Web 3.0 and Predictive, Preventive and Personalized Medicine

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Since January, Berci Mesko over at Scienceroll has been writing about how Web 2.0 is changing medicine. He’s written a number of interesting articles, including Medical wikis: the future of medicine? and Medical Web 2.0 Sites.

In Web 3.0 and medicine, Berci writes about WikiProteins, a new site that plans to use Web 3.0 technologies to incorporate real time community annotation into a semantic framework. The article Meet the uber-wiki is a great review of the up-and-coming resource.

According to Nova Spivack, founder of Radar Networks, a San Francisco based startup that is developing a new web-based online service that will bring the power of the Intelligent Web to consumers, Web 3.0 is closer than you think [1]. His company plans to launch their first product later this year.

What Is Web 3.0 And What Does It Have To Do With Health?

Web 3.0 will bring together advanced technologies that include the semantic web and adaptive data mining, and move towards making content accessible by applications other than a web browser. Everyone will build the next layer of intelligence into the web using integrated tools for social networking, allowing for both interaction and collaboration. Web 2.0-style tagging will be formalized and expanded so that documents and other web data that now must be interpreted by humans can be read and understood by computers.

According to Wikipedia:

The semantic web is an evolving extension of the World Wide Web in which web content can be expressed not only in natural language, but also in a form that can be understood, interpreted and used by software agents, thus permitting them to find, share and integrate information more easily.

The medical industry was one of the first groups involved in the development of the semantic Web. The World Wide Web Consortium (W3C) launched the Health Care and Life Sciences Interest Group, chartered to:

… develop and support the use of Semantic Web technologies and practices to improve collaboration, research and development, and innovation adoption in the of Health Care and Life Science domains. Success in these domains depends on a foundation of semantically rich system, process and information interoperability.

Personal Medicine and Systems Biology

Perhaps one of the greatest challenges for 21st century medicine is to provide effective therapies that are customized to a patient’s genetic and environmental profile to better manage their disease or predisposition toward a disease. Using new methods of molecular analysis, the goal of personalized medicine is to achieve optimal medical outcomes by assisting physicians and patients in the identification of the disease management approaches most likely to work best in the context of a patient’s unique biological state. Thus, personalized medicine is dependent upon an understanding of systems biology and on systems-based developed intervention [2].

In contrast to the reductionist “divide and conquer” approach that has been the paradigm of science since the time of the renaissance, systems biology is centered on the idea one can study complex biological systems by evaluating, in parallel, the interactions of DNA, RNA and proteins that network together in terms of perturbations and model organisms. Systems biology is a comprehensive understanding of how large numbers of interrelated components of a system comprise modules or networks whose functional properties emerge as a phenotype or disease state. Semantic web technologies as recommended by the W3C expand the current data standard technology for biological data representation and management and are of considerable importance to realize the promise of systems biology [3].

Phenotypes and disease states are influenced by genetic variation. Indeed, genetic variation greatly influences how the body processes medication. An example of this is the recent finding by two research groups that the cancer drug gefitinib (brand name Iressa), which produces rapid clinical response in approximately 10% of lung cancer patients, is due to a genetic mutation in their tumors [4-5]. Environmental factors are also closely connected. The microbiome (meaning the collective genome of the human intestinal microbiota) [6] is the exact point where host genetics meets environment and is considered to be a necessary part of future personalized health-care paradigms [7]. Many diseases such as heart disease, diabetes, obesity and cancer may be related to changes in the activities or composition of gut microbiota, and has likely been affected by antibiotic use over the last 50 years [8].

Systems biology also allows researchers to study the underlying mechanisms of human health in relation to diet. As our understanding of systems biology evolves, personalized nutrition will become central to disease prevention. Nutrigenomics, which studies how nutrients interact with humans, taking predetermined genetic factors into account, will bring about new insights into human health that will have a significant positive impact on our quality of life [9].

