The Peter Attia Drive - #118 - Lloyd Klickstein, M.D., Ph.D.： Rapamycin, mTOR inhibition, and the biology of aging

00:00:00.000 Hey, everyone. Welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,

00:00:15.480 my website, and my weekly newsletter all focus on the goal of translating the science of longevity

00:00:19.800 into something accessible for everyone. Our goal is to provide the best content in health

00:00:24.600 and wellness, full stop. And we've assembled a great team of analysts to make this happen.

00:00:28.880 If you enjoy this podcast, we've created a membership program that brings you far more

00:00:33.280 in-depth content. If you want to take your knowledge of this space to the next level at

00:00:37.320 the end of this episode, I'll explain what those benefits are. Or if you want to learn more now,

00:00:41.740 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay, here's

00:00:48.080 today's episode. I guess this week is Lloyd Clickstein. Lloyd's the chief scientific officer

00:00:54.420 at RestoreBio. So that's little R-E-S, big T-O-R, little B-I-O. Get it? TOR, T-O-R. RestoreBio is a

00:01:04.100 clinical stage biopharm company that develops meds that are primarily aimed at targeting TOR,

00:01:10.820 targeted rapamycin. We'll talk a lot about that throughout this episode. So prior to joining

00:01:14.460 RestoreBio, Lloyd was the global head of translational medicine for the new indication

00:01:19.580 discovery unit at Novartis. And prior to that, he was an academic physician at the Brigham and

00:01:25.920 Women's Hospital, which is one of the flagship programs at Harvard. Lloyd received his bachelor's

00:01:30.240 from Tufts and an MD-PhD from Harvard. He's got more accolades than you could shake a stick at.

00:01:35.300 So accolades aside, the reason I wanted to speak with Lloyd was because he is really one of the few

00:01:40.640 people on this planet that has a really nuanced understanding of the clinical application of

00:01:46.960 rapamycin and rapalogs. And we talk a lot about one of them in particular called

00:01:51.940 Everolimus. Lloyd was the senior author on a paper that I have spoken about many times on this

00:01:58.300 podcast, which we'll go into in great detail here. December, 2014 paper, Joan Manik was the lead author

00:02:04.500 on that paper. And that was the study that was basically the turning point in my personal evolution

00:02:09.260 or thinking when it came to the use of rapamycin for the purpose of longevity. Prior to that,

00:02:14.820 there had been a lot of studies that had certainly suggested in animal models that rapamycin could be

00:02:20.260 a true longevity agent, but it was the Manik-Clickstein paper of December, 2014, that was the

00:02:26.980 real turning point in my thinking. And that's really where we're going in this discussion, along with

00:02:32.120 talking about all that's been done since then. It is important before we start this interview that

00:02:36.240 I mentioned, of course, that Lloyd is an employee of RestoreBio. RestoreBio is a for-profit company

00:02:41.040 that is working on mTOR inhibition. So please caveat everything that we discuss through that lens.

00:02:47.160 Before this podcast begins, I want to note that we recorded this interview in September, 2019. Now,

00:02:52.860 in the interview, we discussed an upcoming phase three trial from RestoreBio. Since that time,

00:02:57.860 the results have been published and the study did not meet its primary endpoint. Now, I frankly left the

00:03:04.660 option to Lloyd as to whether or not he wanted to still have the podcast air. And he felt that that

00:03:10.660 would be fine to do. And so we're going to go ahead with it. And eventually, I'm going to be

00:03:15.140 interviewing his colleague, Joan Manik, along with Nir Barzil. I'm going to have the two of them back

00:03:21.020 on an episode where we're going to discuss a whole bunch of things that'll be quite interesting.

00:03:24.760 And this gets more complicated because I think I have a pretty clear understanding of why that study

00:03:30.280 failed and what it does and doesn't say about selective inhibition of agents like it. Nevertheless,

00:03:35.800 I think the most logical thing to do is to go ahead and proceed with this interview, which is

00:03:41.740 one of my favorite interviews on this subject matter. And just know that there are going to be

00:03:46.260 a number of things that are left as open-ended questions from this discussion. We're going to

00:03:51.540 pick back up with Joan Manik when we do that interview, which I'm scheduled to do a few weeks

00:03:57.980 from now. And hopefully we'll try to get that one out at a much quicker turnaround. There were a number of

00:04:02.880 issues that delayed the release of this, not the least of which being some of the COVID stuff.

00:04:07.160 But I can promise you that there will be a shorter gap between when you are hearing this and you will

00:04:12.140 hear the follow-up to this than there was between the recording of this and when you're hearing it.

00:04:16.880 And without further delay, please enjoy my conversation with Lloyd Clickstein.

00:04:25.980 Lloyd, thank you so much for making the trip up to San Francisco today. I know you didn't come here

00:04:29.720 specifically to see me, but I appreciate you carving out a little extra time to meet today.

00:04:33.740 I'm happy to be here and looking forward to our talk.

00:04:36.420 I hope the view is enticing enough here.

00:04:38.460 It's lovely.

00:04:40.240 When the weather's nice in San Francisco, there are a few things that compare to it. And when it's not,

00:04:45.040 it's like Mark Twain said, right? The worst winter he ever had was a summer in San Francisco or

00:04:49.160 something like that. You're from Boston, so you laugh at that.

00:04:53.400 Right now, this is the weather we all wish we had in Boston.

00:04:56.280 Yeah. So Tim Wright, one of your colleagues, offered to make this introduction over dinner

00:05:03.040 one night. And there's probably never been in the history of an introduction from the moment

00:05:09.160 the intro was offered until I was sitting down talking to someone on a podcast that was quicker

00:05:12.800 than this one. In other words, I'm sorry to hear that actually.

00:05:16.300 Well, it was just meaning I was so excited when we sat there and it was, so I was with Tim and with

00:05:21.320 DA Wallet, who some folks listening will know because I've interviewed DA on the podcast as well.

00:05:25.640 And we were having this dinner. And as it's always the case when I'm talking with dorky science

00:05:29.860 friends, rapamycin comes up and one thing led to another. And then I'm embarrassed to say this,

00:05:36.440 but the 2014 paper that I talk about constantly, I always refer to it as the manic paper because

00:05:42.200 she's of course the first author, but you're sort of the lead author. You're the final author.

00:05:46.700 You're the senior author on that paper. And so I was embarrassed to say this. I didn't even,

00:05:50.240 when they mentioned your name, I didn't put two and two together.

00:05:52.200 And I didn't know you were at restore bio at the time either. So anyway, they connected us.

00:05:57.540 We communicated over email. The rest is history. We're sitting here today and I am

00:06:00.700 beyond excited. And then this is a topic that I just know listeners are dying to hear about because

00:06:06.420 it's been over a year since I've had a podcast on this topic. So very early in this podcast,

00:06:11.880 which is about a year and a half ago, we had discussions with David Sabatini and with Matt

00:06:16.400 Caberlin, who are both amazing folks and legends in this area as well. So I'm going to discipline

00:06:22.700 myself for a moment before getting right into the Rapa stuff to give a little bit of background.

00:06:27.820 You've got a pretty interesting background. I want to hear a little bit about it. When did you

00:06:31.720 realize this is what you wanted to do, which was be basically physician, scientist, and then

00:06:36.420 ultimately now move into industry?

00:06:37.720 Well, I guess I can begin by stating that science and medicine is the family business.

00:06:45.420 So it wasn't much of a stretch for me to be here doing what I'm doing now, doing what I've done

00:06:51.500 before on both sides of my family, both sides of my kids' family. All of my kids are scientists,

00:06:59.980 doctors are both.

00:07:01.280 So did you do a combined MD-PhD or did you do them separately?

00:07:04.000 I did the combined one. My wife did them separately, actually, the long and expensive way. 0.76

00:07:10.460 Yeah, exactly. At least when you do them together, they pay for each other.

00:07:13.360 Yeah.

00:07:13.920 When did you decide you wanted to focus on immunology,

00:07:16.300 rheumatology? I mean, there's no shortage of things one can specialize in.

00:07:20.360 One of, at least my challenges, and I know the challenge of many physicians and many scientists

00:07:25.440 is that so many things are interesting. How do you focus? And like many things in life,

00:07:31.320 it was about the people, not the science that led me into immunology, rheumatology, and where I am.

00:07:38.300 When I had left college and wasn't sure where I was going to go next, I spent a couple of years

00:07:43.840 working in a laboratory at Brigham and Women's Hospital. I had such an incredible time and met

00:07:49.180 such wonderful people that ultimately my decision was to stay there and work with them,

00:07:54.460 learn from them.

00:07:55.160 What years were you at the Brigham?

00:07:57.220 I worked in a technical capacity from 79 to 81, started medical school in 81, and finished

00:08:05.400 both degrees by 1989, and then stayed there through all of my training, and then left in 2006

00:08:13.980 to join, actually, Tim Wright's department at Novartis Institutes.

00:08:18.720 Hmm. What prompted that decision? And is that a one-way street for most people?

00:08:24.220 There are people who go back and forth, but I think we have to be realistic that it's more

00:08:29.820 challenging to go back to academia if you don't have extant grants and external funding.

00:08:36.120 It has to come from somewhere in most places. In terms of what drove the decision, I'm a physician

00:08:42.020 scientist. For me, it's important to do both, science and medicine. And it's harder and harder

00:08:48.700 to do that now in an academic environment. At least, I'll get in trouble for saying this,

00:08:54.160 but at least a primitive academic environment like Harvard, where you eat what you kill and you have

00:08:59.980 to, at the same time, see patients be at the top of not just your game, but the world's game in

00:09:07.060 seeing patients and administrative and teaching responsibilities and so forth.

00:09:12.120 Well, I mean, let Harvard get upset at you for saying that, but I mean, there's no denying what

00:09:15.920 you're saying is the case. Every, I interview so many people who are straddling that. And I'm

00:09:22.020 constantly amazed. In fact, I was interviewing someone recently, a very remarkable scientist and

00:09:27.100 academic, and I couldn't believe how much clinical obligation he had and yet how prolific he was.

00:09:33.900 It's sort of amazing to me that some folks can actually straddle that. It's certainly not optimal,

00:09:38.160 I guess, is the point.

00:09:39.540 No. And it was much more challenging than I had seen it in the late seventies and early eighties.

00:09:44.380 What changed? Is the reduction in grant, the competitiveness of the grant environment or?

00:09:49.500 No, it wasn't so much the grant environment. It was more the regulation and the paperwork

00:09:54.280 that was imposed mostly on the clinical side. I need to be fair and say I was both running from

00:10:00.080 something and running to something. As a physician scientist, the goal is to have each of them

00:10:06.660 contribute to the other. And translational medicine, which was a new concept around the turn of

00:10:13.620 the millennium, was growing and was perfect for somebody like me. The Vardis Institutes was

00:10:20.280 created by Mark Fishman in the early 2000s as a new concept and a new approach to drug development,

00:10:28.080 thinking about pathway biology. And they were building translational medicine departments and

00:10:33.840 Tim recruited me to lead the musculoskeletal one.

00:10:37.340 So maybe explain to folks the difference between basic science, clinical science or clinical research

00:10:43.960 and translational research, which as you said, the latter there being a relatively recent phenomenon.

00:10:50.040 Lots of examples of basic science. One that's pretty exciting and has led to Nobel prizes is the

00:10:58.320 study of restriction enzymes. Who thought that studying obscure bacteria and how they limit

00:11:06.020 their infection by viruses might have led to the concept of restriction enzymes, which was required

00:11:13.980 for the development of modern molecular biology? Another one of basic science. You've probably talked

00:11:20.460 about CRISPR technology here. We haven't had a dedicated podcast to it and I'd love to get Jennifer on to do so,

00:11:26.520 but please continue. Yeah, that's a great example. I'll give you a one minute summary. It is another

00:11:32.060 critical element of the bacterial immune system. It's simple, it's elegant, it's powerful. And there

00:11:42.380 were scientists in Europe studying fermentation for yogurt and cheese. And they discovered CRISPR,

00:11:50.060 Jennifer Doudna, and colleagues here, MIT, and the Broad Institute. And they were studying basic science.

00:11:58.560 They were studying bacterial biology. And it became so exciting when somebody translated the biochemistry,

00:12:07.600 if you will, and the bacteria to see would it work in humans. Who would have thought that would work?

00:12:12.800 Bacterial chromatin in the DNA is so different. It's supercoiled in a bacterial cell, whereas

00:12:20.100 human DNA is organized into chromatin and methylated, but it did. So the point here is

00:12:28.480 basic science isn't necessarily in pursuit of anything beyond knowledge, but it doesn't come with

00:12:37.840 the caveat of this needs to have a clinical application with respect to the species of

00:12:42.700 interest. Exactly right. Clinical medicine, I think everybody knows. It's getting your flu shot in the

00:12:48.540 fall. It's being told to diet and exercise and take your antihypertensives if they've been prescribed.

00:12:58.080 Right. Does taking this medication lower your risk of a stroke? Does taking this vaccine lower your risk

00:13:05.220 of getting the flu? Exactly. And translational medicine, there's a big gap between those two,

00:13:11.980 isn't there? Yes. And that's what translational medicine does. People had been doing this for a

00:13:19.000 long time, but never in an organized and conceptually holistic way, if I could say that. It's how do you

00:13:26.980 take a basic science observation and make something useful for human health out of it and prove it,

00:13:33.320 which is surprisingly challenging. So you're saying that basically up until roughly 20 years ago,

00:13:41.620 this hasn't been particularly well organized. And now pharma companies, among others, are saying

00:13:48.780 we'd like to own some of this risk. I think everybody has bought into the concept of translational

00:13:54.340 medicine now. Probably all big pharma companies and many small ones do it. Many academic institutions

00:14:02.720 have organizations to do translational medicine. It's in part our responsibility. It's in part a way

00:14:09.580 to do it more efficiently by providing appropriate training and experience to younger scientists.

00:14:15.160 We always have to think back to who's funding our basic science, especially in academia. Ultimately,

00:14:21.160 it's the people. Most heavily taxpayer funded. Yes. It's most heavily taxpayer funded.

00:14:27.680 And the reason they're doing it is to make their lives better or the lives of their family and

00:14:33.460 friends better. And we need to be better at that. And I think this is taking a step in that direction.

00:14:39.860 So what was the first translational problem then you began to work on when you joined Novartis in the,

00:14:44.680 what would have been, I guess, the nineties, right?

00:14:46.200 It was in the early 2000s. So I joined a musculoskeletal program at the time Novartis

00:14:52.720 was working on, it was a regenerative medicine concept in musculoskeletal biology to increase bone

00:15:00.020 density and increase muscle strength. And so we had to put together some programs that would translate

00:15:07.620 some basic biology observations from human genetics. Remember, translation can go both ways.

00:15:13.820 And in fact, to skip ahead a little bit, we actually did that from that 2014 paper. We took

00:15:20.340 what we learned there and went back into the mouse. And there were a few projects. The one that has been

00:15:27.440 successful is a drug called zoledronic acid to increase bone density.

00:15:32.300 And what was the state of assets that you came into? Did Novartis already have a basic program

00:15:39.600 that had shown some new insight with respect to biology that could then be extrapolated into a

00:15:47.100 compound? Did they already have the compound? What was the actual program you were creating?

00:15:53.200 At that time, Novartis worked very much like most other pharmaceutical companies did. There was a basic

00:16:00.280 science department led by PhD scientists. There was a clinical development organization led by

00:16:06.320 clinical developers, including MDs. And there was a throw it over the wall mentality. The scientist

00:16:13.280 makes something that they like, then they throw it over to the clinical scientists and they have to

00:16:17.260 figure out what to do with it. This is pre-IND?

