The Future of Non-Invasive Diagnostics: Six Technologies Supercharging Preventive Health

Over the next decade, non-invasive diagnostics could save millions of lives and unlock markets worth hundreds of billions, not through one-off gadgets, but through platforms that seamlessly fit into daily life. 

Non-invasive diagnostics are becoming platforms capable of turning into ambient, multimodal health sensing systems. The winners of the next decade will go beyond selling a device or test and orchestrate an ecosystem built upon game changing technology that ultimately combine: 

• Sensors: camera-based rPPG, mmWave radar, microphones, retinal imagers, silicon microsensors
• Software: foundation models, on-device signal processing, cloud analytics
• Setting: home, clinic-lite retail, telehealth, senior living, even your car

What creates defensibility here isn’t the widget or device, it’s the clinical validity, real-world data, and distribution channels that make these systems indispensable. Below are six categories we’re excited about. 

1. Needleless Continuous Glucose Monitoring 

What it is: Technologies like optical spectroscopy, radiofrequency, or microneedle-based microsensors that estimate glucose without painful fingersticks or bulky filaments.

Why it matters: Diabetes and pre-diabetes affect over 1 in 3 adults worldwide. If a company achieves reliable accuracy at scale, the market impact would be transformative.

Example: Biolinq (portfolio) is developing a next-gen, microsensor-based CGM that is minimally invasive, patch-like, and consumer-friendly. Unlike legacy CGMs with bulky transmitters and long filaments, Biolinq’s design emphasizes comfort, discretion, and everyday compliance—positioned at the intersection of clinical rigor and consumer UX. The opportunity addresses a $100B+ glucose monitoring market.

2. Blood-Based Early Cancer Detection

What it is: The future of early cancer detection will leverage liquid biopsy technologies that detect circulating tumor DNA (ctDNA), methylation patterns, or other biomarkers from a simple blood draw (or even finger prick). 

Why it matters: Early detection is the single biggest lever for survival and cost reduction in oncology. A stage shift from late to early diagnosis could save millions of lives and billions in healthcare costs annually.

Examples: Freenome (portfolio): Multi-omics + machine learning blood tests; recently struck a distribution partnership with Exact Sciences, signaling strong validation and commercial muscle.

3. Radar-Based Passive Sensing

What it is: Health monitoring without wearables. Using mmWave and ultra-wideband radar, these systems capture subtle micro-motions—respiration, heartbeat, even falls—entirely passively. No device to charge, no app to manage, no patient action required.

Why it matters: Zero compliance burden. Ideal for aging-at-home and hospital-at-home, where adherence is often the biggest risk.

Examples: Xandar Kardian and Cherish are pioneering FDA-cleared radar sensors that can detect early pulmonary decline or fall risk, reducing costly ED visits.

4. Camera-Based Vitals & Blood Pressure

What it is: Leverage camera phones for vital signs. Remote photoplethysmography (rPPG) and computer vision applied via cameras to derive heart rate, HRV, respiration, and cuffless blood pressure.

Why it matters: Software-first and instantly scalable through smartphones, telehealth, and retail health.

Examples: Binah​.ai, Mindset Medical, and NuraLogix integrate their tech directly into telehealth apps, offering scalable vitals monitoring with almost zero marginal cost.

 

5.  Ocular & Retinal Imaging: 

What it is: The eye as a window to the body. AI applied to retinal scans to detect diabetic retinopathy (already FDA-cleared) and expand to cardiovascular, kidney, and neuro disease risk.

Why it matters: Distribution is already in place via optometry and retail clinics, making it an efficient Trojan horse for systemic screening.

Examples: Eyenuk and AEYE Health are deploying AI retinal screening in primary care, unlocking earlier detection of chronic diseases.

6. Acoustic Biomarkers

What it is: Your Voice as a Lab Test. AI models that analyze voice and cough recordings to detect respiratory conditions, mental health states, and neurodegenerative changes.

Why it matters: The smartphone is the sensor. This enables population-scale screening without hardware costs.

Example: Sonde Health, Canary, and Kintsugi are advancing voice-based diagnostics for COPD, asthma, depression, and more.

The Takeaway

The most investable non-invasive diagnostics of the next decade will combine ambient sensing, AI, and distribution partnerships to become indispensable parts of care delivery.
 

The real moat isn’t the hardware or the test. It’s the stack: sensors + software + setting, anchored by clinical evidence and real-world data, and supercharged by distribution. That’s the blueprint for breakout success

If you believe care is shifting into the home and onto the edge, the next decade belongs to ambient, non-invasive diagnostics. The durable winners won’t just measure, they’ll predict, nudge, and integrate into risk-bearing economics. Pick the teams that can manufacture evidence, own distribution, and stack modalities.