Ep. 5 WILD TIMES IN NASH-VILLE: PART 1

Clinical trial results that are changing how we look at NASH
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Stephen Harrison leads a review of two recent Phase 3 data statements: the outcome of GenFit’s RESOLVE-IT trial and Madrigal Pharmaceuticals’ recent press release on the extension of its MAESTRO Phase 3 NASH trial. Listen to a thoughtful, far-reaching sometimes funny conversation as the group explores WILD TIMES IN NASH-VILLE – PART 1.


Drug developers, investors, researchers and corporate executives wrestle weekly to understand what is happening in commercial development of NASH medications. Join hepatology researcher and key opinion leader, Stephen Harrison, C-SUITE veteran, Peter Traber, and forecasting and pricing guru, Roger Green, as they discuss the issues affecting the evolving NASH market from their own unique perspectives on this week’s edition of Surfing the NASH Tsunami.


 

Roger Green: This is Roger Green, and welcome to episode five of Surfing the NASH Tsunami. This is a revised opening, because the session did not go entirely as planned. Initially, we intended to talk about seven drug trials that have had data or information released in the last two months. However, we got so excited about the topic, we only actually covered the first two. So if somebody says something about, when you hear all this data, you’ll be excited, or mentioned a study and said we’ll come back to that and we never did, I suggest you join us in two weeks when we cover the other five, and you will then be as excited and overwhelmed as we are when we think about the data that we’re going to be talking about. Okay, now on with episode five. Our panelists KOL, Steven Harrison, C-SUITE veteran, Peter Traber and patient advocate, Louise Campbell start by discussing one professional success each had during the week. Louise will go first.

Louise Campbell: Thank you. My professional success this week was the positive feedback we got last week for bringing the patient’s perspective to the clinical trial form.

Roger Green: Okay, I will note that at 9:15 last week, the hour after it dropped, I got my first thank you from another patient advocate for bringing a patient perspective to it. And I got a couple more over the course of the week Louise, I think you’re right. That worked out really well. Next, Peter.

Peter Traber: Yeah, I’ve been trying to think of one that kind of combines some hopeful outlook in this time of pandemic. I’m working with a particular company where we got very rapid FDA feedback and approval on a phase three clinical trial. And we just got that word within the last week of approval to move forward with the phase three trial. And I think in addition to good news for the company, it also indicates that the FDA is working during this challenging time of pandemic and getting back to sponsors. That was good news.

Roger Green: That’s great, Peter. Thank you very much. So Stephen, now that you have heard your first good news of the week, what else would you like to add?

Stephen Harrison: I was blown away by the CymaBay press release and the conference call that happened this week where literally, CymaBay did not give up on Seladelpar. The data were, I would say confusing, in that the report that came out about these atypical findings that led to a clinical hold and stopping of the phase three PBC trials as well as the phase two B NASH trial were a little head scratching. And the independent review team that was put together to review all those biopsies were just phenomenal. Just an all Star cast of characters. And we’ll talk about that in a minute. But at the end of the day, the fact that there was no clinical biochemical or histopathologic drug induced liver injury signal, DILI signal, and a recommendation to lift the clinical hold by this independent external committee.

Stephen Harrison: Now, obviously, it has to be brought before the FDA, the regulators have to make their own decision, but I can’t imagine the regulatory authorities going against the advice of this literally Avengers group of people. I mean, you’re talking Dave Kleiner, Zack Goodman, Pierre Bedossa, Neil Kaplowitz, Willis Maddrey, Paul Watkins, Mike Charlton, John Vierling. These are all icons in the field of liver disease, and they unanimously came to that decision. So I think it’s a huge win potentially for our patients, as well as for the field. And we’ll talk about that more in a minute. But to me, that was a personal win, because I’m the PI on the NASH study there. And I think also just for the field and for our patients in general.

Roger Green: Thank you, Steven. So I’ve got two professional comments, one of which is a good thing. And one of which is just an interesting artifact, that will transition into the client question or the listener question we’re going to address this week. The interesting comment is that this week, I’ve read Stephen’s comments in more press releases than I’ve spoken to him on the phone, the score is three to two, which seems to demonstrate how busy he’s been. And Stephen, I can’t imagine what this week has been for you. Happily, I don’t have to.

Stephen Harrison: It’s been fun. I mean, it’s been fun, but incredibly busy, for sure. For me, this is as a career, a pinnacle moment, to be able to participate in so many opportunities, to find helpful treatments for our patients and advance the field. And there will always be winners and those that don’t quite make it. That’s part of the business for sure. But I think when you step back and we finish this podcast, I hope the takeaway message is a very positive one. And one that reflects the advances that are rapidly occurring in this field.

Roger Green: Yeah, I think we all share the optimism, based on the totality of what we’re going to be talking about, I think that’s right. My second professional good thing of the week is actually about this podcast. As of today, we go on air with listeners in at least 15 countries on five continents, which is amazing. And I want to thank everybody who’s joined us. [inaudible 00:05:22] just listen to subscribers in 15 countries on five continents. And in the past week, three executives and pharmaceutical companies reached out through the Surfing NASH question site to tell us how much they liked and appreciated the value of this podcast for the entire community. Comments we’ve been getting from patients, but had not gotten from executives before this week.

Roger Green: I’m going to read one of the comments and it comes with a question. And that will be our question for the week and then we’re going to dive into a lot of content. The person who sent this question works for a top five global pharma manufacturer. Comment was, first of all, love this podcast. Please let the panel know that we are grateful for it. It really fills a void in the industry. I’m glad they went with a real opening and music is just really well done. So Frank gets a shout out as well as the rest of us.

Roger Green: Okay, now here’s the question. How would a person know to be tested for fatty liver disease or NASH? If and forgive me if I’m wrong, NASH fatty liver doesn’t show any signs or symptoms of its presence.

Stephen Harrison: This is Stephen. That is the $60,000 question. That’s the problem. The problem is this is an asymptomatic disease for the most part, minus the 10% or so that have intermittent right upper quadrant pain and we can speculate on why that is. My own thought is, as fat enters the liver, it stretches Glisson’s capsule, that shiny saran wrap that wraps around the liver. That’s where the nerves are. So it’s a little bit like the meninges to the brain. I mean, the nerves are not in the brain, they’re in the meninges. And so when you get an inflammation of the meninges, we call it meningitis. When you get an inflammation of the liver capsule, that hurts. We strip that capsule off incidentally for liver transplantation. But beyond that, most people don’t have symptoms.