00:16:20.680 Yes.

00:16:21.260 Okay. We should explain what an IND is, I suppose.

00:16:23.860 Yeah.

00:16:23.980 Yeah. Do you want to tell folks what that is?

00:16:25.240 Sure. So an IND stands for Investigational New Drug. And this is the application that sponsors make

00:16:33.980 to the FDA to get permission to begin clinical trials. And there are a whole raft of requirements

00:16:42.360 that are necessary in terms of quality, manufacturing, clinical plans, risks and benefits,

00:16:50.520 experiments and so forth, so that we can make it as safe as possible to test something new in people.

00:16:56.920 But in any event, that's the way Novartis worked is they separated research from clinical development.

00:17:01.660 Other companies did it a little differently. They had the initial testing in healthy volunteers or

00:17:07.020 the initial testing in patients, depending on the risk-benefit argument, as part of the research

00:17:12.080 organization. But in principle, it's the same thing. You had scientists making medicines

00:17:16.940 patients and then clinicians testing them. The goal of translational medicine is to provide

00:17:22.260 clinical input right at the very beginning of the process, even when you're thinking about what

00:17:26.280 to do. And it really helps to focus the drug development process on the patients and the

00:17:34.100 clinical need right from the beginning, so that ultimately the drug that's made is the drug that's

00:17:39.980 needed. Not let's make something and figure out what we can do with it. Let's figure out what we need

00:17:45.940 and then make it. Is there evidence, by the way, this is a bit of a tangent, but that that transition

00:17:51.680 has rendered pharma more efficient at yielding capital? This is studied in an anonymized fashion

00:18:00.140 by an industry organization. It varies by company. I see. So let's fast forward a little bit to the

00:18:08.060 first time you became involved in a molecule that would be involved in a nutrient sensing pathway,

00:18:15.760 what was your foray into that? There's a step before that. And that is, how did I get from

00:18:21.900 musculoskeletal disease to something new? We have to credit again, Mark Fishman, who was the founder

00:18:27.720 of the Novartis Institutes for this, because he challenged me and a few others to put together an

00:18:34.140 organization within the company and answer the question, what aren't we doing that we should be

00:18:40.000 doing? And then start some projects. And again, it's all about medical need and of course,

00:18:46.940 scientific tractability. So we started that project. We called it the New Indication Discovery Unit.

00:18:53.280 What year is this roughly? Mid-2000s?

00:18:55.640 This would have been about 2008 or 2009. We basically applied those principles, a real medical

00:19:04.740 need, a problem that's scientifically tractable, and that Novartis wasn't working on and ideally

00:19:11.500 that nobody was working on. And we ended up with a few very interesting areas. Joan Manick,

00:19:18.780 who was the first author on that 2014 paper, brought the idea forward. Well, maybe the biology of aging

00:19:26.060 is tractable, but how do we actually make a medicine and develop it?

00:19:30.380 That was Joan at Novartis at this time?

00:19:32.740 Yeah, she joined our group in part to do this. Her real innovation beyond just the ideas that she 0.57

00:19:39.320 figured out a way to test a medicine that could alter the biology of aging in humans

00:19:46.540 and find an endpoint that's measurable and modifiable in a reasonable timeframe.

00:19:54.300 Which really is the Achilles heel of aging research, which is the ultimate outcome is

00:20:00.300 virtually unmeasurable in the species of interest.

00:20:03.260 Yes. So our approach is not necessarily what you might read in the popular press about making

00:20:09.540 medicines for aging. Our approach is to address serious aging associated diseases. And if we're

00:20:19.600 successful, the side effect will be longevity.

00:20:22.540 Yeah. So keep going then. Now Joan floats this idea, which is here's a really good proxy for aging 1.00

00:20:30.660 that can be measured out in a time course that's clinically tractable and also frankly amenable to

00:20:37.720 the type of research that we can do in humans. And so what was your aha moment? This is interesting.

00:20:44.780 As in, this is interesting to Lloyd.

00:20:46.740 I needed, and beyond interesting to Lloyd, we then as a team had to persuade the rest of the

00:20:52.760 organization, hey, let's try this idea. And again, we always come back to the medical need,

00:20:58.680 scientific tractability, and in proposing a project, what's the evidence that it's going to be

00:21:03.940 successful? And you know, as well as anybody, there's substantial scientific data that mTOR inhibition

00:21:13.200 will extend health span in many preclinical species, certainly all the ones that have been tested.

00:21:19.940 Now that was not obvious in 2008. I mean, 2009, people had been speculating. And of course,

00:21:26.380 there was a major publication that came out in 2009.

00:21:28.780 I have to correct the timeframe. We started our new indication discovery unit in 2008 or 9.

00:21:34.940 I think Jones started the project in 2010.

00:21:37.640 Got it. So you already had a very important study behind you as a catalyst for that.

00:21:42.600 Let's take a step back now and explain, because it's been a while and there's going to be people

00:21:46.980 listening who don't recall all the details of our discussion with David Sabatini and with Matt

00:21:51.920 Kaberlin. Let's talk about what is mTOR. Sure. Well, I can't add anything to David Sabatini about

00:21:58.740 what mTOR is. Nobody can, but let's assume people have not heard what David has to say.

00:22:03.600 Sure. In a nutshell, mTOR is the master integrator of external availability of nutrients and growth

00:22:13.000 factors. And then is the master regulator of the outputs of that integration, deciding whether

00:22:20.260 cells are going to make proteins, make lipids, make nucleic acids grow, or are we going to circle

00:22:28.380 the wagons, conserve resources, recycle, and wait during times of little for hopefully future times

00:22:35.980 of plenty? So that's the role of mTOR. So it takes a bunch of signals, which are external to the cell,

00:22:43.900 ultimately become internal to the cell because mTOR is in the cell, not out of the cell.

00:22:47.740 It assimilates and integrates across that signal and makes decisions that lead to, as you said,

00:22:56.380 at the risk of oversimplifying, grow or don't grow. Yes. I think that's exactly right. The signals it

00:23:02.780 takes are amino acids, glucose, cellular energy, growth factors from other parts of the organism

00:23:11.120 as probably the major ones, and then decides, are there sufficient resources that the cell should grow 0.74

00:23:17.100 or not? And between, and this is just a little history lesson for the listener, sort of between

00:23:21.260 1991, when Hall first identified what was not called at the time TOR, but what would go on to become TOR

00:23:28.680 in yeast, and 94 when Sabatini identifies it in mammals, you basically had some of the, just the heaviest

00:23:39.740 hitters in biology all sort of converging on this idea, which is, this is a really ubiquitous thing that has been preserved

00:23:48.660 across about a billion years of evolution with very little change. You don't see that every day in biology.

00:23:55.900 Why is that relevant? The simplest argument is that things that have been conserved from single-cell

00:24:01.680 organisms to us are probably important. There's some interesting comparative zoology that's relevant

00:24:09.440 to mTOR here. If you think about where in the cell mTOR lives, it's active on something called a lysosome,

00:24:16.800 and that is a structure in the cells that's responsible for breaking down either cellular

00:24:24.720 material or material that's been acquired from outside the cell into its component elements that

00:24:31.120 then could be recycled, like amino acids and sugars and so forth. Very early in development, well,

00:24:39.680 in evolutionary biology, when there were single-celled organisms and then the early multiple cellular

00:24:45.760 organisms. The way that the organism ate was by creating a vacuole from whatever was on the outside

00:24:54.980 and then creating a lysosome. So we can sort of picture this endocytotic process as the cell membrane

00:25:02.780 or wall, depending on what, if it's eukaryotic or prokaryotic, sort of sucks in a little bit, which

00:25:08.100 creates basically a space. And then the outer parts of that wall reach up, reach around it, and can

00:25:14.120 actually seal. And now you've created like a vacuole that you pull into the cell. Yes. And in the early

00:25:20.360 multicellular organisms, there were specialized cells for doing this, and they were called phagocytes

00:25:26.140 for eating cells. Later on, it was learned that phagocytes could also serve an immunologic role.

00:25:32.980 In other words, that they could eat pathogens as well as nutrients. This happened in the late 1800s

00:25:39.160 when higher quality microscopes were available. A Russian scientist named Ilya Metchnikov did a lot

00:25:45.980 of the pioneering work on this. He was working in Paris. And he described, he was an embryologist and

00:25:53.420 comparative zoologist. And he described by looking at small animals that were completely transparent so he

00:26:00.300 could see all the cells inside and what they were doing. He actually imaged them while they were alive,

00:26:05.860 and he could watch them eat, and he could watch them fight bacterial infections. And he was a

00:26:12.720 major champion of something called cellular immunity. At the same time, some German scientists,

00:26:19.280 notably Paul Ehrlich, were working on what we now understand as antibodies. And they said,

00:26:25.560 no, it's humoral immunity or soluble immunity in your blood. And they had the cellular immunologists

00:26:31.760 in Paris. And we had the humoral immunologists in Germany. Eventually, they figured out they were

00:26:38.040 both right. And they both got the Nobel Prize in 1908. But this is why mTOR is probably on a lysosomal

00:26:47.020 vacuole. Because in the context of evolutionary development, it was on these vacuoles that very

00:26:55.480 simplest organisms used to ingest food and nutrients. And so you want to have it close

00:27:01.660 to, because it's there to sense those things, you want to have it very close to where they enter the

00:27:07.000 cell. Yes, exactly. So if we take a given eukaryotic cell today, take one of our cells,

00:27:13.160 how many mTOR complexes would exist in a cell? What order of magnitude? I'd turf that question to

00:27:20.060 David Sabatini. I don't think I've ever asked David that question. I don't know. I would guess it

00:27:24.640 would be on the order of thousands, not millions, not tens. So one of the other things that David's

00:27:33.600 done is not just recognizing this in mammals, but also recognizing that mTOR, which again,

00:27:40.820 it's one of those things that's funny when you start to explain it to people, because you can't

00:27:44.900 explain what mTOR is without somewhere explaining what rapamycin is given the name. mTOR stands for

00:27:50.060 mechanistic target of rapamycin. But David also played the fundamental role in elucidating that

00:27:58.280 mTOR can be organized in a couple of different ways, and sort of two main different ways it can be

00:28:03.420 organized, known as complex one and complex two. Explain a little bit about what those two mean.

00:28:09.380 How do they organize differently? And perhaps more importantly, is there a functional difference

00:28:13.220 between those? Sure. So in yeast, there are two separate

00:28:16.820 TOR proteins, one and two. And in, I think, all other species, there's just one mTOR protein,

00:28:25.160 and it can be assembled into two different complexes. One of them, or called TORC1,

00:28:32.060 for target of rapamycin complex one, regulates many of the things we've been talking about.

00:28:38.160 So protein synthesis, lipid biosynthesis, protein translation, and so forth. The other complex,

00:28:47.220 TORC2, regulates cytoskeletals. So in other words, the skeleton of the cells organization,

00:28:53.720 and growth decisions. So different. Now this is sort of interesting. So

00:28:59.020 let's talk about rapamycin now. How does rapamycin interact with TOR, its target?

00:29:06.840 That's an excellent question, because you think about TOR being the target of rapamycin. It's not

00:29:12.620 exactly. The target of rapamycin is an immunophyllin called FK binding proteins, or FKBP. And there's

00:29:22.820 several of these. There's three different classes of immunophyllins. The complex of rapamycin bound

00:29:29.060 to FKBP, then binds to the TORC1 complex, and inhibits it. And it inhibits it in different ways

00:29:40.220 for different downstream targets. The one that's most commonly measured is something called

00:29:45.900 phospho-S6 kinase, which name's not important. It's just, this is the protein translation pathway.

00:29:53.840 And it's very efficient at inhibiting that. A little less so for another target called 4-EBP1,

00:30:01.100 and even less so for a target called ULK1, which is involved in activating the cell's recycling

00:30:09.280 machinery called autophagy. In other words, let's go through that again. So rapamycin binds,

00:30:16.320 and how tightly does it bind, by the way?

00:30:18.040 Pretty tightly.

00:30:19.680 So it binds pretty tightly to this binding protein. This binding protein then moves towards

00:30:27.420 TOR. And in the case of, did we explain Raptor and Richter yet? We haven't explained those cases.

00:30:33.080 Do you want to spend maybe just a minute so that they can see the difference between complex one

00:30:36.280 and complex two?

00:30:37.700 So mTOR is present in both TORC1 and TORC2 complex, but there are proteins that are unique to each complex.

00:30:45.320 So as you were saying, the yeast have two different TOR. Everything else has the same TOR,

00:30:51.000 but it's another binding protein. It's another protein bound to it that creates the distinction

00:30:55.720 between complex one and two, correct?

00:30:57.200 Exactly. And we should qualify every organism we've looked at as only one mTOR. I'm sure we

00:31:02.980 haven't looked at all of them. So Raptor and Richter, again, discovered in David Sabatini's group,

00:31:09.440 Raptor is unique to TORC1 complex and Richter is unique to the TORC2 complex.

00:31:15.660 And they're covalently bound to TOR?

00:31:17.880 I don't think it's covalent.

00:31:19.680 Okay. So it's some sort of conformational configuration, but not necessarily...

00:31:24.460 Well, it's a multi-subunit complex, but I think they bind on the basis of having a fairly large

00:31:30.560 surface of interaction, not covalent. And then the complex, to get back to the FKBP of FKBP plus

00:31:39.420 rapamycin, then binds to the TORC1 complex and inhibits it. But again, it inhibits it very well

00:31:49.340 for some of the downstream pathways and not so well for some of the others.

00:31:53.500 And let's review again those three. So the first one that binds really well,

00:31:57.260 the serine phosphate is which one?

00:31:59.600 There's the binding interaction of the rapamycin FKBP to TORC1.

00:32:04.520 Yes.

00:32:05.040 And then that alters the TORC1 downstream activity. It inhibits quite effectively

00:32:10.700 phosphorylation of S6 kinase. S6 is a critical protein in the ribosome required for

00:32:18.300 protein translation. It works a little less well for a protein called 4EBP1,

00:32:24.900 which is an inhibitor of protein translation. So you inhibit the inhibitor and you activate

00:32:30.440 protein translation. And it's less effective at phosphorylating ULK1, which is an early step

00:32:39.760 in the activation of the cell recycling machinery called autophagy.

00:32:44.200 The interpretation of that is as following. Rapamycin is a strong inhibitor of making new protein and a

00:32:55.180 modest activator of autophagy.

00:32:58.540 Exactly.

00:32:59.160 Is that a fair statement?

00:32:59.860 Yeah, I think that's a fair statement. We're talking about these pathways as specific examples.

00:33:05.580 Remember, TORC1 does other things too, particularly in terms of regulation of lipid synthesis,

00:33:11.480 pyrimidine synthesis. Pyrimidines are part of DNA.

00:33:16.180 What about mTORC2? So how does RAPA and FKBP bind to mTORC2?

00:33:23.320 I don't think it does directly because there's no immediate effect of the complex on TORC2 activity.

00:33:30.420 If you look at the downstream targets, they're not affected in the short term.

00:33:34.280 There's a longer term feedback inhibition of TORC2.

00:33:37.660 And is that more due to the failure to re-synthesize enough TOR? Is there a shortfall

00:33:44.360 of TOR because so much of the TOR is bound to the RAPA FKBP complex that you now run out of 0.99

00:33:52.240 enough TOR to make mTORC2?

00:33:54.520 You could imagine that is one possibility, but I don't think that's the case. I think it's more

00:33:58.520 there's a feedback signaling pathway that downregulates TORC2.

00:34:02.640 What you said is very important and we're going to come back to it in great detail,

00:34:06.520 but there's something temporal about this, isn't there?

