Pramod John: I'm probably a little bit different in that I don't have a Pharma background. As it turns out, I will acknowledge everybody on the call that I've never taken a biology class in my life, unfortunately. But I have taken a lot of mathematics classes and so I see a lot of, if you will and I will ultimately talk a little bit about it, but came to the conclusion early on that medicine was really a science and science was about data and facts. And, as we'll talk a little bit more in this presentation, we seem to see that there's a bigger and bigger gap between the facts and the data and how we practice medicine. And our hope obviously is that we can bridge those gaps because our area of interest is obviously in better outcomes for people because that's why health care exists. Every medical intervention ultimately is about bringing either improved life expectancy or quality of life to somebody. And especially when we think about medications, because we're talking a lot about medications in our area of interest, it is driven by research. It's driven by trials. It's driven by data. And it's an area unlike a lot of other parts of medicine where we should expect to see the most data, which we have compared to other areas of medicine and as a result, we should expect to see the use of the most data in the way that medicine is practiced but unfortunately, as many of you probably know, much better than even I do, that's not always the case. And so, I'm actually from the high tech space. I've done a few ventures in the computer security space and then I sort of decided to change gears because I felt that health care was our biggest national social problem affecting our economy in the United States and so that's how I got to the health care space. I worked at McKesson, which is one of the largest health care companies in the world for a few years. And this was one of those experiences of the everything you thought about the way the health care system worked was wrong, type of experience.

I don't know if that people will be able to see this, but we've thought we'd start with the pop quiz, and again, I want to be upfront, a lot of this is US system specific, but there are many aspects that you'll probably see that are actually not US system specific that are actually global problems in the way the health care is ordered. But we thought we'll start out with the pop quiz and I don't know how easy it is for people to answer, but maybe in the chat window if you've got an answer, feel free to pop something up.

1. For a drug to get FDA approval, it must have what:
2. A statistically significant result
3. A clinically important result
4. Both results

And the answer is actually B, neither of the results, which was a big revelation to me personally coming from outside of this space.

2. What percentage of physicians and researchers responsible for developing the NCCM guidelines reported financial ties to pharmaceutical manufacturers.
3. 0%
4. 20%
5. 50%
6. 90%

And so again, take that guess as to what you think those are. Our estimate, over 90% of the population.

3. In a study conducted by the BMJ what percentage of cancer drugs that received accelerated approval were withdrawn from the market in 2021 after failing to improve the primary endpoint in post approval studies.
4. 0%
5. 10%
6. 20%
7. 60%

And this is a study that came out in a couple of years ago and the answer that is 60%.

4. Physicians that receive money from Pharma are what percentage more likely to prescribe a brand name drug rather than a generic alternative.
5. 0%
6. 50%
7. 200%
8. 400%

And then that came in at 200%. So clearly we're probably not great test designers because all the answers were centred around C and D

A little bit about Vivio and about us and what our mission is. So our mission as a company is to use data to ensure that every patient is on an effective drug therapy at a fair market cost. Because the 2 things that we're seeing today in the market is that often people are not on effective drug therapies and we'll talk about some of those reasons why and the costs are not fair. And we'll talk about why those are sort of, especially from a US system perspective, why those things are true. And our goal is really how do we use mathematics data and systems engineering to sort of reinvent the way that we do medicine. And just as a question about the structure of our company, we're a public benefit corporation and so our goal is really that there is a public benefit associated with what we do. And our goal is to improve the quality of health care. And we would argue that today, especially in the United States,  healthcare has become a public trust, and unfortunately it's turned into a public trust fund rather than as a public trust. And our goal is really as a company to figure out how to change that.

Let’s ask how do we define success? And this goes back to I know we started off in a lot of our conversations about the US healthcare system. But our definition of success is we want to change the way that health care is delivered globally. And when we think of health care, our piece of that pie, specifically with one type of intervention, medical intervention, which is medications and how medications are used. And so our hope is that we can change the way that physicians prescribe medications because we think that there's a gap there in how physicians use the data. And we see that gap, not just in the prescribing patterns, but we see that gap in how physicians are trained, how physicians use data in their practice, for example, and we think that we all can do better in those areas of medicine and being able to use that data better. One of the things that we often in our sort of practice, in our ventures in this space we find that, if you think about the medical education system today, there is very little emphasis on clinical trials. How to interpret clinical trials, the mathematics behind clinical trials. And sort of comparative effectiveness, all those things that we normally think about, but starting with the baseline of the trials themselves. And we see that that's a big missing part of the medical education system. And if you ask the question about why is that important? When I was in McKesson, we had MBA interns every year and I had 2 or 3 interns. We were contemplating this question of Medications, what's their frequency as a medical intervention compared to all other medical interventions? So imagine that when you go see your physician and they prescribe an antibiotic, or they give you a vaccine. Those are all interventions using a medication. , contrast it to an intervention that could be I have surgery. And if you think about probably on the call on everyone's personal lives, the number of times that you've had a medication intervention compared to when you've had some other type of medical intervention. Our estimates were it was almost ten to one. Of all other interventions put together. And that makes sense in our lives. We take drugs all the time for all sorts of preventative, non-provenative things. But the number of times that most of us are probably had surgery or something else of a medical intervention in one of those cases is actually very low. And so what's mind boggling about this is the fact that if medications are the most common medical intervention, we would assume that in the medical education process that would be the one thing that is emphasized more than anything else. And today we see almost the opposite. It's one of the things that's least emphasized in the medical education process. And so not only do we want to help or change the way the doctors prescribe medications and their use of data, but that will also lead to more pressure on pharmaceutical manufacturers to come out with drugs that actually offer improvements for members. Today we're going to talk about a lot of drugs that are being created and especially in the US where we pay for them and often in other countries they aren't paid for. But we pay for a lot of drugs that have shown no benefit whatsoever and what ends up happening in that world is that A Yugo and a Ferrari look exactly the same and we're willing to pay the same price for a Yugo as we are a Ferrari because we can't tell the difference between the 2. And that's what we have today in a lot of ways within pharmaceuticals in the United States especially. And we believe that there should be a level playing field. And the reason why a drug should command any price is because it can demonstrate clearly what it does for the patient.

