March 26, 2025
Welcome to Perspectives, a signature podcast series from The Leerink Center for Pharmacoeconomics. Hosted by Dr. Mel Whittington, a health economist and Head of the Center for Pharmacoeconomics will be hearing from individuals across the industry to better understand and appreciate the societal impact of healthcare innovations.
Mel Whittington: Hi everyone, it’s Mel. Today we’re going to talk about drug pricing and the opportunity costs associated with it. Hosting a podcast is far outside of my comfort zone, but the opportunity to talk to people who I have followed for many years and reading their work has really shaped my thinking, does make the discomfort of hosting a podcast worth it. And today’s guest is one of those people. Someone who I have followed for many years. I’ve read her work for many years, and I’m truly thrilled she was willing to join me today and glad this podcast gave us the opportunity to have a one-on-one conversation together. Our guest today is Kirsten Axelsen, Senior Policy Advisor at DLA Piper and Non-Resident Fellow at the American Enterprise Institute. Kirsten, thanks for being here.
Kirsten Axelsen: Thank you so much for having me. I’m really delighted to be joining you today.
Mel Whittington: Thank you. For a brief bio for those who may not know Kirsten, she’s also an economist. So, you’re getting two for the price of one today. She works with healthcare clients on issues around pricing, reimbursement, patient assistance, public affairs, and other strategic matters. She’s worked to develop policy programs for organizations on their positions related to drug pricing, coverage decisions, and regulatory reform. She’s established pricing considering both affordability and value for rare disease medicines and oncology products. And in our last podcast episode with Dr. Frank David, we talked about the use of models to inform decision-making, and Kirsten often uses models in her work to estimate the impact of certain policies and business practices on different stakeholder groups. Now, Kirsten and I have both spent our careers thinking about the value of healthcare innovations and investments and the downstream impacts of their price. But we’ve looked at different things. The downstream impacts I have historically focused on are the opportunity costs of using our pooled healthcare resources, say our insurance premiums, pay a certain price for a specific drug. Thinking about is that an efficient use of our pooled resources? If healthcare costs increase to the extent that premiums then increase and now people leave the insurance pool or have less resources to spend on non-healthcare sectors, you know, things like that. What are the opportunity costs associated with that? Whereas the downstream impacts that Kirsten has focused on are on how pricing decisions affect future investment in R&D and future drug development. Thinking about how those pricing and reimbursement decisions for today’s medicines send signals to investors in allocating resources to pipeline programs and development stage companies for our future medicines. So, Kirsten, I am really looking forward to hearing from you and learning from your perspective. But first, can you just tell us a little bit about what drew you to this industry, how you got to where you are, what a day in the life looks like?
Kirsten Axelsen: Thank you so much. So, I’ve been working in the pharmaceutical industry or around it as a consultant or a policy analyst for about 25 years. And I got a master’s in economics and focused on econometrics. I was drawn to the industry, one for the complexity of the problems in it, both type of regulation, the low likelihood of success that any individual drug program would end up becoming a medicine. And I’ve stayed with it because the problems just keep changing. Drug development changes every year. Policies keep changing. Risks in the industry. And then the industry, of course, has really evolved globally. And I’ve been fortunate to work in global policy, on global strategy. So, I’ve been able to work in just about all of the major markets in the US on primarily pricing and access issues to really enable the successful commercialization of medicines and also to enable them to reach as many patients as possible.
Mel Whittington: That’s terrific. And as I mentioned at the top of the episode, we’ve both done a lot of work thinking about the impact of pricing decisions. But the stakeholders impacted and kind of the types of impact we have looked at has been different between the two of us. So, I’d like to hear from you, how does a drug’s price influence the work you do and your thinking?
Kirsten Axelsen: Yeah, so drug prices both affect how health systems use medicine. Obviously, drugs that are priced too high with a large population are less likely to be used. On the other hand, some drugs are expensive, but relative to the value they offer are probably priced too low. But again, if it’s for a large population, then often there are access restrictions. What you see is that access restrictions are often related to the price of the drug, not the clinical value of the drug. And I got into studying this field early in my career when Medicaid was a much larger purchaser for biopharmaceuticals. This is before the Medicare Part D drug benefit. That was the time when there were a lot of different medicines for cardiovascular disease, for blood pressure and for statins and I was brought in to help identify how states use a preferred drug list, meaning the drugs that they would cover without additional authorizations for their Medicaid population affected adherence to regimen. And what we would see is the states would get a good discount for preferred placement for one drug, and then three months later they’d have preferred placement for another drug because they probably got a better discount from that drug company. And so, people will have to switch medicines. And what we saw is even though the clinically the medicines do the same thing, we saw tremendous drop-offs in adherence because different patients metabolize different medicines or maybe there’s confusion when the medication gets switched. So that really opened my eyes to how much drug management techniques affect what drugs get used and including people just leaving treatment altogether when they had to switch.