00:34:09.160 Yes.

00:34:09.840 Do we know how much exposure to rapamycin or a RAPA log is necessary,

00:34:18.320 constitutive exposure, before you start to see this dual prong of inhibition? Are we talking about

00:34:24.220 a day, two days, three days, a month?

00:34:28.660 I know you had David Sinclair on recently.

00:34:31.240 Yeah.

00:34:31.540 And I listened to your talk with him. He talks about mouse experiments. My bias is to talk about

00:34:37.200 people experiments, given my role. In humans, after a week to a month, you can start to see

00:34:44.460 consequences of TORC2 inhibition with a RAPA log alone, and it's reflected in hyperglycemia and

00:34:52.260 hyperglycemia. So biomarkers in the peripheral blood you can measure.

00:34:57.040 Why is it that inhibition of MTORC2 leads to that phenotype you just described?

00:35:03.480 I don't think we know exactly.

00:35:05.480 Is it confirmed that that phenotype exists in healthy volunteers? In other words, we see this

00:35:10.440 for sure in patients who take rapamycin or its analogs in the context of organ transplantation.

00:35:18.380 But if we took non-diabetic, non-immunocompromised, quote-unquote,

00:35:23.920 as normal as possible subjects, do we have evidence that those things happen?

00:35:29.360 We do. MTOR inhibitors, well, RAPA logs specifically, have been tested in non-transplant,

00:35:35.860 non-malignant disease patients. Some specific examples include the RAPA log RAD001 was tested

00:35:43.540 in patients with polycystic kidney disease. These people are basically well, except for that renal

00:35:49.600 disease. And even in those patients, there were a substantial fraction who saw these biochemical

00:35:56.260 changes in their blood. Now, not everybody gets it. We don't understand that either.

00:36:01.320 Do we know what the dose equivalence was of RAD001 versus rapamycin? In other words,

00:36:08.660 they were getting it daily. Do you recall at what dose did you start to see this consequence?

00:36:14.580 That was a phase three study. It's published, so you can look it up. If I recall, the dose was

00:36:20.960 10 milligrams a day. And I think they had an opportunity to decrease the dose to five milligrams

00:36:27.500 if it wasn't tolerated.

00:36:30.420 Is RAD001 identical to rapamycin in dosing? What's the dose equivalence?

00:36:35.020 Again, it's hard to do an exact dose equivalence because the biochemistry of how exactly the

00:36:40.940 complex works with the mTOR complex is a little different. But if your rapamycin dose is somewhere

00:36:47.540 between two and eight milligrams a day, roughly, at the immunosuppression level of dosing, which is

00:36:54.720 what we're talking about, that's comparable to five to 10 milligrams of RAD001.

00:37:01.240 Got it. So they're pretty similar, but not identical.

00:37:04.280 Yes.

00:37:05.460 So let's put a bow on this particular question and then take a step backwards.

00:37:10.620 Is it safe to say that most of the inhibition of mTOR complex II seems to produce things

00:37:17.580 that are not really desirable at all, whereas the output of an mTOR complex I inhibition pathway

00:37:27.640 seems quite desirable at least sometime?

00:37:30.760 Yes. And in fact, mouse genetic experiments have supported that conclusion.

00:37:36.600 Let's talk a little bit about those experiments. So if you genetically knock out raptor so that you

00:37:41.700 no longer have complex I, but you still have mTOR and RICTOR, so therefore you have complex II,

00:37:47.340 what does that animal look like?

00:37:49.160 Depends on how you do it. If you imagine making a mouse that doesn't have raptor I, which means it

00:37:55.820 doesn't have TORC complex I from conception.

00:37:59.740 I assume it has muscular dystrophy or something like that?

00:38:02.240 They're embryonic lethal.

00:38:03.800 Yeah. Okay.

00:38:04.540 You need TORC one for development.

00:38:06.440 So if you just turn it down by some amount, 50% reduction, not much of a phenotype of that. But

00:38:14.260 the way the experiments have been done is you can conditionally knock out a target in a mouse

00:38:19.220 experiment. So you can create an experiment where the mouse is normal and is born and develops

00:38:28.040 normally. And then when the mouse is a young adult, you can knock out raptor or knock out TORC one.

00:38:35.680 So once they're out of the development window and they've reached adult size,

00:38:41.140 then it's better tolerated.

00:38:42.900 And again, David Sabatini has done a lot of these experiments. His group published a nice paper not

00:38:48.540 that long ago where they knocked out several components of the TORC one complex. Inhibition

00:38:54.040 of TORC one extends lifespan and healthspan in rodents. If you do that to TORC two, it accelerates

00:39:01.220 death.

00:39:01.920 Such an interesting concept. I mean, because what it basically suggests is at least with the

00:39:08.540 tool that we currently have to block TOR, which is like rapamycin or rapalog, giving

00:39:14.380 intermittent dosing may be beneficial. Giving constant dosing may cancel out the benefit.

00:39:21.340 It's hard to know because when you give it constantly, you're getting the quote unquote good

00:39:26.760 inhibition and the bad inhibition. You don't know what the net effect is, right?

00:39:29.480 If you're using a rapalog with continuous administration, yes, you'll eventually down

00:39:34.100 regulate TORC two as well. And as far as we know, that's not favorable. There are some other ways

00:39:40.140 to do this. And Joan Mannix's second paper from 2018 was the first time we've explored that in humans.

00:39:48.780 I want to come back to the 2018 paper, but I want to build up to the 2014 paper. In 2009,

00:39:55.300 this mouse study comes out. It was the first of what would become a series of very interesting,

00:40:01.080 highly reproduced ITPs funded by NIH that sort of did something we didn't typically see,

00:40:07.800 which is consistently across multiple labs and across different strains show the same result.

00:40:14.960 A lot of times in biology, you just don't get that. You get the one hit wonder and it doesn't

00:40:19.480 work in any other model or in any other lab. And that's not because people were nefarious. It's just

00:40:25.460 there's some very, very particular niche sort of circumstances that are being exploited that we

00:40:31.260 don't even understand. That didn't seem to be the case in rapamycin. On a personal level by 2009,

00:40:37.140 I am now very interested in this compound, but I don't know what to make of it because I remember

00:40:44.020 being a resident at the hospital giving lots of sirolimus, a rapimmune, to transplant patients

00:40:52.840 along with their prednisone and their other immunosuppressive drugs. And there didn't seem

00:40:58.380 to be anything about that that seemed to be longevity producing. It didn't make sense that you

00:41:04.600 could suppress the immune system and somehow reduce death. It seemed counterintuitive. I mean,

00:41:11.060 in the transplant patient, it made sense because of course their greatest risk is by far organ

00:41:16.980 rejection, but these animal studies were not replicating that. So I remember being incredibly

00:41:23.880 confused for about the next five years. How did you guys start thinking about that problem inside Novartis?

00:41:30.640 Joan proposed the idea. And again, the real innovation was being able to recognize

00:41:36.840 that, I'm doing air quotes for the listeners, age of the immune system is something that's measurable

00:41:44.920 and potentially modifiable in a reasonable timeframe. And we had that paper from Chen in Science Cell

00:41:52.960 signaling that showed a short course of a rapalog could alter the biology of lymphocytes.

00:42:03.100 And you're saying that in a favorable way, not a disfavorable way.

00:42:06.000 Yes.

00:42:06.280 Because the earliest observations of Soren Seagal were that lymphocytes being highly proliferative

00:42:12.820 were heavily targeted by rapamycin.

00:42:18.040 It's all about the dose.

00:42:19.120 Yeah. So let's talk about those doses. As you alluded to earlier, a transplant patient

00:42:25.840 might be taking five milligrams a day of rapamycin, day in and day out. What types of doses were you

00:42:35.260 seeing that were producing this counterintuitive phenotype?

00:42:39.780 Well, if we get back to the mouse paper.

00:42:42.400 Yeah, yeah, exactly. Like lower or higher, I guess is what I'm saying relative to that.

00:42:45.900 And it's hard to compare as you have to look at exposures. So the doses on a weight basis or a

00:42:52.880 body surface area were much higher in a rodent experiment, but the exposures can be comparable.

00:42:59.140 They were actually fairly high in his paper. They were at least equal to what we use in transplant.

00:43:05.080 Obviously, we couldn't do that in healthy volunteers, especially healthy elderly volunteers. 0.93

00:43:10.280 There was some additional information that gave us some confidence we could use much lower doses than

00:43:17.480 what was used in transplant patients, yielding much lower exposures. And for the listeners,

00:43:23.580 exposures means how much of the drug is actually in your body over time.

00:43:28.000 So let's use Cialis as an example of this. I don't know why, but it's just, I was talking to a patient

00:43:33.080 about this the other day. Cialis is typically given as either five milligrams or 20 milligrams.

00:43:39.660 And patients typically have a choice if they want to take 20 milligrams, quote unquote, on demand.

00:43:46.420 So you're heading into the weekend, you're going away with your wife. It's Friday, you take the 20

00:43:54.140 milligrams of Cialis and erectile dysfunction is ameliorated Friday through Sunday.

00:44:01.020 Conversely, another way to take Cialis is to take five milligrams every single day, whether or not

00:44:07.700 you're going to be sexually active or not. But now all of a sudden, anytime you want to be sexually

00:44:13.400 active, you're functionally like that person who just took 20. Use the lingo of exposure to explain

00:44:20.680 how those two things are comparable. I don't know why this is somehow the first example that came to

00:44:25.500 my mind, but probably just because it was a discussion I had two days ago. It's actually a good example

00:44:30.200 because when you take the medicine doesn't always reflect if the medicine is in your body or not.

00:44:37.460 And medicines that work have to be in your body to work. So the five milligram dose of Cialis

00:44:42.680 taken once might be in your body for a day. A 20 milligram dose of Cialis taken once is in your body

00:44:52.860 for two to three days. So it's why the higher dose taken once can last over the even long weekend

00:44:59.100 perhaps, because it's still there. This we call in drug development a half-life of the drug. So the

00:45:07.700 half-life of Cialis is long enough that it can do that. That is not the case for Viagra, for example.

00:45:13.120 That's right. Now there's another interesting thing here, which will also be another,

00:45:18.180 we'll have a parallel to the Rapa story, which is generally patients will tolerate five milligrams

00:45:24.100 daily of Cialis more than 20 milligrams on demand because of the side effects. You have fewer side

00:45:30.680 effects because you don't have the same peak levels. So five milligrams daily will produce a very

00:45:38.360 consistent and narrow gap between peak and trough, which is therapeutic. Whereas 20 will overshoot.

00:45:46.320 You'll get a very high peak level, which may increase the side effects, lightheadedness, changes in

00:45:51.700 vision, things like that. And then you have a long enough way down before you hit trough. And it's

00:45:58.400 during that entire window that you have the availability of the effect of the drug.

00:46:02.520 Now that's true for the class of drugs.

00:46:05.200 The phosphodiesterase inhibitors.

00:46:06.840 Yeah, P5 inhibitors.

00:46:08.720 It's not true for other drugs. Two specific examples, rapamycin, where if you remember when

00:46:17.000 you were treating your transplant patients, you measured trough levels.

00:46:19.280 We measured, yeah, daily. I mean, we were constantly doing this.

00:46:22.680 But you measured the trough levels, not the peak levels.

00:46:24.560 Not the peak, that's right.

00:46:25.120 Because the side effects are driven by the trough levels as well as the efficacy.

00:46:28.580 And I think that's also true with gentamicin and a lot of the negative, the antibiotics that

00:46:33.540 have the same toxicities on the trough, right?

00:46:35.340 Yes. So gentamicin, years ago, we used to dose three times a day. Modern times, we dose it once

00:46:43.140 a day. And we get better efficacy and far fewer side effects.

00:46:48.100 So why is that the case, that a drug like gentamicin or rapamycin is producing toxicity by its nadir,

00:46:55.580 not its peak?

00:46:56.240 Every drug is different and it depends on the specific mechanism. For gentamicin and aminoglycosides in

00:47:05.560 general, remember these work on the bacterial ribosome. And there's some congruency between

00:47:13.280 mitochondrial ribosomes and bacterial ribosomes. And with sustained inhibition, that can cause

00:47:19.860 toxicity, particularly in the kidney and the tubular epithelial cells, also in inner ear hair

00:47:26.560 cells and some other places. So having some drug-free time seems to allow the organelles

00:47:32.340 to recover. At least that's the hypothesis I heard in medical school. We all know that half of what we

00:47:37.360 learned in medical school is wrong and they just weren't sure which half.

00:47:40.520 You had a better medical school than me. I think 90% of what I learned in medical school is wrong.

00:47:44.620 But you went to Harvard. I only went to Stanford. So I think that's the West Coast,

00:47:47.920 East Coast difference. No, I think that's, I mean, to me, that is the most logical argument,

00:47:52.920 which is drugs that have trough toxicity are drugs where you must have a break from the drug.

00:48:00.220 And the higher the trough, the lower the probability of a break. Peak drugs aren't about

00:48:06.640 time away. It's literally too much of this thing eventually hits a trigger. That's probably an

00:48:12.020 oversimplification, but it's a useful conceptual framework.

00:48:15.180 So let's now taking that model back, the first glimmer of hope that this drug had wasn't uniformly

00:48:23.100 immune suppressing was, well, what if we dose this lower basically? And not from the standpoint of

00:48:31.160 side effects, because that's a common reason you'd go lower, but actually change the profile of

00:48:37.240 inhibition. Was it known at the time that that's what they were trying to do? Like, did they have

00:48:42.380 enough insight into how rapamycin bound to the two different complexes to test this hypothesis

00:48:50.200 proactively? Or was this more empirical, an observation that after the fact, the mechanism

00:48:55.580 became elucidated? We had some information up front. One bit of information that the mechanism could

00:49:02.320 be favorable for immune function, not solely immunosuppressive, was looking again in your

00:49:09.060 transplant patients. And those who were on a calcineurin inhibitor versus those who were on

00:49:14.020 a rapalog. And there was a significant trend that those on rapalogs had fewer cytomegalovirus

00:49:21.920 infections than those on calcineurin inhibitors, all of the things being equal. An observational

00:49:27.620 study, not as well controlled as ideally we would like, but it was intriguing.

00:49:33.820 Do you remember the order of magnitude on that difference? So you're basically talking about FK

00:49:38.680 506 versus cyclosporine.

00:49:41.780 Yeah. Yeah.

00:49:42.680 Well, it was rapamycin versus cyclosporine or FK, right? Maybe, I don't remember, we'd have to go

00:49:49.340 back and look. So that was item one. Item two is we had done exposure response experiments in

00:50:00.200 cellular systems looking at how much drug is required to inhibit the downstream targets of

00:50:07.420 TORC1. And it was much, much lower than the exposures that are observed in the usual dosing

00:50:17.320 framework of rapamycin, at least for transplant and immunosuppression. If we were going to be

00:50:22.760 treating healthy people with a rapalog and test whether their immune function was better,

00:50:29.240 we couldn't be giving them a typical rapalog side effect. And this is, again, a critical element

00:50:34.820 of the translational medicine that Joan did in order to make this proposal, is what doses and

00:50:42.640 what schedule would be required to keep the trough levels actually less than assay, which would be as

00:50:49.540 safe as we could get it, plus nonetheless achieve adequate exposures to at least partially or temporarily

00:50:59.220 fully inhibit TORC1. That would let us ask the question. Let's now pause for a moment to explain

00:51:05.240 we've switched back and forth between the term rapamycin and rapalog. So again, a little bit

00:51:11.340 of a history lesson, but rapamycin is the name given by Soren Segal to the compound identified on Easter

00:51:19.600 Island. That went through two companies before being eventually absorbed by Pfizer through Wyeth.

