Category: Medicine

Works in Progress has a good review of the state of compensating organ donors, especially doing so with nudges or non-price factors to avoid backlash from those who find mixing money and organs to be repugnant. My own idea for this, first expressed in Entrepreneurial Economics, but many times since is a no-give, no-take rule. Under no-give, no-take, people who sign their organ donor cards get priority should they one day need an organ. The great virtue of no-give, no-take is that it provides an incentive to sign one’s organ donor card but one that strikes most people as fair and just and not repugnant. Israel introduced a no-give, no-take policy in 2008 and it appears to have worked well.

In March 2008, to increase donations, the Israeli government imple­mented a ‘priority allocation’ policy to encourage more people to sign up to donate organs after their deaths. Once someone has been registered as a donor for three years, they receive priority allocation if they themselves need a transplant. If a donor dies and their organs are usable, their close family members also get higher priority for transplants if they need them – ​which also means that families are more inclined to give their consent for their deceased relatives’ organs to be used.

In its first year, the scheme led to 70,000 additional sign-ups. The momentum continued, with 11.1 percent of all potential organ donors being registered in the five years after the scheme was introduced, compared to 7.7 percent before. According to a 2017 study, when presented with the decision to authorize the donation of their dead relative’s organs, 55 percent of families decided to donate after the priority scheme, compared to 45 percent before.

What would happen if the FDA regulated pharmaceuticals much less than currently? I have pointed to one useful comparison, new uses of old drugs do not have to go through FDA required efficacy trials in the new use. In other words, new uses of old drugs are regulated for safety-only. Thus,
“off-label prescribing” provides a window on to what a world of safety-only FDA regulation would look like. Off-label prescribing surely results in errors and problems but overall physicians tell us that off-label prescribing is highly beneficial and critical to good medical care.

Maxwell Tabarrok points to another useful comparison, surgery. Surgery is not FDA regulated, despite having many of the same asymmetric information problems as pharmaceuticals. Some surgical procedures are surely ineffective and unsafe. Yet, once again, the FDA-absent surgery market appears beneficial overall and like other markets it improves over time with greater safety and more efficacy. For example,

In the US, the death rate from medical and surgical care complications declined by 39% from 1999 to 2009.

Would we be better off if every new surgical procedure had to go through FDA-required efficacy trials before it could be offered to consumers?

Neither of these comparison proves that a world with less FDA regulation would be a better world but both refute the stories of a world run amuck in the absence of the FDA. In essence, the reason is that the world contains many sources of approval, recommendation, certification and review beyond the FDA and these would grow in scope and stature absent the FDA.

See Maximum Progress for more.

Addendum: More excellent Tabarrok material: The Spice Must Flow: The Dutch-Portuguese War-Part 1.

During the pandemic, when vaccines doses were scarce, I argued for fractional dosing to speed vaccination and maximize social benefits. But what dose? In my latest paper, just published in PNAS, with Phillip Boonstra and Garth Strohbehn, I look at optimal trial design when you want to quickly discover a fractional dose with good properties while not endangering patients in the trial.

[D]ose fractionation, rations the amount of a divisible scarce resource that is allocated to each individual recipient [3–6]. Fractionation is a utilitarian attempt to produce “the greatest good for the greatest number” by increasing the number of recipients who can gain access to a scarce resource by reducing the amount that each person receives, acknowledging that individuals who receive lower doses may be worse off than they would be had they received the “full” dose. If, for example, an effective intervention is so scarce that the vast majority of the population lacks access, then halving the dose in order to double the number of treated individuals can be socially valuable, provided the effectiveness of the treatment falls by less than half. For variable motivations, vaccine dose fractionation has previously been explored in diverse contexts, including Yellow Fever, tuberculosis, influenza, and, most recently, monkeypox [7–12]. Modeling studies strongly suggest that vaccine dose fractionation strategies, had they been implemented, would have meaningfully reduced COVID-19 infections and deaths [13], and perhaps limited the emergence of downstream SARS-CoV-2 variants [6].

…Confident employment of fractionation requires knowledge of a drug’s dose-response relationship [6, 13], but direct observation of both that relationship and MDSE, rather than pharmacokinetic modeling, appears necessary for regulatory and public health authorities to adopt fractionation [15, 16]. Oftentimes, however, early-phase trials of a drug develop only coarse and limited dose-response information, either intentionally or unintentionally. A speed-focused approach to drug development, which is common for at least two reasons, tends to preclude dose-response studies. The first reason is a strong financial incentive to be “first to market.” The majority of marketed cancer drugs, for example, have never been subjected to randomized, dose-ranging studies [17, 18]. The absence of dose optimization may raise patients’ risk. Further, in an industry sponsored study, there is a clear incentive to test the maximum tolerated dose (MTD) in order to observe a treatment effect, if one exists. The second reason, observed during the COVID-19 pandemic, is a focus on speed for public health. Due to ethical and logistical challenges, previously developed methods to estimate dose-response and MDSE have not routinely been pursued during COVID-19 [19]. The primary motivation of COVID-19 clinical trial infrastructure has been to identify any drug with any efficacy rather than maximize the benefits that can be generated from each individual drug [3, 18, 20, 21]. Conditional upon a therapy already having demonstrated efficacy, there is limited desire on the part of firms, funders, or participants to possibly be exposed to suboptimal dosages of an efficacious drug, even if the lower dose meaningfully reduced risk or extended benefits [16]. Taken together, then, post-marketing dose optimization is a commonly encountered, high-stakes problem–the best approach for which is unknown.

