| |
| META TOPICPARENT | name="FirstPaper" |
|---|
Free Medicine
Second Draft -- Ready for Review | |
<
< | Prescription drug spending in the U.S. is projected to nearly double by 2020. At the same time, new drug development is becoming even more expensive and less productive. What pharmaceutical companies are doing now is failing. Today's drug R&D methodology is well suited for the treatment of simple or acute problems, such as short-term symptoms like acute pain, or most infectious diseases. But, any problems have already solved by generics, and even where needed, profitability of infectious disease treatment is limited by the ability of Third World patients or governments to pay. As Big Pharma recognizes, a comprehensive revolution in medicine has begun, based on three big shifts: | >
> | Prescription drug spending in the U.S. is projected to nearly double by 2020. At the same time, drug development is becoming even more expensive and less productive. Today's drug R&D methodology is based on the development of chemicals that target short-term, acute symptoms and infection. But, most of these problems have already solved by generics, and even where needed, profitability of infectious disease treatment is limited by the ability of Third World patients or governments to pay. Medicine in the future is being defined now through a comprehensive revolution based on three big shifts. | | | First, the underlying science, biology, has transformed. The most outwardly visible manifestation of this is the Human Genome Project, and the re-orientation of biology towards the primacy of DNA sequence and understanding the cell as a complex system of molecular interaction. But, the changes are broader than that. The techniques of molecular biology have changed to become more modular, kit-based, and reliant on instrumentation and software applications than it was before. There is now even the possibility of both computational and wetlab tinkering available outside the traditional laboratories, leading to the emergence of "DIY biology" and "biohacking." To be sure, kit-based biology is sloppy and requires substantial tuning, and computational methods are still limited. But, the trend is clear. An already substantial and growing part of molecular biology is no longer trial-and-error, basic discovery-oriented science. | | | Big Pharma has responded by considering and applying these transformations separately in the context of conventional drug development. The problem is that there is simply too much information for a drug to interface with -- the nature of the molecular structures and complex chemical reactions that are reprogrammed by the drug to change the function of cells and organs to affect the course of disease. Moreover, this information varies between individuals. The result is that the state-of-the-art includes drugs like statins, like Lipitor, which have at best an uncertain impact, despite their ubiquity and cost. Alternatively, there have been unequivocal failures like Vioxx -- which was designed to be more specific than its predecessor, but which through that specificity somehow causes more serious side effects. Overall, drug pipelines are running dry, as most projects fail despite the use of expensive new technologies in the development process. | |
<
< | The future of medicine requires absorbing the revolution as a whole: rethinking the integration of information and health. One vision, favored by incumbent interests, is "personalized medicine." The idea is to match treatments to an individual's DNA sequence and information from real-time measurement of biochemical processes. Personalized medicine perpetuates the current legal regime of data exclusivity and patents. Pharmaceutical companies will retain exclusive rights over how to diagnose and treat patients based on their own DNA sequence and sensor data. Drug patents or exclusive rights to market drugs will be extended, by allowing the extension of monopoly rights on chemical isoforms or repurposed drugs (i.e. where new treatment targets or ways of coupling with diagnostic methods are found). Within this context, open source drug discovery” can exist on the margins, where pharmaceutical companies share data and license molecules for humanitarian -- and unprofitable -- problems, like tuberculosis. | >
> | The future of medicine requires absorbing the revolution as a whole: rethinking the integration of information and health. One vision, favored by incumbent interests, is "personalized medicine." The idea is to match drug choice and dosage to an individual's DNA sequence and information from real-time measurement of biochemical processes. Personalized medicine will be based on the current legal regime of data exclusivity and patents on both drugs and sequence information. Pharmaceutical companies would retain exclusive rights over how to diagnose and treat patients based on their own DNA sequence and sensor data. To get there, drug patents or exclusive rights to market drugs will be extended, by allowing the extension of monopoly rights on both chemical isoforms and new applications of drugs, as well as patents on diagnostic methods. Within this context, open source drug discovery” can exist on the margins, where pharmaceutical companies share data and license molecules for humanitarian -- and unprofitable -- problems, like tuberculosis. | | | The alternative is Free Medicine. This is exemplified by the emerging use of social networks for conducting genome-wide association studies at one end of a new pipeline, and clinical trials at the other end. These developments will facilitate distributed innovation in networks of the doctors and patients. Indeed, innovation once emerged from case studies rather than mass trials. In an era when we can measure individual variability, it makes sense to return to a more distributed and flexible form of medical development. |
|