00:51:27.140 And that was a drug named Rapamune or Sirolimus. And that was FDA approved in 1999 for transplantation.

00:51:37.680 What was the first rapalog to come along?

00:51:41.320 Arguably, it's rapamycin. The next drug...

00:51:46.340 Yeah, sorry. Semantics aside. After rapamune, rapamycin, Sirolimus, we're talking about the

00:51:53.340 experiment that we're about to discuss in detail is using a different molecule.

00:51:57.420 It's using a different molecule. We called it RAD001 in the paper. The generic name is

00:52:02.240 Everolimus. It was the second one. Temsirolimus is another one.

00:52:06.280 How does it differ from rapamune or Sirolimus?

00:52:11.180 There's small structural changes.

00:52:13.160 And it was synthesized to be different versus discovered in nature or was it deliberately

00:52:18.880 modified presumably?

00:52:20.520 Yes. Again, to improve the properties of the compound.

00:52:24.720 Has that borne out? I mean, obviously there's an IP reason one would do that obviously,

00:52:28.920 but in terms of clinical efficacy, are there differences?

00:52:32.460 I'm not aware of any comparative studies.

00:52:34.740 In vitro, potency seems to be a little greater.

00:52:38.880 I can tell you from firsthand experience looking at the cost of these drugs, there certainly

00:52:43.020 is a difference. Good Lord.

00:52:46.440 Yes. It's generic versus brand, I think, at this point still.

00:52:50.840 But even rapamune branded compared to... But anyway.

00:52:54.520 I am not somebody who can talk about drug costs.

00:52:56.720 Yeah. Yeah. Well, it's one of the most comical things I've ever seen, actually.

00:53:00.700 So let's now talk about this experiment. I'll tell you from my vantage point, the day I'll

00:53:05.700 never forget, which is I remember getting an embargoed copy on the day before Christmas. So

00:53:14.340 it's Wednesday, December 24th. It's probably noon. It's funny. I was in my office, which

00:53:20.920 is dumb. Why was I in my office at noon on Wednesday, the day before Christmas? I certainly 0.96

00:53:25.920 shouldn't have been. But I remember being in my office and I remember how sunny it was.

00:53:29.620 I remember what a beautiful day it was. And I remember someone from the New York Times

00:53:34.080 emailing me the embargoed copy and it's embargoed. Yeah, it was embargoed for another couple of

00:53:39.580 hours. The person at the time who sent it to me knew how interested I was in the subject

00:53:43.600 matter. And I'm reading this thing and I'm like, this is unbelievable. I just couldn't

00:53:48.980 believe what I was reading. And I have a background in immunology. So of course I can understand

00:53:53.980 what these figures are showing. Give people a sense of how long it takes to get there.

00:53:57.860 So if the public is first seeing this in December of 2014, when did the experiment start? And I

00:54:04.020 didn't mean that conceptually. Like I don't just mean you're enrolling patients. Like this

00:54:07.440 is a, about a four or five year journey, right? That's right. About 2010, we started.

00:54:12.480 So what was the hypothesis that you wanted to test and that you, Joan and the team wanted

00:54:16.780 to test? There was some pre-work before we could ask the question. The pre-work was one,

00:54:21.240 we reviewed the existing literature, especially that paper from Chen. And we then looked at some

00:54:29.400 other work that had looked at drug levels in cellular systems necessary to partially or fully

00:54:37.260 inhibit the target. And we had to look at a lot of different cells because TORC1's biology,

00:54:43.300 while in the big picture is the same in different cells, the sensitivity of the complex to the drug

00:54:51.300 is different in different cells. And we have some hypotheses now for why that is. And we then did

00:54:58.720 some modeling to understand whether the low doses, and we looked at internal data that the company had

00:55:05.300 to see, could we come up with a low dose and a schedule that would yield exposures in people

00:55:13.440 that would partially or fully inhibit TORC1, yet give less than assay trough levels to help ensure

00:55:20.520 safety in the healthy volunteers. Now Lloyd, was this mostly because at the time you wanted to see if

00:55:29.460 it even made sense to pursue a new molecule entirely that would inhibit complex one or so-called

00:55:35.640 selective inhibition? But the idea is why go down that path of doing that without a proof of concept

00:55:41.820 that says it works? Or did you think at that point in time, if we can get this to work, you would never

00:55:47.400 need a selective mTORC1 inhibitor? You're asking really for Novartis thinking that's probably still

00:55:54.180 confidential. But the big picture is we want to know if something works. We want to figure out if

00:56:00.940 we can make it better. Again, ultimately Novartis, we at RestoreBio, and hopefully everybody at a

00:56:07.640 pharmaceutical company is thinking about how can we make patients' lives better? And then everything

00:56:14.100 else is important, but secondary to that. And then what do we measure? What dose do we use? How

00:56:19.920 frequently do we give it? How long do we treat people? How do we answer the question clearly?

00:56:25.400 What do we measure? All of those questions had to be answered. And they had to be answered before

00:56:30.160 Joan brought the program to the decision board of the company to say, give us a lot of money to do

00:56:35.980 this experiment. Each of these clinical experiments cost millions of dollars.

00:56:40.400 And at the time, RAD001 was FDA approved for another indication or no?

00:56:45.600 Yes.

00:56:45.960 It was already approved in cancer or in?

00:56:49.380 I think it was in renal cell.

00:56:51.920 RCC?

00:56:52.640 Yeah.

00:56:52.940 Yeah. Okay. So that only raises the stakes of what you're asking because you're taking a drug that's

00:57:00.760 already gone through phase three and you're going to spend a lot of money on it that you technically

00:57:04.600 don't need to spend. Is that a common thing to do inside of a company as large as Novartis to take a

00:57:10.740 drug that basically you're trying to make the case for a totally different use?

00:57:15.960 Yes.

00:57:16.600 I suspect most companies do things like this where when the drug is registered in one indication,

00:57:22.660 if you can find others, it's a good thing.

00:57:25.960 So, I mean, for the sake of time, I will just, I mean, basically say that you guys did something

00:57:33.700 kind of amazing, which is with so little human data, you did a great job of identifying the right

00:57:42.580 patient population, identifying the right primary outcome, identifying a correct power analysis so you

00:57:50.420 wouldn't miss the signal. So in other words, you didn't know how to power the study, which means

00:57:54.620 you had to have a sense of how much the benefit was going to be, knowing how long to pulse,

00:58:00.280 how to dose. I mean, this could have gone sideways six other ways.

00:58:04.160 It could have. We had some additional help too. At the time, Novartis had a vaccines group and they

00:58:12.040 had commercialized a flu vaccine. So we knew a lot about flu vaccination and responses required for

00:58:20.460 making a clinical difference and so forth.

00:58:23.480 So let's walk people through the study design. You've got what, about 300 people age 60 plus more

00:58:30.560 or less?

00:58:30.700 I think it was 218 in that 214 paper. Everybody was over 65, no unstable medical conditions.

00:58:39.460 Were these subjects all in Australia? Was there something about this that was Australian?

00:58:43.260 Well, because this was a flu vaccination, so let's just skip ahead. The endpoint of the study,

00:58:48.120 the primary endpoint by which we were going to decide, did the study work or not work,

00:58:52.200 was the response to a flu vaccination, the seasonal flu. Now, because it's a seasonal vaccine,

00:58:58.940 we had to do the study when we were ready, wherever in the world people were about to get their flu

00:59:03.180 vaccines. In that paper, we were ready for the Southern Hemisphere because our summer is their

00:59:09.180 winter.

00:59:10.160 Right. And since the CVS in the Antarctica ran out of vaccine that year, Australia made the most sense.

00:59:16.480 Australia, New Zealand.

00:59:17.480 Yeah. So there are four arms in this study.

00:59:21.560 There's a placebo arm. It gets just obviously a placebo. There's three treatment arms. One that

00:59:28.300 gets 0.5 milligrams of RAD001 daily. So Everolimus. There's a group that's getting five milligrams

00:59:37.780 once a week. And there's a group that's getting 20 milligrams once a week. So it's a clever design

00:59:45.780 because the 5 and the 20 that are both getting it once a week gives you a great, you get to answer

00:59:50.900 both efficacy and toxicity questions as they pertain to that dose. The 0.5 daily versus the 5 weekly is

00:59:59.160 your closest aggregate dose where you get to see, is there a difference in trough? So overall,

01:00:05.380 you recall a lot of interesting stuff. What was your personal null hypothesis? Not necessarily the same,

01:00:11.340 but do you recall what your null hypothesis was going into that experiment?

01:00:16.920 I mean, obviously the null hypothesis is that there's no drug effect.

01:00:20.340 Yeah. Sorry. What was your first alternative hypothesis? I guess is a better way to say it.

01:00:24.460 This was a little bit less hypothesis testing the way that academic investigators work than it was

01:00:31.000 asking questions. And the question was, and there were several, but at a high level, it's,

01:00:38.740 can we see an improved vaccine response at an acceptable level of toxicity that would have this

01:00:45.260 drug make sense? And that's the high level question. And you went through the doses and schedules we used

01:00:51.840 and we tested three different ones because each of those doses did a different thing to torque one

01:00:59.500 inhibition. The 0.5 milligram dose partially inhibited in a sustained fashion. The five milligram once a

01:01:07.340 week fully inhibited torque one for a couple of days out of the week. And the 20 milligrams we modeled

01:01:15.340 would fully inhibit torque one over the dosing interval. I didn't realize that actually.

01:01:21.260 20 is so high that it gave you functionally nonstop inhibition of mTORC1 until your next dose.

01:01:29.460 Did any of these have mTORC2 inhibition?

01:01:32.780 I would have expected the 20 milligram would have. I don't remember that anyone had to discontinue the

01:01:39.120 drug for that reason, but it's been a couple of years since I read that paper.

01:01:42.740 Well, let's look at the toxicity table. So table one of this paper, which is again,

01:01:46.540 such an interesting paper. I was surprised. Obviously it was the first thing I looked at.

01:01:50.540 Usually table one is inclusion criteria or something like that, but you guys just skipped

01:01:54.600 the foreplay and went right to it. Table one, incidence of treatment related adverse effects.

01:02:00.040 I wish I could honestly say I remember how I read this the very first time because I've looked at it

01:02:04.240 a number of times since. But what's interesting is I certainly remember seeing that the placebo group

01:02:10.500 had 21 adverse events. So that's important to always keep in mind when you look at clinical studies

01:02:17.480 is there's just a baseline level of adverse effects that have no bearing on the drug whatsoever.

01:02:24.360 So it's almost like you could subtract 21 out of all of the others to get a sense of what the noise

01:02:30.020 is. So the group that got 0.5 daily had 35 adverse effects and each of the treatment groups had about

01:02:37.460 the same number. So, I mean, there were 53 groups in each of the three arms, 59 in the placebo. So

01:02:43.120 the 21, you might discount that slightly, but it basically went from 35 to 46 to 109. So at this

01:02:50.480 point, obviously this means each patient is having more than one adverse effect likely.

01:02:54.700 But here's what I found interesting. The next line in the table tells you how many people actually had

01:03:00.280 adverse effects. So not just the total adverse effects. And this was surprisingly constant. So in

01:03:04.720 the placebo group, it's 12. In arm one, it's 22. In arm two, it's 20. In arm three, it's 27.

01:03:13.340 So looks like 0.5 daily versus five weekly, no real difference in adverse effects. And by the way,

01:03:19.880 I'm not going to, don't worry, I won't read you guys the whole table here. We're going to link to

01:03:22.720 this paper in the show notes. The other thing that really stood out to me though, in terms of side

01:03:28.580 effects was mouth ulceration. Now that's the side effect I remembered the most from residency.

01:03:34.720 Was the patients getting apthos ulcers with their daily dose of rapamycin. And most of them were

01:03:40.260 getting more than 0.5 daily. So most of the patients that I, my recollection was that two to

01:03:46.440 four milligrams was a very common daily dose for rap immune. And again, this is rad 001. So it's a

01:03:53.940 different vehicle, but it's comparable. And so 0.5 daily would definitely be lower than what I was used

01:04:00.520 to seeing people get. And yet 11 and a half percent of these folks had mouth ulcerations.

01:04:05.260 Whereas the people getting 0.5 daily were at 0.5 once a week was about 4%. And 20 once a week

01:04:13.240 was about 17%. So that's really interesting. I mean, that tells a very interesting story about

01:04:18.980 the kinetics of this drug. Was there any other toxicity that surprised you in the study?

01:04:25.140 Well, as you pointed out, mouth ulcers are one of the more common and fairly specific side effects

01:04:32.840 for rapologues. Should we spend one moment explaining why? I think we could certainly

01:04:38.080 speculate why. I don't think anybody knows why there are some hypotheses, but, and it isn't just

01:04:44.260 rapologue associated mouth ulcers. We don't know what causes the ordinary spontaneous apthos

01:04:51.080 ulcerations that people get. There've been a fair amount of work on it, but nobody knows.

01:04:56.300 There are a lot of mysteries in medicine, and that's just another one of them.

01:04:59.740 Anecdotally, through five years of residency, I don't think I went more than two weeks without

01:05:05.460 an apthos ulcer.

01:05:06.620 They can be stress-related.

01:05:08.160 I'm sure they are. And it was to the point where they would drive me so bananas. I couldn't

01:05:12.540 even get relief from those sort of topical lidocaine gels. The only thing that could give me real

01:05:17.880 relief was if I could inject bupivacaine directly into it, because it was such a long-acting

01:05:22.840 agent. Lidocaine only lasts an hour or two. That was not going to do me justice on a call

01:05:27.660 night. And it got to the point where I would sit there and inject bupivacaine into my tongue

01:05:32.140 or into my mouth. And I remember once somebody walking in the call room while I'm sitting there

01:05:36.780 holding my gums out, jamming bupivacaine in, and they must have thought I had some drug problem.

01:05:42.540 But two weeks after leaving residency, I never had an apthos ulcer again.

01:05:48.640 I hope you never have another one. They're very painful.

01:05:51.440 They're unbelievable. But then of course I did get them once I started rapamycin.

01:05:54.920 So we'll come back to that. But I certainly went many, many years without them again.

01:05:59.640 My hypothesis was some combination of stress and sleep deprivation might've played a role.

01:06:04.000 It doesn't help mechanistically though. We just don't understand them.

01:06:07.520 Yeah. So overall, I thought the side effects were less than I would have expected.

01:06:13.120 Let's now talk about the results. I'll actually hand you the table here because I don't,

01:06:16.540 not that I would ever expect you to remember table 2A, but walk a little bit through kind

01:06:21.660 of what you guys saw and how you tested it. So you're using a couple of different flu vaccines,

01:06:27.260 et cetera, a couple of different strains. Yeah. So the standard flu vaccine had,

01:06:31.920 in those days, three different antigens for three different kinds of viruses, two influenza A

01:06:39.360 strains, one influenza B strain. And I think as we all know, the flu vaccine is designed

01:06:45.980 every single year based on the circulating flu strains in Asia to try to match the vaccine

01:06:53.280 to the strains of flu that we expect to get in this case in the Southern Hemisphere or for us in

01:07:00.820 the Northern Hemisphere. So patients were treated with one of those doses of RAD001 or a placebo.

01:07:09.120 And the study was randomized, double blind and placebo controls. So neither the doctors nor the

01:07:14.880 patients knew who was getting what. And I guess there's one detail I omitted,

01:07:19.020 which if my memory is correct, the patients were treated for eight weeks.

01:07:23.720 Six weeks.

01:07:24.320 Six weeks. And then there was a washout. So then they had a period of nothing for,

01:07:28.480 was that six to eight weeks? It was two weeks after the six weeks of treatment.

