Words from the Wise

                 At CMPI’s recent Capital Hill conference ,Personalized Medicine and Responsible Access to Pain Medication, Dr. Charles Inturrisi, professor of pharmacology at the Weill Cornell Medical College, laid down the gauntlet:

I want to make a distinction that really does make a difference.  And this is the distinction between efficacy and effectiveness.  We know that opioids can provide analgesia for some chronic pain patients.  We don’t know what percentage but we know that some, and you’ve heard from them this morning, at least one of them.  But we also know the treatment outcomes with opioids are variable and not predictable.  And this is the take home message if you have to leave.  At present, there are no well-validated means of identifying optimal candidates for effective long-term chronic opioid therapy.  That’s the problem.  That’s the gap in our knowledge.  That’s the gap in our evidence base. 

We need to learn who will experience good analgesic effectiveness at stable dosages with limited side effects and low risk of abuse.  So the critical question there is are there phenotypic or endo-genotypic characteristics that we can associate with better or worse outcomes that will help us to predict which patients might benefit and so that the cost-benefit ratio will be favorable rather than unfavorable. 

Now I’m going to talk about personalized medicine in general and in particular.  This refers to this emerging concept approach that uses patient-related factors including the phenotype, that is what information you can observe about the patient and a lot of that information now is contained in the electronic medical record.  Also genotypic information that you can gain by collecting a sample and it can be either a sample of blood, or in some cases even a sample of saliva and by going through and looking at snips of DNA and creating biomarkers that select optimum medication and dosage for individual patients.  It’s been estimated, on average, that prescription drugs are effective for only about half of those who take them.  And for some drugs like anticancer drugs and antidepressants, the so-called non-responder rate is even higher.

Personalized medicine can reduce the non-responder rate because you can focus in on individuals who are highly associated with being respondersand you can eliminate the trial and error inefficiencies that inflate healthcare cost. 

An audio recording on Dr. Inturrisi’s full comments can be found here (at the 1:03 mark) and the panel discussion that followed here.