Let’s take a step back for a second and ask there's a lot of discussion about this question of value. And we don't really see that it's defined well and we don't necessarily see a lot of ownership around the question but what is value? So we defined value as improvement in quality of life or life expectancy as the function minus side effects, because often it seems like we consider side effects to be something different, divided by the cost of something. So we think that's probably the simplest way to define at a higher highest level, how could we think about what value actually.

So the next question that we want to ask is. But okay, let's define value, and agree on some definition of value. But now the question would be, but whose job is it to prevent low value care? And again, I want to be clear that we're talking about the United States in this talk primarily, but if you look at the United States, we have a lot of parties involved in the patients care. And those for the drugs it starts with the drug company. Well clearly the drug company wants to sell something. They don't consider it their job to prevent low value care. And then we have folks like the FDA, for example, who people think that there's a there's a responsibility on the part of the FDA to prevent low value care and the answer to that is no, if you look at the approvals process, which we will go through in a little bit you'll see that that's not the case. Their focus is not on effectiveness. Actually there are no objective standards on effectiveness at all. Now there are things like relative standards on efficacy, but there are no objective standards on effectiveness itself. And so then we think about physicians because they're primarily the only party that can prescribe and actually in most countries prescriptions can only be written by physicians. And if you go back and look at, especially in the United States, there are a lot of new drugs on the market. There's declining reimbursements for the physicians time. On average a physician gets 7 min or less per patient and often they have no visibility into what a drug action costs. There's the patient and the patient generally their focus is not necessarily clinical. They just want to be better and they don't care how they get better. Their focus is on them getting better for themselves and they tend to trust the physicians and unfortunately they also trust things like media because it’s shaped so much of the way that we think about the world outside of health care it ends up also changing our perceptions of how we think about health care as consumers. Employers in the US for employer funded plans, about 50% of American healthcare just around there is actually paid for by employers in this case and they have limited visibility. It's something that they don't necessarily understand and it's something that they don't necessarily feel that they can control. Then there are parties in the middle like pharmacy benefits managers, health plans, etc, who work on behalf of employers or consumers or states or governments, etc. And their focus is supposed to be on how do we make sure that everybody is getting the most cost-effective care and highest value care? But if you look at their business models. Largely their focus is on procurement and the way that they make money is by when utilization goes up or costs go up, they generally make more money. Which is exactly the opposite of the people who pay for the care and for the people who receive the care. So you've got a problem in the fact that for them the parties who have control over what's going on are also the ones who are economically incentivized to do something that's very different.

Our area focuses on specialty drugs. And so we'll talk a little bit about why we're focused on specialty drugs, but when we think about drugs overall, when you look at sort of volume of drugs in the United States, roughly 4.5 billion prescriptions filled in a year. About 2% of those are speciality drugs, about 8% are BRAM drugs and about 90% are generic drugs. But when you look at where the dollars are distributed, it looks quite different as of end of last year it's actually now 55% of drugs are specialty and they're used by slightly less than 2% of the population. And what's also interesting is that there's been a lot of press about Mark Cuban, Amazon, a lot of these new efforts that are focused on bringing lower cost to the drug markets. And primarily their focus has been in the generic drug space. Now there's a small slight shift with Mark Cuban now getting into specialty with the Humira biosimilars for example, and a couple other brand drugs that they that they distribute on the market. But primarily their focus has been on generics which only account for 15% of our drug spend. Our internal estimates were that we could probably give away 9 out of 10 of those generic scripts to every American it would probably cost us 5% and the drug manufacturers for generics manufacturers would make more money and it would cost us less because we don't need all that infrastructure to give away 9 out of 10 drugs, which account for the majority of all drug interventions in the US. Now, one of the other sort of crazy stats for you is that if you look at the population of the world, the United States only represents about 4% of the world's population. And in 2020, if you look at the united states and the drug spend itself the drug spend came in at about 49% of the overall world's drug spend. That means that 4% of the world's population spends almost exactly as much as the 96% of the world's population put together. And if that if that isn't crazy and as an American if you aren't offended that I don't know what's going to offend you because there is no good reason for this chart to look this way.