01:07:33.780 Oh, that's where the eight came in. So it was six of treatment, two of washout, then vaccination.

01:07:39.400 Right. And the rationale for that was we wanted the drug to be completely gone

01:07:43.660 at the time we vaccinated. So we were asking the question, is this a residual effect of the drug on

01:07:51.040 the immune system? Not a lingering effect on the immune system per se.

01:07:56.220 Yeah. Not a direct effect of the drug, but an indirect.

01:07:58.960 Yes. Okay. So with that said, what was the first finding?

01:08:04.140 So we were looking for whether the response to the flu vaccine was 1.2 fold better in a drug treated

01:08:12.080 group than the placebo. And that 1.2 fold came from a previous study that had been published that

01:08:19.220 showed that was the minimum requirement to see a clinically meaningful decrease in symptomatic

01:08:25.720 flu in vaccinated patients. We saw, and we required, and this was pre-specified,

01:08:32.580 two out of the three strains to have that improvement. And we saw that improvement,

01:08:37.000 or better, in the two low doses of RAD001, but not in the high dose. In the high dose,

01:08:44.020 we just saw one strain was better. One of the three strains was better.

01:08:47.300 And the other two were actually a little below 1, so a little below the placebo.

01:08:52.560 What do you make of that? Is it noise? Do you think there's something mechanistically

01:08:56.180 happening there?

01:08:57.840 Yeah, I do. I think we certainly know that high doses of a rapalog are immunosuppressive.

01:09:04.020 The dose of 20 milligrams once a week is sufficiently high to fully suppress TORQ1.

01:09:09.040 And I expect that we probably interfered with lymphocyte proliferation.

01:09:12.340 And do you think it's just a tweak that you didn't see? What's confusing to me is that you

01:09:17.720 still saw a much greater immunity in one strain. And if I recall, it was even higher than the two

01:09:23.680 low doses. Thinking about the first figure in the top figure in the second figure of the paper.

01:09:30.260 So that would be, my first guess would be, oh, clearly you just hit the daily dose of an

01:09:36.840 immunosuppressed patient if they were all below baseline.

01:09:41.060 But if you did a 25 weekly in there, do you think you would have just seen them all eventually start

01:09:47.380 to go down?

01:09:48.760 Certainly if we got to some high enough dose, I think they all would have been low.

01:09:53.200 I got it. Yeah.

01:09:54.260 So it's almost like there's a J curve here or an upside down J curve really,

01:09:58.600 or an upside down U, I suppose, of some combination of dose and frequency producing a sweet spot where

01:10:04.340 we're seeing, and by the way, I can't recall, it's been so long since I looked at the paper,

01:10:08.820 was there any lymphoproliferation? I mean, these were functional assays. Any changes in the counts

01:10:14.160 of lymphocytes or any other?

01:10:16.840 This specific assay that was the primary endpoint was an antibody titer assay.

01:10:21.020 Right.

01:10:21.360 We didn't do mixed lymphocyte reactions or some proliferation assay as part of this paper.

01:10:28.560 Did anyone ever look at fractions of lymphocytes? For example, did anyone look at CD25, CD3 to see

01:10:38.000 if anything had happened to suppressor T cells?

01:10:41.440 We didn't do it in this study. Well, we didn't do functional lymphocyte assays. Part of this study

01:10:48.120 was a very comprehensive multidimensional flow cytometric assay to get lymphocyte subsets.

01:10:56.020 And we reported one of the results in figure three, which is where we saw improvement in

01:11:04.600 checkpoint protein levels on both CD8 and CD4 lymphocytes, which mean, and checkpoint proteins

01:11:14.160 are very popular in oncology now. And some of your listeners may have heard about those things

01:11:20.120 like PD1, for example, the drug target of Keytruda or Optivo.

01:11:24.340 We had Keith Flaherty on recently, and we had a beautiful discussion about checkpoint inhibition.

01:11:29.240 But that said, let's assume people don't know what that is. It's always worth rediscussing it.

01:11:33.400 Yeah. These proteins inhibit lymphocyte function, and they go up as the lymphocytes get exhausted.

01:11:40.020 And what we saw in this study is that the level of PD1 went down on the lymphocytes

01:11:45.640 in the drug treatment group compared to the placebo.

01:11:48.780 By what percent?

01:11:50.280 It was a relatively small effect, a 10 to 20% change.

01:11:54.000 But comparable to the effect that you saw in the increase in antibody recognition. I mean,

01:11:59.460 it was like the mirror of that.

01:12:00.780 I guess, yeah.

01:12:01.480 Yeah. And presumably the teleologic rationale for that is the more tired a lymphocyte gets,

01:12:06.100 the more it wants to weaken its brakes.

01:12:08.720 I'll go along with that.

01:12:10.760 Everything in me, in my world, Lloyd, comes down to just

01:12:13.460 anthropomorphizing the immune system.

01:12:15.720 There you go.

01:12:16.120 That's how I do things. So has anyone looked at this, by the way, to see what rapamycin does

01:12:21.240 or Rapalog does in this type of intermittent dosing to inhibitory T cells?

01:12:26.800 There have been a lot of studies of T cell subset functions with Rapalogs, both in mice and in

01:12:33.360 humans, looking at effector memory transition, looking at Tregs with high exposures or substantial

01:12:41.460 inhibitory effect on B cell function. There's a lot out there.

01:12:45.320 Do you think that Rapalogs could be used to suppress Tregs? Selectively, of course. 1.00

01:12:50.700 There are a couple of papers that show that.

01:12:53.340 Because it would sure be interesting to start layering in Rapalogs with immunotherapy,

01:12:59.460 oncology specifically.

01:13:00.380 Yes. Yeah. There's a small literature on that.

01:13:03.080 What else did you see in this paper? I think we've touched on the high points.

01:13:07.180 The other experiment we did, which I think we mentioned in the text, but didn't go into great

01:13:12.240 details, is the flu vaccine is a T-dependent antibody response. We also vaccinated patients

01:13:20.260 with a 23-valent pneumococcal vaccine, which is a pure polysaccharide vaccine. So it's a T-independent

01:13:29.520 response. We were thinking, could we improve antigen presentation perhaps if the dose of

01:13:37.320 the Rapalog we used, augmented autophagy? And could that contribute to antigen presentation?

01:13:43.660 We saw, and we measured seven of the 23 antigens.

01:13:49.400 Wait, tell me why that would be, that's not an obvious purview into autophagy to me. So let's

01:13:55.700 back that up a little bit. So you're giving them a pneumococcal vaccine, which is what type of vaccine?

01:14:02.160 That's a...

01:14:03.340 Polysaccharide antigen.

01:14:04.300 Polysaccharide antigen, you're not giving back the whole bacteria. And how does it get presented

01:14:09.540 to the immune system?

01:14:11.800 There are specific elements of innate immunity that recognize bacterial polysaccharide antigens,

01:14:17.180 and that brings it to professional antigen presenting cells, likely dendritic cells.

01:14:22.480 And then it has to be internalized and then presented.

01:14:26.020 So that's MHC class one?

01:14:28.880 This isn't a peptide presentation. This is presented in the context of an innate element

01:14:33.900 that recognizes polysaccharide antigens.

01:14:36.920 Okay. All right. So we're outside of class one, class two.

01:14:40.240 Yes. Yes.

01:14:41.140 And you're saying the ability to internalize, or basically the ability to phagocytose

01:14:47.060 that lipopolisaccharide, and then...

01:14:50.580 And directly stimulate B cells.

01:14:52.720 Yeah.

01:14:53.000 It was an exploratory element of the study. We saw in the seven specific antigen responses

01:14:59.220 we measured, if I recall, six of them increased, but by a small amount. It was an encouraging

01:15:07.200 trend, but we didn't further follow it up.

01:15:09.600 Okay. Any other markers you could have here for autophagy? I mean, did you look at light

01:15:15.220 chain transition or anything like that?

01:15:16.980 No. Autophagy is a really difficult clinical investigation paradigm. And I know you recently

01:15:24.320 saw Mitch Weiss's paper on unpaired hemoglobins in thalassemia patients. I was super excited

01:15:32.520 when I read that paper because here is now a clinical paradigm where we can test drugs that

01:15:37.700 augment autophagy and see something easily measurable in a not that rare patient population.

01:15:44.140 Yeah. Let me think. In those patients, did you collect serum that allow you to look at

01:15:50.400 amino acid levels in the plasma or anything else?

01:15:54.020 No, we didn't do any of that.

01:15:55.400 Do you still have any of that banked serum?

01:15:58.720 I don't think so.

01:16:00.120 Easy enough experiment to repeat. But of course, the other thing I'm curious about is,

01:16:05.140 is there anything about RAD001 administration that mimics fasting, for example? I mean,

01:16:10.800 how much of the benefit here is through direct inhibition of mTOR? And are there any pleiotrophic

01:16:19.860 benefits that aren't quantified through this? Obviously, some of them, I mean, the fact that

01:16:25.460 you waited until the drug was out of the system to check the immune response is actually a great

01:16:29.980 insight because obviously you eliminate some of those things. But in the way that many people have

01:16:34.560 argued statins have a direct effect, they inhibit cholesterol synthesis, an indirect effect,

01:16:40.480 the liver upregulates LDLR, a really indirect effect, which is immune suppression or other

01:16:47.020 sort of benefits around endothelial health and things like that. Do you think there's a possible

01:16:51.680 third leg to this stool that we haven't thought about?

01:16:54.560 The fasting story is kind of complex. So do I think there's some other persistent benefit of

01:17:01.100 of a rapalog? I think the mouse experiments tells us there is. And it's because relatively short

01:17:09.400 course of a rapalog is nonetheless sufficient to extend a mouse's lifespan. And we do not understand

01:17:17.560 that. Although it's so hard to extrapolate what short versus long means in a mouse, isn't it?

01:17:23.020 Yes.

01:17:23.860 Look at the mouse that fasts for 24 hours. Look at Jay Mitchell's stuff where they do a one-day fast

01:17:29.880 prior to a femoral artery ligation and a reperfusion where the mouse that was just fed normally through

01:17:36.840 the insult, they all die. The mice that had 24 hours of fasting prior to a lethal reperfusion

01:17:43.980 injury, either all or mostly live. I don't know how to extrapolate that into a higher order animal

01:17:51.220 because it's not even the duration of the fast. It's the metabolic consequence of the fast.

01:17:56.580 There's some long-term consequence of that that we don't understand. And there's several things you

01:18:02.800 could hypothesize. Is there a change in the DNA structure based on histone methylation or DNA

01:18:10.040 methylation? Is it, or is this something else? Those are just the things that come to mind.

01:18:14.920 Yeah. That's a great point, right? Is you could literally be resetting methylation on that.

01:18:19.720 You could turn back a methylation clock to its template potentially.

01:18:22.860 But people have looked at that with rapalogs and it doesn't seem to happen.

01:18:27.000 In other words, you take a Horvath clock pre and post and you're not seeing unwinding of

01:18:31.980 methylation. Yeah.

01:18:33.620 That's been done in mice as well or just in humans?

01:18:37.980 I suspect it's been done in a bunch of species. It's one of these sort of negative studies that

01:18:42.080 may never get published. That's a pet peeve of mine, by the way. Negative studies not getting

01:18:46.860 published. I think it's a pet peeve of a lot of people. It's hard enough to publish positive studies.

01:18:51.240 And I'm sympathetic and agree.

01:18:55.240 Yeah. So we're high-fiving on New Year's Eve 2014. How do you go from, what does Novartis,

01:19:05.300 again, if this is confidential, by all means, we'll skip it. But what do the brass at Novartis

01:19:11.060 think of the results of this experiment, which is effectively taking a drug that we already have

01:19:15.760 on the market for a very clear indication and now potentially expanding an indication,

01:19:21.340 can the FDA take a study? This is a very well-done study here. This is double-blinded. This is placebo

01:19:27.200 controlled. And this found a significant outcome. Is that enough to change the indication for a

01:19:32.580 medication like this?

01:19:33.560 I can speak in general in that for an indication that could be relevant to many, many people,

01:19:40.780 you need a corresponding, a lot of safety data. This study was way too small for studies that would

01:19:50.340 be required for marketing authorization.

01:19:53.560 I got it. So because something like renal cell carcinoma is relatively infrequent relative to

01:19:59.220 influenza vaccination, you had enough safety data to justify treating people with RCC. This would

01:20:06.380 not constitute sufficient safety data to basically give every person over the age of 65 who's getting

01:20:11.960 vaccinated this type of a medication.

01:20:14.180 That's exactly right. If we fast forward a little bit in the conversation, we've advanced this program

01:20:19.900 in Restore Bio. Novartis licensed it to Restore Bio. And our phase three program is two very

01:20:28.720 similarly designed clinical studies. One has 1,000 patients. The other one will have about 1,600

01:20:34.300 patients.

01:20:35.780 You were able to speak about how the decision was made for Restore Bio to basically acquire a piece

01:20:42.240 of an asset from Novartis and what else was brought in to create that company. And how did

01:20:46.800 you, Joan, and I assume many others decide to leave? I mean, that's obviously a loss to Novartis,

01:20:52.220 presumably, which implies that they probably still have a vested interest in the success of Restore Bio.

01:20:57.260 Yeah. Let's take one step backwards and answer an earlier question you asked, which is,

01:21:02.720 what did Novartis think when we got these results?

01:21:05.500 Oh, yes. Yes. Thank you.

01:21:06.140 And I think everybody was very excited for reasons that you're excited.

01:21:11.240 That was my Christmas present of the year.

01:21:14.180 And the guidance was, this is so important. Let's go back and do it again.

01:21:20.040 Try to do it in a more TORC-1 selective way.

01:21:24.500 Are you able to say how much that study cost just to give a sense of...

01:21:27.740 I don't think we talk externally, but any clinical study like this, a phase two study with

01:21:34.200 two to 300 patients costs millions. And a lot of the cost is driven by often exploratory assessments

01:21:43.400 you do in the context of the study beyond the per patient cost and investigator cost,

01:21:48.360 but millions. I mean, it's a lot of money for anybody and it's done with a lot of deliberation

01:21:54.680 and thought. So the guidance was to go back and do it again, make sure it's real, come up with a way

01:22:00.680 to be more TORC-1 selective.

01:22:02.100 But using the same vehicle, which means putting a finer point on the dosing, not necessarily...

01:22:09.460 I mean, you're still not at the point where people are saying,

01:22:11.320 we need to make a new molecule to replicate this?

01:22:14.860 Well, we had one.

01:22:16.000 Oh.

01:22:16.900 The research team at Novartis had come up with a very cool finding that a combination of an

01:22:24.020 allosteric and catalytic TORC inhibitor could be more TORC-1 selective and more potent.

01:22:31.840 And there was actually synergy. And this is published by Beatt Neifeler and Lone Murphy.

01:22:39.020 They showed synergy. So Arapalog... 0.99

01:22:42.120 Can you explain to folks what the difference is between allosteric versus catalytic inhibition?

01:22:45.940 Sure. So catalytic inhibition means an inhibitor that's binding at the catalytic site of TORC-1

01:22:55.100 and blocking phosphorylation of targets. An allosteric inhibitor is a fancy way of saying

01:23:01.320 an inhibitor that binds someplace else on the molecule and nonetheless inhibits it.

01:23:07.600 Rapamycin complex...

01:23:08.440 I always think of allosteric as sort of shape blocking.

01:23:11.360 Could be.

01:23:11.920 Yeah.

01:23:12.560 Let's say shape blocking. So in this case, the allosteric inhibitor is the combination of FKBP-12

01:23:18.120 plus rapamycin binding to TORC-1.