Stephen Harrison: In fact, we just published a paper. If you look at the Medicare, Medicaid and payer data, most people that present with advanced liver disease, in fact, decompensating cirrhosis to the emergency room. So if that’s the case, how do we alert patients to this disease and to whether or not they could be at risk or have it even? So one of the areas we focused our efforts on over the past several years is looking at risk factors, risk factors that could point to an increasing probability of having fatty liver. And I’m going to take a shameless plug for my prevalence study that we finished up a couple years back, and I’m happy to say we are in the final weeks of writing that primary data and submitting it to New England Journal, hoping that they’ll take it. I mean, one thing I learned a long time ago from my awesome mentors was if you put it in a very good journal, they won’t take it if you don’t submit it.

Stephen Harrison: So we’re going to aim high. We’re going for New England Journal on this one. But essentially it’s an 800 patient trial. 664 people were ultimately enrolled and underwent all the MRI testing that we included in the baseline characteristics. And what we found was 35% of the population has fatty liver. And this is in Texas, mean age of about 56. We broke it down and any one of these people that had fat, they had fibrosis, they had abnormal ALT, whatever, we offered a liver biopsy. They didn’t have to have it, they could turn it down. Some did, for sure. But about 250 some odd people underwent liver biopsy. So we were able to determine not only the prevalence of fatty liver by the gold standard PDFF, but were also able to determine the prevalence of NASH. And we used 664 as the denominator, and so the overall prevalence of NASH was around 14%. Which becomes important when we get to the second part of this conversation and we start talking about drug development. And the sheer numbers and volume of people that have fatty liver.

Stephen Harrison: But to answer the question for today, we looked at demographics. We looked at clinical variables. We looked at things that could tell us who was likely to have fat and who was likely to have bad fatty liver. And clearly the diabetics standout. Obesity stands out. Hispanic ethnicity stands out. Believe it or not, hypertension stands out. Hyperlipidemia, not so much. But the combination of obesity, diabetes, Hispanic in postmenopausal female, that combination, that singular group of characteristics gives you a 90% chance of having fatty liver and a 46% chance of having NASH. If you said, “That’s too complicated Doc, break it down.” Diabetes alone, two thirds of the patients have fatty liver and about 40% of them have NASH. So you can begin to think about risk factors, even if you’re asymptomatic, no symptoms. If you’re a diabetic, if you’re overweight or obese, you have hypertension, the more of those you put together, the higher the probability is that not only you have fat, but you have an inflamed fat, that you have fatty hepatitis, you have NASH. That has a risk of progressing attached with it.

Stephen Harrison: ALT and AST, not that helpful. 50% of the time you have bad disease and normal liver enzymes, 50% of the time of the time you have elevated liver enzymes, and just a little fat in your liver. So I would say, if you listen to this podcast, and you have risk factors for fatty liver, to go to your doctor and ask, “Hey, I want you to wake me up for fatty liver. And don’t just stop with an ultrasound that shows fatty liver, I want you to do some sort of stratification to tell me if I’m in the at risk category. Meaning, do I have a risk for NASH? And if I do, I need you to figure out if I have NASH.” And we’ve gotten some pretty good non invasive tests, blood tests that you can do to help determine that. It’s not as great as a liver biopsy. In some cases, a liver biopsy may be warranted or needed, but I think you start with looking at your risk factors, the ones I mentioned today, and then ask your doctor, “What can we do next?”

Roger Green: Thanks, Steven. Go ahead, Peter.

Peter Traber: Outstanding answer, Stephen. And I would just add a couple of things for the audience. First of all, in medicine, it’s not so rare to have a situation where you’ve got an asymptomatic but important disease. I mean, let’s just think about it. Hypertension is asymptomatic for most of one’s life. Even diabetes is asymptomatic until it gets more severe. Hypercholesterolemia, hypertriglyceridemia. There are a lot of things that are asymptomatic that we get tested for now, because there is a simple, straightforward, inexpensive point of care test for those things. And I think that what we really need and we probably have all the potential for putting together that type of test now, where we can identify the risk factors as Stephen has stated. Which would increase the prevalence of the disease in that population of risk factors. And then have a simple, straightforward test that could be done initially to give you a likelihood of having fatty liver disease and/or NASH.

Peter Traber: I think that we’re on the brink of being close to that, but we need a larger number of studies focused on that. I know that Louise has been very interested in screening for patients with NASH, and maybe she has some comments on that as well.

Louise Campbell: Thank you Peter. Yeah, I’d like to echo what Stephen was saying about comorbid conditions and yourself. I think one of the problems that we have, and the British Liver Trust did a very good piece of research and collated a lot of data in the UK and they’re one of our prime charities. But only one out of four patients with liver disease actually gets diagnosed in a primary care area. That’s even with a lot of those patients with comorbid symptoms within those practices, we could argue, maybe we need to do the screening. We need to screen for liver disease in primary care. And I would potentially argue we need to do it in everyone. Because diabetes, heart disease, liver disease is three or some of the biggest spends that the NHS spend or societal spends with alcohol. And I think GPs aren’t aware of fatty liver disease as part of the same study. 78% of GPs did not know, or felt there was no referral pathway to patients with liver disease. So I think it is not a high profile, despite a high spend for all of these practices.

Louise Campbell: And I think when we talk about all of the comorbid conditions, and looking at trying therefore to screen those who have most of these conditions, we’re looking at COVID-19 reading article, after article, after article linking all of those comorbid metabolic conditions, and not one article has really nailed down whether or not any of them are being assessed for NAFLD and NASH. And I think it is important to screen for NAFLD and NASH. But it’s important to screen the population for one of the biggest growing killers, which is liver disease. And we will find NAFLD, NASH and other diseases that people are being exposed to or have hopefully, in a timeline that gives us an opportunity to manage them better and well. And [inaudible 00:14:23], when would be the right time, with childhood obesity growing and therefore early onset diabetes, pre-diabetes and cardiovascular disease in that cohort, I’d probably start screening with fiber scan, initially, everybody from the age of 50 and up, to look at those risk factors.

Louise Campbell: That’s a big ask, but we may prevent an awful lot of diabetes, heart disease and liver disease, if we find it early enough as part of the screening program. So that was my comment for screening. And in relation to the actual question, I would say, reverse the question. Who shouldn’t we be screening for fatty liver disease? It’s got a worldwide prevalence of 24 to 25%. So who should we not be screening?

Roger Green: Thanks Louise, as I was listening to you-

Stephen Harrison: It sounds like pandemic.

Louise Campbell: It does.

