Via the Economist‘s “Free Exchange” blog comes this provocative paper (PDF) from the University of Chicago, Harvard, and MIT. Its authors are looking at the effect of patents on the oncology drug market, and they conclude that the current system is probably hurting patients (and the broader economy).
That’s a big statement to make, so the first thing to do is dig into the paper and see how it was arrived at. The authors are looking at effective patent terms: how long an invention really has an exclusive market term. That’s a big issue in drug development, of course, since the regulatory pathway to approval can be so long that only a few years are left on the patent by the time a drug can be sold.
. . .Since society cares about an invention’s total useful life, but private firms care only about monopoly life, a distortion emerges not just in the level of R&D (as arises in standard models), but also in the composition of R&D: society might value invention A more highly than invention B, but private industry may choose to develop B but not A. Note that, other things equal, commercialization lag lowers both monopoly life and total useful life: both society and private firms prefer inventions to reach the market quickly. But, under a fixed patent term, commercialization lag reduces monopoly life more rapidly than total useful life, hence the distortion away from inventions with both a long total useful life and a long commercialization lag.
The problem with oncology, the paper claims, is that drug firms therefore have an incentive to work on compounds whose clinical trials are shorter, because they have a better chance of a longer effective patent lifetime). Slow-moving cancers, which might be more treatable, are relatively neglected, because there is less likelihood of return from them given the patent timelines.
Cancer drug development tends to be specific to a cancer type (e.g. prostate) and stage of disease (e.g. metastatic). . .providing a natural framework for estimating how expected commercialization lags (as proxied by survival time) and R&D investments vary across different groups of patients. Aggregating survival information from patient-level cancer registry data, we document stark variation in survival times across patients of different cancer types and stages of disease. In order to measure R&D investments on cancer treatments relevant to each cancer type and stage of disease, we use newly-constructed data from a clinical trial registry that has cataloged cancer clinical trials since the 1970s. The key feature of this data which makes it amenable to our analysis is that for each clinical trial, the registry lists each of the specific patient groups eligible to enroll in the trial – thus allowing a match between our measures of expected commercialization lag (as measured by survival time) and R&D activity (as measured by clinical trial investments) across cancer types and stages of disease.
They show that there is much more clinical focus on the severe short-time-course cancers than on the slow-moving localized types, and they ascribe this to distortion caused by patent terms. But as far as I can tell, the authors don’t consider some other factors, and as someone who’s done drug discovery work in oncology, I’d like to bring these out as well.
There’s no doubt that patent lifetimes are a factor, since these allow a company to recoup its development costs – and the costs of all the other failed projects. It’s worth remembering that the overall clinical failure rate is still roughly 90%, so there are a lot of costs to be made up whenever sometime actually does work. But imagine that patent terms were suddenly doubled to forty years instead of twenty. This might bring in more investment into slower-moving long-term cancer projects, but I don’t think it would be as simple as this paper’s model suggests. Overall, a drug company would prefer not to tie up its time, effort, and capital for longer than necessary in the uncertain business of a clinical trial. Even with the prospect of a longer patent term reward at the end of the process, the disincentive for multiyear trials would still be there, because there are so many shorter alternatives in oncology. (That’s as opposed to Alzheimer’s, where it’s long trials or nothing, at least until we understand a lot more about the disease). It’s not like the slower-moving cancers are any easier to understand, find targets for, or progress into the clinic: they’re all hard.
This is even more the case when you consider that the oncology field has a good number of small companies in it. The barriers to oncology drug development are lower than in some other areas – it’s easier to identify patients, and there’s a lot of unmet medical need. And those relatively short clinical trial times are another incentive: to do another thought experiment, if you suddenly required all drug companies working on oncology to work only on the slower-moving cancers, there would be far fewer drugs in development, since most of the smaller companies would drop out. They don’t have the funds to keep going that long. So while short clinical trials may be a distortion in one direction, they have distorted the market in another, arguably beneficial direction as well, by bringing more companies and more ideas into the field.
I say “beneficial”, because some of the drug mechanisms that are being tried on the faster-moving cancers would also be of use on the slower, more localized ones. The genomic, metabolic, and proteomic information learned by studying the faster-moving varieties (and the techniques used to do so) are immediately applicable to the slower-moving ones as well. It’s not a zero-sum game.
There’s also that unmet-medical-need factor to consider. It’s easier for a company, especially a small one, to raise money and justify its spending to investors when it’s working against form of cancer with a low survival rate and a relatively fast progression. The belief is that the regulatory barriers to approval are lower for such drugs, and that uptake by physicians would be faster if the drug gets approved. Side effects are also going to be more tolerated for more severe conditions, too, and oncology drugs, as is well known, tend to have some pretty significant ones.
The authors, after considering several alternatives, present evidence that when regulatory agencies allow surrogate endpoints as a factor for drug approval that investment in the longer-term cancers improves. They suggest that research into validated markers of this sort could have the best returns overall, compared to other possibilities (such as just lengthening patent terms, not that that’s going to happen in the real world, anyway). And I agree with them there – but I also note that drug companies themselves have been seeking such surrogate endpoints on their own, for the same reasons. (These things speed up all trials, not just the longer ones). Large incentives for good clinical trial markers already exist, but such markers are pretty damned hard to come by, unfortunately.
But as for the main subject of this paper and its explanatory power, I’m not quite convinced. As far as I can see from going through the manuscript, none of the other factors mentioned above have been considered – everything is tied to the effective patent lifetime. And while that’s probably real, and a partial surrogate for some of these issues, I have trouble buying it as the only thing that’s going on. Now, this may be what economists do: find a correlation that is open to a mathematical treatment and run with it. But I don’t see how you can make statements this sweeping without going into more of what (from my perspective) I see as the real world of drug discovery and development.