End of last year, a congressional report about the approval of an Alzheimer drug by the FDA was published. It critiques both the FDA and the sponsor company Biogen. Reuters and many other major news organisations reported about it.
Today, I interviewed Anja Schiel about this topic. We talked about the background of Alzheimer and its impact, incidence, and prevalence.
The combination of large incidence rates, chronic condition over many years, bad prediction about what is going to happen for an individual patient (or not yet patient), and high drug prices (and other things) form the “perfect storm” for healthcare budgets.
During the interview, we talked a lot about trust in the different players in the field, reputation, influence of statisticians within the different organisations, and many more topics associated with this story.
I believe, every statistician within the healthcare area should know at least a high level what is going on here.
Everything that is happening around this topic will have an influence on all of us – as an industry and also as societies.
The recent Alzheimer story – an absolute low for the industry and especially for statisticians
Alexander: You are listening to the Effective Statistician Podcast, the weekly podcast with Alexander Schacht and Benjamin Piske. Designed to help you reach your potential, lead great science, and serve patients without becoming overwhelmed by work. Today I’m talking to Anja Schiel, one of the most prominent statisticians, the HTA area, probably around the world. And we are talking about the recent Alzheimer’s story, which is an absolute low for the industry and especially for statisticians. So stay tuned for this interesting, but also pretty sad story that you as a statistician in the industry should really know about. Have you already signed up for the Effective Statistician Conference that is happening on April 25th?
Then head over to my homepage, the effective statistician.com/conference/ and register for it. It’s a free five hour virtual event that will help you to learn about many different aspects within your job. We’ll talk about data visualization. We will talk about safety. We will talk about reproducibility, we will talk about programming, we will talk about simulating studies, we’ll talk about medical affairs. We will talk about patient designs. In early phase, we will talk about. Digital applications. And of course we will also talk about Estimands and we have a huge and great lineup of speakers. So we’ll not have very long talks and so will be lots of opportunity for interaction and asking questions. So check out the effective statistician.com/conference.
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[00:00:00] Alexander: Welcome to another episode of The Effective Statistician, and today I have Anja Schiel again as a guest. How you doing, Anja?
[00:00:08] Anja: Thanks, Alex. Quite well. It’s the beginning of the year, so the stress level is only slowly rising. .
[00:00:16] Alexander: Yeah. And today we have a very interesting topic. Actually quite a controversial topic as well and a very hot topic. And so I changed my editorial calendar because of some recent news that we have seen. But before we have go into the news, let’s dive a little bit into the background story because here, for all the Alzheimer Researched that is really important. I personally have also worked on Alzheimer’s research, both early phase, a little bit touched on that as well as, have been a little bit involved in the late phase research and have seen what’s going on there.
And I know it’s a really difficult research area because progression takes a lot of time. There’s a lot between and present patient variability, the symptoms are like typically in neuroscience it’s not straightforward to capture. There’s a lot of variabilities here and also the population. Getting the right population is really difficult because it’s such a long process. So that’s, really difficult. So what is your take on the history of pharma and Alzheimer here?
[00:01:32] Anja: It is a field of extreme failure. Not for lack of trying, but maybe for lack of willingness to explore. Also alternative theories. There has been an extreme focus on the amyloid hypothesis for a very long time. People have had difficulties looking outside that framework of where research should go. Both academic but most definitely also the pharma development has been really very heavily focused on this bond target, which everybody thought would be, the solution. But let’s be honest, this is, has been going on for a very long time. And we have such an amount of evidence that rejects the amyloid hypothesis that this is one of the elements that has made this discussion so controversial. I think.
[00:02:19] Alexander: Yeah. And we are not speaking about, small numbers here. So there is various companies that have worked on this have done big studies, thousands of patients, many followed up. Each of these studies is usually at least one and a half year long. These studies, each party costs hundreds of millions of dollars. Yeah. So this is truly not an area where people were, not willing to spend money because the need is also really big. I think, if I just look into how many patients would be affected just in Germany alone? Yeah. It’s a huge number. It’s broadly, lots of people beyond a certain age get it. And as we have a growing population that is getting older and older, the incidence rates will only increase. The prevalence will only increase. And and that is one thing. The other thing is it’s not just the patients that are affected, it’s also the, everybody around the patients is affected. I have one case in the family. Where the husband is now getting it and he’s forgetting about, who his wife is and, can’t sometimes, treats her like a stranger and then of course becomes fearful and, is things like, oh, there’s a stranger in my house. Yeah. And you can only imagine what happens thereafter. It’s really bad. Yeah. So it doesn’t only affect the patients that affect the families around it. And so the burden is really. And of course, you can have Alzheimer for very long time before you die actually.