Roger Green: One could argue that if you get COVID-19 and fatty liver disease together, you have a exponential pandemic. Which is why people with fatty liver disease might be at higher risk than others, might actually be, to some degree, conceivably, the central unifying theme behind all the other metabolic factors. We can’t get at that yet, because we can’t prove it. But one can suspect it. The stat geek in me Stephen, listened to your numbers and said that 46% with the four risk factors you mentioned had NASH, 40% just on diabetes. I hear that rightly or wrongly as suggesting that, if I know that you have diabetes, I can figure out whether you have NASH, I need the other things to help me figure out whether you have fatty liver disease. And maybe a little more about NASH. Am I interpreting that right, or are those fundamentally independent metrics?

Stephen Harrison: Oh, remember, these are big numbers we’re talking about. I think on an individual basis, each one of those have independently been linked to NASH. So it is additive, but just having obesity, your BMI is 40, so a little bit of hypertension in there. Most of these people are all pre diabetic anyway. I mean, even if they haven’t crossed that magic 126 fasting glucose level times two that gets them to the diagnosis of “diabetes”, their pancreas has been suffering for 10 years. Their beta cells have been making up for elevated glucose for a long, long time, pumping out excessive amounts of insulin to make the brain happy. It’s just a matter of when the beta cells go on strike and your glucose shoots through the roof. And you’re A1C is greater than six and a half. I mean, at the end of the day, you don’t have to be a diabetic to have NASH for sure. But you almost invariably have to have insulin resistance.

Stephen Harrison: Now, there’s some data that suggested a minority of people do not have insulin resistance and still have NASH. But if you’re just taking all comers, just lump insulin resistance right on in there. So any of those risk factors, even if you don’t have all of them, independently puts you in that high risk category.

Roger Green: Thanks, Stephen. That rounds it out, I think quite nicely. One more comment of mine, which is a spoiler alert. We’ve mentioned the importance of being able to screen everybody, not this week, not next week, but some time in the next few weeks, we will start a conversation about diagnostics and diagnostic tools, and what has to happen for them to be good enough and well accepted enough that we can start to do that. Well, thank you, everybody. I think that was a remarkably complete answer. And since the person who asked was from a major pharma company, I’m hoping that that person will be able to make use of all that information and the rest of our listeners will understand themselves or the patients they treat or the issues they resolve better as a result. Thanks to all three of you. Now, let’s jump into our discussion for the day.

Roger Green: In the last several weeks. There have been eight press releases or study releases coming from different drug development companies about studies reaching pivotal points. Two phase threes, I think it’s three phase two Bs and three phase two As. What we’re going to do today is ask Stephen to review the group by what phase study was completed? We’ll talk about it a little bit, and then we’ll go on to the next phase. And after that, we’ll have wrap up questions. So Stephen, why don’t you kick us off with the phase three studies that you want to talk about?

Stephen Harrison: Yeah, sure. So just to echo those initial comments, I don’t think I’ve ever been around a disease that has had this much activity this quickly, at least in the field of liver disease. I mean, when Hep C was coming along, we were getting hit left and right with some pretty impressive data. And it wasn’t all positive, but it quickly moves the field forward. I would say these eight different reports that have come out since February, many of which have come out just in the past two weeks is amazing. It’s a different story than it was last year. 2019 will go down as the year where there was just a lot of unfortunate data reporting out. And I think we all looked at 2020 to say, maybe the new year would give us a new hope. And I would say that’s definitely the case. A mentor of mine used to show a slide on drug development, he’d show all this hope and promise with all these mechanisms of action being studied. And then the next slide would be the graveyard where a lot of those went to die.

Stephen Harrison: And with any drug development, you’re going to have winners and losers. And NASH is no different. It’s the multi hit disease, multi pathway disease. And so we’re targeting different aspects of those pathways. And what I’ve said from day one, long before this podcast started, was the higher up in that pathway that you can affect a positive impact or change, the greater the probability that you’re going to have an impact on the histopathology that we really are looking for to show that we’ve resolved or improved or mitigated this disease.

Stephen Harrison: I’m going to start with the phase threes, then go to phase two Bs, and then the two As. And what I’d like to do is just give a top line, my thoughts on the data, and then we’ll kind of break and discuss that. But I think two important points need to be made, particularly for listeners who don’t understand the nuances of drug development in NASH. The first is, how do you get approval? Well, we have this opportunity in NASH, where the agency has said, we will give you what’s called subpart H approval. That’s conditional approval for your drug, at which point you can go and you can sell it. However, it’s conditional approval, you still have to show me that the drug changes how a patient feels, functions and survives. Basically, you need long term outcome data.

Stephen Harrison: So there’s always two parts to these phase threes. There’s the initial part that gets you that conditional approval, and then there’s an ongoing arm that continues out for many years afterwards, looking at a certain number of adjudicated events of your drug compared to placebo, to show that it actually has a positive impact. So we’ll talk mainly about the phase threes in reference to that. Now, that endpoint is a histopathologic endpoint, meaning you have to do a liver biopsy, which means you have to have one at the beginning, you have to have one at the end of a certain period of time, predefined in the protocol, approved by the FDA. And you have to meet these histological endpoints.

Stephen Harrison: Right now, there are two ways to get approval. One is NASH resolution. NASH resolution is not defined by a pathologist like in clinical practice, where he or she puts the slid into the microscope and says, “There’s no NASH here.” Or, “Yeah, there’s NASH there. And in fact, it is this severe.” That’s not the way drug development is done. The FDA came up with a very finite set of criteria that define the way we say NASH is present or absent. And that’s using the state called the NAFLD activity score. And to show that NASH is no longer present by the Agency Regulatory Authority guidelines, you have to have no ballooning, which is a marker of a hepatocellular cellular injury, you have to have zero or mild inflammation, this is lobular inflammation. And it doesn’t even matter how much steatosis is present.

Stephen Harrison: So that defining NASH resolution. It’s not looking under the microscope and doing a gestalt, hey there’s NASH there, or there’s not there. And that has become an issue in some of the studies because, a good friend of mine Quintin [Anstey 00:22:31] says it this way, “You know a tree is a tree just because you can look at the tree and you know it’s a tree or not a tree.” We don’t look at the tree and say there are 30,000 leaves, they’re green. They’re in the shape of whatever. And there’s bark on the side of the tree. It’s Brown, it stands straight up and has branches. And so therefore, it must be a tree. We just instinctively know it’s a tree or it’s not a tree. So that’s kind of the way the gestalt diagnosis of NASH is.

