...Modern drug discovery aims to amplify Fleming's serendipitous circumstances a millionfold: pharmaceutical companies search through combinations of molecular compounds at random, hoping to find a hit.
But it's not working as well as it used to. Despite dramatic advances over the past two centuries, in recent decades biotechnology hasn't met the expectations of investors -- or patients. Eroom's law -- that's Moore's law backwards -- observes 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. Compare biotech startups to their counterparts in computer software.
[comparison table here]
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's 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't design our bodies, and the more we learn about them, the more complex they turn out to be.
But today it's possible to wonder whether the genuine difficulty of biology has become an excuse for biotech startups' indefinite approach to business in general. Most of the people involved expect some things to work eventually, but few want to commit to a specific company with the level of intensity necessary for success. It starts with the professors who often become part-time consultants instead of full-time employees -- even for the biotech startups that begin from their own research. Then everyone else imitates the professors' indefinite attitude. It's easy for libertarians to claim that heavy regulation holds biotech back -- and it does -- but indefinite optimism may pose an even greater challenge for the future of biotech.My readership is far more knowledgeable about pharma than I am. Suffice it to say that Thiel's characterization of modern medicinal chemistry is a lot closer to, say, Marcia Angell's understanding than it is to someone in the industry. "combinations of molecular compounds at random" Eyeroll.
What I am really stunned by is Thiel's suggestion that biotech startups having insufficient willpower and intensity for success. Most of the time, they're structured just like software startups, with a staff of smart, hungry young scientists who are fully employed by the companies and strongly incentivized by their pay structure to make big impacts and meet their milestones. I'm not really sure that it matters that the professors are only consultants -- most of the time, it's the relevant laboratory folks (postdocs, grad students) that get hired in full-time to really get the laboratory work started.
Why does Peter Thiel think that software startups have sufficient willpower to wield the Green Lantern ring, but biotech startups do not? I'd love to know what kind of interactions with biotech that he has had that he's come away with such a poor (and misinformed, in my opinion) viewpoint. We'll never know, I suppose.