Let's talk about some of the reasons why. Why is it that it works this way? Well, we see that one of the biggest problems that we have is that everybody in the supply chain makes more money today. The regulators, over 50% of their revenues come from fees that are paid by pharmaceutical manufacturers. And if you look at the FDA, you'll also see the FDA is a revolving door into Pharma. I mean, people lose very little time between when they leave the FDA and when they end up in Pharma, which tends to be their next job. I mean, take a look at Scott Gottlieb, for example, and how many days there were between a board seat in the pharma company and leaving the FDA. When you look at folks like PBMs, as  now PBMs have not only started to make large amounts of money in the US, but they're moving a lot of their profits offshore through GPOs that now collect all rebates. And so a lot of money is now being held offshore now for these PBMs who own these group purchasing organizations. And as you can see, they make a large amount of money, which is tied to either the utilization increasing or the cost of drugs increasing. Physicians, and you've probably seen the Sunshine Act, the open payments, etc and you look at a lot of  physicians you find there's quite a disparity of physicians who receive everything from large amounts of money to small amounts of money like, for example, someone bought me lunch if I were a physician and there's quite a range there. But the more insidious thing isn't even that range, it's the amount of research funding that is provided by Pharma. Imagine you're an academic medicine. Where is the primary area that you're probably going to be doing research, drug trials. And if you're doing drug trials, who's going to be funding that? Pharma. How many physicians could actually provide data that went contrary to what the pharma company wanted? Well, it turns out you can't publish any data because nondisclosure agreements prevent you from doing that and generally speaking, you don't have any information on the trials themselves post the trials either. So it's quite a situation in which now even inadvertently physicians’ decisions and what they can say is being influenced by pharma in a very negative way. Then we have medical journals, right, and their editorial committees and they're preprints and you've all probably seen the work that's been done showing how much money comes to medical journals indirectly and how much influence Pharma has where they're supposed to be independent and today we see they're not independent. We also see things like free samples. This is almost the get somebody hooked on a medication and then it's hard to make a decision to get them off afterwards. And we see pharma companies using these mechanisms by large amounts of free samples getting people on their drugs whether it's a right drug or not, and about 7 billion dollars in consumer advertising and then we also see the insidious effect of government lobbying to the government in the United States.

Some of the other problems are, again,  we represent, I believe it's 2 countries in the world that actually allowed direct to consumer advertising. And it's very troubling that not only is there advertising, but it's just such false advertising. This is an example that came out of the Olympics. It's Ryan Murphy talking about what a great drug this is and then in the very fine print, which they've intentionally, here's the beauty of it, do you guys see how that on the third graphic? They have intentionally put a white object, , those lines, marking lines in the background and they put the part that Ryan Murphy's name is clearly visible, but that does not take Emgality is very hard to see because the contrast of the white object in between. So I mean, when you look at something like this, the contrast of the white object in between. So I mean, when you look at something like this, you realize this is intentional deception. And part of the problem here isn't just that consumers see this, is it how they imagine physicians also in the way that they practice medicine? They also see these ads, a physician is still a consumer before they're even a physician. And it turns out that a lot of the techniques that are used against consumers work just as well on the medical professionals themselves.

When we break it down a step further and look at, well, what about the FDA and what about FDA approvals? In the United States, there's very little understanding of what an FDA approval is or the different approval types. We see the statement all the time where people use things like it's approved by the FDA or it's not approved by the FDA but we all very rarely see any understanding of what does an FDA approval mean. Or more importantly, what are the different types of FDA approvals and what do these types of approvals mean? And today, American society has been almost pre-programmed to think that FDA approval means that a drug works. And we're not really critically asking the question of, but what is an FDA and what is an FDA approval actually mean. Now, as far as consumers go, of course, this would be great information, should be great knowledge, but where we see sort of the biggest divide here is in areas of both of medicine, of physicians themselves not understanding what the different types of approvals are and what they mean and the limits on what those approvals are and the data behind it. But also people who are in public policy of any form. Of health care policy, we see a real disconnect in health care policy. And one of those areas where you could see that disconnect sort on a daily basis was the arena of when COVID and the first vaccines and things were coming to market and listening to experts in the market talking about what an approval was, what an approval meant. You could see this disconnect and understanding on what an approval actually is and the different kinds of approvals.