Stephen Harrison: A pathologist can look at a slide and tell you right away, or with just a few little twists of the microscope, if it’s NASH or it’s not NASH, generally speaking. Now, there’re some other nuances to that. And that is the disease is heterogeneous, and it’s not always the same in every slice of liver that we look at. But for the scope of this presentation, let’s assume it is. And then there’s the more nuanced version, which is trying to apply these structured ordinal criteria to meeting the definition. And I say all that because you’re going to hear us talk about some differences in some of these study reports, that make people want to say, “What’s really going on here?” And the biggest one is the placebo response rate. It’s all over the map. It’s between seven to gosh, upwards of 15, 16% in some cases. And it makes it challenging for companies to sit down and do drug development when they try to power a study and there’s such a wide variance in the placebo response.

Stephen Harrison: And so that’s something that we’re going to probably discuss a bit later in this call. When we talk about the phase twos, you can’t get to phase three without some histology, at least currently, you can’t. And so that’s what phase two Bs are all about. They’re about doing paired liver biopsies to get a signal on which dose might be most appropriate to take into phase three. And they’re also gathering more safety data to build their overall robust safety database. And phase two A is really proof of concept. It’s saying, do I have anything here? Yeah, we’re going to get safety. Yeah, we’re going to get tolerability, but we’re also going to try to get a signal non-invasively, that can predict whether or not we’re likely to have a histopathologic response when we go to phase two B. So that is a framework, let’s jump right in.

Stephen Harrison: GenFit pressed their data this week on their phase three trial called the RESOLVE-IT study. Now this study is a very large study. What they’re reporting is that initial subpart H data that read out in 1,070 patients, huge trial, multi-centered, multinational, multiple continent trial. And they had about 717 people that actually took Elafibranor, 120 milligrams a day, and they compared that to the placebo group, which was the delta between 717 and 1,070. Ultimately what they found on their primary endpoint, was that the drug resolved NASH by the definition, the very prescriptive definition I told you the FDA uses. 19.2% of the time versus 14.3% per placebo, and that was not statistically significant. The other way to get FDA approval I didn’t mention, but I’ll just throw it out there, is improving fibrosis by at least one stage without worsening NASH. So they looked at that as well, and it was 24.5% in the Elafibranor group, and 22.4% in the placebo group. That was not statistically significant. For a key secondary endpoint, for which that was one of them, there was also no change in metabolic parameters, which I found very interesting and completely different than the GOLDEN-505 trial, maybe that’s worth a comment.

Stephen Harrison: But it’s interesting, they did not comment on the gestalt resolution of NASH, that’s just a pathologist. There was only one pathologist in this trial. And they didn’t comment on whether or not just looking at the slide, if he felt NASH resolved or not. And I want to say that’s important, because our only other study to compare to that phase three trial to, is the REGENERATE study, Intercept’s Obeticholic Acid trial. And comparing this to Intercept’s phase three trial on NASH resolution, the placebo response rate was 8% compared to GenFit’s 14.7. And that’s probably worthy of a discussion, looking at the placebo response rate. And then the high dose Obeticholic Acid, 25 milligram arm, 11.7%. So 11.7 versus 8 for REGENERATE, 14.7 versus 19.2 in RESOLVE-IT. Neither one of those were statistically significant.

Stephen Harrison: Switching over to fibrosis, this is where REGENERATE did have an impact. Placebo response rate 12%, high dose drug 25 milligram of OCA was 23.1, and that was statistically significant. But I would make the note here that the 23.1% improvement in fibrosis in the high dose OCA arm, was not different than the 24.4% improvement of fibrosis in the Ela 120 arm, but they hit STAT SIG, they being Intercept, because the placebo response rate was 11.9. So it was 23.1 versus 11.9. Placebo response with GenFit’s drug was 22.4. So the difference of 2.1% was not statistically significant. But this gets to the point of a high placebo response for both NASH resolution and fibrosis improvement. And I think it’s worthy of a discussion there. On the gestalt resolution of NASH, when you look at the data generated by Intercept, there was a statistically significant difference comparing drug to placebo on the overall gestalt resolution of NASH.

Stephen Harrison: So I think those two points are worth the discussion, the placebo response rate for both NASH resolution and fibrosis improvement different between these very large phase three trials. And why is it different, many of the same sites were used to enroll both trials. The study designs were wildly similar, both 72 weeks studies. If you look at the baseline demographics, very similar. Similar amount of diabetics, similar amount of stage threes. There was a difference in the NAFLD activity score only in those that were greater than or equal to six. It was 56% for GenFit and 70% for REGENERATE. Meaning that REGENERATE had more people that had significant activity in their liver than RESOLVE-IT, and maybe that has something to do with the placebo response rate. So I know we want to have a little discussion about that. GenFit went on to say in their press release that they are engaging with the agency and the regulators to determine the next steps regarding the extension phase evaluating outcome data.

Stephen Harrison: Remember this study goes on. And so the question comes up, do you continue the study and look for long term outcome? And that becomes important, because if you buy into the fact that really the only reason that drug didn’t hit STAT SIG, was because of the high placebo response rate, maybe we need to dive into the liver biopsies a little bit more, using artificial intelligence. Whether that’s HistoIndex or Path AI or some sort of not ordinal scale, but more of a fully quantitative scale. Take the human eyeball out of it, and let’s see what the computer shows. Because if the computer lends this notion that there actually is a benefit, then maybe there is a reason to continue the trial to outcomes. I would say also there’s a difference in the female/male ratio; it’s flipped. In REGENERATE 60% were female, RESOLVE-IT 60% were male. We’ll come back to that. I just briefly want to hit on the Madrigal phase three data and then we’ll open it up for discussion.

Stephen Harrison: Madrigal press release date on April 14th. It seems like a year ago, April 14, with all the pandemic, all the COVID-19 News, it seems like it was just eons ago. But it wasn’t, it was about three weeks ago. As you know, Madrigal’s currently enrolling two phase three trials. And they had submitted a couple abstracts to EASL, which is a big liver meeting in Europe set to be in London in mid April. And that didn’t happen. So they went ahead and pressed their abstracts to the public. And a couple highlights from those, liver fat decrease at three months by PDFF predicted NASH resolution and fibrosis improvement. 80 and 100 milligram doses in their extension trial, if you remember back to their phase two B data, 60 milligrams was the majority of the dose that was used. However, a couple people did get 80 and a few got 100. And then they did an extension study for another nine months where everybody that met a pre determined criteria went on and got the real drug. And it was either 80 or 100 milligrams, not 60.

