July 2, 2002

BioSignia Scientists Present Results of Novel Predictive Modeling To Identify New Drug Targets to Prevent Heart Disease 

C-Reactive Protein Not Necessarily an Independent Risk Factor for Coronary Heart Disease

Research Triangle Park, NC – A science team with a company that has developed a unique, patented process to unravel vast medical data to better understand how drugs might work better to prevent disease recently presented a study that challenges widely held views about the risks of heart disease.
The paper, delivered by Dr. Martin Root during the Experimental Biology 2002 conference in New Orleans April 20-24, suggests that the presence of a certain protein believed to be an important signal that a patient is likely to develop heart disease in fact might not add significantly to risk factors already known to contribute to the progression of the disease.

The finding is important because drug makers look at such indicators – in this case, C-reactive protein -- as a potential  “target” for the development of new pharmaceutical products, a process that costs many millions of dollars and several years to develop.

“Common wisdom today among scientists working with heart disease says that C-reactive protein in a patient contributes independently to the risk of heart disease,” said Dr. Root. “However, our multivariate study suggests that C-reactive protein, in fact, may not contribute to our knowledge of an individual’s risk of heart disease beyond what has previously been discovered including blood values like cholesterol, fibrinogen and albumin. If this is true, then those companies spending millions of dollars developing drugs may be wasting their time and money if they target a disease factor that is already being managed through another drug’s effect on another risk factor. ”

Using a novel, multivariate risk calculation, BioSignia’s scientists rank-ordered seven blood biomarker risk factors that are thought to cause heart disease. A multivariate model of heart disease risk with 17 risk factors was developed based on the well-known Framingham model. Using this comprehensive model, the BioSignia scientists found that HDL and total cholesterol, fibrinogen, and C-reactive protein (CRP) dominate as risk factors when considered individually. However, in a multivariate model, which combines the risk factors together, CRP does not necessarily contribute to heart disease beyond what is explained by more traditional risk factors such as fibrinogen and albumin.
The BioSignia study suggests that by examining univariate and multivariate contributions, drug development scientists can be more targeted in developing new, more appropriate compounds to treat disease and can minimize wasted efforts and much of the guess work that goes into drug development.

BioSignia’s Pharmaceutical Technology Group currently is offering drug development scientists the ability to build robust and discriminatory Composite BioMarkers from all of the available longitudinal research and clinical trial studies, which can be employed to predict a drug’s effect on long-term disease outcomes. Composite BioMarker technology can help pharmaceutical companies provide earlier insight into drug efficacy, safety, and cost effectiveness, efficiently recruit and enroll patients for clinical trials, and enhance the support of physicians by helping them fully consider all available evidence regarding the risk of chronic disease.