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The Genomic Revolution
November 10-13, 2005 - Irvine, CA

The theme for 2005, developed by a Steering Committee chaired by Robert Waterston of the University of Washington, was "The Genomics Revolution: Implications for Treatment and Control of Infectious Disease". 

Understanding and diagnosing the host-pathogen interaction for infectious diseases is critical to successful treatment.   Embedded in the complexity of host-pathogen interactions is the mode of initial exposure.  This exposure may occur through the natural spread of existing or emerging infectious organisms or the deliberate exposure to either low or extremely high concentrations of organism by a bioterrorist attack.  There is an urgent need for rapid, sensitive, specific and cost-effective diagnostic technologies for infectious diseases for point of care use, especially in the developing world.  At the same time there is a growing need for more effective control of infectious agents, whether established, emergent or potential.  The advances in biotechnology and genomics over the last decade present an opportunity to address the scientific needs underlying public health challenges through non-traditional scientific collaborations able to generate truly innovative strategies.  There are important opportunities for science, engineering and medicine, which would be stimulated by connecting those who are currently engaged in research at the high-tech, cutting edge with those who understand the real world challenges “on the ground”. 

  • The ideal point-of-care or laboratory-based diagnostic tool, technology, or platform would be fast, accurate, inexpensive, easy to use and interpret, specific, rugged, portable, and sensitive, providing a definitive assay for identifying the microorganism in the clinical sample and require little or no sample preparation. How might we combine knowledge of genetics and pathogenesis with nanotechnology or other technologies to design diagnostic tools for point-of-care use, able to identify infectious agents (such as malaria, tuberculosis, Ebola, or SARS) in real-time, so that appropriate therapeutic intervention can be provided?  Can these technologies also be used in the diagnosis and prevention of other common diseases such as cancer, diabetes or MS? Can biomarkers be used to detect pathogens, indicating host-pathogen interaction and response? What delivery challenges must be overcome? How might low cost medical diagnostics evolve as the pathogen changes?

  • Fighting infectious agents occurs at multiple levels from vaccination through public health measures to direct therapy.  How can genomics combine with computational approaches to design effective vaccines more rapidly?  Are there better delivery systems? How might we use new technologies for the earlier identification of disease etiology and the spread of infectious diseases? How does the transmission mechanism (human to human; animal to human; etc.) affect the technologies?  What are the opportunities for computer science and data acquisition in epidemiology? Could biomarkers be coupled with molecularly targeted imaging and therapy to treat the disease as alternatives to antibiotics?  Can more rationale approaches to antibiotic use prevent emergence of widespread resistance?

  • Improved understanding of the pathogens and their interactions with hosts will open avenues for diagnosis and control.  What do we know about pathogen evolution? What effect does the interaction between hosts and pathogen have on its evolution? What tools and networks are needed to determine how pathogens work? What do we know about the genetics of infectious diseases and their pathogens and what insights might our new ability to use genomic technologies reveal, ranging from the molecular to population demographic? How can an engineering systems approach help us derive knowledge from very large biological data sets?  To what extent can we use computational models and data mining to make better use of available biological data?  Can biology become more of a predictive science so that we can anticipate the next pandemic?  What are the gains from data mining versus deterministic modeling?

  • Much human genetic variation evolved through past selection for resistance to diseases. In what way can this be captured and used to enhance health outcomes?  What are the implications for drug development and vaccine development of an increasing use of the developing world as a data source?  How might we take advantage of the natural world’s variations, e.g. the sub-Saharan African population’s resistance to malaria?  How can we develop more efficient ways of harnessing our knowledge of immunology and genetics to develop safe and effective vaccines?  How might we advance our knowledge of clinical variation in drug and vaccine response?  How might knowledge of the diversity of the human genome and that of disease-causing agents help to target disease prevention, intervention or repair at a population level?

  • What are appropriate technologies for resource poor countries?  How can we develop technologies, such as implantable systems or new kinds of refrigeration that address the challenges of delivery under constraint?

  • What kinds of new science and technology will we need over the next 10 years?    What are the legal, societal, economic and geopolitical obstacles and the drivers?  What can we learn from health economics and health law?