The possibility that we can define the specific and unique treatment for an individual’s specific disease is the holy grail of therapeutics. Our current therapy is largely defined by randomized clinical trials (RCTs), which provide an average response of therapy in a given disease tested in hundreds or thousands of patients.
RCTs identify the statistical benefit of a particular treatment when compared with a placebo in heterogeneous patients who, at best, are demographically similar but do not truly represent the general population.
Although an RCT shows an average statistical benefit, some individuals may have a profound benefit; others in the trial may not benefit at all, and some may do worse than placebo. The reason for the differential response is poorly understood. Therefore, treatment programs based on RCT data by definition are crude and imprecise by design for a variety of conditions, including cancer and cardiovascular diseases.
There has been a call for more personalization and precision in defining and developing predictably successful therapy. It is proposed that precision medicine will lead to optimal targeted individualized treatment based on patients’ genetic profile. This has led oncologists to use genetic profiling of therapy based on cells derived from patient’s tumor. Cancer therapy is in the forefront of genomic analysis of tumor tissue in order to guide specific tumor therapy. Unique DNA gene mutations are now being identified that may explain the genesis, spread, and growth of a tumor. It also provides a potential link between the genetic characteristics of the tumor to specific therapy. As a result, a number of laboratories have developed genetic probes that can mitigate gene expression or overexpression and thereby modify progression of disease.
To some degree, the field of cardiology has found some precision in defining individual therapy for the treatment of a variety of expressions of cardiovascular disease. We have drugs that are aimed at the treatment of hypertension, hypercholesterolemia, heart failure, and vascular thrombogenesis, to name some of the major targets. Just as the oncologists are searching for specific treatments of individual tumors, cardiology is searching for specific targets based on our understanding of the pathophysiologic mechanism leading to the expression and progression of disease. We have been fortunate in a large part to be able to measure pathophysiology and therapy at the bedside.
For some time, investigators have been examining the genetic variants in human tissue in order to understand drug responsiveness in several cardiovascular environments. Single nucleotide polymorphisms (SNP) have been discovered in beta-receptors that may define risk factors for disease and function as modifiers of disease once it has occurred. These factors also have the potential to modify beta-receptor response to adrenergic agonists and antagonists. The understanding of the SNP expression is anticipated to lead to the individualization of drug therapy and define or predict an individual’s response to particular drug therapy. As a result, they may explain the spectrum of clinical response observed in RCTs. Similar observations have been observed with the genetic polymorphism, of renin-angiotensin-aldosterone system and sympathetic systems. The understanding of genetic polymorphism may also provide insight into the expression of disease in particular demographic groups.
So far, the cost of these drugs is huge when applied to just a few individuals who are potential beneficiaries of the therapy. Consequently, patient and society and your insurance company are asked to pay the cost of the drugs to treat just a few patients. Over time, it is possible that these unique genomic characteristics can be applied to larger populations and may spread the costs over a larger number of patients. So far, the potential for this to happen is limited.
Dr. Goldstein, medical editor of Cardiology News, is professor of medicine at Wayne State University and division head emeritus of cardiovascular medicine at Henry Ford Hospital, both in Detroit. He is on data safety monitoring committees for the National Institutes of Health and several pharmaceutical companies.