Eroom's Law - When things take a turn for the worse

Eroom's Law is an opposite of Moore's Law: discovering new medically relevant drugs tends to cost exponentially more over time. An analysis on the phenomenon and possible reasons behind it.

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. This law is named in contrast to Moore’s law of course, which states that the compute speed you can get for a fixed dollar amount doubles every 18 months.

It’s hard to say what’s worse, the staggering decline, or the fact that Eroom’s Law went on unchecked for six decades.

By 2010, the total R&D spend per drug approved was about a hundred times higher, in real dollars, than it was in 1950.

Although some aspects of this disturbing trend line were known since the 1980s, Eroom’s law was formally articulated in 2012, at the tail end of the long decline, in a seminal paper published in Nature Reviews Drug Discovery by four co-authors led by Jack Scannell.

“While the financial returns on R&D may be poor, the idea that you brag about slashing R&D costs has been largely discredited. No one wants to look like Valeant.”

In many therapy areas, you end up with this ever-expanding back catalog of virtually free and very good medicine, against which any new medicine would have to compete. That reduces the value of as-yet-undiscovered drugs. It also pushes drug R&D towards the areas where we don’t have a catalog of good cheap stuff, or precisely the areas where R&D is likely to be harder.

Target Validation

“The rate-limiting step in drug R&D has to do with what people in the drug industry call “target validation” and what I would call “screening and disease model validity.” Target validation is about making sure that the piece of biological machinery really does what you think it does, before you run expensive clinical trials in people.” Jack Scannell

You can only easily experiment on the biological machinery outside of humans, whether in a test tube, in a rat, or with a bit of tissue in a dish. You assume performance in those correlates with performance on humans.

A marginally better model is 10 or even 100 times more productive than a marginally worse model. It used to be that medicinal chemistry was the difficult bit in drug R&D, and patents were a great way to protect unique chemical compounds. Today, it’s target validation that’s difficult, and drug companies don’t have a great way of appropriating much of the value of incremental R&D investment on target validation.

For instance, a drug company could spend a few hundred million dollars working out a new biological mechanism for Alzheimer’s and developing a very valid in vitro or in vivo model. It might even patent the model and use it to find drugs that worked in early-stage clinical trials in people.

But at that point, the basic therapeutic mechanism is proven for all to see. The target has been well and truly validated by the human result. All the other companies can then develop drugs against the same target without having to do all that investment in preclinical models. (Due to Leap-Frogging effect).

Source: Life after Eroom’s Law, Refoundable.

[Share on twitter]

21 Dec 2020 - importance: 5