Stephen Harrison: And what they found there when they looked at this, is that 50 to 60% decreases in liver fat content were seen with these higher doses. Remember it was about 39% for the 60 milligram, and it went up to 50 and 60% relative liver fat reduction with the higher doses. And when you go back and reanalyze the phase two data, if you were able to achieve that, what I call super responder level of a 50% drop in PDFF, it actually predicted 64% NASH resolution, among whom 60% had fibrosis improvement. So that was one piece of press data. And I think that’s really important, because what that tells me is, maybe we can use at least for Resmetirom, we have a non-invasive marker that can help us as an efficacy endpoint. Meaning once you start a patient on a drug, treat them for a bit, get an MRI, and if you haven’t had that magic reduction in PDFF, you’re probably not responding to the drug. But if you are, I can predict your probability of response and what that’s likely to be.

Stephen Harrison: Now, obviously more data needs to be done there, but that’s the initial take anyway. We also looked at markers of fibrosis deposition, or net collagen deposition. And in patients with NASH resolution, what we were seeing is an improvement in PRO-C3, particularly. And there’s one last point I want to make there. And then it appears PRO-C3 might be correlating not only with collagen, but also ballooning degeneration, or this hepatocellular injury, which is quite interesting. And then finally, in patients that have NASH resolution, let’s flip it around. Let’s don’t use PDFF to predict NASH resolution, but let’s look at those that have had NASH resolution, the mean decrease in PDFF was 56% relative. So if you had NASH resolution, 56% was the mean decrease in liver fat content at 12 weeks. The optimal cutoff for PDFF decrease is 41.5 with an [inaudible 00:32:56] of .89.

Stephen Harrison: So here you’re saying if you achieve this 41.5% drop, that’s the optimal sensitivity and specificity for predicting a response, is still pathological. So with that I want to stop, pause, give everybody a chance to weigh in on what they think relative to these two studies. One more comment on Madrigal, they’re still enrolling both phase three trials. So this isn’t a report of histology at subpart H time point, this is just some looks at glimpses, deeper glimpses into the phase two and looking at some of the extension data from the phase two to begin to pull some non-invasive predictors together. So I’ll pause there and see what you guys have to say.

Peter Traber: Thanks, Stephen, this is Peter. I’ll make a couple of comments. Excellent summary. First of all, for the GenFit data on RESOLVE-IT, certainly disappointing to the field. We have been used to having some disappointments over the last few years, but I would say this is a disappointment for patients and for the field. I think that it was pretty clear that they missed their endpoint. Although there was a bit of a trend in the primary endpoint, certainly the endpoint on fibrosis was clearly no trend. The fact is that one of the things we have to think about also in terms of all these different clinical trials is the mechanism of action of the drugs that we’re looking at. And I’m going to come back to that with a comment at the end, maybe during the rest of the discussion. But you have to ask yourself, what does this mean for the PPAR agonists and the other ones coming down the line. Just like you can think about FXR agonists with Obeticholic Acid and Intercept’s results. The very important point you raised about placebo rate or NASH resolution in particular, which was the primary endpoint in the RESOLVE IT trial, is an important one.

Peter Traber: I mean, Madrigal’s placebo rate was about 6%, Obeticholic Acid was about 8%, and the placebo rate in the GenFit trial was 14.7%. So nearly double. And yet the inclusion exclusion criteria were very similar. I think all the issues you raised need to be looked at very carefully; male, female, balance, et cetera, to try and see what some of the baseline differences might have been. I will point out, however, that another trial that we’ll talk about later, the Semaglutide trial, the placebo rate for NASH resolution was 17%. Though it’s not completely off of the charts that the placebo rate would be in this range of 14.7%. Now, I have to be honest, that when we start talking about shifts in placebo rate, it is very important that it’s doubly important when you’re dealing with drugs that have very modest effects on your disease.

Peter Traber: Let’s face it, if there was a 50% response rate, this difference in placebo wouldn’t have made any difference. And so I think that highlights that with the two phase three trials that we now have read out, we’re seeing pretty modest effects on the primary endpoints. And when you have that situation, even small changes in your placebo rate can change a trial from positive to negative. So I think that even though the placebo rate was high, it is disappointing that the response rate was so low. And we’re going to talk about other drugs where the response rate is higher. The other thing that I want to mention, is the whole mechanism of action. PPAR agonists come in three primary flavors: alpha, delta and gamma receptor agonists. And if you look at the field, there are all kinds of receptor agonist combinations, pan PPARs with Lanifibranor, Seladelpar which is a delta specific, Elafibranor which is an alpha delta, Pioglitazone which has been studied in the past, all of these different receptor agonists have a very complex biology.

Peter Traber: It is difficult to sort out all the different effects that may be important. So when we talk about the PPAR field, we can’t paint an overall blanket with just saying, “Well, it’s a PPAR agonist.” You have to also look at the specific subgroups of receptors that it binds to. But I do think that this study paints a bit of a [pail 00:37:32] on the PPAR mechanism as well as the marginal results of previous trials with Pioglitazone and other PPAR agonists. So whereas the positive results with the FXR agonists, with Obeticholic Acid, kind of spurred the industry on to look at other FXR agonists, I think in this case, it lends a little bit of a [pail 00:37:56] to the mechanism of action of PPAR agonists. So those are some of my thoughts, Stephen.

Stephen Harrison: I think those were excellent points. The caveat about Novo’s placebo response rate we’ll get to when we talk about two Bs, but I’ll just make this overarching comment. Anytime you only give me three or four sentences in a paragraph buried in your quarterly report, I can’t make any inferences on what that is or what that isn’t. The comment was 59% on NASH resolution versus 17% for placebo, and the 0.4 milligram dosing arm with a safety profile consistent with observed profile, other trials and disease areas. I have no idea what to make of that. There’s no comment on fibrosis. What I’ve learned about press releases, is to pay attention to what they don’t tell you. And what they don’t tell me is anything really about fibrosis, and they really don’t tell me anything about tolerability, side effect profile, AE profile, did they take the medicine appropriately, were there drug holidays? All that I think are questions. And I get it, I think they’re trying to save that for Congress to present that orally on stage or whatever, or maybe for the paper. And maybe if you’re a big pharma, you don’t have to divulge a lot of that information in a press release. But we’ll get to that in a minute.

Stephen Harrison: The other thing I would say is when we talk about the mechanism of action of PPAR’s, Peter, you alluded to FXRs. And remember, all FXRs are not created equal. They have different scaffoldings, different chemical structures, some are bile acids, some are non-bile acids, some are intestinal, et cetera. And I think what we learned from that mechanism, was also it’s important to know the binding affinity and sustained binding versus transient binding. And I wonder if some of that is applicable in this field with the PPARs as well. And we’ll also talk about the CymaBay data, I mean, what’s buried in the fact that the conversation is all about this independent committee. What’s buried is their press release that shows the drug actually had a pretty significant dose response on NASH resolution and fibrosis improvement, with a pure PPAR delta.

