The American patent on Human Growth Hormone -- useful for fighting wasting diseases associated with AIDS -- expired in 2003. So why isn't there a far-less-expensive "generic" version available in the US? Because HGH is a protein "biologic" drug, and protein drugs are far more difficult to produce than "small molecule" drugs, and the FDA says it can't be certain that the generic versions are identical to the originals.
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 them—and perhaps reducing the amount of clinical testing necessary. Generics companies such as Israel’s 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 structures—the products of exceedingly complicated series of twists and folds as the proteins are being manufactured in the cell—profoundly 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 it’s possible to completely characterize a protein,” says Alan Crane, Momenta’s CEO. “If you can show it’s 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.