deCODE genetics was the biotech industry’s champion at scientific discovery – contributing more research papers to top journals than any other company – but its commercial model was far from successful. In November it filed for bankruptcy protection.
Today, happily, the core deCODE genetics business is resurrected as a private company, with new funding – including some from the venture capitalists who originally backed it in the 1990s.
The Icelandic company’s press release boasts proudly but correctly: “deCODE operates the most productive human gene discovery engine in the world.”
It has discovered an amazing number of genetic variations that contribute to common human diseases, often in collaboration with academic groups. But deCODE’s drug development and DNA testing business brought in less revenue than expected, and the company lost serious money in the 2008 Lehmann Brothers crash.
deCODE founder Kari Stefansson will remain as executive chairman and president of research, joined on a two-man executive committee by new recruit Earl “Duke” Collier, previously executive vice-president at Genzyme.
The company says it will continue to offer deCODE diagnostics disease risk tests, deCODEme personal genome scans, and contract service offerings including genotyping, sequencing and data analysis. “Going forward, deCODE will concentrate on translating its science into medically and commercially important products and services,” it says.
deCODE was not universally popular but I am delighted that this very distinctive Icelandic enterprise will live on and, I hope, contribute more to human healthcare.
Financial mathematicians are unlikely to be impressed by Lord Turner’s review of the banking crisis. Their discipline features quite prominently in the first part of the report, looking at what went wrong, but hardly at all in subsequent sections that prescribe solutions.
Lord Turner, chairman of the Financial Services Authority, blames “misplaced reliance on sophisticated maths” for misleading banks’ top management into a false sense of security about the risks they were taking. That is unfair. As Tim Johnson of Heriot-Watt University puts it, the problem was that banks did NOT use sophisticated maths; their mathematical models were far too simple. They had no incentive to employ more complex and realistic models because the simple “single factor” models used for pricing gave an illusion of accuracy and precision – and lulled the market into believing banks had everything under control.
Putting it another way, the models were built to fit market prices. The result was that whacky prices were reinforced by an overlay of scientific respectability.
Lord Turner should have said that we need more and better maths for the future. In particular we require better models of the interdependency of different financial variables and of the risk of extreme events. That means more funding of research in financial mathematics, by the public and private sector.
Another priority, not mentioned by Lord Turner, is to educate bankers about the mathematical basis of their industry. It should no longer be acceptable for them to use models as “black boxes” without making any attempt to understand the underlying assumptions.