Roger Green: Next, Peter.

Peter Traber: The other thing I would point out is that we are now seeing a pattern in NASH development, which is not uncommon from other types of development, where all the animal data looks very good. The biomarkers look pretty good in phase one, phase two, A and two B, give everyone confidence to go into phase three. And then phase three doesn’t look as good or fails. And we’re seeing that over and over again. And I think that should make us examine how we think about mechanisms of action based on animal models and early clinical trials.

Roger Green: Okay, Louise, why don’t you go ahead.

Louise Campbell: I have a couple of comments on top of what the guys have been saying. Unlike a lot of studies where we look at chemical reactions and processes of drugs, there is a confounder in that whole studies naturally, and that is the human part of the study, which is the patients. I have never, in my trial experience, seen a placebo arm perform as well as the RESOLVE-IT study. What we do know from patients’ behavior or people’s behavior, is that they would have all been coming to study visits. And primarily, this is the study in people who are overweight, have a degree of reason to lose weight, have regular visits with hospitals. And that confounding factor of attention does very well in any modeling study or behavioral study. The behavior belief model, for example. Where I believe I can make a difference to my health, I engage. We see it in breast screening, we see it in prostate screening, and it’s a compounder when you get to studies where people are getting a benefit by attending appointments and positive feedback, and I wonder whether or not that could be something we’re seeing in that high placebo response.

Louise Campbell: But there’s a positive to that. If you can give me a placebo with very few side effects, that gives me a one stage improvement in my fibrosis score, I’ll take it. From a different perspective, that’s actually not a bad outcome. But moving on to the Resmetirom and Madrigal study, I think from the Hepatitis C study that Stephen alluded to earlier, we love anything that can give us a positive indication of what’s going to happen. It engages people, it keeps them motivated and it really enhances the behavior that they show within studies. Whether that’s changing their diet, whether that’s attending more visits, whether that’s recording more accurately, early predictive values, they’ve been always very helpful in studies. But looking at the mechanism of these drugs may not be the only way that these drugs are either successful or non-successful.

Louise Campbell: Some of this may well be down to the psychological impact and the behavioral impact that patients make when you get to large numbers of studies with such a behavioral disease. And so those are my comments from looking at both of these studies.

Peter Traber: Let me just make a quick comment to Louise’s, Louise, I think that’s a very important factor. And while many diseases have very low placebo rates, those that have behavioral aspects do have higher ones. And one of the areas that I’ve worked in in the past is irritable bowel syndrome. Well, the placebo rates in clinical trials with irritable bowel syndrome are on the order of 25%. In depression trials, the placebo rate is high. So I think you’re onto something in terms of the type of disease, the behavioral aspects and those can be very difficult to control and also very difficult to sort out what is causing them. So I think that’s a very good point.

Stephen Harrison: This is Stephen again, let me just jump in with a couple other thoughts on this. Remember with NASH, it’s not a disease that steadily always marches forward. Over a year period of time, 20% of biopsies are going to get better on their own despite anything. So as somebody that looks at drug development the way I do, one of the things that would be attractive to figure out is, who are these people that are getting better? Let’s say I have a patient that comes in to screen for a trial today. We do a liver biopsy and they have NASH with an NAS of six in stage two fibrosis. What if that patient, just in its natural history, was going through a resolution phase all on its own? And I biopsy the patient a year later, we learned from the [inaudible 00:44:44] that 20% of those people are going to get better. So if you’re unlucky enough to enroll a lot of those people that are in the resolution phase, that’s going to play into the placebo response. It just is.

Stephen Harrison: The other thing is remember, all these trials have a very baseline criteria to get in. And that’s a NAFLD activity score of four or more. So let’s say that patient has an inflammation score of one, a ballooning score of one and a Steatosis score of two, the NAS is four. And you do the repeat liver biopsy a year later, you don’t see any ballooning. So now you have a ballooning score of zero, inflammation score of one, Steatosis at two. By the agency’s criteria, that patient is “cured” of their NASH. Now did they really cure, or did you just happen to miss the ballooned cell? Or was it not there to begin with, and it was just called? And so that makes it very easy for placebo to get to zero or to get cured.

Stephen Harrison: One thing I’ve been a proponent of is increase, in addition to having the standard criteria for natural resolution, you need a two point improvement in the NAFLD activity score. Meaning that if you had that same case, NAFLD activity score four, one point in ballooning, one in inflammation, two in Steatosis, you would have to have a two point improvement in the NAS, meaning that ballooning would have to go to zero and you’d either have to move the Steatosis by one point, or inflammation by one point. Or if ballooning was two, you’d move ballooning down to zero. I think that gives placebo a much harder time in trying to get to NASH resolution. And I think it levels the playing field a bit more.

Stephen Harrison: That’s why I brought up the point about RESOLVE-IT versus REGENERATE, when you look at the NAS of six or more. 56% in RESOLVE-IT, 70% in REGENERATE. So REGENERATE had many more patients who had much more active disease, in theory, making it harder for placebo to get to zero. Imagine a placebo patient that has an NAS of seven or eight, to get to zero, that placebo is going to have to work really, really hard. And so it just makes it harder to do that. I’ll stop there and see if there are any comments before we move to phase two B.

Roger Green: I had three points, one was a simple data point, which was that Stephen went back to the Resmetirom data and talked about 41.5% being the right cut place in terms of specificity and sensitivity. For those who aren’t familiar with the study, if I recall correctly Stephen, both sensitivity and specificity at that level, were somewhere in the low 80s, 81, 82, 83% on both sides, do I have that right?

Stephen Harrison: I’d have to go back and look.

Roger Green: Okay, fine. The point about that for listeners is fundamentally what that means is you could take $100 to Atlantic City or Las Vegas or the gambling location of your choice on a Friday night, you could bet $10 on red or black, get it right 80% of the time, and by Monday, you’d never have to work another day in your life. So that’s not perfect prediction. Perfect would be up in the mid 90s, high 90s. But that’s a really strong ability to improve your assessment of what’s going on. That’s note one. Note number two, we’re talking about shifts in placebo. And Stephen, I’m really fascinated by the whole point about NAFLD scores. But one of the things I’m curious about, when we do marketing research and we’re trying to simulate patient behavior in areas where compliance might be important, we’ve actually gone and done research with doctors about what do you learn in a patient interview that suggests that a patient is less likely to comply?

