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Team:Paris Bettencourt/Human Practice/Technology Transfer
From 2013.igem.org
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| + | Moreover, as Allison S. Rhines points out in an excellent review article, | ||
| + | <q>the global TB epidemic is characterized by significant differences in prevalence between men and women. That rates of TB are much higher among men than women in large areas of the world has been extensively documented. Nevertheless, some scholars believe that these differences are in part, if not wholly, due to the effects of confounding variables such as differential access to care, which would bias case reporting (REF2) </q> | ||
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Revision as of 11:22, 4 October 2013
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new challenges to synthetic biology
As we began working on tuberculosis, we started to raise some concerns on the possible impact of our project “outside” the iGEM community. Since part of our work consisted in designing a bacterial vector for treating tuberculosis, we started wondering how this new item of technology could be possibly translated into an actual therapy. Besides ordinary safety concerns, we had to take into account the fact that tuberculosis epidemics are particularly widespread in the so-called “developing” and “emergent” countries, whereas they are relatively rare in the “developed” ones. According to the WHO sponsored Global Plan to Stop TB, whereas tuberculosis affects all countries around the world, 85% of cases occur in Africa (30%) and Asia (55%), while India and China alone represent 35%. This means that thinking about possible applications of our genetically engineered bio-machine consists precisely in raising the question of how synthetic biology could be subject to “technology transfer” from developed countries to developing ones.
the global TB epidemic is characterized by significant differences in prevalence between men and women. That rates of TB are much higher among men than women in large areas of the world has been extensively documented. Nevertheless, some scholars believe that these differences are in part, if not wholly, due to the effects of confounding variables such as differential access to care, which would bias case reporting (REF2)
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