Personalized medicine is medical care customized to a patient’s specific genetic and demographic profile. It is an odd idea to think that traditional medicine was not always personalized, but truly personalized treatment has been an elusive goal in medicine for many years. It was not until the completion of the human genome project in 2003 that personalized medicine blossomed into a dedicated field full of hope and intrigue. While the bulk of personalized medicine focuses on finding genetic markers that underlie certain diseases or biological processes, personalized medicine is also seeing innovation in the areas of data analysis and novel drug therapy models. It appears that within the next decade, personalized medicine will simply be a part of any standard medical care.

Of course, genomic medicine is the largest and most publicized area of personalized medicine. Genomic medicine looks for genetic markers and biological mechanisms in patients and diseases that allow doctors to prevent and treat them more effectively. The Food and Drugs Administration (FDA) has already approved medications that target specific, genetic forms of breast cancer, melanoma and, potentially, many more. For example, Zelboraf is a drug that was developed to fight a specific strain of melanoma that has the BRAF V600E mutation. This melanoma is particularly deadly, and it does not respond well to normal treatment. This new drug and genetic test allows doctors to not only identify this deadly cancer, but it provides them with better tools in destroying it.

Of course, access to all the genetic and demographic information of patients is just as important. With medical advances occurring so quickly, doctors will not be able to keep up with the research into every specific gene or demographic link. Therefore, data storage and data analysis are an important part of personalized medicine. IBM is collaborating with researchers in Italy to develop a platform that will deliver customized treatment options for cancer patients. The platform will work by storing tons of genetic and demographic information, as well as different treatment options and their outcomes. This platform should make it easier for doctors to personalize medicine for their patients because it can keep track of way more information than is humanly possible. More importantly, many researchers feel that with the amount of data now available, these types of platforms could be built for almost any disease. A similar collaboration between IBM and the Memorial Sloan-Kettering Cancer Center in New York is using the IBM Watson technology to build a diagnostic support tool.

Yet the strangest thing to come out of research for personalize medicine is your own human analog mouse. IBM’s platform will only be able to let doctors know that there is a link between patients with certain genetic conditions or demographic information and a nasty side effect or treatment outcome of some drug. What if doctors could test the treatment on a human analog before the patient takes the risk? Well, research from Columbia University suggests this might one day be possible. The researchers were able to recreate an entire human immune system within a mouse by transplanting bone marrow and thymus tissue.

The researchers hope to use these freaky mice to study diabetes, but the authors do consider that one day the mice could be used to predict how certain patients would react to certain drug therapies. This could eliminate much of the risk that patients take on when taking any drug. Of course, people concerned about their little furry friends should not worry yet. It is very unlikely that mice will be used in this manner any time soon. Also, if researchers can grow animal meat in a test tube, they might be able to mimic the human body in a bioreactor and save the mice from an untimely death.

Either way, it is clear that the future of medicine will take genetic and demographic information much more seriously. Soon, a trip to the doctor might routinely involve a genetic test and demographic survey that the doctor plugs into a computer to get the most suitable medical treatment.