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We haven\u2019t yet uncovered the secrets of life, but insurers and statisticians in the 19th century successfully revealed a secret about death that still governs our thinking today: they discovered how to reduce it to a mathematical probability. \u201cLife tables\u201d tell us our chances of dying in any given year, something previous generations didn\u2019t know. However, in exchange for better insurance contracts, we seem to have given up the search for secrets about longevity. Systematic knowledge of the current range of human lifespans has made that range seem natural. Today our society is permeated by the twin ideas that death is both inevitable and random.<\/p>\n\n\n\n
Meanwhile, probabilistic attitudes have come to shape the agenda of biology itself. In 1928, Scottish scientist Alexander Fleming found that a mysterious antibacterial fungus had grown on a petri dish he\u2019d forgotten to cover in his laboratory: he discovered penicillin by accident. Scientists have sought to harness the power of chance ever since. Modern drug discovery aims to amplify Fleming\u2019s serendipitous circumstances a millionfold: pharmaceutical companies search through combinations of molecular compounds at random, hoping to find a hit.<\/p>\n\n\n\n
But it\u2019s not working as well as it used to. Despite dramatic advances over the past two centuries, in recent decades biotechnology hasn\u2019t met the expectations of investors\u2014or patients. Eroom\u2019s law\u2014 that\u2019s Moore\u2019s law backward\u2014observes that the number of new drugs approved per billion dollars spent on R&D has halved every nine years since 1950. Since information technology accelerated faster than ever during those same years, the big question for biotech today is whether it will ever see similar progress.<\/p>\n\n\n\n
Biotech startups are an extreme example of indefinite thinking. Researchers experiment with things that just might work instead of refining definite theories about how the body\u2019s systems operate. Biologists say they need to work this way because the underlying biology is hard. According to them, IT startups work because we created computers ourselves and designed them to reliably obey our commands. Biotech is difficult because we didn\u2019t design our bodies, and the more we learn about them, the more complex they turn out to be.<\/p>\n\n\n\n