Over the last five to ten years, personalized medicine and biomarker discovery have reached an exciting time, as technological advances in biotechnology, information technology, and mathematics have merged to create the potential capability of efficient biomarker discovery specific to disease and therapeutic intervention. Such discoveries provide for effective diagnosis and treatment of disease, specific to a patient's needs, and include drug efficacy and possible drug toxicity for a particular patient.
Historically, the development and evaluation of new drugs and medical therapies has been both expensive and time consuming. Bringing a new drug to the market takes an average of 15 years and $800 million dollars, leaving pharmaceutical companies only two to three years to recoup their investments before patent protection is lost. Such a commitment of time and expense has created an emphasis on the development of "blockbuster" drugs, which are developed only for multibillion dollar markets. Using such an approach, however, results in the development of drugs which are effective in only 16% to 60% of patients who are prescribed these drugs. Giving drugs to a large number of patients for whom it will not be effective increases the number of patients needlessly suffering adverse drug reactions. The significance is that the estimated economic cost of drug-related morbidity and mortality in the United States is between $30 billion and $130 billion annually.
Health Discovery Corporation's three-pronged approach to molecular diagnostics allows for more specific, effective diagnosis and treatment. By applying cutting-edge computer technology and mathematical modeling to available and emerging data sources, the company aims to uncover meaningful relationships useful in prevention, detection, and treatment of disease.
First, revolutionary new biotechnology approaches have led to the development of high throughput platforms in genomics (rapid cost efficient DNA sequencing and SNP detection), proteomics (multiple mass spectroscopy and chip formats based on monoclonal or single chain antibodies) and metabolomics (mass spectroscopy and NMR based technologies for evaluating metabolic patterns in health and disease). Implementing these biotechnical advances in the drug discovery process has led to the production of a staggering amount of new biological and medical data.
Second, advances in the world of information technology has led to a drastic increase in the amount of data that can be stored at an ever decreasing cost as well as the capability to access that data electronically almost immediately.
Third, world-class mathematicians have been motivated to enter the biomarker discovery arena and have successfully developed new types of mathematical tools to analyze this new type of biological and medical data.
The realization of personalized medicine can only be accomplished with the development of molecular diagnostic tests. This development is possible only through advanced mathematical pattern recognition techniques as demonstrated by Health Discovery Corporation's SVM and RFE-SVM technology, shown to be effective in hundreds of published papers from some of the top accredited universities in the world.