There’s R&D, there’s r&D, and there’s R&d –

In his book “Science Business”, Harvard Business School professor Gary Pisano makes a great argument for far more collaboration between biotechnology researchers and businesses such as being attempted by Sage.

In the book, Pisano argues that the biotechnology industry has been organized on the “one patent, one company” high-tech model in which one organization tries to go it alone to create the blockbuster drug.

The problem is that with an electronic widget the challenge is primarily development not research. The basic science is usually known. The specs–the required input and output–for the device are known. Little research is needed; the work is development. Pisano refers to this as little “r”, big “D” — as in r&D.

But in biotechnology there are just to many possible complications, too many unknowns, so the task of product development remains research heavy: “R&d”.

Furthermore with a widget you know relatively quickly if it’s going to work. If things don’t look promising, you can quit while you’re ahead. A promising biotech product, on the other hand, can fail in a phase III clinical trials after decades of work.

Pisano concludes that what biotechnology companies, investors and academic researchers need to do is find a way to breakdown the silos so they can share the costs and risks of the research phase of biotech R&D.

It’s a good read: recommended.

I have always supported the idea of an open network for sharing all the vast amounts of biologic data that has been collected since the early days of microarrays and genomic sequencing. It is frustrating that there have been so many groups that have developed proprietary platforms that have high barriers to entry (primarily cost) or are closed networks (much of big pharma) and I think Stephen is going in the right direction by trying to open this all up.

The value for users is to increase the “connectivity” of the data so that new therapeutic approaches can be developed and the costs can be greatly lowered for people and organizations to find new methods to treat disease. You can still derive a proprietary approach to drug development from this sort of data so the incentives will still remain for investors and no one can complain that it will devalue IP because the sheer volume of information will be so enormous that there will be plenty to go around. Just the ability to take all the disparate data out there and present it in a digestible and useful fashion would lead to explosive growth in drug development in my opinion.

Nice to have the financial links in the story. Why is there no clear link to Sage?