PERSONALIZED MEDICINE

Personalized Medicine uses new methods of molecular analysis, like StaRT-PCR™ to better manage a patient's disease or predisposition toward a disease. It aims to achieve optimal medical outcomes by helping physicians and patients choose the disease management approaches likely to work best in the context of a patient's genetic make up and environmental profile. Such approaches more precisely diagnose diseases and their sub-types, or help physicians select the type and dose of medication best suited to a certain group of patients. Personalized medicine has the potential to change the way we think about, identify and manage health problems. It is already having an exciting impact on both clinical research and patient care, and this impact will grow as our understanding and improved technologies like StaRT-PCR™ are more widely used.

It is already clear that personalized medicine promises four key benefits: (1) Better diagnoses; [Molecular analysis could determine precisely which variant of a disease a person has, or whether they are susceptible to drug toxicities, to help guide treatment choices.] (2) Predisposed to a particular condition and earlier interventions; [For preventive medicine, such analysis could improve the ability to identify which individuals are predisposed to develop a particular condition - and guide decisions about interventions that might prevent it, delay its onset or reduce its impact.] (3) More efficient drug development; [A better understanding of genetic variations could help scientists identify new disease subgroups and their associated molecular pathways, and design drugs that target them. Molecular analysis could also help select patients for inclusion in, or exclusion from, late stage clinical trials - helping gain approval for drugs that might otherwise be abandoned because they appear to be ineffective in the larger patient population.] and (4) More effective therapies. [Currently, physicians often have to use trial and error to find the most effective medication for each patient. As we learn more about which molecular variations best predict how a patient will react to a treatment, and develop accurate and cost-effective tests, doctors will have more information to guide their decision about which medications are likely to work best. Testing is already being used to find the one in four women likely to respond to a particular breast cancer drug. In addition, testing could help predict the best dosing schedule or combination of drugs for a particular patient.] This information abstracted from Personalized Medicine Coalition web site. For more information on personalized medicine see Personalized Medicine 101 on Personalized Medicine Coalition web site.