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Development of Personalized Medicine

  • Kewal K. JainEmail author
Chapter

Abstract

In conventional medical practice, physicians rely on their personal experience in treating patients. In spite of advances in basic medical sciences and the introduction of new technologies, physicians continue to rely on their judgment and sometimes intuition because the practice of medicine is an art as well as a science. Physicians of the last generation had limited access to information. With advances in molecular biology and its impact on medicine, a tremendous amount of new basic information has been generated, particularly in genomics and gene expression. Digitalization of information has made it accessible. The problem now is a flood of information, which requires strategies to sort out the relevant from the irrelevant. Information on a large number of studies with stratification of a large number of patients will have to be analyzed to make decisions about treatment for an individual. The massive amount of publications needs to be sorted out and analyzed for its relevance to individualized treatment. The development of personalized therapy requires the integration of various segments of clinical medicine, pharmacology and biotechnology. Genotyping is an important part of such a system. Various technologies for genotyping have been described in the following chapter and their advantages as well as limitations have been pointed out. The vast majority of relevant gene variants are rare, making it difficult to demonstrate utility − in particular for the much more frequent heterozygous carriers who have only one affected allele. Moreover, multiple factors play a role such that genetic data represent only a portion of the information needed for effective therapeutic decisions. Therapeutic areas in which personalized medicine is expected to play an important role are listed in Table 9.1.

Keywords

Bayesian Approach Personalized Medicine Intestinal Microflora Personal Health Record National Human Genome Research Institute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Jain PharmaBiotechBaselSwitzerland

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