| |
| META TOPICPARENT | name="FirstPaper" |
|---|
Free Medicine | |
<
< | Second Draft -- still under revision | >
> | 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: | | | 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, is "personalized medicine," which is about matching treatments to an individual's DNA sequence, as is possible today, and information from emerging technologies that will allow the real-time measurements by microscopic sensors. The interim is data exclusivity and patents, and the future is to extent data exclusivity and patents to diagnostic algorithms, repurposing of drugs that have lost patents, etc. The problem is that exclusivity as the driver of innovation only incentivizes this kind of research -- which focuses on particular kinds of drugs, rather than looking at holistic intervention, which doesn't see drugs in the context of health generally or with other kinds of non-drug treatment. | >
> | 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 alternative way forward is Free Medicine, exemplified by successful first steps towards the use of social networks for conducting genome-wide association studies at one end of a new pipeline, and clinical trials at the other end, with biological "tinkering" in the middle. These developments will facilitate distributed innovation (or peer production) driven from the doctor-patient level. This is not itself new in medicine. 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. Networks of scientists with access to collaborative computational tools, like molecular libraries and free data sharing, can rapidly and effectively search for and refine potential targets and leads. Then, distributing clinical trials globally and freely sharing data reduces their expense. Such an "open source" drug discovery network has started for tuberculosis drug development. Free medicine works on health as a process, rather than just making drugs as products. So, it will lead not to just better health care, but to better health. | >
> | 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. | | | | |
>
> | The power of free medicine is that it works on health as a process, rather than just focusing on products, like drugs. So, it will lead not to just better health care, but to better health. The problem is that free medicine isn’t rooted to products that can be tied to exclusive rights, whether through patents or patent-like legal schemes. But, this is actually the power of free medicine, which is that it does not rely just on particular treatment products -- drugs -- but on a range of ways of treating patients, including natural products, changes to diet, and a world of research that has been neglected because it can’t be incentivized by the award of exclusive rights. | | | -- BahradSokhansanj - 12 Jan 2011 |
|