BioTrillion

Building AI at the intersection of Smartphone Technology and Human Physiology.

[BioTrillion @BioTrillion]

@Google just published research showing a phone can passively estimate heart rate and resting heart rate using the front camera during everyday interactions, aiming for wearable-like monitoring without a wearable. #AI #DigitalBiomarkers #Cardiology

@BioTrillion is built on the same premise, but goes broader: one intentional 10-second #HealthySelfie can capture multiple objective signals from the face (and beyond), then layer interpretation on top. If your phone can watch your heart in the background, what other “vitals” should never require a device again? #DigitalHealth #HealthTech

https://t.co/OmNtPzYiIH

[BioTrillion @BioTrillion]

@ParkinsonsNewsToday reports a Phase 2 @Herantis trial using @Indivi’s smartphone-based digital biomarker platform to detect early motor and cognitive changes in Parkinson’s. The thesis is simple: higher-frequency, real-world endpoints can beat infrequent clinic scores.

@BioTrillion is pushing the same direction: multi-signal neuro and cardio biomarkers from a short selfie video, designed for decentralized settings and clinical studies. If trials can measure tremor and gait remotely and repeatedly, what does a “site visit schedule” even mean anymore? #ClinicalTrials #Parkinsons #Biomarkers

https://t.co/TvwMDVH9O8

[BioTrillion @BioTrillion]

@HealthcareITNews says #RemotePatientMonitoring is hitting a reality check: more devices and more data do not automatically translate into better outcomes. Programs are leaning on #AI and automation, but long-term success still depends on making RPM usable for humans.

@BioTrillion is built for the usability constraint. A single 10-second smartphone scan can add objective “digital vitals” into telehealth and RPM without shipping hardware, charging it, or getting patients to wear it. If RPM has to feel effortless to stick, why are we still designing it around gear? #DigitalHealth #Telehealth

https://t.co/8BoxXI9Px1

[BioTrillion @BioTrillion]

@Withings analyzed data from 470,000 U.S. women and found that atrial fibrillation prevalence rises 3.8x across the menopause transition, while heart rate variability declines during the same period. That is a sharp reminder that #WomensHealth and #CardiovascularHealth still contain major under-measured windows of risk hiding inside everyday physiology.

@BioTrillion is building around that same belief: subtle physiologic changes often begin long before traditional workflows notice them. If smartphone-based #DigitalBiomarkers can help quantify health trends earlier, more objectively, and at scale, then the real opportunity in #PreventiveHealth may be catching change before it becomes disease. What other major health transitions are we still measuring far too late?

https://t.co/YKk8Cirgm1

[BioTrillion @BioTrillion]

@InsideTracker just unveiled Terra, an AI platform aimed at helping wellness brands deliver hyper-personalized health guidance at scale. That is a strong signal that #DigitalHealth is moving beyond dashboards and toward true health orchestration.

@BioTrillion is building toward that same future from the signal layer up. While others focus on interpreting existing data, our BioEngine4D and #HealthySelfie platform are focused on generating new objective #DigitalBiomarkers from a simple 10-second smartphone video, which raises a bigger question: who will own the next great source of health data?

https://t.co/ke5i277GTx

[BioTrillion @BioTrillion]

@UC Irvine researchers just introduced a wearable, bioelectronic sweat sensor for long-term health monitoring that is wireless, battery-free, and designed to restore its own sensing surface for continuous use. That is a provocative glimpse of where #HealthTech is heading: toward physiology that can be measured more continuously, more passively, and with far less friction.

@BioTrillion shares that same core thesis from a smartphone-first angle. The future of #DigitalBiomarkers may belong to the platforms that make subtle physiology easiest to capture in everyday life, whether through a sensor on the body or through BioEngine4D on the smartphone already in your hand. When health signals become ambient, what part of medicine still stays episodic?

https://t.co/NWvBi75I01

[BioTrillion @BioTrillion]

@Samsung just announced a breakthrough study showing Galaxy Watch6 could predict fainting episodes up to five minutes in advance using PPG, HRV, and AI, with 84.6% accuracy and 90% sensitivity in the study. That is a bold shift from tracking what already happened to warning users before something happens. #Wearables #AI #DigitalHealth

@BioTrillion shares that same thesis from a smartphone-first angle: the future is not just passive monitoring, but predictive physiology. Once consumer devices start surfacing clinically meaningful changes before they become obvious, the line between everyday electronics and real health infrastructure gets very thin. When our devices begin to warn us before our bodies do, what still counts as a routine checkup?

https://t.co/08BERZ6pzR

[BioTrillion @BioTrillion]

@Roche agreed to acquire @PathAI, building on a partnership that had already expanded into AI-enabled companion diagnostic algorithms and strengthening Roche’s position in digital pathology. That is not a niche deal. It is a clear sign that image-based AI is becoming core infrastructure for modern diagnostics and treatment selection. #Pharma #Diagnostics #AIart️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️

@BioTrillion is making a parallel bet from the smartphone side: that subtle visual physiology can be quantified at scale, not just in the lab, but from everyday devices people already use. If pharma now sees machine-read images as strategic assets, the next question is obvious: how many valuable biomarkers are still hiding in plain sight on the face, in the eyes, and in the motion signals we generate every day? #DigitalBiomarkers #ComputerVision #HealthTech

https://t.co/cirlezayfL

[BioTrillion @BioTrillion]