Much work needs to be done to move personalized medicine from promise to practice. Keith over at Omics! Omics! writes about the long slog, detailing the realities of a clinical trial by Millennium Pharmaceuticals that had a personalized medicine component for bortezomib (brand name Velcade) in multiple myeloma [10]. Genes predictive of response or survival were identified, but an interpretation of the results is limited.

Personalized Medicine in 2007

The Personalized Medicine Coalition (PMC) is a non-governmental, non-profit group established to foster discussion and advance the understanding and adoption of personalized medicine for the benefit of patients. The PMC website lists numerous research studies that reflect the evolution of personalized medicine.

There are a number of genetic tests currently available that can help predict likely responses or bad reactions to certain medications [11]. Some of the more common tests are:

  • Cytochrome P450 genotyping test, useful for certain antidepressant medications, anticoagulants, proton pump inhibitors and many other medications.
  • Thiopurine methyltransferase test, used to test patients prior to chemotherapy for some leukemias.
  • UGT1A1 TA repeat genotype test, used to test patients prior to chemotherapy for colorectal cancer.
  • Dihydropyrimidine dehydrogenase test, used to test patients prior to chemotherapy.

In January 2007, about 1,000 patients with atrial fibrillation started participating in a study that matches their warfarin (brand name Coumadin) dose to their specific genetic needs using DNA fingerprinting [12]. Those patients whose bodies break down the drug faster or slower than normal can be readily identified so that their doctors can adjust their dosage accordingly. Medco Health Solutions, a leading pharmacy benefit manager company based in Franklin Lakes, New Jersey, is collaborating in the effort with Mayo Clinic.

Edward Abrahams, Ph.D., Executive Director of the PMC predicts that if the study is successful, patients will start demanding personalized medicine. If the study proves to save money and protect patients, insurers will too.

In todays information age, data and computational systems are being used to make illness more predictable, disease more preventable and treatment more personalized. Get ready … personalized medicine coming, perhaps sooner than you think.


  1. Ready for Web 3.0?. MSNBC. March 26, 2007.
  2. van der Greef et al. Metabolomics-based systems biology and personalized medicine: moving towards n = 1 clinical trials? Pharmacogenomics. 2006 Oct;7(7):1087-94.
    View abstract
  3. Wang et al. From XML to RDF: how semantic web technologies will change the design of ‘omic’ standards. Nat Biotechnol. 2005 Sep;23(9):1099-103.
    View abstract
  4. Paez et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science. 2004 Jun 4;304(5676):1497-500. Epub 2004 Apr 29.
    View abstract
  5. Lynch et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med. 2004 May 20;350(21):2129-39. Epub 2004 Apr 29.
    View abstract
  6. Gill et al. Metagenomic analysis of the human distal gut microbiome. Science. 2006 Jun 2;312(5778):1355-9.
    View abstract
  7. Nicholson et al. Gut microorganisms, mammalian metabolism and personalized health care. Nat Rev Microbiol. 2005 May;3(5):431-8.
    View abstract
  8. Nicholson JK. Global systems biology, personalized medicine and molecular epidemiology. Mol Syst Biol. 2006;2:52. Epub 2006 Oct 3.
    View abstract
  9. Desiere F. Towards a systems biology understanding of human health: interplay between genotype, environment and nutrition. Biotechnol Annu Rev. 2004;10:51-84.
    View abstract
  10. Mulligan et al. Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib. Blood. 2007 Apr 15;109(8):3177-88. Epub 2006 Dec 21.
    View abstract
  11. Personalized medicine: Tailoring treatment to your genetic profile. Mayo Clinic. June 30, 2006.
  12. DNA-tailored medicine moves into mainstream. MSNBC. January 12, 2007.
About the Author

Walter Jessen, Ph.D. is a Data Scientist, Digital Biologist, and Knowledge Engineer. His primary focus is to build and support expert systems, including AI (artificial intelligence) and user-generated platforms, and to identify and develop methods to capture, organize, integrate, and make accessible company knowledge. His research interests include disease biology modeling and biomarker identification. He is also a Principal at Highlight Health Media, which publishes Highlight HEALTH, and lead writer at Highlight HEALTH.