I'd love to be here, but you know what? You know, everybody would love to do much less surgery. I can do less if the tumor is gone but if the tumor isn't gone, my surgery isn't going to fix them. So, you've got to figure out the next drug. I think everyone's like, ‘oh my God, you're putting them at risk.’ You're not putting anybody at risk. I think we've learned that. Right. And that's how you found, you know, in colon cancer to some remarkable treatments for immune drugs in the right patients, but you don't bring them to the wrong patients because they have a lot of side effects. So, the idea is you give them the first set of drugs, but you make that a non-standard chemo. It can be, you know, bispecific antibodies. It can be anybody drug conjugates, you know, any number of things.

John Marshall, MD: What's so crazy about that from most of our traditional thinking is that this is curative. In this neoadjuvant, I mean, think about the old days that it would take 10 years to find an adjuvant therapy because you had to wait forever—you've developed a system where you can change the standard of care within a year or two based on neoadjuvant pathologic complete responses, right?

Laura Esserman, MD, MBA: Right. So, here's the thing, patients care about efficacy and toxicity.

John Marshall, MD: Exactly.

Laura Esserman, MD, MBA: Right? Not just efficacy, you know, and I think a lot of clinicians are like, I just don't want to be blamed for making a mistake. You know,

John Marshall, MD: Regret avoidance,

Laura Esserman, MD, MBA: You’ve got to come up with a strategy that makes people feel comfortable. So, what we did was we've been using MRI and quantitative imaging, not RESIST criteria, that it's like doing some two dimensional thing when you've got really, you know, rich data.

John Marshall, MD: You created a new endpoint of essentially pathologic complete response that ultimately gets regulatory approval, right? So, you changed the rules on, you know, the old established rules that weren't doing us any good.

Laura Esserman, MD, MBA: Right. As you know, we have to let go of some of the rules stuck in our heads because you can't improve without that. The thing is, we need to not be afraid to do some safe experiments. You know, it's true, you might make a decision that you might find that something's wrong. Okay, just set it up in a way that you've got your safeguards built in, but you're giving everybody the chance for benefit. These new drugs, you don't know if they're going to work, but six weeks, no one's going to die in six weeks. And there's a huge upside if they work in avoiding future therapy. And, if by 12 weeks it really works, you can skip the toxic chemotherapy and go to the OR. Same thing for going on to block B. So, you've got some agency in the middle, and we have good algorithms, and we keep working on making them better. If you want these companies to build these new exciting therapies, you've got to give them a place to test them and to do it much more quickly. You know, the whole Silicon Valley, the whole dot tech tech revolution is about systems-based learning and, you know, rapid learning. You know if it's not going to work, learn fast, fail fast. If it's going to work, great, build on that and move on.

John Marshall, MD: You've done it, right? Got it. And the way I think about…

Laura Esserman, MD, MBA: People are following it.

John Marshall, MD: Yeah, we're coming after you.

Laura Esserman, MD, MBA: And now we're working with the FDA on developing a regulatory strategy around it. We haven't finished we haven't gotten there quite yet, but we will.

John Marshall, MD: It really is Innovation and individualization are the two priorities, that you want to make sure that that patient in front of you, their individual tumor characteristics are recognized and optimized, the therapy for them learned from that through innovation. And you bring those two things together and then you create a new way of practicing medicine and cancer.

Laura Esserman, MD, MBA: So, the basis of this new trial is a smart, sequential, multiple, Assignment randomized trials,  

John Marshall, MD: You certainly sold me as a GI oncologist of how we might partner with your team for similar things you have learned. You've already done it. You're doing it with COVID vaccines as well

Laura Esserman, MD, MBA: During the COVID trial, you know, the, one of the agencies that was sponsoring us was concerned. I said, look, we do not need to have, every time there's an adverse event, someone doesn't have to fill out an adverse event report because when people are dying of COVID, they have ARDS, they're dying. They have multi system organ failure. I mean, you could be filling these forms in all day. Here's a checklist of 10 things that happens to every patient. Do it the same on every single patient. It'll take you two minutes. That's a much smarter way of going about it. But they were concerned that we were hiding things or not collecting information. And they made us do this full audit. And you know, we spent six and a half million dollars doing this audit. And we didn't find one adverse event.

John Marshall, MD: You know, you say that that would have bought a kick ass booth at ASCO, six and a half million dollars. That would have been money well spent, is to take that money on your audit and spend it on a fancy booth.

Laura Esserman, MD, MBA: I'm trying, I'm trying to get this published, but, you know, it's going to be very threatening to the industry, but it should. But, to us, it's like we need to take back control of our profession. We need to, like, develop better systems for clinical care that actually help us with research because the goal of clinical medicine, what are we practicing for? We should be practicing to improve, but if you don't know what you're doing, you can't improve it. So that's my story and I'm sticking to it.

John Marshall, MD: I think we should just leave it right there. Dr. Laura Esserman taking a break out of her clinic from UCSF Department of Surgery there and the leader of the I-SPY program, transformative. Dr. Esserman, thank you for joining us.

Laura Esserman, MD, MBA: Oh, you're welcome. Thanks for having me.

John Marshall, MD: I hope everybody enjoyed this episode of Oncology Update. My name is Dr. John Marshall and maybe while you're out there, think a little bit about why is cancer so expensive?