01:23:21.780 So the combination of those two synergistically inhibits TORC-1 and it's a little more TORC-1

01:23:29.180 selective.

01:23:30.660 Everolimus does the same thing. It also binds to FKBP.

01:23:34.900 Yes. It binds to FKBPs also. Maybe later on we can get to that Laming paper, which is...

01:23:40.920 Which, yeah, I'd love to get to that paper.

01:23:42.580 Yeah. So with that understanding, we could then explore, put a finer point on the dosing as well

01:23:52.360 as explore the biology of that catalytic inhibitor with and without RAD001. And that's what the next

01:23:59.480 study did. Overall, a very similar study design. We treated for six weeks, two-week washout,

01:24:05.840 interrogated the immune system function with flu vaccination and got fundamentally similar results.

01:24:14.060 There's one other point I'd like to bring in because it leads to where we are now. In the very

01:24:19.440 first study we did in analyzing, we saw immune function improvement, which, and our marker for

01:24:26.540 that was flu vaccine response. In the adverse event listings, we saw fewer infections in the drug

01:24:33.140 treated people compared to the placebo patients. Over what time horizon?

01:24:38.320 We followed people for a year. And by the way, did that increase in vaccination translate to a

01:24:43.440 reduction in influenza? Or was that the infection you're speaking about? Are you speaking about all

01:24:47.920 infections? All infections. Okay. What about influenza specifically?

01:24:51.680 Too few events to be able to make a conclusion. It's underpowered to look at the flu. Exactly.

01:24:56.740 If you think about all infections you get or patients get, most of them are respiratory tract infections.

01:25:03.720 Colds and flus in the winter season. An interesting thought experiment, you wouldn't do this experiment,

01:25:08.960 but an interesting thought experiment would be a two-by-two, vaccine, no vaccine,

01:25:15.300 RAPA, no RAPA, powered to see difference in infection. Big experiment. 0.73

01:25:20.940 Huge experiment, but great gedanken, right? Yes, I agreed. So in this very first study, we found, 0.99

01:25:27.320 again, we weren't thinking about it and we weren't looking for it, but we observed it

01:25:33.980 in the adverse event listings. So what were some of those infections,

01:25:37.400 Lloyd, that you saw, like UTIs or cellulitis, that kind of stuff?

01:25:41.060 Two most common ones. By far, the most common was upper respiratory tract infection or respiratory

01:25:46.780 tract infections in general. That was not influenza, yeah.

01:25:48.940 Maybe some of them were. We didn't measure. We don't know what the pathogens were. We do know

01:25:54.460 from surveillance experiments that the CDC has done that most of them are rhinovirus and then

01:26:00.980 there's metanemovirus. There's various other-

01:26:04.520 Echo, God only knows what.

01:26:05.520 Yes. And we saw a decrease in UTIs also.

01:26:09.500 And that persisted for a year?

01:26:11.720 The biggest effect was when the patients were shortly over the course of drug treatment and

01:26:17.400 some time thereafter. But even if we analyze it over the course of a year, we saw it,

01:26:22.140 although the effect waned. In this very first study in 2014, we brought patients back a year later and

01:26:27.860 revaccinated them to see if the improvement in immunologic function persisted.

01:26:33.260 And?

01:26:33.700 It did not.

01:26:34.620 Okay. So by a year, they'd clearly lost it.

01:26:37.120 Yes.

01:26:37.640 And of course, we didn't do the experiment, but do you know if six weeks was necessary or could

01:26:43.420 you have done four plus two or three plus two or two plus two? Would the benefit have been better

01:26:48.820 if you went eight plus two or 10 plus two or 12 plus two? Like, how did you agree on six weeks of

01:26:54.900 treatment? I understand the two-week washout, but what about the six weeks of treatment?

01:26:58.540 It came from two places. One is that that's what they did in the mice.

01:27:04.540 My same caveat implies.

01:27:07.080 Totally agree. And then secondly, we know the timing of lymphocyte production from committed

01:27:13.960 precursors in human bone marrow. And we were thinking that the drug could be acting at that

01:27:18.780 level. And six weeks of treatment is sufficient to, by the time you vaccinated eight weeks,

01:27:26.660 have some new lymphocytes from those committed precursors.

01:27:29.800 So your hypothesis would be six was the minimum time required to get a full turnover and going

01:27:37.400 eight versus 10 would not necessarily bring benefit and might only expose you to longer side effects.

01:27:43.560 We actually never tested this. We came up with our dosing period for the rationale that I gave you,

01:27:50.320 and we've not, at least with a rapalog, tested other intervals. We did see in the second study,

01:27:57.140 which also worked on the vaccine endpoint, we promoted respiratory tract infections and

01:28:03.680 infections in general to secondary endpoints. So we're looking at them prospectively. We're

01:28:08.460 collecting them more carefully.

01:28:09.780 That was in the second study.

01:28:11.260 In the second study. And again, the drugs decreased the incidence of respiratory tract infections.

01:28:18.780 The biggest effect was observed with just the catalytic inhibitor alone. The second biggest effect...

01:28:25.060 Wait, the catalytic inhibitor was a new molecule?

01:28:27.700 Yes, it's a new compound. It was, in that paper, it was called BEZ235. And this is the molecule

01:28:34.000 licensed by RestoreBio.

01:28:35.500 So BEZ235 is not RAD001 combined with something else?

01:28:41.560 No, we tested the combination and it also decreased respiratory tract infections. And the combination was

01:28:47.300 the best at improving the flu response. But the single catalytic inhibitor was the best at

01:28:53.800 preventing respiratory tract infections. This study had an extra arm. It was a somewhat bigger study,

01:28:59.360 264 patients.

01:29:01.520 Was this the one published two years ago?

01:29:03.420 Yes, 2018.

01:29:04.660 Oh yeah, yeah, yeah. A year ago. Okay. So let's now talk about the creation of RestoreBio.

01:29:10.440 So essentially the story is that we did the second study for prevention of respiratory tract

01:29:17.260 infections and enhancing immune function with mTOR inhibition. Worked again. Everybody's excited.

01:29:27.140 And Novartis, as in most big companies, big pharma companies, the research teams produce

01:29:34.640 more than global development can handle. And it's done deliberately. It gives early in drug development,

01:29:42.340 you never know exactly what's going to work best. You want to create enough opportunities so something

01:29:46.880 will be exciting. And the program transitioned to global development and they had a lot of exciting

01:29:53.040 things to do. And this fell below the funding line. It reflects in part the excellent productivity

01:30:00.400 of Novartis research. It reflects in part the great opportunities the global development has.

01:30:05.700 Of course, as the champions of the program, we were kind of disappointed.

01:30:10.100 But Novartis felt, and again, I'm speaking for myself now. I'm not a Novartis spokesperson,

01:30:15.360 but Novartis felt this drug looks like it could work and it could help people. We have to find a way

01:30:21.280 to make it available to people if it could work. So other pharma companies do this too. The decision

01:30:28.120 was to outlicense it. And Joan is the sort of originator of the idea and the biggest champion

01:30:35.820 wanted to go outside of Novartis and start a company. I introduced her to an absolutely awesome CEO

01:30:42.760 I know who was ready for his next role and they raised money and they created RestoreBio.

01:30:50.680 And that was a pretty quick path to going public. RestoreBio went public late in 18, didn't they?

01:30:54.940 It reflected in part the need for funds to run a phase three program.

01:31:00.460 Yeah. What did RestoreBio raise in the IPO?

01:31:03.720 You're asking me a hard question. I was at Novartis, but probably around 90 million, I think.

01:31:09.000 Wow. Yeah. So yeah, as you said, you're basically going right to phase three at this point. So you

01:31:16.240 licensed one or two molecules from Novartis?

01:31:18.760 RestoreBio licensed BEZ235, which is now named RTB101.

01:31:23.420 And they then did a phase 2B study. These two studies we had done were phase 2A, if you will.

01:31:31.000 Phase 2A, yeah.

01:31:31.780 Right. So in the first study published in 2014 that we've been discussing,

01:31:37.460 respiratory tract infections and infections in general were observed to be decreased in the

01:31:42.140 drug-treated group compared to the placebo by reviewing the adverse event listings. This was

01:31:47.540 not something we had considered a priori. But we recognized decreased infections could be a

01:31:53.840 consequence of improved immune function, which is why we looked in the first place in the listings.

01:31:58.600 And then in the second study where we explored a catalytic inhibitor, which is now RTB101,

01:32:06.500 RAD001, as well as the combination, we promoted respiratory tract infections and infections in general

01:32:14.560 to a secondary endpoint. And we specifically included collecting those data, both by patient reporting,

01:32:21.940 as well as investigator querying the patients at home regularly. And again, we saw decreased

01:32:30.820 respiratory tract infections. The best drug was BEZ235, which we now call RTB101 in terms of decreasing

01:32:40.300 respiratory tract infections. The combination also worked. Interestingly, the combination as well as

01:32:48.740 RAD001 improved the flu vaccine response, but the BEZ235 or RTB101 did not.

01:32:58.980 Remind me, it's catalytically inhibiting. So it's binding directly to TOR?

01:33:05.500 Yes.

01:33:05.940 And is it binding equally to TOR when bound to Raptor, meaning complex I, as it is binding to TOR

01:33:14.540 bound to Richter, known as complex II?

01:33:18.020 So the way this is usually done is in a cellular assay context. So we don't look specifically for

01:33:24.640 the binding, but we look for inhibition of phosphorylation of sites.

01:33:30.620 Of serine-6 or which one?

01:33:32.540 S6 kinase for TORQ1 and phospho-AKT there. And we look specifically at the phosphorylation site

01:33:40.100 that TORQ2 does, not the one that any other enzyme does. So we're able to see that a catalytic

01:33:47.200 inhibitor at high concentrations will inhibit both. RTB101 has some preference for TORQ1,

01:33:56.580 and it's a little different depending upon which cell you look in.

01:34:00.140 I wanted to come back to that because, and I've got to remember where we are in this story because

01:34:05.420 I don't want to lose this thread. So maybe we can agree to just park this again, but I definitely

01:34:10.900 don't want to leave the discussion of tissue selectivity. We've focused so much on C1, C2

01:34:18.620 selectivity, but we haven't talked about muscle versus liver versus adipose tissue, for example,

01:34:23.760 which you could argue you might want very different behaviors there. In terms of drug

01:34:30.260 design, drug pharmacokinetics, is it easier to target tissues or is it easier to target

01:34:38.920 enzymes, proteins, et cetera, when designing a drug or waving magic wands?

01:34:44.740 No magic wands involved. It's far easier to design a drug to hit a target. To hit the target in a

01:34:53.080 particular tissue is harder but doable. Sometimes you can do it in a deliberate designed fashion.

01:35:01.300 For example, making a prodrug that's cleaved to an active form only by an enzyme present in your

01:35:06.420 desired tissue. You also have to be mindful that within every tissue there are multiple cell types

01:35:11.820 and you want the drug in the cell type that will make the difference. And again, all of this is

01:35:17.660 possible and it's just how much time and effort you're going to put into it.

01:35:21.940 So when you go back to even the first experiment in 2014 and all of the animal data that came from it,

01:35:28.740 did you have a sense of where this was acting tissue-wise? Did you feel like you were acting

01:35:34.040 on bone marrow? Did you feel like you were possibly acting in the thymus? Did you feel like

01:35:39.340 you were acting in some other cell line that directly or indirectly was playing a role? I mean,

01:35:45.680 or did you have a sense that you were seeing this everywhere but it didn't seem to matter except in

01:35:50.900 the bone marrow? We thought it would be bone marrow and perhaps secondary lymphoid tissue,

01:35:56.340 which are lymph nodes or glands, but we didn't explore it exactly. In general, small molecules that

01:36:03.500 aren't specifically tissue targeted will often go to many tissues. We knew from toxicology studies with

01:36:11.040 the compound that it distributed to our target tissues. We felt we had enough information to move

01:36:16.980 ahead. Yeah. So when RTB-101 was basically the basis upon which RestoreBio was formed, correct?

01:36:26.360 That's right.

01:36:26.860 Now, I was very confused during your roadshow, which was about a year ago, maybe more than a year ago.

01:36:33.380 It might've been early 2018. I've sort of lost track. You were at Novartis at the time, so it

01:36:37.700 wasn't really your roadshow at the time. But I naively, I guess, thought that RTB-101 was actually

01:36:44.760 RAD-001, the Everolimus, combined with a PI3K inhibitor. So that's actually what I thought was

01:36:53.060 happening. And I remember even having discussions with other people looking at the data and saying,

01:36:57.140 is this what this company is? So I assume that this company out-licensed Everolimus combined with

01:37:03.780 a PI3K inhibitor. So how were we confused by that?

01:37:07.100 When RestoreBio was formed, it licensed RTB-101 from Novartis for all uses. And there was also

01:37:16.980 a limited license to use RAD-001 only in combination with RTB-101 for our indication.

01:37:27.220 Now, the phase 2B study that RestoreBio ran showed that the most effective drug or drug combination

01:37:37.860 for preventing respiratory tract infections was just RTB-101 alone at 10 milligrams.

01:37:43.820 And remember the previous study that Novartis had run had shown that although the combination was

01:37:50.540 best at augmenting a vaccine response, it was just RTB-101 alone, which at the time was called

01:37:57.860 BEZ-235, was the best at preventing respiratory tract infections. We believe this is because

01:38:06.740 the mechanism by which it prevents respiratory tract infections is upregulation of an interferon

01:38:13.800 stimulated antiviral gene response. Interferon, remember, is a substance in the blood that

01:38:22.780 upregulates many different proteins, most of which are involved in preventing viral infections.

01:38:29.600 And you need protein synthesis to make all of these proteins. And I worry that if we inhibit

01:38:36.400 mTOR for a long time, we can upregulate the genes, but they won't be expressed adequately. And there are

01:38:43.740 some literature data that you need mTOR in order to express the proteins induced by interferon.

01:38:50.200 So these experiments taken together suggest to you that, I guess it just reinforces this idea of

01:38:55.640 intermittent dosing. Not just intermittent within the week, which I think was clearly established by

01:39:01.720 the phase 2A study, but even applying a secondary cycle over the course of a year, for example.

01:39:08.800 I mean, you know that doing a 6 plus 2 once a year is probably not adequate.

01:39:14.620 So there's some frequency upon which you want to metacycle that. But the reason you don't just want

01:39:20.560 to go all the time taking it, presumably, is you might actually start to impair protein synthesis that's

01:39:28.980 necessary to, for lack of a better word, basically empower your new superpowers of immunity through

01:39:35.580 enhanced protein synthesis. Yes. Protein synthesis, there's several different kinds of protein

01:39:41.280 synthesis, and some are more or less sensitive to inhibition by rapalog. Mitch Weiss's very recent

01:39:48.840 paper, one of the interesting things I found in it was that there wasn't much of an inhibition of

01:39:56.020 hemoglobin synthesis, despite the fact that they were using fairly high exposures of a rapalog.

01:40:01.740 So I think there are some proteins that are sensitive to translational inhibition by rapalogs,

01:40:08.160 and perhaps some that are less sensitive. Before we go down this path of getting a little bit more

01:40:14.280 into RTB 101, I want to take a step back here and say, do you think that all of the benefits that we saw

01:40:20.960 in the ITPs across all these other species, if you think of the benefits that Matt Caberlin is seeing in

01:40:26.580 dogs, if you think of sort of the global excitement that exists around rapamycin and rapalogs,

01:40:33.420 how much of it do you think is mediated through what you guys are testing, which is you're clearly

01:40:40.120 enhancing immunity in a positive way, which could have at least two very distinct benefits. One is the

01:40:47.080 reduction of infection. The other could be, frankly, reduction of cancer through increased surveillance.

