Remembering

Today, May 25, 2013, is the two year anniversary of my first bone marrow biopsy (BMB).  I note this because it was a particularly painful experience for me.

I had been discussing blood test results that day with my hematologist, Dr. Rabinowitz.  I was a little nervous, because the results looked a bit ominous.  Something was definitely wrong, and I was probing for answers.  He was getting annoyed with me for persistently asking what he must have assumed were stupid questions.  In retrospect, I am questioning the wisdom of taking a confrontational stance with him just before allowing him to plunge a large needle into my pelvis.  I don't know if there is any correlation there, but boy did that hurt!

When I started treatment at the Farber in July 2011, the first procedure I had to undergo was another BMB.  Bummer!  Needless to say,  I was more than a little trepidatious about this.   To my relief, however, the procedure, while uncomfortable, was not nearly as bad as my first experience.  I have subsequently undergone three more BMBs at the Farber, and all of them have been quite tolerable.  I no longer fear the procedure, not that I would volunteer for it, mind you.  Fortunately, as long as I stay in remission (knock on wood), I shouldn't need to undergo a BMB more than once a year.

A recent article in the Boston Globe featured a Cambridge-based company called GNS Healthcare, which is pioneering the use of "Big Data" analytics to healthcare.  This involves using enormous computer power to crunch troves of information on patients, diseases, and medical outcomes collected by medical providers, insurers, and others.  Hopefully, this will eventually lead to personalized treatment for various diseases, including cancer.

GNS uses artificial intelligence algorithms developed out of chaos theory to determine what treatment made the crucial difference for each patient and what is likely to work best for the next patient.  The approach is to try to reverse engineer the mechanisms that give rise to the data to determine cause and effect relationships.  As genetic profile data becomes more available and cheaper to collect, this approach will become much more powerful by using individual genetic information at the molecular level.

What I found most interesting about the article is that GNS is working with DFCI and Mt. Sinai Medical School to build a computer model of Multiple Myeloma!  The objective is to better understand what works well for patients today, as well as develop more effective personalized MM treatments in the future.  This is exciting stuff!

For anyone interested in following up on this, the article was written by Globe correspondent, Karen Weintraub, and appeared in the Business Section of the May 15 Boston Sunday Globe.  Here is a link:  Big Data Can Personalize Healthcare