Genomically any two human beings differ by only 0.1%; we are 99.9% the same! That 0.1% is responsible for the physical differences that we see, our disease susceptibilities, and the metabolic differences we experience when taking medications. Patients diagnosed with the same disease respond differently to the same medication. Some are cured; some end up in the hospital and the rest experience something in between.
The recently established Patient-Centered Outcomes Research Institute to supports studies comparing the effectiveness and safety of alternative ways of addressing common clinical problems. Interventions to be evaluated will include pharmaceuticals, devices, procedures, and diagnostic approaches. This research will fill important information gaps facing clinicians, patients, and payers concerning what works best. [Read more about Comparative-Effectiveness Research]
Currently, the Food and Drug Administration often approves new medications on the basis of modest-sized patient studies for brief periods of time. Sometimes the only effectiveness requirement is a demonstration that a new product works better than placebo in improving a measurable outcome, such as a laboratory-test result, rather than the achievement of an actual clinical benefit.
Presently, vigorous marketing of the costliest new approaches fills this informational vacuum, encouraging the widespread use of goods or services that may be no better, less safe, or more costly than usual care. Many new interventions are clearly better clinically but there is no systematic way of collecting or disseminating such information.
P4 medicine is about matching the right drug with the right person, but without an accurate tool to measure those genetic differences prescribing pharmaceutical treatment is nothing more than an educated guess. The Iris BioWindows™ Informatics System for Personalized and Targeted Medicine handles the analysis of the Nano-biochip™ gene expression data. This artificial intelligence system correlates the genetic data with a database of other molecular signatures, patient demographics, lifestyle information, family medical histories and treatment-response profiles. This will allow physicians to more precisely diagnose the stage of the patient’s disease, and more accurately predict their responsiveness to specific drugs and the likelihood of adverse side effects.
In essence the system is a comparative effectiveness approach to a specific disease. By comparing patients with similar backgrounds and gene profiles you increase the probability of prescribing the proper protocol the first time. The physician’s job becomes one of fine-tuning the therapy and eventually reducing or even eliminating trial and error medicine.