So here's an example of an FDA approval that In some ways this was one of the best things that could have happened and this was last year when the, when the Alzheimer's drug Aduhelm made public front page news in the United States. And what's fascinating about this example is that generally speaking, this example isn’t something that's new. That Aduhelm wasnt the first drug that didn't have any evidence when it was approved, but it was the first drug because it had a lot of public scrutiny around it. And the public scrutiny came around because, in this case, it was scrutiny because the primary payer for this drug would have been Medicare and now it's public funds that are used to pay for this, not that a lot of other things are public funds. But it just doesn't have the same level of disability. That other things do. But in this case, because it seemed like a direct Medicare expenditure, there was a huge amount of press and that press was actually a good thing because for the first time physicians and consumers and policy makers across America were asking the question as a result of this but then what does the FDA actually do? And if you think about, let's go through the history of this drug. If you look at the trial data behind this, there was no evidence of benefit whatsoever. And let's define what the question of benefit is. The question of benefit is not a surrogate endpoint in this case, which is not correlated to actual improvement in life expectancy or quality of life. In this case, benefit would be defined by a demonstrable improvement in either quality of life or life expectancy. And there was none whatsoever in this case because again, the drug was looking at a surrogate endpoint in this case, amyloid plaque is the hypothesis in this case, which is at best a hypothesis and at this point, there's conflicting data and stronger data potentially that it does not and is not correlated to Alzheimer's disease and this was a primary endpoint in this case. And as you can see, there was no benefit. But 41% of the population had severe side effects and almost everyone had some form of side effects in this case. And what was interesting about this approval in this case was that for the first time, a hundred percent of the FDA advisory committee voted against this approval. And the FDA went ahead and approved the drug anyway because of pressure from patient groups and as  a lot of these patient advocacy groups are in fact funded by the same pharma companies who benefit from the drugs being approved. And Medicare also as a result of that announced the largest price increase in Medicare's history for there was this and one other reason that contributed to those price increases. And so this was a case where we saw a direct correlation between something being approved and costs going up. And we also, and in retrospect, one of the other things that happened, some very notable folks like Aaron Kesselheim at Harvard and other people actually quit the FDA advisory committee as a result of this approval because they said this is crazy, that the FDA approved something that has no evidence whatsoever. And again, this has happened many times before, but this is the first time we saw a mass exodus from the advisory committee. By the way, just recently, we saw something very similar occurring, but this was for a Sarepta pharmaceuticals drug that was approved and in this case, the person at the FDA actually went against the panels inside the FDA where every one of the committees within the FDA that had looked at the Sarepta pharmaceuticals drug at all, had all stated that there was no evidence of benefit whatsoever within the FDA and the person who actually was ahead of that area went ahead and approved the drug, even though all the groups in the FDA provided data that there was no evidence at all. And so this was a case of where clearly points out that there are serious problems with the FDA and the process with the United States. Not only, , so you've got the case of where the advisory committee votes against it and the internal committees vote against it and it gets approved anyway. That is not how public policy and regulatory agency should be run. It's clearly a case of this is as an agency that needs reform in this country.

One of the other problems we see is that there doesn't seem to be a general understanding of what the definition of working actually means. A little story about my own background of when we started video in 2016 our chief science officer who was involved in drug research at Genentech and especially R&D and he was also the medical director for several plans he asked me one of those questions which sort of changes your perspective on many things and it was this question was have you ever read a clinical trial before? And I said, no, I'd never even thought about the question of a clinical trial. I'm not a physician why would I care about clinical trials? And like most people in life, I've always assumed that the physician who's prescribing this must have read the clinical trial themselves. And he said, hey, I'd like you to read these trials. And so he sent me a bunch of the trial data on Humira and a lot of the common specialty drugs and that for me was one of those eye opening experiences in life and it was an eye opening experience for me in life because of 2 things. One was because for the first time I realized I kind of understood the details of the mathematics and the trial. I may not have understood all the details of the mechanism of action and everything else but at the point of a trial, all those things have already been set. And the trial itself when you think about something like a phase 2 or phase 3 trial especially a phase 3 trial, all those things have already been said in motion. We're not arguing about the biology or the mechanism of action or any of those things, or how something works. We're actually arguing about does it really do something in a population? And that's a statistical mathematical question. It's not really a clinical question at all. And that was sort of my first in into the understanding of a clinical trial really isn't clinical. A clinical trial is really a mathematical construct. And I understand mathematics and so do a lot of other people who aren't clinicians. And the second realization that came out of that sort of exercise was that Pharma's definition of a drug working had absolutely nothing to do with what I thought of drug working meant. And , this is the biggest selling drug in all of history, Humira. And for example, one of the other things I discovered very quickly was that we use the word efficacy all the time everybody uses it. And for the first time I realized I had no idea what efficacy. I thought it meant the drug working. And for the first time I realized that efficacy actually from a technical perspective related to the population response rate. It had nothing to do with what was the response itself. Was it meaningful or not? And , this gives you a visual representation, for example, of Humira in trials. And as you can see, an ACR 20, it's a really interesting question to ask the question of well, is an ACR 20 a meaningful response and in this case an ACR 20 would refer to a 20% improvement on an ACR score. , of some approved metric like a C die or something else that someone is using, for example. And so when you look at that and you say, wow a 20% improvement. Is a 20% improvement worth spending $60,000 a year in the United States because the majority of patients all fall into that bin. So not only do you see the distributions moving to the right, as you can see the distributions get smaller as the effectiveness grows. The population distribution gets smaller. So an ACR 70 probably could be considered probably a great response for somebody. I mean, that could be the difference between somebody who's in a wheelchair. And you can walk again. I think most of us would agree that's probably a great response for that person. But an ACR 20 and those are the things that we're not really having any sort of meaningful conversation about.  Going back, we can talk about the trial data for Humira but what's much more interesting isn't the trial data for Humira, but it's a question of how did Humira become the biggest selling drug of all time? Because most of us would step back and assume that look, if it's the biggest selling drug, it must have done something big. It must have cured something. It must be better than every other drug out there, right? How else could something become the biggest selling drug of all time, with one of those 2 things being true. And it turns out that neither of those 2 things is true. So for example, until this year, the bio similar for Humira wasn't available in the United States and this year was where the launch of the biosimilars occurred starting early in the year and so most of the biosimilars were available only mid this year passing the 180 day exclusivity point and so if you step back and ask, why is that: in the rest of the world this was available but in the United States it wasn't. And you'll also notice another interesting thing. In the United States, the difference between the brand originator drug and the biosimilar is significantly larger than it is in other countries and you're like why. Well that's because in almost every other country the brand or the originator drug in this case had a significantly lower price than the United States, closer to 10 to 15% of the cost in the United States is where most of the countries where that drug sits. And as a result the biosimilar has a much lower delta between those 2 things. Whereas in the United States the biosimilar, and I'll show you some charts on that, has a much more significant delta between the net cost itself. But even with the large delta, you'll see the uptick has been very slow and very small, even though it costs significantly less. And by the way, the question is, is it better than everything else out there? And you'll see that that's not the case and if there are physicians on the call, as  that's not the case either. There are a lot of other drugs in that space, different mechanism of actions and also the issue that some of those drugs with different mechanism of actions work differently for different people. And so this is also not a case of one size fits all. This is a case of where it's a question of which drug works best for that patient. And our goal should always be, how do we figure that out, to make sure the patient is on the most effective therapy for them. And if you go back and ask why that Humira has been the biggest in all of history? Well because it's the biggest rebated drug of all. Basically what's happened is that Abbvie has purchased market share by paying more than everybody else does. In the United States one of the analogies we use is the question of if you go into a grocery store there’s shelf space that you can buy. So eye level shelf space if you're selling something costs more than the bottom row, which is hard to seeor the top row which is harder to see. So as a result manufacturers pay more for eye level space in a grocery store. But  what's very crazy about this situation is that drug companies with formularies and rebates have gone a step further. Not only have they paid for the shelf space on the eye level, they've also required that all other drugs be removed from the shelf so that the only drug you can see is their own drug. And what would be considered anti-competitive in a grocery store today is not considered anti-competitive in one of the highest cost industries to the American people at almost 20% of GDP. And so all of the things that we're sort of used to in a competitive market, for some reason all of those things don't apply in health care because health care is special allowing us to create bigger and bigger monopolies.

