Wednesday, July 22, 2015

Analytics in Medicine

In an ever-changing world where data analytics have now become a driving factor in most industries, many are trying to apply such ideology to healthcare. James Kobielus describes how, under the idea of 'precision medicine,' the ideal treatment of the same illness may vary from patient to patient. Every person is unique, and thus small differences in molecular physiology should be accounted for.
By using analytics to approach patient treatment options, every illness is personalized to the individual. To personalize medicine, it is important to locate and understand the purpose of biomarkers associated with each illness. Then it is important to build a computer model of each system of the human body. Running the simulation specific to each patient can then yield precise treatment options.

Precision medicine sounds great in theory, but effectively applying its concepts requires in-depth research of the human body for many specific pathologies. The field of precision medicine is promising; even President Obama gave it his endorsement.

Saturday, July 18, 2015

Finding a Relationship between Accelerated Shortening of Telomeres and Cancer Diagnosis

Telomeres are protective caps at the end of chromosomes which shorten as we all age. It is widely theorized that the rapid shortening of telomeres increases the number of errors during DNA replication, which leads to higher rates of cancer. Now thanks to research at Harvard and Northwestern University a precise way of predicting a future cancer diagnosis using the rate at which an individual's telomeres are shortening.

Research indicates that telomeres age rapidly in those who will develop cancer. The telomeres stop shortening four years before the cancer is actually developed. This is a great advancement in the field of predictive medicine because if the right tests are put in place, a various number of cancers can be caught much earlier than it would now with current diagnosis methods.

The use of genetic tests such as these raises some issues regarding the cost of healthcare. Insurance premiums would increase drastically for those who are at high risk of developing cancer in the future. However, if there was a way to prevent cancer in those who are found to be genetically predisposed, then it would alleviate the increase in insurance premiums.