Getting patients back to normal

All opinions my own and do not necessarily reflect those of Novo Nordisk.

Inspired in part by this column from David Shaywitz

Here is a story I had the privilege to hear from Fred Modell, one of the founders of the Jeffrey Modell Foundation (check them out; they’re a great group):  Fred was at their annual picnic, where they host kids with immune system defects.  Fred walked by two early teenage girls, and as he passed by he heard one of them asking the other, “You really kissed a boy?”  Which seems like a common enough thing for two teenage girls to be talking about.

Only in this case it wasn’t.  If your immune system doesn’t function like most everyone else’s, then kissing a boy is not just part of growing up.  It can be dangerous to your health. It’s something  about which you have to think hard, and try your best to understand the implications, and you need to be careful, cautious and measured.  Everything your first kiss really shouldn’t be.

For these girls, though, because of groups like the Modell Foundation and the treatments they’ve helped pioneer and support, these girls could experience the spontaneity of an event that so many kids take for granted.  And they could feel normal, like their friends in school.

We develop medications to cure disease, to make the sick healthy, but a recent post by David Shaywitz, which itself was in support of this NEJM piece by Ethan Basch, points out that another important part of drug development is understanding what a patient is going through as she takes a drug.  A key part of treatment is just making the patient feel better.  More normal.  His article discussed oncology drugs, and I’ll expand on that particular area, but the concept is not limited to cancer.

The problem, as Shaywitz states, is that drug development has been highly focused on the clearly measurable, clinician-determined outcome.  How long did the average patient survive in the clinical trial?  Did the tumor shrink and by how much?  What is missing, but also important, is a measurement of how did the patient feel while on the drug?  What was her quality of life?

Shaywitz discusses the need for drug developers to expand the range of characteristics they measure when developing drugs, and also calls upon clinicians to be more proactive in tracking other elements of the patient experience.  He suggests that a key element of this change will come from mobile health tools and metrics.

One way mobile tools could help to track patients’ experiences is with apps like Emotion Sense for the Android.  This application, being developed by the Cambridge computer lab, records both user feedback and other data that a smartphone can capture passively, such as frequency of calls.  The data are combined to estimate user emotional state. One argument against using patient reported feelings has been subjectivity.  And it’s true, every person has different thresholds for reporting emotions and sensations like pain.  But an app that both samples frequently a user’s subjective mood and cross-correlates that with other measures that a phone can collect passively may provide a reliable, calibrated tool for assessing patient experience.  Emotion Sense is being tested by the Cambridge team, and they’re encouraging others to take advantage of the app’s open source code to conduct their own research.  It seems like another nice opportunity for drug developers.  Ethan Basch’s description of the development of ruxolitinib, and how Incyte recorded patient input via handheld devices to support their FDA filing, shows that using mobile media can be a useful approach.

Curious about diet as another element of patient experience?  If the patient is in the hospital, intake can be measured.  But if patients are outside the hospital, a better option to written surveys may be a tool like Lifewatcher, which was developed in Japan and takes advantage of smartphone ubiquity to help people track their food intake.  You know how everyone with a smartphone always takes it out and puts it on the table when he or she sits down?  With this tool, at every meal a patient simply takes a picture of her meal with her phone and the image is cross-referenced to an image database of various foods, providing an estimate of nutritional intake.  Possibly with future developments, a second picture after the meal is finished could allow an estimate of percent consumption.

This is interesting beyond the question of caloric intake because it also serves as a proxy for quality of life.  I think an argument can be made that showing how patients were interested in and consumed a variety of foods, instead of forcing themselves to down bland nutrient “shakes” at every meal, is a pretty good proxy for patient appetite and improved quality of life.

Like many things in drug development, external pressures drive changes.  The FDA has been moving towards clarifying their policies toward methods and tools for measuring patient reported outcomes (for example, 2009 guidance here).  And the FDA has been working with groups like the Critical Path Institute to continue the dialog about different types and usages of patient reported outcomes.  However, the pace of change could be quicker.  The FDA originally requested feedback on mobile health applications back in 2011, and says they will be reporting their guidance by October of this year.  Fortunately, it sounds like any regulation will only cover those tools that could injure health if used improperly, which presumably will not include monitoring tools.

As we begin moving toward more public-private partnerships to accomplish large initiatives in general, maybe a pre-competitive consortium between drug developers, the FDA, and interested groups like the Quantified Self movement and CATCH could make things move forward more quickly–or maybe, hopefully, such a consortium already exists.  Because whether the FDA approves or not, patients are becoming more empowered with tools for measuring their own quality of life, and they are highly incentivized to figure out the best ways to get themselves back to normal.


One thought on “Getting patients back to normal

  1. Pingback: Maternal immune systems, autism and the value of prediction | Biotech, Baseball, Big Data, Business, Biology...

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