[00:04:01] Anja: Yeah. And I think that is probably one of the issues that make this one of the most challenging fields for academics, for regulators, but most definitely also for HTAs and payers, because the consequences of this complex, Doomsday scenario I would call it. The idea of not still not being able to predict who might get Alzheimer the wish of the industry to find some way to, find some prediction, whether it might be true or not to. Yeah. And the question is what is the motivation behind it? Do we really want to help patients by scaring them into all believing we are going to get Alzheimer’s, so we need to treat ourselves right now?
So are we just increasing the number of potential bias for our product, or are we really trying to identify. The sources and the different kinds of mental diseases that come with age, because we should not forget, everybody focuses enormously on Alzheimer, but there are other forms of dementia. They are equally bad for everyone around it. Yet they are not as popular, I would say to talk about, and it’s convoluting, everything is convoluted in this field, I must say. So it’s the idea of that you might not be able to distinguish between different types of dementia and Alzheimer. That you might not be able to distinguish between a risk factor at a group level and a true risk for the individual, because that is really the main problem. We cannot predict, no matter how much we scan or tap, blot or spinal fluid, we really can’t tell that a patient above level will definitely get Alzheimer. And that’s the issue here because if you have a situation of a disease that is going to come, 50 years down the road in or developed to the degree that you personally might be affected by and others might be affected by it, then we, humans are usually very bad in behaving accordingly, we are not going to reduce our risk.
And I don’t want to be treated for 50 years with an antibody, to be quite honest, because that’s not going to work. No antibody treatment can be used that long. So you want to have a treatment and then. One year follow up, one and a half year follow up and then claim something will not happen in 50 years. That is in essence the problem for everyone, including patients because you can’t make a decision based on this kind of assumptions. It’s very difficult. Healthcare systems on the other hand, really, we know what the costs would be. The costs to healthcare systems are exort. This is one of the criticisms that was raised by the US and that’s really very interesting that the US of all places has a report that criticizes a company for their business model, which deliberately aimed and accepted the fact that they would target a vulnerable patient population.
They tried to have a, commercial approach to it. Trying to make to remove all kind of concerns to get as many patients as possible, knowing that they would actually break the bank because Medicare would’ve died simply by having to cover these costs. And that is not just for the US, so if even they already realized that, then you can imagine that everybody else who actually has an HTA was happy when we realized it wasn’t going to come to Europe. Because the challenge, we are very much aware of the challenge the methodological issues that come with this kind of scenario of a preventive treatment, which is a horror scenario for each HTA, when you have no proof of what you’re preventing is really not going to happen , and you don’t even know why it’s happening, and that’s the problem.
We don’t know about the natural history of the disease sufficiently to predict who can get it and who should be treated. And if in that scenario, all the HTA, I think we’re very happy that it didn’t make it to the European market. And then we get an extension of the time to think about how we want to handle this because this is a complex problem. It’s not just methodology either from statistical side or from HTA side. This is societal problem. This is a political problem. This has to do with, do we have the finances for something like this? Should we go along these argumentations, these kind of prices for such a huge amount of our population with such little evidence and this high uncertainty. And I think that’s going to be, whenever the first one comes, it’s going to be a really harsh discussion in the public. When it becomes clear that this is just not bearable for the healthcare systems, no one has this kind of money.
[00:08:37] Alexander: Yep. I was exactly saying this to my wife when I was working on this Alzheimer component that if that comes true, will be headline in the top news in Germany and probably around Europe at least. Because if a little bit of a calculations and calculated at the lower end of an antibody per year. Let’s make it cheap and just say it’s 10,000 euroes. Let’s make it cheap. Even with that number multiplied over the, because you need it for years. It’s not, you take and then you’re done. No, you take it and take it. It’s a chronic disease for a very long time, multiplied by the number of patients that would like to get it. You would break the German healthcare system directly? Yeah. This is just, more spans than I think the healthcare system actually in the moment spends overall. Yeah. , just this kind of calculation shows you that something is wrong here. Yes. It just doesn’t work. There’s no way we as patients, as a society could pay for that.