So how about hospitals and the providers themselves. So this was a study that came out in JAMA internal medicine and it was looking specifically at NCI cancer centres. And so it wasn't even looking at all hospitals across the US it was looking at the cream of the crop centres, the ones that are the biggest brands in the United States from a hospital perspective. And these generally for oncology are the NCI cancer centres. And so when they looked at those centres, what they found was that generally there was a 2 to 6 X increase in the price of a drug that was administered at one of these centres compared to the cost of the drug itself and if you were to go back and ask, hold on for a second, what additional value is being provided by an NCI cancer centre? Does the fact that the NCI cancer centre infuse that drug change the outcome in any way? And the answer to that is no, that's ludicrous. It would not have made any difference on who infused that drug. None of these cancer centres actually made any of these drugs. There's no special dispensation for them, meaning that if they were to prescribe it, the drug would behave differently in that number and if any of these facilities were to administer that drug, would there be any difference, and the answer that is no, it's ludicrous. The drug manufacturer was the one who deserves credit for creating the drug. Not somebody in the middle who either prescribed or administered it. And today you're seeing hospitals mark up a drug by 6 times for something that they had nothing to do with. And by the way, to put this into perspective, remember, these drugs are not $2 drugs. The average cost of these therapies is north of a hundred $100,000. So when we look at these drugs that they're marking up, they're marking up by hundreds of thousands of Dollars, in drugs that they had absolutely nothing to do with at all.

And then in the United States, we look at things like guidelines. There's an expectation if you go back to the practice of medicine for all the reasons that we talked about before that look we can't solve all these issues of time, etc therefore, we rely on guidelines. And it turns out that we don't spend a lot of time looking at, well how are these guidelines themselves created? And are there financial interests associated with these guidelines? So for example, this is looking just at oncology cancer approvals and this is a general issue around the accelerated approvals, for example, failing to improve life expectancy or quality of life. And this gives you some stats on some of those therapies that were shown to have, originally again, whenever an accelerated approval goes through, it's around a promise because there might be some data on a surrogate endpoint, for example. So now we have physicians putting into guidelines drugs for which there is absolutely no evidence that it improves life expectancy or quality of life. And we have drugs that we see that are withdrawn by the manufacturer later that have in fact actually made it to the guidelines. In some cases we see an endorsement at a level at a category of one for example which is the highest level guideline of a drug that has no improvement, for life expectancy or quality of life and why the 7 at category 2a is very important because you're like why does 2 A matter? Because 2a is generally were Medicare in the United States it's an automatic approval. And so most manufacturers are looking for a category 2a approval, which means an almost automatic approval by Medicare and when things have been approved by Medicare, that also generally means that everyone else approves it too in the commercial space. And so the problem with these things is that we see that these guidelines themselves do not follow the science itself. And so when we make a assumptions about guidelines and not reflective on, well how are these guidelines created, we run into this issue of the guidelines themselves may not follow the facts. And then of course the bigger issue is that we see the guidelines themselves are often written by physicians who are compensated by Pharma or who have either indirect or direct influence by Pharma in the pharmaceutical industry and they are the ones who are creating the guidelines themselves and that is a clear conflict of interest when guidelines are created that way. And so we would take a step further back and argue that, but if we had great data and we understood the data would the guidelines matter? And is it an unfair expectation that we would have would, look physician's first job in life is primary data. They should be steeped and understand the primary data. And as a result, things like guidelines, etc, should be secondary to the practice of medicine.