01:40:51.160 They're very similar. Viruses and cancer obviously behave or susceptible to the similar branch of

01:40:58.080 the immune system. Do you think there are other things that we haven't talked about yet, such as

01:41:03.120 increased autophagy, targeting of and or destruction and or desilencing of senescent cells, reduction of

01:41:10.720 inflammation, enhanced mitophagy? What other mechanisms do you think could be involved here and

01:41:15.980 what evidence exists to support or refute that? Well, I think we know from academic experiments

01:41:22.280 that every single one of those mechanisms can extend health span in preclinical models. We do

01:41:29.640 not know in people. And I think similarly to follow up our earlier discussion about what tissues you have

01:41:36.600 to inhibit mTOR in in order to get a clinical benefit, we don't really know the answer to that either.

01:41:41.880 It's been studied in some of the preclinical models. I can recall an experiment in the drosophila fat

01:41:47.260 body where inhibition of mTOR right there was sufficient to extend a fly lifespan. There's still

01:41:53.940 a lot we need to learn. What does your intuition tell you? How much of an overlap or parallel do you

01:41:59.360 see between the benefits of fasting and caloric restriction and the benefits of rapamycin globally?

01:42:05.440 Yeah. So one of the interesting things that we did and was done previously in a nature publication,

01:42:13.840 I think the author was Sengupta, was looking at the consequences of fasting on mTOR activity. In young

01:42:22.160 people, as you would expect, fasting leads to suppression of mTOR activity, activation of the

01:42:31.080 cellular recycling machinery, autophagy, suppression of protein synthesis and DNA lipid synthesis and so

01:42:39.240 forth, basically preparing for lean times. In old mice, that's impaired. We've only done the liver

01:42:47.060 tests in mice. So we back-translated this experiment and gave, actually I think it was rats,

01:42:55.740 it was old rats, doses of mTOR inhibition that corresponded to the doses we were using in people

01:43:03.040 that were well-tolerated. And then we looked at their ability to suppress mTOR. So in the old rats,

01:43:10.820 even with fasting, their mTOR was still active in the liver. In a young rat, it's suppressed.

01:43:16.280 So the young versus old had the same degree of inhibition to the same dose of rapamycin?

01:43:20.180 Well, you couldn't test in the young rats because their mTOR was already low.

01:43:26.840 Oh, but if you did it outside of the fast, I mean.

01:43:29.120 Well, certainly the exposures were the same. There was no age-dependent difference in exposure

01:43:34.460 of the liver or the blood.

01:43:37.160 That's interesting. Does that suggest that the older animal lost the ability to respond to the

01:43:44.200 environmental reduction in nutrient?

01:43:46.480 Exactly. Exactly.

01:43:48.460 Hmm. That's upsetting. Although it does explain a very interesting finding, which is everything

01:43:55.440 comes back to the 2009 paper. What really was interesting scientifically was that those mice

01:44:02.360 were 600 days old. Those were mice that if you fasted them, wouldn't have lived longer.

01:44:08.840 They'd already passed that stage where caloric restriction would extend their life. And yet their

01:44:14.380 lives were extended 15 and 25% by rapamycin. That was a big freaking deal.

01:44:22.200 Yeah. We published our experiments in that 2008 paper. It was sort of an interesting back

01:44:28.620 translation experiment where we treated the old rats based on what we do about the old people.

01:44:34.000 And of course we could do in rats. What we can't do in people is take their livers out and study

01:44:37.840 their mTOR inhibition. But we weren't the first ones to do that. There was a very good nature paper

01:44:42.600 that showed the same thing. Do you think this applies to humans? I mean, do you think that

01:44:47.500 intermittent periods of caloric restriction are not beneficial to people in their 60s or 70s,

01:44:52.560 which would be the equivalent of those quote unquote old rats?

01:44:55.120 The only thing that our group has been able to try is we looked at whether we could detect

01:45:01.280 mTOR activity as assessed by things like phospho S6 kinase in the peripheral blood leukocytes of old

01:45:08.200 people that we couldn't detect activity. We can't answer the question. I think we would need liver

01:45:12.920 samples under fasting conditions. Are you volunteering?

01:45:16.920 Yeah, I'm absolutely volunteering. No, I tell you, there's a lot of things I subject myself to.

01:45:21.160 I'm never excited about the liver biopsy. I just, I think that's the problem of doing a

01:45:26.940 residency in general surgery is you've had one too many calls down to the interventional radiology

01:45:31.240 suite with the patient that you have the recency bias of you only remember all the cases of liver

01:45:36.580 biopsies gone bad. All those hepatologists that have never had an issue, you don't hear about those

01:45:41.320 cases, but you hear about every one that. Yeah. There's sort of a referral bias. You never see the

01:45:46.220 thousand that go well. Yeah. You only see the one that didn't. Yeah. I don't know. I think at some

01:45:50.840 point I'll probably have to sign up for a liver biopsy. I think there's a lot going on there.

01:45:54.280 There's so many questions I have about the liver, especially my own. No liver biopsies. You can get

01:45:59.940 samples other ways, at least for this reason. But it is an interesting open question. And yet another

01:46:05.280 one of these things we don't know is, is mTOR suppressed in elderly people with fasting and in

01:46:13.360 which tissues. And by the way, do we know if autophagy is impaired in older folks with fasting?

01:46:22.820 Because autophagy and mTOR inhibition are not synonymous. That's right. They overlap, but they're

01:46:27.820 not synonymous. Yeah. Well, there's a lot of biology there and it's not only mTOR that can

01:46:34.580 trigger autophagy. There's other mechanisms. There's Becklin-1 mechanisms and so forth. But it's an

01:46:40.460 interesting set of experiments to do with a young group of patients and an old group of patients.

01:46:46.160 And there's a priming effect to this that I just don't, I mean, it's so multifaceted to study all

01:46:50.860 of these things. You think of the infinite combinations you can have, which is what's

01:46:55.860 the effect of RAPA plus fasting when staggered, for example? Does one prime the other? It's hard.

01:47:03.040 You can't really go on fishing expeditions with these questions. You have to be more thoughtful

01:47:07.140 in your hypothesis generation. There's just too many variables. That's right.

01:47:10.740 There's too many ways to be fooled. That's right.

01:47:12.880 So what can you tell us now about RTB-101? What has been published on this? In other words,

01:47:17.440 I don't think we can speak about obviously anything that's not published at this point,

01:47:20.100 or at least hasn't been publicly signaled. What's next for this compound?

01:47:24.420 So the excitement is in the phase 2A study that Novartis ran, we saw decreased respiratory tract

01:47:30.520 infections in elderly people treated with it. In the phase 2B study that Restore Bio ran,

01:47:37.760 again, the same dose, 10 milligrams once a day saw the same thing, a decrease in respiratory

01:47:41.920 tract infections. Now that study was a complicated study.

01:47:46.340 And did it also have an RTB-101 plus RAD-001 arm?

01:47:52.000 It did. And there was not a decrease in respiratory tract infections there,

01:47:55.980 but there was an increase in immunity or was that, that was a secondary outcome?

01:48:00.460 That was assessed, but it hasn't been talked about yet. The cool thing about the 2018 paper

01:48:05.800 that was published from the Novartis study is that because we saw a decrease in respiratory

01:48:12.080 tract infections, but we did not see an increase in vaccine response, it told us that the mechanism

01:48:20.020 for the decrease in respiratory tract infections had to be something different. And we had,

01:48:25.980 collected some samples for exploratory profiling, we learned that there was an upregulation of

01:48:32.880 antiviral gene expression in peripheral blood leukocytes. So a set of interferon-stimulated

01:48:40.340 genes responsible for antiviral activities was upregulated. So we identified a candidate mechanism

01:48:47.280 and it makes a lot of sense.

01:48:49.580 So to put that in English, it's not that the response was mediated by better recognition

01:48:56.040 of viruses. It was mediated by more efficient targeting of and or disposing of viruses.

01:49:03.100 Perhaps another way to say it is that the vaccine response we were measuring as the primary endpoint

01:49:09.180 was a lymphocyte acquired immunity measurement. So in other words, you're immune to flu because you've

01:49:18.220 been vaccinated. If you've been vaccinated for rabies, you're immune to that. I've never been

01:49:23.140 vaccinated for rabies. I'm not immune to rabies. In contrast, there's something called innate

01:49:27.940 immunity, which is the immunity of our species. This is an immunity that was developed because we have

01:49:36.000 all co-evolved with our pathogens. And those of us who are here-

01:49:40.220 Yeah. This is why the LPS on strep is, you don't need to be vaccinated to recognize it.

01:49:45.860 Exactly. So there are many, many, many, many other things that we can recognize,

01:49:50.260 elements of pathogens, so we can mount an effective immune response. And we're born with this. We don't

01:49:56.500 have to be immunized for it. And this part of the immune system is what mTOR inhibition can also

01:50:03.100 activate.

01:50:03.620 Yeah. Which is, to go back to historical, that's not what we care about in transplant.

01:50:09.100 No.

01:50:10.000 Because in transplant, you certainly didn't, we didn't evolve to reject kidneys. We evolved to

01:50:14.900 accept our kidneys. Therefore, we reject someone else's kidney. That's MHC-based.

01:50:20.240 Right. Although blood type matching of your organ transplants is for-

01:50:24.820 Well, that's true. And now they're doing so many ABO incompatibles that it's, I mean,

01:50:28.740 the immunology involved in organ transplantation today is remarkable.

01:50:31.720 A subject for another time.

01:50:33.160 I know. And all started at your alma mater. That was the Nobel Prize right there, right?

01:50:36.600 That's right.

01:50:36.980 Dr. Murray.

01:50:38.140 So is there anything else you can tell us? Because this is obviously something like,

01:50:42.420 have you guys spoken about what the phase three is going to look like?

01:50:45.100 Yeah. Well, we're almost halfway through.

01:50:48.300 Halfway through enrollment.

01:50:49.600 We enrolled the first phase three study fully and getting ready to start the second.

01:50:54.860 So tell us about the first one.

01:50:56.180 Yeah. So, well, let's do a little more on the phase 2B because that study answered several

01:51:02.060 questions in one study. We enrolled patients with pre-specified comorbidities and pre-specified

01:51:09.300 an analysis of them independently. We did doses. We did five milligrams and 10 milligrams. We did

01:51:16.300 a different schedule. We did 10 twice a day. And we did a combination with a rapalog, our RAD001,

01:51:22.900 with the primary endpoint of decreased respiratory tract infections. We also extended the dosing

01:51:28.580 period to cover a winter cold and flu season. So now we're dosing 16 weeks.

01:51:33.640 Uninterrupted?

01:51:34.580 Uninterrupted.

01:51:35.140 Okay.

01:51:36.140 Although with the once a day dosing, which is where we saw efficacy, we're only inhibiting

01:51:42.900 mTOR partially for part of the day.

01:51:45.920 By the way, if you had to speculate going back to the very, very first, the 2A with RAD0001,

01:51:51.620 if you had taken all four of those groups and measured them at the end of six weeks and then

01:51:59.360 after the two-week washout, what's your prediction as to how they would have differed?

01:52:03.720 I'm sorry, because we didn't vaccinate until, if we vaccinated at six weeks versus vaccinated

01:52:08.060 at eight weeks.

01:52:08.880 Correct. And you did comparison. In other words, I'm asking on drug versus off drug. How much,

01:52:13.740 I know why you had the washout, but is it also possible that on drug you would have the same

01:52:19.920 immune response? Yes. On the low doses, on the high doses, I'll bet we wouldn't have.

01:52:24.800 And do you define high as 5 and 20?

01:52:27.000 High as 20.

01:52:27.860 Okay. Got it. So you think the 5 and the 0.5 still would have had benefit on drug. 20 probably

01:52:33.520 got a benefit. In fact, that might explain the question I asked, which is why did they still

01:52:37.700 at least have one good strain response? It could have been that the two weeks off gave them recovery.

01:52:42.660 Could be.

01:52:43.040 Yeah. So back to RestoreBio, we figured it. And then the other element of the study is we ran it

01:52:48.900 in two different cold and flu seasons, one in the Southern Hemisphere, one in the Northern Hemisphere.

01:52:54.840 652 patients in the study because we answered a lot of questions. We found that some patient

01:53:00.480 populations responded well, over 85 patients and patients with asthma. Patients with diabetes also

01:53:09.020 responded. Patients who were smokers or had COPD did not. There are some preclinical data that

01:53:15.760 provides a mechanism for why this is the case in the sense that it's a different mechanism for

01:53:21.580 airway inflammation and smoking and COPD, and it's exacerbated by mTOR inhibition.

01:53:26.940 Oh, so I thought it was going to be a different way of antigen presentation or something.

01:53:30.060 I don't think so.

01:53:30.840 Okay.

01:53:31.080 The coolest thing about the study is that we saw the same degree of efficacy if we looked at the

01:53:38.320 patients in the Southern Hemisphere as in the Northern Hemisphere. It's almost as if there was

01:53:42.220 two sub-studies in this study. Now, each of the patient groups by themselves were

01:53:47.220 insufficiently powered to get any statistical significance, although overall, the patient

01:53:53.600 population did.

01:53:55.520 That's a bold study design move. That could have backfired badly, right?

01:53:59.400 Because if you had discordance between the Northern and Southern Hemisphere, you would

01:54:03.180 have been underpowered.

01:54:04.640 Well, the goal of the study was to look at the overall patient population, which we did,

01:54:09.020 which included responders and non-responders. And we saw a 30% decrease in respiratory tract

01:54:15.800 infections.

01:54:16.980 Yes, but you had two different strains of the flu, didn't you?

01:54:20.060 Flu was not involved here. There was no vaccination in this study.

01:54:23.820 Oh, sorry. I mean, what I mean is you had two different environments of viruses.

01:54:28.080 Yes, absolutely. Absolutely.

01:54:30.800 So you diluted, I'm just saying you loaded the deck against yourself. If you did everything

01:54:37.240 identical, but they were all in the same country, presumably you'd have a higher concentration

01:54:42.060 of pathogen. You'd have a better chance of seeing a signal is sort of all I was saying.

01:54:45.780 Yeah. I think you'd have a more consistent, you'd have a higher chance of seeing consistency.

01:54:50.080 That's right. And you had the lowest chance imaginable because you spread out across two

01:54:54.040 hemispheres.

01:54:54.640 Yet we saw consistency.

01:54:55.900 Yeah. So I think we're saying the same thing, which is it's more a credit to the finding.

01:55:00.800 Yes.

01:55:01.100 And I'm just saying, thank God.

01:55:04.640 Well, if the drug works, this is what we should have seen.

01:55:07.160 Yeah. It's just a big bet for a startup to take.

01:55:09.020 Yeah. And so now we've seen 10 milligrams of RTB-101 decrease respiratory tract infections

01:55:17.260 in the phase 2A and in each of the parts of the phase 2B. And we use the phase 2B to power

01:55:25.280 the phase 3 program. So the phase 3 program is-

01:55:29.220 And the primary indication is respiratory infection or all infection?

01:55:31.700 Respiratory tract infections.

01:55:33.400 And patient population is 65 and up?

01:55:36.160 65 and up. So the first study that we're calling the program, the protector program,

01:55:40.780 the first one is fully enrolled, 1,024 patients. They're getting 16 weeks of drug treatment and

01:55:47.920 we're following them for respiratory tract infections with sort of an electronic record that the patients

01:55:54.580 fill out. If we were just targeting this at Northern Hemisphere patients, is it your view

01:55:59.200 that the optimal 16-week window would be sort of May, June, July, August? How are you deciding when-

01:56:07.160 Winter, cold, and flu season.

