refoundable

> Why do you think that cheaper development costs will ultimately lead to lower drug prices?

If the cost of drug development were to drop by a factor of 100-1000, say from the $3B it costs today to the $3-30M range, that would likely unleash a massive wave of decentralization in the industry that would make it very hard to justify outrageously high drug prices for long.

However, short of a large drop of that magnitude, I agree that we'll probably continue to see Pharma companies charging as much as they can get away with and the political climate allows.

> I don't need a thousand drugs on the market to treat every indication. [...] If lowering the efficacy standards doesn't get me treatment for new indications, why would I want it?

It's true that the Better than the Beatles problem rewards consumers with cheaper drugs, but on the flipside, it robs them of the benefit of newer drugs.

As a result, all the technical capabilities that the Pharma industry gained into developing drugs that are less toxic or better targeted do not get translated into consumer benefit when the BTTB problem is in the way.

Moreover, once an area of drug development stops seeing new commercial success in decades, hysteresis sets in and can drive Pharma companies out of such areas, which has largely been the case with anti-infectives since the 1980s. (See Question 11 in the interview)

Thanks for the great catch. Fixed.

That's certainly what's implied by Scannell's answer to Question 8, but such a solution comes with its own set of limitations related to design by committee.

Small startup teams are still the most effective way to solve hard problems in our society, and so I suspect that any definitive solution would likely be built and sold to the industry by such a team.

No disagreement on the skewed stats. And I won't dispute the need for a minimum standard of efficacy.

However, if anything, the problem that we've had over the last 60 years is setting the standard of efficacy too high. This caused the Better than the Beatles problem, and placed Pharma companies in an impossible situation where they have to run faster and faster just to stay in the same place.

Moving forward, if we're not going to lower the efficacy standard, then the questions that Scannell raises about model validity and the search problem writ large become even more pressing and important.

On the other hand, if we're not going to solve the search problem, then the pragmatic solution would be to lower the efficacy bar somewhat so Pharma companies can at least create slightly less effective but way cheaper drugs.

In theory, we should be able to do both. In practice, we're likely to get one way before the other. The current path we're on of fewer drugs and higher prices is simply unsustainable.

On angiogenesis, see Judah Folkman: https://www.tobinproject.org/about/judah-folkman

On cancer immunotherapy, see Fran Visco's story as partially told by Daniel Sarewitz (section titled "War on Cancer"): https://www.thenewatlantis.com/publications/saving-science

I echo both observations and urge you to name that law.

Will look under the hood at the CSS.

It's worth noting that the most effectives breakthroughs against cancer in recent decades (Immunotherapy, angiogenesis-suppressing drugs) have largely been based on ideas that were first dismissed and widely ridiculed by senior scientists working on cancer research.

I suspect that in another 50 years, when the war against cancer is (finally) over, we will end up with a completely different perspective on the history of cancer research than the often self-serving and propagandized perspective we have today.

You're right on the money.

Any breakthrough that could either dramatically shorten the feedback cycle (from years to weeks), or reduce the cost of drug development by 100-1000x would unlock so much value as to completely reshape the structure of the Pharma industry.

The consolidation of the industry in recent decades could be justified by the high fixed costs of drug development that made it necessary to seek greater economies of scale, but in a world where the cost of drug development drops precipitously, the pendulum could swing in the other direction, unleashing a wave of decentralization in the industry.

Absent this kind of breakthrough, I expect only more intense regulatory and pricing pressures for the Pharma industry in coming years.

I see no reason why we can't do both. We obviously need better drugs for the diseases we haven't yet cured, and we need cheaper drugs for the diseases we've already cured. The two are related yet distinct problems.

Incidentally, Scannell wrote one of the best teardowns of how drug pricing actually works: https://www.forbes.com/sites/matthewherper/2015/10/13/four-r...

> Having better tox models seems like the highest value, albeit very difficult, route here. Which to me is a separate, more general, problem than a specific disease model.

Agreed. Better toxicity testing would go a long way towards solving some aspects of the search problem.

I agree that discovery is far from a straight-forward process, and that many of the cavalier ways in which it happened in decades past would be criminally prosecuted and beyond the pale today.

But I don't think that there was ever much low-hanging fruit to begin with. Discoveries always look "obvious" ex post and almost never ex ante.

I find it best to think of "low-hanging fruit" as a euphemism that polite people have agreed to use in order to excuse the massive failure that has taken place and stop curious people like Scannell from asking too many questions.

The FDA does not allow Pharma companies to create safe and slightly less effective drugs than the best-in-class, even if such drugs were 10-100x cheaper and would thus alleviate most people's complaints about outrageous drug prices.

Scannell's observations are focused on the problem of finding drugs that are more effective than the current best-in-class, the so-called Better than the Beatles problem.

This turns out to be a really hard search problem, given for instance that animal models make unreliable and poor substitutes for humans beings, or that you're generally not allowed to base drug approval on small but highly representative patient populations (with some exceptions). There are even more technical problems I won't get into here (see Question 9 in the interview).

In short, I see no reason why we couldn't be getting slightly less effective but way cheaper drugs today if the FDA was willing to slightly relax its use of the precautionary principle. But in order to keep pushing the frontier of drug efficacy, we'll need new technical breakthroughs to help us solve the search problem.

Most people tend to focus on the cost side of Eroom's law, but I find its most disturbing implication to be the other side: That between 1950 and 2010, we got ~100x worse at finding drugs that actually work.

That suggests that there's something deeply broken about the science, and not just about the regulation or the cost structure.

Thank you. It takes a fair bit of time to put something like this together, so I appreciate your kind words.

Author here.

I interviewed Jack Scannell on the hypothesis that the man who wrote the now famous paper on Eroom's law would likely have many more insights to offer that didn't necessarily make it into print.

One of the oddest things about biotech and pharma is that cures trail improvement in technology by at least a couple of decades. That's terrible news if you're a patient/consumer though maybe great news if you're a lab technician.

A more accurate definition pulled from the introduction:

> Eroom’s law is the observation that the cost of developing a new drug roughly doubled every nine years from 1950 through 2010. All in all, it shows a roughly 80-fold decline in the productivity of drug R&D.

No idea what's causing this for you. Can you say a bit more about your setup?