This is an example of what's happening in the United States today. As many of you may know and have heard the term rebates, the way that our industry works today generally is that an employer will go to a pharmacy benefit manager and the pharmacy benefit manufacturer will offer them rebates on certain drugs. And the argument is that their net cost goes down because they're getting rebates. The conventional thought about how this works is that these are group purchasing agreements in which pharmacy benefit manufacturers have gone out and received group purchasing benefits and therefore you are buying into a group purchasing agreement. Well, it turns out that's not how they work. They work as we talked about before because a formulary ends up being a steering mechanism. And today that steering mechanism has nothing to do with the purchaser, it has everything to do with profitability for the supply chain. So if you were to take an example of today and ask with the biosimilars for Humira or the Adalimumab biosimilars being available in the United States Coherus Biosciences has the lowest cost biosimilar for Adalimumab on the market today. It's about 7,400 bucks and Mark Cuban cost plus drugs is distributing that, roughly it's in the $8,400 range for an annual cost of 28 days times 13 fills for example. And the same cost for Humira with the best rebates on the market, this is after rebates saying, I went out and got the best rebates on the market. This is after rebates sayingI went out and negotiated the best rebates from one of the big 3 PBMs in this country. Our estimate is that they're paying about $34,700 is what they're paying after the rebates. Now just to put this into perspective, the drug itself today cost the employer on the order of $75,000. And then the rebates make the gap between that $75,000 depending on how well you do and this $34,700. Now if you take that $34,700 and break it down and ask where is the money going? You'll see that almost all of this money is just excess dollars that are being paid to intermediaries. They're the group purchasing organizations of which 2 out of the 3 big group purchasing organizations are actually offshore to the United States. Estimates are that they retain about $7,800 and remember those are not rebates, those are stored offshore so they don't have to be reported as rebates. And the PBM, our estimates are based on their public numbers, are at 6% or about $3,100 is what the estimate on the PBM makes in this case. There's the wholesaler that makes a much smaller portion. There's a lot of misunderstanding about wholesalers in the industry and people think that it's the wholesaler. It turns out they make a much smaller piece now we could argue that that too is unnecessary, which is a fair argument, but again their piece is much smaller and then you've got the pharmacies themselves making an average about $3,500 on a drug like Humira, of these specialty pharmacies that dispense this. And then it turns out that on a drug that cost 75,000 to $80,000 Abbvie is only making about $19,400. Now again, as much as I feel bad or not for Abbvie only making $19,000 the drugs market value today is less than half of that at $8,400. That's what the market value of this outcome is whether you use Humira or use one of the biosimilars. And so in the United States, we continue to pay the $34,700  which is what most employers, most health plans, and the government are doing and this defies common sense. But we continue to do things that break first grade mathematics in the United States and break common sense.

So if we were to go back and ask the question of: How could we fix this? Now, our argument would be the right way to fix this is to do the opposite of what we're doing in this country today and what we're doing across the world. Which is to focus on the first and fundamental core question is that that every prescriber should know the answer to the question, not somebody else, not a drug representative, not a marketing ad, not a key opinion leader that actually provides information, but that every physician who's prescribing a drug should know is does this drug work? What does it do? And again we don't mean this from the general perspective, but we mean with the specific technical description in the pharmaceutical world of does this drug work, right? That should be question number one. And number 2 should be the question of is this the best therapy for this patient? That’s question number 2, and then the question of is it working for this patient? Today it's very much a set and forget. Unless there's a side effect, unlikely the patient is going to call back. But there needs to be an objective assessment understanding of is this drug doing what we're paying the big bucks for and are they getting the outcome that we signed up for? That again is on the physician to understand the question of is this providing the benefit because I'm the one who signed up on that prescription saying that this person should receive this. And then the question of the benefit. And then the last question of is it a fair price? When an outcome through an Adalimumab biosimilar is $8,400 a year and the originator drug which markets to me is $35,000 or more a year, I have an ethical obligation to make sure the patients are on the $8,400 a year therapy because from a public health perspective, everybody has an obligation to make sure that we're not overpaying for healthcare services and that is every person who is involved in the chain. The employers, the member, the physician, the health care systems, everybody has an obligation to make sure that we're not over paying for health care because health care is in fact a public trust.

And so how do you accomplish this? We accomplish this by breaking the current models, which are like formularies because formularies are just steering mechanisms. All they do is steer people to higher profitable drugs or higher profitability drugs instead of is this the right drug? And by the way, that same mechanism is what ends up with us getting a drug like Humira being the biggest selling drug in all of history. We get crappy drugs that become blockbusters when we use things like formularies.

So if you were to use this approach, what would be the result? Well, in this case, what we would argue is that the result is what we've shown in the market. So in 2016 we started an experiment and our experiment was. Is there anything preventing us from breaking the way the whole system works? Is there anything that says that we have to work like this PBM or that or do we have to care what the FDA says etc. And it turns out that most of those questions are just this is the way that we've done things versus this is the way that we must do things. So in 2016 we launched an experiment that said, well what if we just do the opposite of everybody else? We're not going to have a formulary. We're going to focus on cost effectiveness. We're going to make sure that every patient is on a cost-effective therapy and we're going to make sure that every patient is getting an outcome instead of assuming that it must work and they are. What we've shown was that this data is from national benchmarking from a well-known organization on what their customers spend on a per member per year basis on specialty drugs. And as you can see in 2021, their average was about $1,295 per member per year. And using our experiment, and by the majority of our customers have carved out specialty to us, but still use their traditional health plans, still use one of the big 3 PBMs, the majority of them. And as you can see, our customers who underwent this experiment of doing the opposite. Ended up paying about $435 instead of $1,295 and this is without a formulary and doing the opposite of what everybody else is doing.