Mel Whittington: Yeah, I think it talks about the benefit of having multiple drugs even treating the same condition. One to give patients more choice to figure out what works best for them to find the right medicine for them, but also to create this form of market between payers as well of trying to figure out, trying to negotiate, trying to leverage products against each other and helping their decision making.
Kirsten Axelsen: Absolutely, I always say that we have the least information about a drug we will ever have on the day it’s launched. And yet we use those labels from the clinical trials, which are very artificial setups, right? It’s not really how anyone is treated in real life and make determinations that, you know, two drugs are the same. For example, when in reality people experience different side effects. They work better for some people than others. And oftentimes we really know nothing about that variation between different populations because a clinical trial reports out on the average effect.
Mel Whittington: And you talked about these different kind of coverage decisions and reimbursement decisions. What signals do those send to investors and development stage companies? Are they looking at reimbursement and coverage decision making for on the market drugs and informing their decisions for development programs? Or what does that feedback loop look like?
Kirsten Axelsen: Absolutely. And sometimes there’s no analog. But, when a company or an investor is deciding whether or not to proceed with the clinical development program, and I’ve worked primarily in larger biopharma companies. So, thinking a little bit more about the later stages of development, there’s sort of two axes in your decision. Is the program likely to be successful? Meaning is there going to be a therapeutic effect with a good safety profile? And if it is successful, is the market going to pay for it? And is the market going to pay for it an amount that is sort of commensurate with the risk you’re taking on for developing this drug and then monitoring it? Because remember, once a drug is launched, it is the drug company responsibility to monitor its safety and do additional clinical studies, literally forever, including when the drug is off patent. And so, you know we see the effect this has. We’ve seen the gene therapy market largely dissolve. And no one’s saying gene therapies aren’t miraculous or good, but the market didn’t sustain the price. And then, you know, we’ve seen a huge amount of interest in drugs that treat obesity, even though there’s already some good drugs on the market to treat obesity, because there seems to be very high demand for them. And consequently, we’re also seeing the prices getting pushed down through competitive negotiations, really to a point where many cost effectiveness analyses would say, you know, we’re probably paying too little for these drugs. And I think there are people who would say the same thing about the hep C drugs, that as the prices came down, we’re getting more for them than we need. So, when investors are thinking about engaging in the costly and usually high failure rate event of clinical development, for a large population drug, you can sometimes sustain that with a bit of a lower price, although it depends on the drug and the value and the clinical, the pathway to clinical development. And then for smaller population drugs, if you don’t think the market will bear a higher price, then you’re not going to continue in that drug, even if you’re pretty confident that the mechanism will be successful, unless you believe that you can secure additional indications and then expand the market to the point where it will make the clinical development program financially successful even considering the high probability of failure.
Mel Whittington: That’s a great point and something that I feel like I’ve been exposed to more since I have had more and more conversations with investors and innovators is how prices that we do pay today that informs their decision making and their investment and development of certain programs and that’s kind of an opportunity cost that I historically hadn’t thought about prior to having those conversations. I have thought about the opportunity costs of our pooled health care resources, but in that there’s this unquantified or not considered opportunity cost is what does that mean for future innovation? If we aren’t willing to pay for something, or if we are only willing to pay X dollars for something, what future innovation might we not get because of those decisions? And conversely, if we are willing to pay for something, what future innovation are we getting because of that? And I think the Inflation Reduction Act and the Medicare drug price negotiation components within it have really forced us as an industry, and honestly, as a society, to start grappling with those trade-offs. And if there is government price negotiation during the patent period, what signals does this send to innovators and to investors? And if that time to negotiation is different for small molecules versus biologics, what signals are being sent with that? And so, we’re seeing a bunch of evidence starting to develop around those trade-offs and the impacts in this feedback loop between prices today and innovations tomorrow. And one of the pieces of evidence I read was an article that you wrote that summarized the evidence on the relationship between financial returns and research and development, that this actually is a research piece of work with empirical evidence around it. And I’m hoping you could share a few key takeaways or pieces of evidence on that relationship.