That’s just No way. Yeah. And now there’s the only solution to this success you mentioned is to make sure that only those patients that really will benefit from it get it. That’s the first point. The other point is, of course, also to speak about prs. Yeah. I’ve just read an article on LinkedIn that was about another urologic disease, ALS. Where there’s prices, yearly prices of $160,000 per year called on from companies, and this is not covered. Yeah. And then I think this doesn’t even make financial sense from a company perspective, I think. Because why should you sell just a very little amount of your drug for high price? Why not help many patients for much reduced price? Yeah, of course. Producing an antibody is not the same price as producing a pill, but come on, it’s also not as, expensive as it was 20 years ago. And, there’s a lot of opportunity to have much, much more patients treated and helped and still get a good financial situation for the companies that provides it. If there’s a lower price. I think one of the things is I once talk to a marketing person within a company and I ask him, this is business 101. Yeah. So revenue is price times volume. Very easy. Yeah. Why do we always scale for high price to get this revenue? He said it’s pretty easy because people incentivized this way and it’s much easier to incentivize, to have a high price and then, it’s much more difficult to go for volume because that is more difficult to achieve. Yeah. So I think one of the problem is within the companies, for the individuals, the incentives of wrongly set.
I think the incentives should be set for how many patients can you help and then you can say, and also make, good benefit for the company. But I think set should be the first target. In history there’s so many cases where companies provided, nearly for free year for a very minimal price. If you think back 100 years ago when Lilly first brought insulin on the market they didn’t charge a fortune for it. They charged a very moderate price for it to make sure that as many patients as possible can get it. Because it was obviously lifesaving. There these pictures of these kids that I have in my mind, these super skinny, diabetic kid and then, he gets insulin and then he looks normal. That’s a history, we also have, as pharma companies and we very often talk proud about this. Let’s talk proud about this in the future again, that’s my kind of, that’s my kind of feeling. Okay. That’s a little bit my soapbox. .
[00:12:57] Anja: Yeah. But I totally agree. The director of my agency always likes to talk about the ethical obligation that the pharma industry has to society, and I think that is one of the elements that’s broken. The other element is also that that every time they test wine they come up with it. The cheap wine never makes it to the top unless it’s tested blinded, because apparently we are all also very primed by now that expensive means better by definition, and that works perfectly also in pharma. And the other point really is that I agree that yes, it should be volume, but just look at the list of shortages we are having constantly by now. And we knew when the pandemic was coming that the bottleneck wasn’t even the fact that we didn’t have a vaccine, but the understanding that it didn’t have the capacity to even produce enough vaccine in time for everyone. And that is another aspect because sure, you can say, it isn’t really that expensive to produce an antibody anymore. And, in Alzheimer, one can say that the investment was large. But not for the individual company per say. It’s never made transparently clear what the real development costs are and the real production costs are. But if you have limited capacity, then producing less. and selling it for more for a higher price makes absolute sense.
[00:14:18] Alexander: Yeah, of course.
[00:14:19] Anja: And you see something like this also in the CAR-T world where a certain shortage and unavailability is still effect no matter how much all academics are praising it and saying this is the future of everything. Then I’m still wondering why there isn’t a factory outside my window producing CAR-Ts. That’s really one of the aspects where there is, again, misalignment. There’s misalignment in Alzheimer, in the other helm story, just everything collided, all the misalignment. All the problems we have in our system. We have seen that the FDA behaved in a way that many found unacceptable. We found it unacceptable that they very actively tried to remove every obstacle for this company and this antibody to make it to an approval. Which is not their role. As regulators we are supposed to be objective. We have transparent rules, but we also have rules of engagement, which we have to stick to.
