I never discuss my own research on this website – it’s more fun (for me at the very least!) to dive in to the great results the rest of the economics community produces. So I hope you’ll forgive me for breaking this rule today, as I want to show a few interesting, very time-sensitive results Jorge Lemus, Guillermo Marshall and I have developed about Covid-19 innovation.
Many of us in the innovation economics world have been asked by governments how they should handle R&D right now. The basic problem is clear. There is a pandemic. Stopping this has enormous economic benefits – a vaccine that arrived tomorrow would literally be among the most economically valuable inventions ever made. Treatments which allow normal economic activity are incredibly valuable as well. As always, governments have limited knowledge about who is able to invent what. There is tremendous uncertainty about how various R&D projects will pan out. Should government be running huge prizes for specific inventions? General subsidies for medical R&D? Precommitments to buy certain remedies? Perhaps laissez faire alone is enough to induce this invention? Should patents be stronger, to increase the returns to R&D, or should they be weaker, to encourage the WHO’s global access to remedies?
These are very challenging questions. Let’s instead narrow down to a simpler one: given existing policy, is the rate and direction of Covid-19 R&D worrying in any way? Our basic finding is that the rate of Covid innovation is incredibly rapid, but competitive forces are pushing that research in a very short-term direction. The policy implications are subtle – many ideas that we normally think of as useful for R&D, especially on global health issues, may actually be counterproductive.
Here we compare the rate of therapies somewhere in the pipeline, and the number of academic publications, related to Covid-19 compared to other epidemics like Zika, Ebola, and H1N1, and compared to breast cancer, the most heavily-funded long-run disease. The pipeline data is from BioMedTracker, a standardized commercial research database that independently validates reports of new projects on a given indication. Note two things. First, the rate of Covid research far exceeds the long-term average for breast cancer or the post-epidemic rate of research on Ebola, H1N1, or Zika. Second, this gap grows even larger after the globalization of the pandemic in early March 2020, as indicated by the vertical line in the figures. Covid therapies are entering the pipeline at a rate 15 to 80 times faster than any previous epidemic, with over 4 new therapies entering the commercial pipeline every single day. The number of these therapies in clinical trials within four months of the early December beginning of the epidemic exceeds the entire first-year number of trials for H1N1, Zika, and Ebola combined. This figure tracks through April 22, but the rate of new drugs in the pipelines since that date has continued at nearly the same pace. The expected return on Covid innovation is high enough to induce an incredible amount of entry.
Alas, there is a downside. Let’s split the pipeline into vaccines vs. other drugs, and repurposed drugs vs. novel compounds. The relative share of “short term” solutions – non-vaccines and repurposed drugs – is unusually high. 23 percent of Covid therapies are vaccines, versus at least half for the previous three recent less severe epidemics. Over 60 percent of Covid therapies are repurposed drugs, versus no more than a quarter of those for Ebola, Zika, or H1N1. The short-term share is particularly strong after Covid explodes globally in early March – the rate at which new vaccines enter the pipeline is essentially the same in February and April! Broadly, as the epidemic gets worse, a greater share of R&D goes to projects that can be developed quickly.
How should we interpret this? We need a model to understand what the direction of invention “should be”. Theoretically, let there be firms of different sizes considering paying a fixed cost to enter the market for drug therapies on a particular disease. After entering, these firms choose whether to work on short-term therapies, which can be developed quickly but are not as valuable, or long-term ones, which take time to invent but are quite valuable. Once some firm invents a remedy, the marginal value of other remedies change: for instance, a vaccine is more valuable than a treatment, but the marginal value of the vaccine if a reasonable treatment exists is lower than it would have been otherwise.
Let’s model an epidemic intensifying by a multiplicative increase in the payoff to all inventions related to that disease. This increased payoff for successful invention, holding the number of firms constant, increased each firm’s expected payoff from R&D. The higher expected payoff induces more firms to enter, particularly firms with limited specialized research capacity who otherwise wouldn’t bother with a disease outside their wheelhouse.
Increased entry means a more fractured market for R&D, with many small firms doing research instead of just a few big ones. Assume it would be efficient for most firms to try to invent a vaccine. A small firm – say, one which represents 1% of total research capacity in the industry – will reason as follows. “I can try to invent the vaccine, but the Sanofis and the Modernas of the world are likely to get their vaccine way before I do. However, since their projects will take many months to develop and validate, I can instead try to quickly develop a marginally useful treatment. The existence of that treatment, once invented, lowers the marginal payoff to working on vaccines, but who cares – I am very unlikely to invent a vaccine in any case.” The increased entry driven by huge payoffs to any successful Covid therapies causes entrants to inefficiently race toward lower-value therapies. If enough small firms begin to race in this way, even the large firms that otherwise would have worked on vaccines will give up. And note that this pattern appears empirically: more severe epidemic leads to more entry by small firms, more work on short-term projects, and a decreasing share of long-term projects even from large firms as that competitive racing gets worse.
The policy implication is somewhat worrying. Normally, we worry in global public health that there isn’t enough incentive to work on a disease class at all, since firms worry that poor countries would either be unable to afford, or would expropriate ex-post, any useful invention. Things like the advance market commitments supported by last year’s Nobel winner Michael Kremer, have richer governments precommit to buying successful therapies for diseases like malaria. In the case of Covid, however, the main problem isn’t the rate of innovation, but the direction – the expected financial return on innovation may be too high for short-run, partial solutions, yet too low for vaccines or novel therapies.
So how can society both encourage a ton of Covid-19 R&D so we can escape this pandemic, while also discouraging racing behavior toward minor solutions? We propose three solutions. First, limited antitrust enforcement on research joint ventures can help by causing firms to partially internalize the racing externality they would otherwise have imposed on their joint venture partner. Second, targeted subsidies specifically for vaccines or promising novel therapies reshift the balance back toward the social optimum. It’s amazing how little of this is being done: a recent Guardian roundup of leading vaccine candidates proudly notes that 40 million pounds of support has been given to the Imperial College London team. 40 million in support for a vaccine that, if successful, probably has a net present value of over a trillion pounds! Third, we suggest AMCs can be useful as long as the value of the AMC is based on the ex-ante value of the therapy being developed, rather than the ex-post value – doing so allows firms with ability to work on long-term, high-value solutions to ignore the racing being done by their smaller rivals.
April 2020 Draft: “Innovation During a Crisis: Evidence from Covid-19”. We worked very hard – literally many all nighters – to get an analysis done quickly which nonetheless uses the best available Covid R&D data, and provides policy advice based on rigorous innovation theory. In my work with an entrepreneurship program here at the University of Toronto since we finished the draft, where we consult with very experienced biotech VCs, I’ve actually noticed our proposed mechanism in action – everyone is aware of the competitive nature of Covid research, and the first-order questions are always whether a firm has the capacity to work at high speed, and whether their therapy could be modified into something less significant but quicker to develop. I truly do not believe the externality we suggest is merely a theoretical curiosity.