This assumption—that understanding a system’s constituent parts means we also understand the causes within the system—is not limited to the pharmaceutical industry or even to biology. It defines modern science. In general, we believe that the so-called problem of causation can be cured by more information, by our ceaseless accumulation of facts. Scientists refer to this process as reductionism. By breaking down a process, we can see how everything fits together; the complex mystery is distilled into a list of ingredients. And so the question of cholesterol—what is its relationship to heart disease?—becomes a predictable loop of proteins tweaking proteins, acronyms altering one another. Modern medicine is particularly reliant on this approach. Every year, nearly $100 billion is invested in biomedical research in the US, all of it aimed at teasing apart the invisible bits of the body. We assume that these new details will finally reveal the causes of illness, pinning our maladies on small molecules and errant snippets of DNA. Once we find the cause, of course, we can begin working on a cure.Alas, the human body is one of those complex systems that cannot be understood that way. A drug that fits perfectly into one well-understood loop may have impacts on some other system in another part of the body that undo the good done in the targeted part. The only way to know what some compound will do in the body is to try it out in several thousand volunteers and watch.
We have made great progress in understanding the world through the statistics of correlation, measuring precisely how likely it is that two things go together. In some cases, like smoking and lung cancer, the connection turns out to be very powerful, and leads to simple prescriptions. More and more often, though, the reason for the correlations we observe remains murky at best. Cause, as philosophers have understood at least since Aristotle, is a slippery thing. Once you get beyond the collisions of rolling steel balls, it is just very hard to be sure that one thing causes another. Lehrer:
The reliance on correlations has entered an age of diminishing returns. At least two major factors contribute to this trend. First, all of the easy causes have been found, which means that scientists are now forced to search for ever-subtler correlations, mining that mountain of facts for the tiniest of associations. . . . Second—and this is the biggy—searching for correlations is a terrible way of dealing with the primary subject of much modern research: those complex networks at the center of life. While correlations help us track the relationship between independent measurements, they are much less effective at making sense of systems in which the variables cannot be isolated. Such situations require that we understand every interaction before we can reliably understand any of them. Given the byzantine nature of biology, this can often be a daunting hurdle, requiring that researchers map not only the complete cholesterol pathway but also the ways in which it is plugged into other pathways. Unfortunately, we often shrug off this dizzying intricacy, searching instead for the simplest of correlations. It’s the cognitive equivalent of bringing a knife to a gunfight.It may be that our ever increasing knowledge of the body and other complex systems will eventually add up to a profound understanding, but right now that isn't happening.
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