Kirsten Axelsen: Absolutely. there’s very little question that there is a relationship between financial reward and investment in clinical study. I think there is some question around the magnitude of that relationship. In part, it’s very hard to measure. A lot of the studies that have been done to measure that relationship are you know, they’re retrospective, they’re looking at variations often in European market size or in relation to a change such as the Medicare Part D benefit. There’s nothing that examines the impact of reducing the revenue stream nine years after launch versus 13 years after launch, for example. So, I acknowledge first that there’s, it’s a challenge because there isn’t great evidence. And so, when, you models are developed to help guide policymakers, those models are only good as the information that we’ve had so far. And there’s a couple of existing limitations, I think, in particular, the evidence that was considered around the Inflation Reduction Act. One is, there’s a consideration of the new drugs not developed. But really, I think the concern that many of us have around the Inflation Reduction Act is the post-market research, the additional indication, especially for things like cancer drugs, where you typically study it first in a smaller metastatic population, and then you study it earlier and earlier in the disease. And that’s part of why we have the leading cancers with 90% or greater five-year survival rates, because we’ve learned about the medicines and can initiate them earlier and earlier in the disease state. So, I think that’s one major limitation. The other is the one that I mentioned that these studies are typically done on historic drugs, and the drugs of today are very different than the drugs of 10 years ago. The costs of development are different, the likelihood of success is different, trials have gotten much more complex, which with a lot more measurements. So that’s also different, the probability of success is different. Now, you know, which way this affects the estimates, there were some reasons to say the estimates of new drugs not developed are too high. There’s also a lot of evidence that says the estimates of new drugs not developed as the result of something like the Inflation Reduction Act are too low. But again, I think the main impact is going to be on the second indications for these drugs, which has not even been considered by some of the models. So, there’s still great need for gathering more evidence, as particular on early decision-making, because what you really don’t see is the drug program that was never even initiated as a result of a market change, or again, the follow-on program that was never initiated as a result of a market change.
Mel Whittington: And so, there are these methods that are commonly used to model the impact of these policy changes on the biopharmaceutical innovation and what do policy changes mean for future innovation. But from your paper, it seems like there are still a lot of gaps in the data and the methods that are conventionally used. And I know you just talked about some of those limitations as to why some of those gaps might exist. But in your opinion, are there areas where logical areas where these gaps could be closed, or new methods could be developed, and we could better inform decision making?
Kirsten Axelsen: Definitely, I mean, the one is considering the impact on post-market study. You know, the thing to enhance these models is considering what types of drugs will have the most impact. You know, some people say, “it’ll just be the marginal drugs.” That’s not clear to me because the true therapeutic advances are higher risk. Developing a mee-too drug is relatively lower risk. You already know that there’s a mechanism of action that works and maybe you’re just developing an enhancement. So, I actually think there is a likelihood that policies such as the Inflation Reduction Act are going to limit investment, in some of the hardest diseases to treat. So those are a couple of things. There’s also, I think, an assumption in policymakers’ minds that capital is not mobile and in reality, venture investors who really are a large source of the funding for earlier stage development and smaller biotech companies can put their dollars elsewhere and their limited partners will insist they put their dollars elsewhere if they think that there’s better returns on AI driven healthcare or energy or whatever. And so, getting a better understanding of the mobility of capital built into these models and not assuming that any drug that covers its cost of development is going to be developed.
Mel Whittington: Yeah, I think that’s one of the second biggest lessons I’ve learned since I’ve had more and more conversations with investors and innovators is they also have to allocate scarce resources. You know, I’ve always approached this from an insurance pool and those resources, you know, are finite and we want to use them efficiently. Investors and innovators have that same dilemma and have to consider the allocation of their resources and how can they use that efficiently. And that’s just something that I am embarrassed to say that was not at the forefront of my mind up until recently.
Kirsten Axelsen: Well, absolutely. And while there are surely ways we can get a more efficient health system, and some of that is in drugs, some of that’s in hospital spending, you know there’s a bunch of ways we need to be looking to reduce our spending on health care resources. The fact is living longer costs money. And yes, we’re in a resource constrained environment, but countries that spend less on their health care, they have better life expectancy than we are, but it’s not necessarily because of the healthcare spending. There’s more money spent on social services and different types of supportive services that we know improve health even more than healthcare. So that direct comparison of what’s spent in the US to what’s spent outside of other, in other countries needs to also include broader things that affect health.
Mel Whittington: Absolutely, I think international price comparisons, I don’t love it. I don’t love it when people make international price comparisons because I think it’s a lot more complicated than people make it seem. We release a newsletter as part of the Leerink Center for Pharmacoeconomics and in a recent newsletter we looked at branded price comparisons between the US and other high-income countries and then we looked at, okay, let’s actually look after the exclusivity period and there’s research to show that the price in the US drops much steeper and much quicker after loss of exclusivity when competition enters. And so, when you expand that over a product lifecycle, the differential in price between US and other high-income countries goes down. When you adjust for purchasing power parity, then the differential goes down as well. And so, I think it’s clear that the US I think it’s well accepted that the US pays more over the patent protected period, the period that’s really incentivizing ongoing innovation. But then when you expand over a product life cycle or when you consider some differences in purchasing power, that differential changes. So, I think international comparisons are just so challenged by so many reasons, including the ones that you mentioned about just preferences of investing and other things. I’m kind of against international price comparisons. I think they’re far more complicated than people make them seem.