…With that motivation, we present in this manuscript the development an efficient trial design and treatment arm allocation strategy that quickly de-escalates the dose of a drug that is known to be efficacious to a dose that more efficiently expands societal benefits.

The basic idea is to begin near the known efficacious dose level and then deescalate dose levels but what is the best de-escalation strategy given that we want to quickly find an optimal dosage level but also don’t want to go so low that we endanger patients? Based on Bayesian trials under a variety of plausible conditions we conclude that the best strategy is Targeted Randomization (TR). At each stage, TR identifies the dose-level most likely to be optimal but randomizes the next subject(s) to either it or one of the two dose-levels immediately below it. The probability of randomization across three dose-levels explored in TR is proportional to the posterior probability that each is optimal. This strategy balances speed of optimization while reducing danger to patients.

Read the whole thing.

A reader in the industry writes with excellent comments on yesterday’s post on the Chris Rock hypothesis.

Long-time reader, first-time emailer–love the show ;).  I’ve been in and around the pharma industry for nearly 30 years, and I’ve spent time in gene therapy/gene editing where the one-time cure model dominates.  Some thoughts on chronic vs. curative dosing and why a curative therapy is likely worth less:

1. There’s a potential mismatch between payment for a drug and the accrual of value that justifies its price point.  If I take a curative therapy for a disease like hemophilia (e.g., the new $2.9 M drug, Roctavian), the insurance company immediately incurs the cost of the drug, but the prime financial benefits (no more expensive chronic therapy, reduced expensive visits to the hospital) accrue over time.  Patients switch insurance companies as they switch jobs, so the “payout” that justifies the treatment price accrues to the subsequent insurers.  On chronic therapy, if a patient switches to another insurer, the new insurer picks up the payments so there’s no such disconnect.  Rationally, insurers should pay more for chronic therapy, even in present value terms.
2. Durability of effect is unknown until it isn’t.  It’s difficult to charge for a drug as a cure until such time you know it’s a cure and have proven it as such.  How long do you have to follow treated patients to prove that?  Gene therapies are starting to show waning efficacy in some cases.  The FDA mandates that you cannot include something in the drug label that has not been proven.  Payors will point to a label and ask why they should pay for something that’s not on there.  This can be mitigated by programs where the drug company pays back a portion of the cost if it doesn’t work, but collecting on that seems like a huge hassle–how do you prove that it stopped working (I can hear Mike Munger–“the answer to your question is transaction costs…”)?
3. Sticker shock and headline numbers.  A drug that costs $3 M or more is something the White House can use at a podium and get a reaction.  Never mind that it gets paid back pretty quickly by discontinuing a therapy that costs hundreds of thousands per year–life-saving drugs should not cost millions of dollars!  This puts downward pressure on one-time cures.

So, my perspective is that it is more difficult for a one-time treatment/cure to capture the value it creates vs. a chronic therapy.  So, why did Lilly shares tumble on the news?  More important than duration of therapy is market share vs. competitors.  A more permanent solution (with no rebound after discontinuation) would more than make up for lost revenue on the back end by taking share from the competition on the front end.  And THAT is why pharma is incentivized to pursue cures.  Making a better drug will beat the competition, and a cure is a better drug.  Big Pharma doesn’t necessarily pursue curative treatments directly because they don’t know how.  Technologies like CRISPR and mRNA have to come up via biotechs that are purpose-built to maximize the platforms’ value and to understand/navigate the underlying technology.  That said, Big Pharma has inked HUGE deals to gain access to these technologies (e.g., Pfizer/BioNTech), so they do seem to come around eventually.

These are all excellent points. On point 1, note that Medicaid creates similar incentives in that insurance firms want to farm long term costs onto Medicaid.

Point 3 suggests that we should be especially wary of price controls on cures. Sticker shock may drive us to price controls leaving us with treatments that look cheaper but are even more expensive in the long-run (and by present discounted value). Sovaldi is a case in point. Its initial $84,000 price generated huge opposition even though it typically cured hepatitis C infections and avoided many later liver cancers and saved money overall. Indeed, as I pointed out earlier, Sovaldi so reduced the number of liver transplants that more people with other diseases ended up with life-saving transplants.

This is also what I meant by starting in the right place. If you start in the right place you have some hope of getting to real causes and possible solutions.