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We are at an exciting time in biomarker discovery as the confluence of three emerging technological advances has occurred over the past 5-10 years leading to the potential capability of efficient discovery of a biomarker or a panel of biomarkers specific to the many different faces of disease and therapeutic intervention including diagnosis, disease progression, drug efficacy, and drug toxicity. 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.
Developing and evaluating new drugs and medical therapies historically has been a time consuming and expensive process. Bringing a new drug to market takes, on average, 15 years and $800 million dollars leaving pharmaceutical companies with only two to three years to recoup their investments before patent protection is lost. This extended time frame and enormous expense has placed an understandable emphasis on the development of “blockbuster” drugs. With such a time frame and financial commitment, drugs are routinely developed only for multibillion dollar markets. This approach, by its strategy, results in the development of drugs which are effective in only 16% to 60% of the patients who are prescribed these drugs. Further, giving the drug to a large number of patients in which it will not be effective, substantially increases the number of patients who will needlessly suffer adverse drug reactions. This is significant since it is estimated that the economic cost of drug-related morbidity and mortality in the United States is between $30 billion and $130 billion annually.
The drug development process has relied on evaluating the effectiveness of new drugs against established end points such as a decrease in morbidity and mortality or a decrease in specific clinical symptoms associated with the condition in question. Besides proving their effectiveness, researchers must also prove the safety of new treatments through a lengthy clinical trials period that may take up to seven years to fully evaluate. Understandably then, clinical validation of efficacy and safety is a costly, time-consuming process.
In an effort to streamline this process and bring more new drugs to market, the US Food and Drug Administration (FDA) has moved gradually to allow acceptance of other endpoints as valid indicators of the effectiveness of a drug or treatment. A new emphasis has recently been placed on the importance of discovering novel biomarkers whose presence correlates with the pathophysiologic process of the disease to which a drug is targeted. More simply stated a surrogate molecular marker may now be substituted for the lengthy process of following the effect of a drug on the ultimate outcome of a disease. Therefore, a drug’s effectiveness against the disease process in question may be monitored more efficiently by evaluating the presence or absence of a specific biomarker. One example of the successful application of biomarker data to therapeutic evaluation is the use blood cholesterol levels to evaluate the effectiveness of the drug Lipitor. By obtaining valid results without having to continue a study through to the historical endpoint, HDC can cut years off the process while saving millions of dollars for the pharmaceutical and diagnostic industries.
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