The FDA didn’t in that. We are not, we can discuss with the industry, but we are not supposed to sit in the same boat with them. That makes us look very suspicious. One of the things that many of us felt very uncomfortable with, we are not supposed to ignore the input from experts. If you have an expert committee and they unanimously vote against a product, then I can’t understand how the FDA can simply ignore it. There have been internal problems. Everybody can read it in the report that has been coming out about the lack of communication. As a statistician, it really hurts me because there are so many statistical issues that made you frown at least, or even gasp. At best hearing that my FDA bio statistics colleagues were not involved. Until the very last moment they didn’t know what was going on.
One department, not talking to the other department, not accepting the criticism, not listening to their concerns. That is just an collection of everything you should never do because you ruin your reputation. And not just FDA’s reputation, they ruin our reputation in Europe too because there is enough concern. We have suddenly popped up on the radar of many people during the pandemic, people that have never heard of drug approval in Europe at all. Now suddenly are aware of that. There is such a system and they wonder, how independent are we, who we working? And that is really a problem. I tend to say I’m increasingly feeling a pressure because I’m working for the Ministry of Health, not for the Ministry of Commerce.
It shouldn’t be my task to finance and incentivize the industry that is for the Ministry of Commerce. My task is to ensure that my patients get good treatments, working treatments, and had this antibody been a miracle drug without any question, with amazing results, the discussion would’ve been completely different. But this was not it. This was one of these cases where statisticians feel like somebody has been trying to squeeze out something that wasn’t really there. Ignoring all the negative studies, all the negative results and declaring success on one single finding. While every statistician can tell you that’s not good statistical practice, the analysis that were done questionable. You can ask, what did you do? How much did you have to torture the data to reach the positive result? That is an additional aspect to this procedural. Everything went wrong. Statistically, we are not buying this clinically massive criticism. The amyloid hypothesis was dead as a dodo before this product was launched as a the rules. No, not the devot. The Alzheimer meeting in loam the year before was really in the mood of, okay, we have to look somewhere else. And that’s the worst aspect of it. The industry was already ready to look somewhere else. They were opening up to, to look at different avenues to consider different hypothesis, different targets, and then comes among these and suddenly everybody’s just opening the drawers, pulling out all these stuff they had put away already and say if they get approval with this kind of data, then we can get approval easily because we also have something like this. So we are just going to be a bit more inventive in our analysis and then we go down the same road and we are making a shitload of money out of it. No, because these patients deserve better. If this had happened with an amazing drug, nobody would discuss it, but it’s not an amazing dock. It comes with extreme risks. The next generation or the next type of same are coming with the same risks. We are seeing it as we speak, about the brain issues on the safety side that are coming up.
This is a class problem. It’s a problem of the system. The idea, the hypothesis behind it and everything has been ignored. Everything has been ignored because, Biogen essay, openly admitted, wanted to make this a blockbuster being, the savior of the world with something that. Lots of people doubt that it actually works, and that is a combination of the worst decision ever. That’s what it is. Many people have described it as the worst decision ever because this is undermine the trust in everything we do. It undermines the trust in the academics. It undermines the trust in the regulators. It undermines the trust in the pharma foremost, and it brought something to the foreground. Where I have always been of the opinion that we need to be willing to discuss what the industry calls a value proposition. And value pricing is in reality, a desperation pricing. The more desperate the patient population, the higher the price. It has nothing to do with what your drug is and this is something that now we reach, we are all reaching, including the us, the breaking point where we say we can’t, so the solidarity in the healthcare system that we have in Europe is at risk. By this kind of behavior, not because we don’t want to pay, but we can pay. No one has this kind of money, as you correctly said.
And this is really the problem, this conflict, this constant conflict between we are supposed to support the industry and their commercially interests. I don’t fully agree. I honestly do not agree, and I don’t think that, business as a science is working business has rules, but only if the market really follows these rules. And the farmer market is not following the normal rules of economics. That’s what our problem is. We have monopolies, we have arrangements behind the scene. We know that people are not really competing with each other. We don’t see that prices go down if there are three or four products, no, it’s like going to the gas station, it doesn’t really matter which gas station you take, because they have been arranging with each other what the price will be on Monday morning, and that’s exactly the same. We see also in pharma only, you know the, okay, we might be bickering about the gas prices, but the farmer prices are in a completely different dimension and they said they break the bank and that’s the problem.
