20 July 2006

Massively Multi-User Medicine

I've just had a medical check-up. In my working life I am saturated with news about biomarkers and translational medicine, so I was curious to know just what goes into a health assessment these days. To what extent has medicine embraced biomolecular science?

There are thousands of genetic variations associated with disease and disease states. I wanted to put myself under this microscope. I figured here in Basel, Europe's pharmaceutical capital, I would have as good a chance as any to experience the state of the art.

I was not prepared for the perfunctory taps to the knee, and the ear, nose and eye spying that awaited me. As a child, I had tapped and spied using the same tools taken from my father's medical kit.

I told my check-up story to a colleague. He had developed software for a medical diagnostic kit that used 5 markers to detect periodontitis from a mouth swab. What struck him about the project was the sheer triviality of the analysis and the enormous emphasis placed on usability: it all had to be dead simple.

What can we conclude here? Things being as they are, translational medicine is progressing at a snails pace. It will need to speed up if we want to see anything resembling the state of the art in a clinical setting. Change is unlikely to be driven internally, from doctors. It will only come when people ask for it.

More than that, people will themselves need to develop, collectively, methods of using this information. It doesn't take a genius to do this and there are ample numbers of qualified people who could make a start. Genome-wide assays of the transcriptome and, more recently, DNA, are now in the $1000 range. All that's needed beyond that is a familiarity with the data itself.

High throughput biological data, such as SNiP (single nucleotide polymorphism) chips, can be analyzed at different levels of detail. A simple analysis needs no more than a spreadsheet and some gene annotation data, which is readily available on the Internet.

Using these resources alone, a SNiP assay could reveal all kinds of insights about ones susceptibility to disease and sensitivity to different treatment alternatives.

This simple kind of analysis is the sort of thing that could develop very quickly in a collaborative setting. With some basic coordination and peer review, important gene annotation could be gathered and developed quickly as people pooled their knowledge.