Roger Green: I’ve got some triggers for that. For example, if the patient tells doctors about side effects they’ve had on previous medications that are either extremely rare and they consistently have extremely rare side effects, or side effects the doctor never heard of, that’s generally a tip off that the patient is likely to be a poor complier. I’m wondering if any of the intake criteria for clinical trials take a look at any of the, not asking people, “Do you comply or not?” They’ll lie, but getting personal narrative in such a way that you can start to predict who a good complier might be. Are we doing anything like that right now? Just curious.

Stephen Harrison: No, that’s a great point. It’s not something that we’re routinely doing.

Roger Green: Okay. Good. Thank you. Point number three. I know that we discriminate strongly between drugs that treat fibrosis versus those that have an impact on NASH score. I’m mindful of the idea that Resmetirom has an impact on both or appears to, I’m mindful of the comment that you made about the phase two B data with Seladelpar, and we’ll get back to that in more detail in two weeks. That it appears to have an impact on both, and some of the other data that we’re going to be reporting out. I wonder whether what we’re likely to learn over time, is that having an impact on one versus the other is merely a signal of weak efficacy. I can’t state that metabolically, as I’ve said before and will say again, my last natural science course was high school biology. But I do know what patterns look like when they come together.

Roger Green: And this is starting to feel to me like it might be a pattern. Not that I’m right. Not that there’s an explanation for it, but it’s just a thought to keep in mind. Does that sound completely off the wall? Or is it possible that that might pan out over time?

Stephen Harrison: No, that’s not off the wall at all. I would say the one caveat there is, if you’re a drug that purely works on fibrosis, you’re not going to have an effect on NASH or on fat reduction. There’s some fascinating drugs that are in early phase development that really are targeting fibrotic pathways directly. As it pertains to fat reduction, to me, I’m a simple guy. When liver wants to heal itself, if I get the insult away from the liver, the liver will resolve the injury on its own. It goes through a wound healing response, it lays down scar that allows it to heal, and then it reabsorbs the scar over time. Hep C, Hep B, autoimmune hepatitis, alcoholic liver disease, you take away the insult, it gets better. To me, if you take away the fat, inflammation will resolve, fibrosis will eventually resolve.

Stephen Harrison: Here’s the issue with PDFF, it measures inert triglyceride content. That triglyceride is not bothering the liver whatsoever. In fact, the liver’s defensive mechanism is to take free fatty acids and convert them to triglycerides and store them so that they don’t bother the liver. Or they burn them through beta oxidation or they repackage them in VLDL and ship them out of the liver, and kick them down the road to somebody else. What may be happening, is that drops in PDFF are really a surrogate for improvement in toxic cholesterol metabolites, like diacylglycerols and ceramides that we just can’t measure with proton density fat fraction. We can measure it with MR spectroscopy, but that’s such a rigorous tool. It takes an incredible amount of expertise to not only perform the exam, but to interpret it, that it’s not applicable widely like PDFF is.

Stephen Harrison: So that may be mechanism-specific, I might say. And I think with Resmetirom we’re seeing that that is a correlatory, non-invasive endpoint that is predictive. And so potentially that’s applicable to other thyroid hormone receptor beta agonists in development. For the PPAR delta, and we’ll get to that next time, with CymaBay and Seladelpar their primary endpoint was not met with PDFF, but they did report out a positive histopathologic benefit, at least clinically, relative to NASH resolution and fibrosis improvement. Showing a disconnect there between PDFF and histology. I think that gets to that point, that PPAR deltas may be working on some of these inert, toxic cholesterol metabolites that we just can’t measure routinely. And has nothing to do with the PDFF and triglyceride content. So that’s a long winded answer to your point, but I think it’s one worth making.

Roger Green: Okay, thank you. So let me ask just one or two quick questions because we’re running towards the end of our session. One is, everybody looking at this disease, from drug development to clinical research investment, wonders what will happen when Obeticholic Acid goes before the FDA committee on June 7th? Is there anything to take out of these two trials that might give us a clue of what will happen or what we should expect or how we would interpret the case they’re going to make?

Peter Traber: It’s a good question for how the results of other trials might affect the commercial outlook or other development aspects and so forth, of Obeticholic Acid. In terms of the NDA filing with the FDA, I think that the FDA is going to look at that package separately, and on the basis of risk benefit, is going to determine whether or not to approve that drug. And in large part, the FDA’s assessment is going to be independent of any results from Elafibranor or any other drug out there at this point. So the challenges that Obeticholic Acid is going to have is the risk benefit. There’s clearly a benefit shown in these subpart H endpoint on fibrosis.

Peter Traber: And then there are some risks that are associated with it in terms of increase in LDL cholesterol, some side effects such as pruritus, and they’re going to look at that risk benefit ratio and decide whether or not to approve the drug. Which I think will likely get approved. And then the discussion will start with, what are the most appropriate patients? How do we target them, and how do commercial payers and governments look at the risk benefit ratio? That’s my assessment, and I don’t think that the RESOLVE-IT trial will likely have an impact on that.

Stephen Harrison: I think that’s probably true. I would just say that I think there has been a bit of a paradigm shift within the agencies thinking, and again, I may be reading way more into this than there is, but when it comes to liver biopsy interpretation. There’s just been more and more data coming out about some of the challenges with interpreting liver biopsies relative to NASH, the Kappa statistics that exist particularly with inter reader variability. And just remember that REGENERATE was read by two different pathologists and they didn’t all read all of the paired liver biopsies. My understanding, and I may be wrong, but my understanding is that they split half of them, half read a group, and the other half were read by the other guy.

Stephen Harrison: Then they just put the data together. Which in light of some of the new findings that CymaBay has shown, in light of some of the data that Siri has put together with intra and intra related statistics, Kappa statistics showing differences in the same biopsy being read by different pathologists, this committee that’s going to meet on June the ninth may take a look at that, and there may be some more looks at that data. I may be completely wrong.

Stephen Harrison: I want to end with this point that Peter made, which I think is really important. The point was, if the drug is knocking it out of the ballpark, if you have a drug that’s knocking the socks off NASH and fibrosis, you can have a noisy placebo response, and it won’t matter. You’re gonna hit statistical significance, clinical significance, every which way significance it’s going to be good. However, if you have a drug that’s marginal, placebo response rate can become a major problem in your drug development. And my point here is that the liver biopsies are noisy instruments. Baseline liver biopsies, follow up liver biopsies, very noisy for lots of reasons.