[00:21:36] Alexander: Very good summary. By the way, if you haven’t heard about the news I’ll put a link to the report about what happened at the F D A that was issued by the US government in the show notes. I think it’s a must breed for everybody that works in our industry to understand what’s going on and to understand the bigger picture. Because we don’t work in silos. We work in bigger systems and it’s for us to understand what’s going on here. I think it’s also up to us to change, drive change in the right direction. And we can do that from outside the companies. We can do that from inside the companies. In the end, it’s always up to the individual people to drive change. Don’t wait that someone else will pick it up, move within the company. Speak to the different people. I once heard from someone saying when this truck got approved from the FDA, great day for the share price. Worst day for statistics. And, I think that’s probably sum up also pretty nicely. Let’s see. As price change. Speak about it with your colleagues. Speak about it internally. Makes these help people understand where the problem is. Help people understand that it’s in no one’s interest. If we ruin the trust. Because that only gets us back into, it’s the last century where there was. There was only actually one industry that got, has less trust since the pharma industry and said was tobacco. And so really we don’t wanna live there. We don’t, I don’t want to, speak to my friends and, be ashamed to talk about that I’m working in pharma. I wanna be proud about working in pharma. And I think that is up to each of us to drive set change, to make set change happen to speak about it, build alliances. And help people understand, that we need to collectively work in the right way.
[00:23:49] Anja: You are allowed to earn money. But you can question yourself, how much money do you really have to earn on something on the back of someone else? And that’s the point, you need to have these ethical discussions because it’s allowed to be ethical.
[00:24:03] Alexander: Yeah. Completely agree. I recently read the book the Psychology of Money, really interesting book. I can highly recommend it. And says one chapter that speaks about when it’s enough. And that says, people said no when it’s enough for them and they are happy with it and there’s other people for them it’s never enough. And the goalpost for what I want to reach it’s always moving. They always compare themselves to another person and another person. And of course there’s always a person that, earns more, is more richer. You can ultimately compare yourself to Jeff Bezos or, people are on that side. It’s, there’s always someone that earns more. There’s always bigger companies, but where’s enough for you? Where’s good enough? I think that is to think about that kind of psychological thing was a big insight for me. Any final thoughts from you Anja for this really interesting and actually pretty different episode here in The Effective Statistician?
[00:25:09] Anja: Yeah. It might have been different. But I think it it all started with with one of my LinkedIn posts where I also agreed that this was one of the low points of regulatory decision making. And I said, on so many levels, and as a statistician, it really also hurt me seeing what had happened there because as a statistician, I feel I should enable people to make good objective decisions. Understand that we help them to not see what they want to see, but we help them to see what is really there. And this principle has been violated so normally in this process that I felt like, okay it highlights a little bit one of the problems of drug regulation and decision making. Also on the pharma’s side, that people move away from the objective tools. They’re having and decisions are made on so many other elements, including can I make even more money, which should not be part of some of the decisions. And that is what I’m saying. This convolution of the commercial interest permanently with the science. And as a scientist, I refuse to be part of the legitimizing something that is wrong simply. And I know that the pressure is extremely high, in particular in the pharma industry, that you should shut up. And just give them, some kind of support, somehow find some solution for them for what they want to see. And that’s exactly what we are not supposed to do. We don’t want to help people to make arguments for something that’s wrong.
[00:26:44] Alexander: Thanks so much. That was a awesome discussion. And thanks so much for speaking on the show. That was super, super insightful and helpful. I also tried to get some statisticians. From companies, but it’s really difficult in the current climate for people to. Openly about it which I can understand from a certain perspective. So unfortunately, I’ll not be able to cover that in my podcast. The other point of view. But I really, I, you have a look into what’s going on there. It’s very informative and it’s something that we as a community can do something about, and it’s actually in our own interest to do something about it.
Thanks so much. Have a nice day.
This show was created in association with PSI. If you haven’t yet registered for the Conference, the Effective Statistician conference that is taking place on April 25th, head over to TheEffectiveStatistician.com/conference. Thanks to Reine and her team at VVS who helped with the show in the background. And thank you for listening. Reach your potential lead GREAT SCIENCE and serve patients. Just be AN effective statistician.
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