Noodling on samples, the real currency of the life sciences.

While it’s obvious in retrospect, until recently I didn’t really understand the one thing that fundamentally makes it difficult to move the life sciences forward. It comes down to exactly one word: samples.

We have no credible virtual models of the human body, so the only way we can figure things out is to measure “stuff” in real people. Stuff that usually requires cutting or poking into their bodies. Often many times, over the course of many years. After giving them drugs or other agents that we’re not really sure about. And not just any people, but those that match certain disease or other criteria that may be pretty rare. And not just a couple of people, but enough to be able to draw statistically-relevant conclusions.

Looked at in this way … it’s amazing we learn anything, actually.

We’ve tried to create mathematical models of biology. We’ll get there someday, but so far we’ve struggled. Which is why, despite all the ethical questions around humanely managing the practice, we do so much of our experimentation using animals — preferably animals like mice that reproduce quickly and can be engineered to approximate the conditions that affect humans.

But the gold standard, and the one required by civilized society before calling any new drug or intervention “good” … is human studies. And that is just a long, long, expensive road.

This reality has a surprising impact on just about every facet of our work. For example, over the last week or so I’ve been helping out a couple of our scientists set up a public data set we’ve created. It’s pretty awesome — immune sequencing data that we’ve created at significant expense — and we’re giving it away for free. (Of course, it’s not completely altruistic; we want folks to see for themselves the value of the assays we’ve developed and sell, but still.)

The route to publicizing data like this is to publish it in a “respectable” journal. To do that, you have to get through a gauntlet of peer review that passes judgment on its overall scientific value. And human nature being what it is, this is an EXTREMELY political process. It’s a perfect vehicle for cranky scientists to show just how much smarter they are than everyone else. Super annoying.

There must be a better way, I thought. Certainly in a connected world like this we have plenty of options to make people aware of the data. But our CSO pushed back on me — how would this really work? Folks need some confidence beyond “we say so” to believe that the data we share is valid and trustworthy, because all science is building one discovery atop another.

And here’s the rub — it is so expensive and time-consuming to run life science experiments; there is simply no practical way to validate them all in the real world. So we’ve adopted peer-review, an intentionally political process as a proxy to, hopefully, ensure that at least we aren’t actively lying and can back up our processes and methods.

Fields backed by well-understood math don’t have this problem. In theoretical physics, anyone (ok not anyone, but enough) with a computer or maybe even a pencil can validate published results with minimal investment. And they do, so bogus research gets noticed pretty quickly. Not so for us.

It’s frustrating when I can’t come up with a better solution for something that seems so obviously broken. But I guess that’s one more reason that the work we’re doing now is important … it gets us closer to understanding the systems, and with enough understanding we will begin to create the mathematical models that will accelerate progress and eliminate human ego from the game.

Wait, would that be the singularity?



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