01:56:08.740 Is when they actually want to receive the drug?

01:56:11.300 Yes.

01:56:12.360 Okay. So basically, so you're so confident that 10 milligrams is not too high that you're willing

01:56:18.780 to give them the drug during flu season or during winter, cold season?

01:56:22.540 Yes.

01:56:22.820 All right. So let's turn over to something else you brought up earlier, which was the

01:56:28.060 Laming paper that came out about two months ago. That's a prolific lab. Laming was a postdoc in

01:56:34.520 David's lab. So no stranger to this science. There are lots of folks out there that are working on

01:56:40.580 selective mTORC1 inhibition, notwithstanding the potential ways around it through intermittent dosing

01:56:46.520 or looking at catalytic binding or things that might be off you a little bit more insight.

01:56:52.040 What is your take on the biochemistry of selective binding and selective inhibition

01:56:58.500 more specifically? The binding is quite selective.

01:57:02.380 Yeah. I thought basically to summarize that paper for the listeners, the Laming group looked at,

01:57:09.020 I think it was 90 different rapalogues, presumably related to rapamycin, and looked for their ability

01:57:19.820 to be selective for TORC1, even with more sustained exposure. Then they identified a couple that were,

01:57:28.420 and most of the paper was on one that they liked the best. The really cool thing, and this is going to

01:57:34.840 get us into an immunophyllin discussion, is that they found possibly the reason the compound was

01:57:41.680 selective was that it bound to one of the immunophyllins, but not another. So specifically,

01:57:48.900 it bound to FKBP12, or at least FKBP12 was required for the compound to have activity,

01:57:55.760 but another FKBP51 was not. But I still don't understand this. If you bind to FKBP12 and then

01:58:05.480 the rapalog plus FKBP12 binds to mTOR, don't you still get into the same problem where after a long

01:58:14.300 enough period of time, you don't have enough TOR to make complex II? I don't think that's why complex

01:58:20.700 II is inhibited. What do you think rapamycin specifically is doing to inhibit complex II then?

01:58:25.760 I think it's a downstream and indirect sort of counter-regulatory signaling mechanism.

01:58:32.160 I see. So it has to do more with sort of the serine kinase or the 4EBP1 or something like that,

01:58:37.840 like something downstream of a direct phosphorylation is counter-regulating or...

01:58:44.480 Yes.

01:58:44.980 Yeah, I see. And you're saying presumably if you only bind a rapalog to FKBP12,

01:58:52.020 you somehow don't hit that target? Well, I think what their data say is because the compound that

01:58:59.240 they show has no TOR2 activity at all, does not bind to FKBP51, or at least that's the implication

01:59:06.700 because down-regulating FKBP51, which I think they did within siRNA, had no effect on its inhibitory

01:59:15.520 activity, suggests that there's a complexity to the complexes formed, sorry for that, that we don't

01:59:22.840 yet understand. And it's an exciting area to explore. So remember, every cell has many

01:59:28.760 immunophyllins in it. It has several cyclophyllins. It's got several FKBPs. So FKBP12,

01:59:36.960 51, and 52 are probably the big three, but there are a few others.

01:59:41.560 By the way, I thought RAPA only bound to 12. RAPA binds to what?

01:59:45.460 They showed that it binds to at least 12 and 51.

01:59:49.080 Okay. I mean, that's amazing. I had always thought that RAPA binds only to FKBP12,

01:59:55.900 which then binds to TOR. I didn't even realize it was binding to 51.

01:59:59.480 So we know it binds to 51 in their paper, and there've been some other papers studying the

02:00:03.600 ryanidine receptor that show that it binds to 12.6 also, which is in cardiac myocytes.

02:00:10.860 We've talked all about inhibition. Are there any times when you want to be activating this?

02:00:15.820 There's a lot of talk that ketamine may be activating mTOR, and obviously ketamine has

02:00:21.880 some really interesting properties as it pertains to recalcitrant depression.

02:00:25.420 Yeah. So two points here. For patients with major depression, intravenous ketamine is almost a

02:00:35.300 miracle drug. We're accustomed to typical antidepressive drugs requiring weeks and weeks

02:00:42.820 to work and having modest effects at best.

02:00:46.140 Or even days, but this is minutes.

02:00:48.740 Ketamine works in minutes to hours and a huge effect size. It's really amazing.

02:00:54.180 I don't think we know what the specific cellular mechanism is of that. I'm giving you lots of

02:01:01.640 things we don't know in our discussion.

02:01:03.740 Wasn't there a study that showed rapamycin blocked the effect of ketamine?

02:01:08.200 Yes. And there's a biotech company called Navator.

02:01:12.020 I know them well.

02:01:12.940 And they're using an mTOR activator to treat depression.

02:01:17.020 Their Lloyd equivalent is also a very smart guy. George is fantastic.

02:01:23.380 Yeah. So Lloyd, is this a relatively recent understanding then about how RAPA is binding

02:01:29.040 to the FKs and how it's the complexity around, first of all, how many of these things there are

02:01:36.180 and how you can change their properties by which ones you're binding to?

02:01:40.220 Yeah. So it's something that's not discussed a lot in the literature, but there are several

02:01:44.980 FKBPs or FK506 binding proteins. We almost always talk about FKBP-12 and it's sort of a shorthand,

02:01:55.280 but the understanding has been that rapamycin binds to all of them in a few specific cases that's been

02:02:01.320 shown to be true. There's also a bunch of other activities and roles for FKBPs that aren't at all

02:02:10.320 part of TORC1 biology. For example, they all have an enzymatic activity. They're peptidylprolil

02:02:17.120 isomerases. But what the biology of that is remains pretty much unclear. It's a very interesting

02:02:25.800 enzymatic activity. It's involved in protein folding, but there've been some studies where

02:02:31.480 maybe a dozen different of these immunophyllins are completely eliminated at the same time from cells.

02:02:37.360 There was no clear cellular phenotype. So whether that means the others can all substitute because

02:02:42.940 it's such a critical function or they have no function that's important.

02:02:47.920 Are there disease states where people are lacking any of these?

02:02:51.920 There may be, but I don't know them.

02:02:53.780 And how conserved are they across species?

02:02:56.840 Highly conserved. These immunophyllins are present in almost all species,

02:03:00.920 although they can vary a little bit.

02:03:03.040 Is there any cell in the body that does not contain mTOR?

02:03:06.160 I would bet some of the terminally differentiated anucleate cells may not.

02:03:12.760 Red blood cells, for example, do?

02:03:14.940 Certainly red blood cell precursors do. I was thinking about platelets, for example. I don't

02:03:19.980 know if they have mTOR.

02:03:21.220 Yeah. Yeah. Interesting. And I bet that's known. It's just, I don't know the answer. And I feel

02:03:26.380 better that you don't. So now we need to make a list of David Sapatini questions.

02:03:30.280 Well, I'll make sure David listens to this and you know what, maybe we'll do an AMA with David

02:03:33.900 specifically on TOR. So last thing I want to chat about, because the paper came out kind

02:03:38.220 of recently, was this sort of interesting paper. It's interesting, not in the sense of the

02:03:42.440 intervention because it was an N of nine and it was a very poorly controlled study in the

02:03:47.620 sense that there was no placebo group. And every patient actually was on their own sort

02:03:51.820 of tailored cocktail of three different drugs or two hormones and a drug. But the paper did get

02:03:58.100 a lot of press because it used an epigenetic clock. Are you familiar with these clocks?

02:04:02.880 Yes. Yeah. This is the Horvath's work, right?

02:04:04.760 Yeah. Yeah. Horvath's probably the best of these clocks. Maybe it's just a little bonus

02:04:09.380 episode. Tell folks how these things work, what they're measuring. We've already talked

02:04:12.520 a little bit about methylation. So maybe we put a bow on this by discussing that.

02:04:17.960 So I forget how many years ago it was now, but it wasn't that many that we learned from

02:04:26.100 Horvath and others, that by looking at the methylation pattern on peripheral blood leukocyte

02:04:33.020 DNA, we can tell how old you are within about six months to a year. And this has been replicated

02:04:38.700 by several groups. So we're all familiar with DNA.

02:04:43.920 And that's even true among centenarians and people that are just genetically blessed to live

02:04:49.120 longer?

02:04:50.100 Excellent question. The studies that I've seen, and actually the one that we participated in,

02:04:55.480 I don't think we had people over 80.

02:04:58.780 Okay.

02:04:59.260 I don't know the answer to that. But for people between about 20 and 80,

02:05:04.940 there's a stereotypical change in methylation patterns on DNA. And this is just a chemical

02:05:13.560 change to DNA that happens over time. That's quite characteristic of your chronologic age.

02:05:20.400 This is the, what David Sinclair talks about as sort of the scratching of the CD.

02:05:23.540 The CD being the master copy of your genomic.

02:05:28.140 Yeah. I guess we have to say something like that because we can't use wearing out of the

02:05:31.920 vinyl anymore. But I think about it a little differently. I think about aging fundamentally

02:05:39.300 as a biologic process controlled by pathways. And presumably it's a consequence of changes in

02:05:47.820 gene expression. And this methylation changes gene expression. So it's a pretty cool story.

02:05:55.060 And certainly we know that if you take a differentiated cell and treat it with a set

02:06:01.460 of transcription factors called the Amanaka factors, you can reset the cell back to a

02:06:06.360 pluripotent stem cell. And the methylation goes away too. So I'm thinking that DNA methylation

02:06:13.780 likely, could be, causally related to the gene expression changes that not only are associated

02:06:22.620 with aging, but may cause aging.

02:06:24.740 So has anybody looked at the effect on the Horvath clock or DNA methylation in response

02:06:31.420 to the rapologues we've been discussing today?

02:06:35.100 I'm thinking of one experiment, but I don't know that it's published yet. And I think the

02:06:39.140 answer was negative.

02:06:40.460 So it's interesting because the paper that I was talking about, again, there are 10 ways

02:06:44.920 to Sunday. This could just be an outlier, especially without a control group. I mean, it's really

02:06:50.000 difficult to make any conclusion. But if any of this benefit was real, which was growth

02:06:56.240 hormone DHEA and metformin set the Horvath clock back, I think it was a year and a half

02:07:02.120 or two and a half years. The initial hypothesis of the experiment was that this was going to

02:07:08.200 improve thymic function, which was going to improve immune function. It doesn't seem like

02:07:12.640 a stretch that you could potentially see that benefit from a rapolog if it's also acting

02:07:19.320 on immunity, which is why I think I was sort of, that's probably why I asked about the thymus

02:07:23.620 in the past.

02:07:25.360 Yeah. So I have a few comments about this. One is first DHEA we know goes down substantially

02:07:32.600 with age, but there've been several to many studies of replacing it and there's no clinical

02:07:39.500 benefit. And I think the author used it for the effect of reducing the hyperinsulinemia that

02:07:47.300 follows the administration of growth hormone. And in his, I think, personal experience taking

02:07:53.280 growth hormone noted that he could blunt the hyperinsulinemia by taking something like 50

02:07:58.880 milligrams of DHEA by itself. But again, that's not something that's well-documented in the

02:08:03.920 literature. And your point, of course, is documented, which is DHEA by itself. You can fix the number,

02:08:08.980 but that doesn't seem to have any clinical bearing.

02:08:10.860 Exactly. My second point is the growth hormone, the biologic activity of it is mostly driven,

02:08:20.660 not exclusively, by IGF-1, which used to be called, I think, somatomedin when we were in medical school.

02:08:28.760 We know that lymphoid tissue is probably the most sensitive target organ for IGF-1,

02:08:35.960 and it causes hypertrophy. So if he's looking for enlarged thymus in patients he's treating with

02:08:45.600 growth hormone, I would be surprised if you did not see that.

02:08:49.420 And he did. And so the question is, wouldn't you have expected that to have sped up growth?

02:08:55.100 I would have expected, if he treated long enough, I would have expected to increase the size of the

02:09:00.040 thymus if he could find it in people.

02:09:01.860 I believe the study looked at MRI and showed an increase in thymic size. They were treated for

02:09:07.580 a year, I believe.

02:09:09.020 Not surprised at all. I bet the spleen increased too.

02:09:12.680 Is there any reason to believe that that would enhance immune function?

02:09:16.780 I'm thinking if I've read a paper about that, and I don't know.

02:09:21.140 And then what about the metformin wrench in the works?

02:09:24.060 Yes. Metformin is a really interesting compound. I think we have excellent data that in diabetics,

02:09:31.960 it is a wonderful drug. And there's some retrospective data of longevity in diabetics

02:09:38.900 treated for a long time with metformin. And of course, this is the question Nir Barzilai

02:09:42.980 wants to answer with the TAME study.

02:09:44.680 Right. And Nir and I have spoken about this many times. And I agree that it's hard to make the case

02:09:49.820 for a more beneficial agent in someone with diabetes or hyperinsulinemia, metabolic syndrome,

02:09:55.860 or anything on that continuum and on that spectrum. Of course, the question is, what is the benefit of

02:10:01.200 metformin in a perfectly healthy person or even a fully optimized person with respect to other

02:10:06.740 variables?

02:10:08.040 I'm not aware that there is a benefit of it. Remember, it has some adverse effects on mitochondrial

02:10:13.100 function too, potentially.

02:10:14.220 It's so funny you bring that up. That's exactly the question that I think most plagues me, which is,

02:10:21.400 if it is a weak mitochondrial toxin, is any benefit that you might see in a non-diabetic

02:10:28.020 more than dwarfed by that downside? Whereas even the simplest benefit of it, like a reduction in

02:10:34.720 hepatic glucose output in diabetics might more than make up for the sort of inhibition of mitochondrial

02:10:39.920 function.

02:10:39.940 Yeah. I don't think we know the answer to that question.

02:10:41.600 It's one I'm super interested in and working on. I'm actually going to volunteer for a study that

02:10:46.440 will take some muscle biopsies and look at peak mitochondrial function, which you can induce

02:10:51.320 through certain types of exercise with and without metformin.

02:10:54.480 Interesting.

02:10:55.120 Yeah. Well, Lloyd, this has been just a fantastic discussion. I am so grateful for the introduction

02:11:00.880 that Tim made. And it's been an honor to sit and speak with you. You know, I had tried to reach

02:11:05.480 out to Joan about a year ago. I never heard back. So I'm gathering it was just too busy a time.

02:11:11.120 But in many ways, it was better to get to talk now because so much more has happened in the last

02:11:15.660 year. And maybe that might've been just after the IPO. So it was a very busy time.

02:11:21.000 I'm guessing my email went to spam, but this has worked out really well. And I'm incredibly

02:11:25.520 grateful for this. I wish you all the continued success with this program.

02:11:28.700 Well, thanks. We remain optimistic and we will have top line data from the first phase three

02:11:33.960 by the beginning of 2020. So the data will speak for themselves.

02:11:38.560 Well, we'll count down the days till we see it.

02:11:41.320 It's been a great discussion. I've enjoyed being here. I feel like I've said,

02:11:44.620 I don't know an awful lot. I'm feeling a little bit like I'm back in school,

02:11:47.840 but it's been fun and I have some homework to do. Thanks.

02:11:51.540 Well, I think that's one of the beautiful things about folks that come on this podcast is

02:11:55.320 great scientists saying, I don't know, probably more than they know the answer. So that's,

02:11:59.540 I think a testament to your honesty, but thank you, Lloyd. Appreciate it.

02:12:02.140 Thank you. Thank you for listening to this week's episode of The Drive. If you're interested in

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The Peter Attia Drive - July 06, 2020

#118 - Lloyd Klickstein, M.D., Ph.D.： Rapamycin, mTOR inhibition, and the biology of aging

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