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Molecular Techniques for Blood and Blood Product Screening

  • Yuan Hu
  • Irvin Hirshfield
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  • 2.6k Downloads

Abstract

“Blood banking has become a manufacturing industry, an industry that must conform to high standards and quality control requirements comparable to those of pharmaceutical companies or other regulated industries,” said David A. Kessler, M.D., former FDA commissioner (Revelle, 1995). Screening donated blood for infectious diseases that can be transmitted through blood transfusion is very important in ensuring safety. The United States has the safest blood supply in the world (Revelle, 1995), and the Food and Drug Administration (FDA) is striving to keep it safe by decreasing the risk of infectious disease transmission. The regulatory agency is continuously updating its requirements and standards for collecting and processing blood. An important step in ensuring safety is the screening of donated blood for infectious diseases. In the United States, tests for infectious diseases are routinely conducted on each unit of donated blood, and these tests are designed to comply with regulatory requirements (Table 21.1). The field of clinical microbiology and virology is now moving into the focus of molecular technology. Currently, nucleic acid testing techniques have been developed to screen blood and plasma products for evidence of very recent viral infections that could be missed by conventional serologic tests. It is time for all blood safety staffs to use molecular detection techniques. This approach can significantly aid in blood safety to reduce the risk of transmission of serious disease by transfusion. This chapter will review the current antigen/antibody–based technology, molecular biological technology, and published regulatory policy data for blood safety.

Keywords

West Nile Virus Severe Acute Respiratory Syndrome Severe Acute Respiratory Syndrome Window Period Nucleic Acid Testing 
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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© Springer 2006

Authors and Affiliations

  • Yuan Hu
  • Irvin Hirshfield

There are no affiliations available

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