So
goes the

story in the December
Technology Review. Biotech companies have
made substantial sums on life-saving complex protein drugs,
and now the patents are starting to expire. With "small
molecule" drugs (the kind regularly advertised on television
and in the hundreds of pieces of spam you got today), the
process of duplicating the molecule in order to create a
generic version is straightforward, as are the tools for
confirming that the drugs are identical. But proteins are
big, complicated molecules, with varying properties
depending on

how they fold.
Biomedical proteins aren't just conjured up in test tubes,
but are often produced by reengineered bacteria. Duplication
is difficult. But help is on the way:

 

Emerging technologies, however, could
improve the precision of protein characterization,
helping to divorce biotech products from the processes
used to make themand perhaps reducing the amount of
clinical testing necessary. Generics companies such as
Israels Teva and GeneMedix in England, for instance,
use ever improving analytical techniques and
computational methods to accurately characterize the
three-dimensional structures of proteins. Those
structuresthe products of exceedingly complicated
series of twists and folds as the proteins are being
manufactured in the cellprofoundly influence the
molecules efficacy, potency, and side effects.

Startups such as Momenta
Pharmaceuticals in the United States and U.K.-based
Procognia have developed technologies to scrutinize
another source of proteins fickleness: the sugar
molecules that are often attached to them during their
manufacture. The enzymes in mammalian and human cells
that add these sugars to proteins follow rules that seem
to vary with the cells growth conditions, so figuring
out the number and types of sugars attached to a
particular protein has proved especially challenging.
Momenta has combined proprietary enzymes, traditional
analytical techniques, and unique computational
algorithms to precisely map such sugars. Procognia uses
sugar-detecting arrays, analogous to gene chips that
analyze gene sequences or activity, to do the same
thing. From a technical standpoint, I believe its
possible to completely characterize a protein, says
Alan Crane, Momentas CEO. If you can show its all the
same, what are the arguments for not allowing a
generic?

This is one of the situations where open source-style
biotech could be of great value. Many of the protein drugs
with patents near expiration (or already expired) are
life-saving, important medicines costing tens of thousands
of dollars per year. Efforts both to identify and to
duplicate proteins, if opened up, could be of incredible
value to those trying to provide medical relief to those in
poverty. Collaboration and distribution can speed the
lengthy research process, as well as spread the skills and
knowledge beyond a small cluster of bioscientists.

The open biotech idea is picking up a lot of steam:
BIOS.net, which

we talked about last
December, is
now up and running,
working on "new means for the cooperative invention,
improvement and delivery of biological technologies." The
Economist, hardly a bastion of radical thought,

endorsed the idea
specifically around bio-pharmacological research this last
June. And, unsurprisingly,

groups in academia
are strong supporters of the idea.

An open approach to building generic biologics would be
an important step in the evolution of the open source
biotech movement, as it could showcase the power of the
approach and its value to the world.