Let's talk about the upshot of all this and why you should care. There's a lot of discussion about equity and healthcare. And most of that discussion about equity and health care today comes from the health care industry talking about why we need equity and health care. But the reason we don't have equity in healthcare today in America is because of the health care industry. We spend 20% of our GDP on healthcare. We spend as much money as the 96% of the world's population put together and the healthcare industry keeps saying that it's because we have to. That's a lie. It's a dastardly lie. It's not because we have to. It's because everybody in the healthcare industry is happy that we spend 20% of our GDP on health care and as a result of that, how that affects the average American, is that the average American has to work 2 minimum wage jobs to be able to make enough times 2 people just to be able to make a median income in this country. And that is inequity and that is unfair. And the only way we're going to shift that is by changing the way the health care system works and taking out this fad that's very profitable for all of the people in health care industry. And so that is my challenge to everybody who's listening is to do the opposite and instead of choosing what's best for you, choose what's best for everyone other than you.

Leeza Osipenko: You really make me miss the NHS in the UK. On the other hand, you really inspire me to the fact that a lot can and should be done in the US.

Joel Lexchin: I think that you're missing one key element which is the drug companies and how much they control the knowledge about the drugs. So I was one of the people who participated in a Cochrane review that looked at the outcomes of clinical trials depending on the source of the funding and if drug companies were the source of the funding compared to anybody else, hospitals, charities, government, etc, the results and the conclusions were much more likely to be positive and the drug companies that use that data that they've generated to amplify the message. So they ghost write the results in medical journals. As you pointed out they fund either directly or indirectly the clinical guidelines. They pay for the CME. So getting accurate information objective information to clinicians and to other people is very difficult, especially in the United States where the government is not allowed to produce comparative information about medications.

Pramod John: That's, that's a fantastic point that you brought up, which is the fact the lack of the information, not only on the trials, but also on the negative trials being, being a necessity to be reported where today it’s the information that's missing that's also just as important as the information that we don't have as you brought up and we're very much as you can imagine for open data that if someone else is a third party payer, they should have the right to see the data. Whereas today we don't have access to that under guises of confidentiality and all of those things, which are a very poor argument. If somebody wanted to argue about their manufacturing process or the mechanism of action or other things,  that's a fair argument for confidentiality. But who in the trial that the drug worked for, what the actual side effects were and the raw data, the argument that that's even confidential, that makes absolutely no sense at all. And the fact that governments allowed that to be confidential, I’m agreed with you. I think one of the things that we see in the United States is that you're right that there's a lot of data that we don't have access to, but our fundamental frustration is that we're not even using the data that we do have. Right, a lot of these cases, as we, the ones that we talked about, the data is available. Even in that world of where the data isn't all available, we're not even using the available data. And so what we're arguing for is at least start with the data that's available. And then we can argue about regulations and things on making the data that's not available public. For example.

Leeza Osipenko: Following up on that, considering from publicly available sources you might not be able to extract data that you'd like or you need to put a lot of scrutiny on top of that, how do you make decisions, especially on the new drugs and not something like a Humira which was around for a long time.

Pramod John: Yeah and by the way, almost all the new drugs are in oncology, because there are very few drugs that are out of that space but they seem to all be oncology drugs. Our hands are tied In many ways and the data, a sword cuts in both directions in exactly the same way, meaning here's the data that we have and often we can only make decisions on what we do have but that also means it does allow us to have a much higher level of scrutiny, right? For example, we can look at things and say: Was this the right kind of trial? Was it the right comparator, for example? Were the trials themselves gamed in certain ways and we have a lot of ways that we look at the trials themselves to understand the trial itself. Was it measuring the right thing? Did they do the trial in the right way? Now if you were to go back and ask, hey, were there other issues that were part of the trial that we don't have visibility into. Well Ockham's razor dictates that we can't use that information in either direction that we don't know about. We can only use the information that we do have. So could somebody intentionally, for example, pollute drug trial data and falsify it. Of course they could. We see that academic, medicine, and all those areas all day long in science where people fabricate data. And so we can't solve the data fabrication problem, but we can at least ask some of those questions because we see it all the time of where it's the wrong comparator arm. It's a wrong type of trial that they're doing. Their conclusions were inconclusive. We don't agree with their conclusions themselves. We see those sorts of things all the time as we analyse drug trials.

Kristina Zakurdaeva: I missed the very beginning of it so you probably talked about it, but coming back to your point on how the guidelines are currently driven and especially the NCCN guidelines which we're all using, I'm curious to learn your opinion on the involvement of the patient advocacy groups in that because we know that some of these recommendations can be driven by the desperations that our patients especialy in the cancer field have and even if there is some hope or some signal of efficacy then the patients will be so insisting on including them and having access to these drugs. So, I mean, you made a great point about the industry involvement, but then there is the patient involvement and in the end of the day, we're working for them and they are going to be the main players on that. So what are your thoughts about how they could be better involved or  how their influence can be used in a more efficient way.

