Do we have Digital Biomarkers?

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There is no denying the pace and reach of digital tools seems exponential. As some digital tools mature are we able to create a palette of digital biomarkers so patients and providers can reliably tell if a digital device is working? First, some definitions, a biomarker in the classic sense is objectively measured and can be anatomic, like waist circumference, physiological, like blood glucose, or pathologic, like a biopsy or cell sample. A digital biomarker may include sensors, wearables, implanted or ingested technology that provides clinically relevant data.

A new paper by Andrea Coravos from Boston’s Children’s Hospital published in the current issue of Nature Digital Medicine expands our current understanding of digital biomarkers and also addresses safety and privacy considerations as we enter a new era in digital health.

The first wave of digital tools have entered the marketplace and are gaining traction. The rise in popularity of telemedicine and remote monitoring means glucometer readings can now be sent and monitored by a care team while also supporting a person with diabetes move through their daily routines. This first wave, in essence, digitized established clinical markers, like blood sugar, and blood pressure and allow for more repeated measurement which may, in turn, inform more rapid titration protocols to manage a chronic condition optimally. For the patient, they have a quick and easy way to share data with their care team and may, for example, have additional support via a nutritionist to deal with moment to moment adjustments to their regimen.

The advent of this digital era in medicine also means doctors and care teams will need new ways to evaluate whether a digital tool is helping their patients. Some companies have gone the B to C route to go directly to the consumer, this can often be a crowded market and unless the companies have a healthy bank balance, may mean they run out of money before they can demonstrate value.

One of my key takeaways from DTxWest is the movement of B to B to C in digital therapeutics, demonstrating improvement in patient outcomes is becoming table stakes for those entering the marketplace, and incumbents have learned many hard lessons on their road to adoption. Digital biomarkers are measured across hardware and software, and one big advantage is assessment over multiple timepoints which can add a richer perspective on someone’s health- assessment in clinical settings is less frequent.

Coravos proposes dimensions to consider both the quality of the digital biomarkers and ensure that safety and effectiveness are embedded into metric development to demonstrate improvement in patient outcomes. These include measurement, verification, validation, modularity, and regulation.

Measurement– does the product measure validly? Do the layers of software and hardware communicate appropriately to render the correct metrics?

Verification– does the product measure accurately, precisely and reliably as compared to bench test?. For example, translating the necessary raw data into a heart rate measure.

Validation– does the product measure appropriately across a target population in the right context? For example measuring sleep quality (waking, sleep cycles, and phases) may differ in those who have healthy sleep habits as compared to those experiencing insomnia.

Modularity– are the product components, both hardware and software interoperable? As more sensors and monitors come on the market, this will take on increasing importance.

Regulation– The FDA is working on several digital therapeutic offerings to develop a path to regulation. They aim to “pre-certify” companies and products so they can get to market faster while still going through the rigor of regulatory processes.

Current examples of digital biomarkers are also included and span dimensions such as risk assessment, diagnosis, monitoring, prognostic, predictive and pharma-dynamic. In the diagnostic biomarker category, an example might consist of the diagnosis of ADHD in children using eye vergence metrics.

Many of the algorithms that govern products are proprietary which may be a barrier to more in-depth testing of the products in clinical settings. The move toward multi-faceted tools will also need great transparency if the full benefit is to be realized.

Ensuring that connected devices that transmit sensitive health data have privacy policies in place that safeguard the information and that they are rendered safe against cyber threats will be paramount if they are to be widely adopted. We are entering an exciting phase of digital tool development and deployment.

Thanks for reading – Trina
(Opinions are my own)



Developing and adopting safe and effective digital biomarkers to improve patient outcomes. Nature Digital Medicine

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