Kirsten Axelsen: Well, absolutely. I agree with you and it is true, as you say, that the US pays more during the patent protected period and also gets faster access to medicines. You know, I found it very frustrating watching, as of most recently, through the hearings and investigations around the obesity drug prices, and you’d see the price in the US and the price in Germany. Well, the German public health system doesn’t cover these medicines. And the Canadian provincial health systems don’t cover these medicines. So yes, the price is higher in the US, but we get faster access to medicines and not just the drugs for obesity, but cancer drugs. If you’re going to have price controls, you have to have some willingness to cut off or limit supply until you get the price you want, which maybe we do. Typically, you know, the US has benefited from faster access to medicines and well, there are lots of things dragging on our health and our lifespan. In the US, you are more likely to survive cancer after five years later than you are in other countries, in part because we have a much better access to medicines.
Mel Whittington: Absolutely. So, I’m a methodologist, and I always think better methods can inform better decisions, and better methods will save the world. As we’re thinking of different strategies to integrate the value of investment into pricing considerations, and we’ve talked about some of the data gaps and the limitations of current methods, are you aware of any method that is being developed or on the horizon that could more explicitly integrate the impacts of future investments and the value of investments into pricing considerations.
Kirsten Axelsen: The Information Technology and Innovation Foundation recently put out three grants specifically for new research into methods to better understand the relationship between R&D and investment. So, I’m anticipating that some good development will happen there. I do think there is interest here. You know, it’s hard. And it’s not, I think, a turnkey thesis, for example, the last Econ meeting I attended, think every paper was about 340B, which is an interesting conundrum, but understandable, right? But I think there’s a lot of room for simulation models and better understanding. Where I think we have a huge data gap is in understanding how venture investors make decisions and understanding how there’s different risk reward profiles at each stage of development. And it is rare that any one drug gets developed sort of from inception to launch by one entity, right? Like many, many initial concepts are developed in an academic setting, often with NIH grant funding. And then, you know, those universities make a lot of money through those royalties if they transfer the technology and the patent to an early-stage biotech firm. And then they need venture investors. So that’s one risk profile. And then big pharma companies have another risk profile. And they’re also looking across their whole portfolio. So, you may have acquired a drug from a small biotech as a large company that is, likely to work in patients, but it may be that some other therapeutic area is really promising. spoke to an investor at the ASCO conference last year and she said, since the advent and the popularity of medicines to treat obesity, the bar is raised even higher on getting investments in cancer drugs because your investors are like, “well, but wait a second, why should I invest in cancer if there’s this other therapeutic area that’s really going gangbusters?”
Mel Whittington: Opportunity costs, competing demands.
Kirsten Axelsen: Opportunity costs, exactly. And none of that is considered, that I’ve seen any of the models today. We really have to be appreciating this as very complex problem. I also think there’s not one answer. I know policymakers have to make decisions on models, but I feel like we’ve put out this perception that it’s, it’s eight drugs not going to be developed as a result of IRA. Well, it’s probably somewhere between zero and 800, you know, reality and what I think we need is more ongoing monitoring as policies are implemented because it’s just almost impossible to know of a change with a large magnitude like that what the impact is going to be on the drug development.
Mel Whittington: Understood. We do like to ask one final question at the close of all of our episodes. You’ve given us already good advice about some data gaps that need to be filled and some things we should be considering in our decision making and in our evidence generation. But we’re hoping to ask you, what is the best piece of advice you have ever received?
Kirsten Axelsen: Thank you. I had a boss once, an economist, love them, my coworker and I brought him something we had literally been up all night working on. And we handed it to him, and he said, “it’s not good.” And we said, “but we’ve been up all night working on it. There’s like, 10 hours of work in here.” And he said, “do I look like a Marxian?” And I was like, “what?” And he said, “I don’t believe in labor theory of value. Just because you worked for a long time on something doesn’t mean it’s any good.”
Mel Whittington: Clearly an economist.
Kirsten Axelsen: Clearly an economist, right? So, I think about that all the time, that sometimes we put a lot of time into something and get stuck on it being good, but in fact, it maybe was just a bad idea in the first place. And so, sort of to remind myself, sometimes you just need to take a pause and reevaluate and not fall in love with the labor you’ve already put into something that might have been a bad idea from the beginning.
Mel Whittington: Okay, well that definitely leaves me thinking I probably have some self-reflection I need to do. Well, Kirsten, thank you so much for being willing to do this podcast episode with us. I’ll continue following you and reading your great work and appreciate all of the content that you do put out in there for us to make better informed decisions and improve the healthcare system.
Kirsten Axelsen: Thank you so much.
Mel Whittington: Thank you.
Thank you for listening to this episode of Perspectives. If you’re interested in participating in future podcasts or would like to learn more about the Leerink Center for Pharmacoeconomics, please email cpe@medacorp.com.