Stephen Harrison: You may not have a big enough sample, the disease is very heterogeneous, you’re looking for these obtuse balloon cells, which sometimes are hard to find. They’re not always classical. Sometimes they’re non classical. These are words that the pathologists will use, a little bit harder to find and identify. And pathologists don’t always agree on what’s a balloon cell versus not, but yet it’s critical for the diagnosis of NASH. So there’s a lot of noise, a lot of noise in these biopsies. And you’re trying to find the signal of your drug. I’m just saying all this to say, it’s a noisy endpoint. And I think the first drug across the finish line, OCA, is going to give us hope, it’s going to give us something to offer our patients. I think it will be approved.

Stephen Harrison: But it’s the first step. It’s the first step in a building block. As we begin to build the cure for this disease, we have to start somewhere. It’s not the end point. It’s not going to be what we use as a singular agent. Two, three, five years from now, we’re going to be at combination therapy. There’ll be a different backbone agent that we use. But it’s a start, and I’ll get off my soapbox.

Roger Green: Soapbox, well addressed. One comment, then one from Louise, and then I want to wrap up. For those who don’t do numbers in their head, if you took those numbers that Stephen gave that were 23 for OCA and 24 for Elafibranor, and you increase them both by 20 points, so they’re 43 and 44, both results are significant. And that was Peter’s excellent point about placebo response mattering only when there is not a strong marker of efficacy. That precisely are the numbers that prove that. Louise, go.

Louise Campbell: My comment was fairly quick, it was really to echo Stephen and Peter. And the fact that it is hope, with OCA being approved, if that’s what the FDA decide later on, then people and patients have hope that we will get stronger and stronger agents, and we will get combination therapy. And I think it means they still have to work on their own positive strategies. But hoping this feels good, and there are more coming behind, even at a distance.

Roger Green: Okay, thanks, Louise. So let me go around on the last question, which is the one thing you heard today that surprised you most, or something you hadn’t thought about before? And Louise, let me start with you.

Louise Campbell: The thing that surprised me most was really, how close the differences are that make a trial successful at phase three, and unsuccessful given Stephen’s data between… Or Elafibranor and Obeticholic Acid, so that was the thing that surprised me, how close the margins are [inaudible 00:58:09].

Roger Green: Okay, Stephen.

Stephen Harrison: I would just echo that. Not a surprise, by the time we got to the podcast, when I was putting all this data together, that struck me. Face value, it struck me. I mean, the numbers aren’t that different. One gets to go to FDUFA date, and one is looked at as a failed study. So I just want that to sink in. That’s pretty dramatic, I think.

Roger Green: Certainly for investors. And I think for everybody else as well. Peter, go ahead.

Peter Traber: One of the things that doesn’t necessarily surprise me, but it does in a way, that is that if you recall the phase two study that set up the phase three RESOLVE-IT study, which was the golden study, there was a big issue with placebo response in that study. They had to sort out both the way they did the analysis of the biopsies as well as the various sites, in order to really show an effect that compelled them to go forward into phase three. And that’s all fine, because phase twos are really to get enough data and enough confidence to go into a phase three. But now we end up with a phase three trial, which as by the standard, has failed, and we’re back talking about the same thing. Where the placebo response was higher. Well, it was part of the issue in the phase two golden trial.

Peter Traber: And I think if we look at the history of NASH clinical development, there is a recurring theme of not extracting all the necessary information from phase two trials to adequately design phase three trials to be successful. And we’ve seen that with [inaudible 00:59:51] and we’ve seen it with others. That’s a continued issue, I think in the NASH field that we need to think about how we extract the best information from our phase two trials, to both determine whether we should go into phase three and also the design of those phase three trials.

Roger Green: Thanks, Peter. That’s a really great and thoughtful answer. We all appreciate it. I want to come at this from a different direction. We’ve spent most of this podcast talking about what went wrong with Elafibranor, not surprisingly, and about the medicines immediately ahead of us, which as Stephen pointed out, OCA may be a starting point, it’s definitely not a final point. But what struck me today is we might be closer than we’re thinking. Peter made the comment a couple of weeks ago, which we all bought off on, that until you get a drug that can address fibrosis and the hepatitis, in 50% or more of patients, you don’t really have a platform for treating. But the way I understand the data that Stephen presented for Resmetirom, if you go to the higher doses in the extended release memo, 50% is not an unrealistic goal, or an unrealistic expectation either.

Roger Green: I’m sorry, maybe it’s a little bit high, but the way I’m doing the numbers in my head, it seems perfectly realistic to hope for that. And that would say that we might be just a couple of years away from really being able to treat this disease. With medication that we have some confidence in, that will succeed a lot more often than not. Before we stop the podcast guys, tell me if you think that… Stephen, is that a realistic expectation?

Stephen Harrison: Yeah, I think so.

Peter Traber: Yeah, I agree. And the other the other aspect, Roger, as we go to the second part of this, the phase twos, I think we’re going to review drugs that do have higher response rates than either Elafibranor or OCA, and they’re in the midst of phase two trials. And we have phase two trial data. So we can kind of correlate this. What about these new phase two trials that are positive gives us confidence in going into phase three? Or are we going to repeat history? And number two, do the higher response rates for [inaudible 01:01:56] really seeing some robust effects in phase three. I think Resmetirom is one of those, by the way. And we may want to revisit that, because I think that in comparison to OCA or Elafibranor, it looks much more robust.

Roger Green: Okay, so thank you for that. Thank you panel for a really excellent and informative session. I want to let the listeners know that next week, the chair that Louise sat in this week, the figurative chair, will be occupied by Professor Quentin [Anstey 01:02:26] of Newcastle University. And we will be talking about the issue of, what’s in a name, and what do we think this disease should be called at the end of the day anyway. In two weeks, Louise will be back and we’ll be talking about an array of phase two A and two B studies. And if I don’t miss my guess, I’d like to think that in three weeks, we’re going to be talking about issues around diagnostics for the first time, in part, because as Steven pointed out, understanding those issues will have something to do with understanding how the FDA might respond in the OCA Advisory Committee. So I’d like to get that information in front of people first, if we can.

Roger Green: Thank you to Frank Sasso for as usual, excellent work. Thank you to Eric Rounds, the social media master who makes sure that all you people who are listening and all the people who you know, get to know what’s going on and what we’re up to. We look forward to seeing you next week. That’s a wrap. Thanks.


You’ve been listening to Surfing the NASH Tsunami. Send in your questions by filling out our Ask The Panel form (link below), and our panelists will spend the first five minutes of next week’s episode answering your questions.

[Listen to Part 2 – Episode 7 – NASH-VILLE PART 2: Better Days Ahead?]

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