Personalized Medicine, Biosensors, Mobile Medical Apps, and More

At the Quantified Self Meetup, someone was praising the Rock Health slides. Of course, I had to go explore and see what was so great. These are my favorites.

About FDA’s Guidance for Mobile Medical Apps

FDA 101: A guide to the FDA for digital health entrepreneurs by @Rock_Health:

I especially took note of slide 10, where they describe things I would think of as an app, but which do not qualify as such for FDA regulation. This is an important distinction I hadn’t previously considered. Slide 12 takes it further by describing the categories of regulation as based on risk to patients, with good clear examples. Slie 21 on “pro tips” would have really benefitted companies like 23andMe (even though that isn’t actually a mobile medical app, the pro tips still apply, and in spades).

Biosensing Wearable Tech

The Future of Biosensing Wearables by @Rock_Health

This one definitely gets into topics relevant to the quantified self movement and self-tracking. Slide six emphasizes the shift from the low hanging fruit (fitness, pulse, sleep) to the long tail — more targeted solutions for specific challenges (hydration, glucose, salinity, skin conductance, posture, oxygenation, heart rhythm, respiration, eyetracking, brain activity, etc.). That’s really quite interesting, and it gives examples of companies working in each space.

Slides 19-24 get into several of the areas our own local meetup defined as challenges to success for companies working in this space and for the future success of the entire area — it has to work, easily, and dependably. Slides 27-30 extrapolate these challenges into the transition into healthcare environments.

Personalized Medicine

The Future of Personalized Health Care: Predictive Analytics by @Rock_Health Video



It’s probably safe to say that most individuals working in the quantified self / self-tracking space eventually end up struggling with the issue of how to use their data to anticipate avoidable problems. This idea can be translated into the jargon phrase of “predictive analytics.” Slide 11 does a nice job of lining this up with how traditional healthcare is practiced, which is very useful. Slide 12 places this in the context of big data resources, databases, and tools, listing several of the main players. This context is essential for making personal data relevant beyond the drawn out process of n=1 studies. Slide 14 identifies the BIG problem of how companies working in this space largely focus on hospitals and health care providers, and seem to have entirely missed the idea that patients are deeply and actively engaged in this space. And, frankly, there are more of us than them (even if our pockets aren’t as deep). I love the phrase on slide 18, “Symptom calculators are the “recommendation engines” of health care.” Most of the rest of the deck identifies challenges and opportunities, which I hope any entrepreneurial types would examine closely. Do notice that there is a video with this one. You can hear the entire webinar as well as reviewing the slides.

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