The next decade may well see a revolution in treatment and diagnosis of disease, as the Internet of Things (IoT) is brought to bear on medicine.
Here are 10 examples of IoT in healthcare.
1. OpenAPS – closed-loop insulin delivery
One of the most fascinating areas in IoT medicine is the open source initiative OpenAPS, which stands for open artificial pancreas system.
Dana Lewis and her husband Scott Leibrand have hacked Dana’s CGM (continuous glucose monitor) and her insulin pump.
Using the data feed from the CGM and a Raspberry Pi computer, their own software completes the loop and continuously alters the amount of insulin Dana’s pump delivers.
As of summer 2016, when Dana presented at OSCon in Austin, 59 people were using the open source software and hacking their own equipment.
This example shows how patients have been waiting for years for improved technology which the healthcare industry has not delivered.
Security concerns and lengthy development and testing periods mean that connected devices have taken some time to come to market.
Dana Lewis told e-patients.net that, in the view of OpenAPS, “the relative net risk of this [loop] feature is far outweighed by the net benefit of providing users the ability to control their own devices, as discussed here.”
The OpenAPS website
Reading the FAQs on the OpenAPS website gives an interesting insight into some of the issues in this part of the healthcare market.
2. Pharma is following, though, and developing its own connected systems to help diabetes sufferers. In 2016, Roche acquired distribution rights to an implantable long-term continuous glucose monitoring (CGM) system which uses a 90 day sensor below the patient’s skin.
The sensor communicates with a smart transmitter which then sends blood glucose levels to a sister mobile app on the patient’s phone.
3. Activity trackers during cancer treatment
The Memorial Sloan Kettering Cancer Center (MSK) and cloud research firm Medidata are testing the use of activity trackers to gather lifestyle data on patients being treated for multiple myeloma.
Patients will wear an activity tracker for up to a week prior to treatment and then continuously for several months over the course of multiple treatments.
The trackers will assist in logging activity level and fatigue, with appetite also being logged directly, and all data saved to Medidata’s Patient Cloud ePRO app on their personal smart phones.
Using a variety of data gathered day-to-day through wearables or apps is a fairly obvious way that diagnosis and treatment can be improved for many conditions.
This is particularly the case for a disease such as cancer, for which the reaction to therapy plays an important and determinant part in prescribing the right treatment.
4. Connected inhalers
The most immediate use for IoT technology in healthcare is not to assist in diagnoses, though, but to ensure adherence. Adding sensors to medicines or delivery mechanisms allows doctors to keep accurate track of whether patients are sticking to their treatment plan.
This provides motivation but also clarity for patients. Devices connected to mobile apps allow for patients to receive reminders, as well as to check on their own adherence.
Novartis is undertaking connected inhaler research with both Qualcomm and Propeller Health, developing inhalers for chronic obstructive pulmonary disease (COPD).
Propeller’s Breezhaler device connects to its digital platform via a sensor, passively recording and transmitting usage data. Novartis’ own device will likely not be released until 2019, though, showing the timescales involved in this sort of research.
5. Ingestible sensors
Proteus Digital Health and its ingestible sensors are another example of digital medicine.
Again, the chief purpose of this technology, trialled with an antipsychotic and a hypertension pill, is to monitor adherence. However, in this case, the pill dissolves in the stomach and produces a small signal which is picked up by a sensor worn on the body, which again relays the data to a smartphone app.
According to a study by the World Health Organisation in 2003, 50% of medicines are not taken as directed. Proteus’ system is one effort to reduce this figure.
6. Connected contact lenses
Alcon (part of Novartis) has licensed Google’s smart lens technology which involves non-invasive sensors embedded within contact lenses.
The lenses may eventually be able to measure glucose levels of diabetes patients via their tears and then store the information in a mobile device, though Novartis backtracked on a plan to test the system in 2016.
Novartis is also hoping to develop the smart lens to help those with presbyopia, helping to restore the eye’s focus.
7. Depression-fighting Apple Watch app
Takeda is testing the use of an Apple Watch app to help patients with major depressive disorder (MDD), starting with a 30-patient trial.
The app, developed alongside Cambridge Cognition, is designed to monitor and assess cognitive function, with the trial set to examine how an app compares with traditional testing and self-assessment when reporting mood and cognition.
Both passive and active data is collected.
8. Coagulation testing
In 2016, Roche launched a Bluetooth-enabled coagulation system that allows patients to check how quickly their blood clots.
This is the first device of its kind for anticoagulated patients, with self-testing shown to help patients stay within their therapeutic range and lower the risk of stroke or bleeding.
Being able to transmit results to healthcare providers means fewer visits to the clinic.
9. Arthritis – Apple’s ResearchKit
In 2016, GSK became the first pharma company to use Apple’s ResearchKit software.
The initial study was not testing a medicine, but looking at the impact of disease on patient lives. GSK’s Parade app for iPhone app is built on the ResearchKit software platform, launched in 2014, which integrates with iPhone’s Health platform.
GSK’s study involved 300 patients over three months, collecting and tracking common symptoms of rheumatoid arthritis, alongside activity and other quality-of-life measures.
Project Blue Sky is an ongoing collaboration between Pfizer and IBM, involving a planned clinical trial using ‘a system of sensors, mobile devices, and machine learning to provide real-time, around-the-clock disease symptom information to clinicians and researchers.’
The aim is to monitor the progression and treatment of Parkinson’s.
Pfizer intends to develop the system by 2019, when one of its experimental Parkinson’s drugs enters phase III of development. However, phase III trials are typically rigorous and time consuming, meaning it may be a while before we see IBM’s system tested in a trial.
mPower, on the other hand, is an ongoing research study (not medical care) by Sage Bionetworks using surveys and tasks within a mobile app to activate a smartphone’s sensors and provide feedback.
There are obvious concerns of vulnerability involved with connected healthcare, which along with the rigour of drug development may be slowing the development of new digital medicines. However, it’s clear which way the wind is blowing. From adherence to diagnosis, the applications are many fold.
In particular, life logging (which granted is often a case of mobile health, not strictly IoT) seems still to be a powerful idea, changing how patients interact with their clinic. This is particularly the case for measuring subjective data for those suffering from anxiety or depression.
Ultimately, one can see see why Apple is getting into this space with HealthKit (100,000 people have participated in HealthKit studies), and Google with GoogleFit. It’s not hard to imagine a future in which iOS or Android apps interact with much of our medicine.
A recent NHS trial of a blockchain-like technology, created by Google DeepMind to log when data is accessed, shows just how tech-driven the future of not just medicine but the regulation of healthcare may become.