Tag: #IoTDevices

What does the term precision medicine mean to you? Typically, people think of precision medicine as being about genomics, but it goes well beyond molecular biology to encompass everything that moves us away from a one-size-fits-all approach to medicine. As far back as 1969, Enid Balint, formerly in charge of the training and research course for general practitioners at the Tavistock Clinic in London, published a paper on “The possibilities of patient-centered medicine,” and described precision medicine as the field that understands the patient as a unique human being.

The question, therefore, is: How do we do that? Certainly, genomics has been widely touted. But another area at the forefront of precision medicine is digital health technology, which Steven Steinhubl, MD, of Scripps Research Translational Institute, addressed in his presentation, “Precision Medicine and the Future of Clinical Practice.” Digital technology moves us in the direction of understanding each patient and away from the current practice of defining health in ways that make little sense to many people. Further in this blog, I am expanding on key elements of Steven’s talk to present a different perspective on precision medicine. While many of the messages in this blog have been raised by Steven, I’d like to offer my perspective as well.

So, what exactly is wrong with current practice in our healthcare system? For starters, the current model is based on a model in which, when you get sick or hurt, you see a doctor and you get fixed. There is little to no incentive for doctors to keep you healthy, and the system rewards them on what is called “activity-based funding” rather than “outcome-based funding” or “value-based care”.

As for population-based benchmarks, they actually don’t work for you as an individual. Let’s take wellness recommendations, such as walking 10,000 steps a day or eating a certain amount of proteins and carbohydrates each day. We know that some people need more and some need fewer carbohydrates and that the 10,000-step benchmark is fairly meaningless at an individual level.

Time to stop the generic trials

As mentioned by Steven, precision medicine is, in fact, already here in several settings. The most prominent is optometry, where an eye exam determines your specific needs, and an optometrist prescribes a pair of glasses tailored entirely to your current condition. You can also pick a model of frame and material that fits your lifestyle (e.g., sports or work) and your taste in fashion. Without this specific focus, you would end up with a generic pair of glasses that might not suit your needs and lifestyle.

Medicine needs to adopt the same approach by moving away from a generic approach to clinical studies and towards trials that focus on individual responses to therapy. In his article titled, Personalized medicine: Time for one-person trials, Nicholas J. Schork looks at the 10 most-prescribed drugs and notes that for every person they help, they fail to improve the condition of between three and 24 people. Some drugs, such as statins, benefit as few as one in 50 people, and some are even harmful to certain ethnic groups because clinical trials have typically focused on participants of European background.

Dosage is also seldom geared towards the individual. We know it’s possible to do this because the company provides dose recommendations based on pharmacokinetic drug models, patient characteristics, medication concentrations, and genotype.

Generally, however, we don’t know who will benefit from a drug and who won’t. While genomics plays a key role, there are multiple other factors that have an impact on outcomes, including our environment (e.g., city vs. rural), having access to good produce or being limited to convenience store food (e.g., doughnuts vs. fruits and veggies), whether we live in a cold or hot climate, whether we live in an industrial area with pollution, and what our work and family environment is like. Taking all these factors and more into account is essential if we are to treat each person as unique.

With the growing realisation about these effects, more clinicians are turning to digital technology, deploying internet of things (IoT) sensors and smartphones to improve patient outcomes. A study of 2,000 Americans shows that the average person uses his or her smartphone 80 times per day, so why not leverage it as part of a care plan? The fact is that people are already using their phones for health, with one out of 20 Google searches being health-related.

Setting baselines with sensors

Sensors and apps are being used by many people to check their vitals and provide far more relevant information than using standard measures for what is normal with sleep patterns, heart rate, blood pressure, glucose, temperature and stress. The context in which these measures are taken varies dramatically. For example, maybe it is normal for my stress and blood pressure level to rise when I’m rock climbing, and perhaps a pregnant woman can expect her sleep pattern to change.

Expanding on Steven’s idea, wearable IoT devices are redefining the human phenotype (i.e., all of the observable physical properties of an individual) by performing unobtrusive and continuous monitoring of a wide range of characteristics unique to each of us. This will allow us to define our “normal” blood pressure when we are stressed. After all, do you really need to worry if your blood pressure rises when you’re stuck in traffic after a busy day at the office?

Sensor technology enables continuous monitoring, so you can create a baseline and compare your own readings. When something doesn’t feel right, you’ll be able to go back and compare it to a day when you did feel right the month before. This is a far better measure of your own health.

For example, a study into temperature shows that although your normal temperature should be around 37 degrees C, the normal temperature of a person can vary from 33.2 degrees C up to 38.4 degrees C. This means that if your normal temperature is 33.2 degrees C and you have a 37-degree C temperature, you’re having a pretty severe fever, but most doctors won’t realise this because they don’t know your normal temperature.

Another study shows that although the average daytime heart rate is around 79, the normal heart rate of a person varies from 40 to 90. This makes a big difference when treating a patient for a heart condition. This data comes from Fitbit’s analysis of 100,000 persons’ resting heart rates. So obviously, you can’t apply a population average to your own body. This is important because with the trends in your heart rate, we’d be able to find early signs of influenza, for example.

The challenge for people who have wearables (like me, yeah, I own a Fitbit … how cool am I?), is that we’re not quite sure what to do with all that data.

Following this trend, the National Institutes of Health in the United States has created the All of Us Research Program, the largest precision medicine longitudinal study ever performed, which aims to follow 1 million people from all walks of life for decades. The program will provide a set of IoT wearable sensors to the participants and then correlate this data with their clinical data from the healthcare ecosystem — hospitals, family practitioners, specialists, etc.

This study differs from your typical research study because this program will provide insights on the data to its participants, so they can improve their health in real time.

Today, anyone has access to wearable technology; it’s relatively cheap and easy to use, and it gives you real-time insights into your own health. Don’t be afraid to build your own baseline and talk to your doctor. As more people and clinicians embrace wearables and apps, we’ll start to see a broader shift towards precision medicine supported by both genomics and digital health.