Pramod John: It's a really good question because as we talked about before a lot of these patient groups are funded by the pharma organizations themselves. And then the point you bring up is very valid because where do new drugs come from? Experimentation. So any drug or any therapy that comes to market, there's an assumption of experimentation associated with it. That's how they all come to market, you have to experiment. And so I think our argument isn't that we're against experimentation. We're actually pro experimentation. We're pro trials. We're pro all of those things. So for example, you've got the patient where in some ways I hear this from oncologist a lot. We don't want to be the position where we can't offer anything. And so hope is better than nothing as a strategy. And I'm sure you're in that seat every day as you see patients and their last hope, they're looking for something that might work and statistically it's not going to work for them and we know that. But I hear that a lot and I sympathize right? I empathize that yeah if it were my family member, I'd feel the same way. I think the question though is who should pay for that? In the rest of our world, like for example, if you're an Apple iPhone user or you're a Samsung user. I as a user, I buy the product and I know what I'm getting. And I don't have to pay for Apple's experiments somewhere else. If Apple is experimenting on a new set of ear pods, no one forces me to buy their air pods and make me pay for them because it may or may not work. And in the same arena, what's happening in drug discovery today is that someone who's a third party is being forced to pay for a pharma experiment. For example, an accelerated approval in which there's no evidence of benefit in, for example, life expectancy or quality of life and in oncology it’s almost always life expectancy, not quality of life and in that case it's well who should pay for that? And in the rest of our world, it’s that if you're putting on an experiment and you're the one who makes money, well then you pay for your experiment not me. Because either you pay for your experiment and you own the rights or I'll pay for your experiment and I own the IP rights, but it can't be that I have to pay for your IP and then you own the IP. And the United States today what we're ending up with is that whereas the public is obligated to pay for somebody else's development of IP and then they own it at the end. We're saying is that's not equitable that doesn't make any sense. Either you pay for your IP and you bear the consequences. I'm an entrepreneur I've had businesses that have failed. I've had businesses that have been successful. Who bears a risk for that. Me and the investors. Nobody else does, right? And I can't walk over to my neighbour and say hey, you need to pay for my failed startup. And today in healthcare today, what's happening is that some third party is being forced to pay, but they don't own it. Someone else buys another jet or another house somewhere as a result of someone else having to pay for someone else's care. So our argument there would be we're for those things because experimentation is what leads to progress. It's just who should pay for the experiments?

Leeza Osipenko: If you at Vivio are actually showing that you can make these savings why isn’t the entire of the United States is not your client? Is it because you have a lot of competition? Is it Because people are not trusting this new way of a potential provision of specialty drugs. Or is there some other reason or is just a matter of time?

Pramod John: I think that it's a really good question because we get asked that question all the time. If it's this obvious, why isn't everybody doing it? Well, that's because if you go back, we talked about the PBM industry, for example, just take one microcosm of one industry that has some level of control in the US and you ask, why does this model exist and why does it work? There's a huge amount of scrutiny now, public scrutiny in the United States around the PBM industry, right? So if you go back and ask the question, but this is so obvious. Why isn't anybody saying I want visibility into how your model works, how you make money and all these things for example, and then anybody could do what we're doing but nobody seems to be doing it. And if you go back and ask, well why is that? Well because do you know that the top 10 lobbies in the United States, 5 of them are healthcare. The American Hospital Association, Pharma, and the list goes on. So let me take you into a simpler example. Does it break common sense where in this case, there's no argument about the model,  when a hospital charges 6x more for the same drug. In that case there's perfect visibility. Nobody's arguing about business model. Are they saving money or not? Everyone looks at that and everyone knows that's happening. So you take even a simpler example like that and say, how in a civilized society, when everybody agrees, no one's arguing that it's not happening. How are we looking at a NCI cancer centre marking up a drug by 6x. Why isn't everybody looking at that and saying that you can't do that? That's even simpler than what Vivio is doing. From the perspective of we don't even have to get into is it the right therapy, is it clinically about all those things. Just common sense. We're not able to break the common sense barrier in this country, let alone the more complicated things.

Leeza Osipenko: Unfortunately common sense is not just about healthcare in this country.

Lydie Meheus: What is your view or the view of vivio on the upcoming trend at least in Europe that every cancer patient should get NGS sequencing and then targeted therapy should be used off label while there are no data on the effectiveness of this off-label use and we're not against the concept but we think it should be in a clinical trial environment while everybody is pushing for having it even reimbursed and using that as standard treatment, off label use of targeted therapy based on NGS sequencing without decent clinical trial data.

Pramod John: Yeah, we're in a hundred percent agreement with you. So we've been very vocally opposed to in the United States, a whole bunch of the liquid biopsy and other types of companies that are doing that kind of sequencing. And so we're seeing especially like in academic medical centres and in other areas where they're doing exactly what you're describing. And our position has been exactly the same as yours, which is those should be fodder for actual randomized clinical trials because those could identify what the targets for the trials themselves should be. But until we've had those trials, we have 0 evidence of any benefit. And at this point, that's very much an experiment. And so we are in agreement with your approach that that is the right way and that's what we should be doing.