Venture-capital guy Bruce Booth has a provocative post, based on experience, about how reproducible those papers are that make you say “Someone should try to start a company around that stuff”.
The unspoken rule is that at least 50% of the studies published even in top tier academic journals – Science, Nature, Cell, PNAS, etc… – can’t be repeated with the same conclusions by an industrial lab. In particular, key animal models often don’t reproduce. This 50% failure rate isn’t a data free assertion: it’s backed up by dozens of experienced R&D professionals who’ve participated in the (re)testing of academic findings. This is a huge problem for translational research and one that won’t go away until we address it head on.
Why such a high failure rate? Booth’s own explanation is clearly the first one to take into account – that academic labs live by results. They live by publishable, high-impact-factor-journal results, grant-renewing tenure-application-supporting results. And it’s not that there’s a lot of deliberate faking going on (although there’s always a bit of that to be found), as much as there is wishful thinking and running everything so that it seems to hang together just well enough to get the paper out. It’s a temptation for everyone doing research, especially tricky cutting-edge stuff that fails a lot of the time anyway. Hey, it did work that time, so we know that it’s real – those other times it didn’t go so smoothly, well, we’ll figure out what the problems were with those, but for now, let’s just write this stuff up before we get scooped. . .
Even things that turn out to be (mostly) correct often aren’t that reproducible, at least, not enough to start raising money for them. Booth’s advice for people in that situation is to check things out very carefully. If the new technology is flaky enough that only a few people can get it to work, it’s not ready for the bright lights yet.
He also has some interesting points on “academic bias” versus “pharma bias”. You hear a lot about the latter, to the point that some people consider any work funded by the drug industry to be de facto tainted. But everyone has biases. Drug companies want to get compounds approved, and to sell lots of them once that happens. Academic labs want to get big, impressive publications and big, impressive grants. The consequences of industrial biaes and conflicts of interest can be larger, but if you’re working back at the startup stage, you’d better keep an eye on the academic ones. We both have to watch ourselves.
Update: by request, here’s a translation of this page in Romanian