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Semka Biomedical Technologies Project
Each year 7.6 million people die of cancer in the world, according to American Cancer Society, the total economic impact of premature death and disability from cancer worldwide was $895 billion dollars in 2008. This represents the 1.5 percent of the world’s GDP; cancer is the primary cause of economic loss worldwide. The 90% of the deaths related to cancer are due to the process known as metastasis. Currently there are no accurate tools to predict or monitor the time in which this process occurs. This process is initiated by the metastatic tumor cells; these cells derive from the primary site and travel through the body by the bloodstream settling in different organs, giving rise to new tumors.
The analysis of these cells in cancer patients has great clinical potential, the problem is that they are very difficult to capture with current technologies. Thanks to advances in manufacturing and device miniaturization we have developed a whole new approach that makes possible to capture and analyze in detail these cells, this will provide the opportunity to develop a new tool for doctors that actually contributes notoriously to reduce cancer deaths annually.
The separation and characterization of metastatic tumor cells in blood will allow to monitor non-invasively and in real-time the characteristics of the cells making up the tumor, allowing the physicians to determine the resistance of cancer treatment, giving the opportunity to take decisions in a timely manner to significantly increase the chance of survival of patients due to the administration of personalized treatments in cancer patients and allowing great savings of money in world’s health systems.
In the research area, the entrapment and study of such cells by noninvasively extraction will allow to perform genetic profiles which might trigger the development of improved therapies and drugs, as well to increase our understanding on how the cancer spreads through the body. Finally as technology becomes perfected, many experts believe that this approach could be used for early cancer metastasis detection.