@Google is making a much bigger health play than a simple app refresh: the Fitbit app is becoming the Google Health app, bringing wearable data, Health Connect, Apple Health, medical records, and an AI health coach into one place. This is what happens when #DigitalHealth stops being a feature and starts becoming an operating system. #AI #HealthTech

@BioTrillion is building toward the same future from the signal layer up. While others organize health data, we are focused on extracting objective #DigitalBiomarkers from a simple 10-second smartphone video through #HealthySelfie and BioEngine4D. If @Google is trying to become the interface for health, who becomes the source of the next great health signal?

https://t.co/mmm0sTRrsO

[BioTrillion @BioTrillion]

@WHOOP is moving beyond wearables by adding Specialized Panels, one-time blood tests spanning 75 to 89 biomarkers across heart, metabolic, performance, women’s, and men’s health. That is a bold sign that the winning health platforms may not be single-sensor products at all, but longitudinal systems that combine lab data, behavior, and continuous biometrics. #DigitalBiomarkers #AI #PreventiveHealth

@BioTrillion sees the same endgame from a smartphone-first angle: pair low-friction sensing with objective biomarkers and AI, then make measurement scalable enough for everyday life. When blood, wearables, and camera-derived signals finally converge, what will the new baseline for prevention look like?

https://t.co/Lc5JUs0EbF

[BioTrillion @BioTrillion]

@linushealth announced new findings showing how digital cognitive assessments and personalized endpoints may improve identification of patients for emerging Alzheimer’s therapies and help measure treatment impact in ways that better reflect what matters to patients. That is a powerful example of #DigitalHealth moving toward biologically anchored, scalable screening and smarter trial prescreening in #BrainHealth.

@BioTrillion is building toward a similar future by quantifying subtle physiology from everyday devices, so earlier screening and longitudinal monitoring can happen with less friction and at far greater scale. The big opportunity in #HealthTech may not be just better models, but better front doors into care and research. Who will own the first truly scalable layer of objective health measurement? #DigitalBiomarkers #Neurology #AI

https://t.co/whaHLSKiyk

[BioTrillion @BioTrillion]

Excited to share another patent granted to BioTrillion!
https://t.co/bklrAfqrLI

It’s been known for centuries that the eyes are windows into the brain. Valuable signals tied to stress, cognition, and #neurology are hidden in tiny pupil responses that have traditionally been too difficult and expensive to quantify—even during annual medical visits.

The @BioTrillion solution is a patented method that uses #computervision to quantify pupillary psychosensory responses, transforming subtle eye behavior into objective, trackable #digitalbiomarkers — directly from a selfie video using a simple smartphone (and other/future devices with cameras).

Imagine a future where changes in #brain function can be monitored from a simple smartphone scan—opening the door to more accessible #screening, #remotemonitoring, and improved #outcomes for patients, providers, researchers, and industry partners.

[BioTrillion @BioTrillion]

@Google expanded @Fitbit with a more personalized AI health coach and medical records integration, bringing consumer tracking and clinical context closer together in one experience. That is a meaningful step toward more connected #DigitalHealth and more useful, context-aware health guidance.

@BioTrillion has been building toward this same future from a different direction: software-only, smartphone-based biomarker measurement from a 10 second #HealthySelfie. When visual biomarkers, AI, and personal health context converge, #PreventiveHealth becomes more scalable, more accessible, and far more actionable.

https://t.co/OL7hOTzeK5

[BioTrillion @BioTrillion]

@WHOOP’s new $575 million raise at a $10.1 billion valuation shows that investors still see major upside in AI-enabled, continuous health monitoring. The broader message is clear: platforms that turn everyday behavior into longitudinal health insight continue to attract serious attention in #HealthTech and #AI.

@BioTrillion sees that same long-term shift through a software-only smartphone lens. While others scale wearables, we are helping push toward a world where a simple 10 second #HealthySelfie can unlock richer biomarker insight, lower friction, and wider access to #PreventiveHealth.

https://t.co/9NnVSTxZYv?

[BioTrillion @BioTrillion]

In February, @FDA appointed a new leader for its Digital Health Center of Excellence—underscoring how quickly #AI and software-driven healthcare are moving from “innovation” to “regulated reality.”

@BioTrillion is building right into that direction: a smartphone-native digital biomarker platform with a clear path toward modular clearances—turning a ~10-second #HealthySelfie into objective “signs” that can scale across payors, providers, and trials. #DigitalHealth #MedTech #HealthAI

https://t.co/ROSLlnZsnv

[BioTrillion @BioTrillion]

@HLTH argues we’re at a “digital biomarker inflection point,” where infrastructure—validation science, governance, and regulatory pathways—is finally catching up to the tech.

That’s exactly the moment @BioTrillion was built for: our ~10-second #HealthySelfie reduces motion/lighting “taint,” boosts repeat usage, and creates cleaner longitudinal baselines—so digital biomarkers can actually work at population scale. #DigitalHealth #AI #RemoteMonitoring #DigitalBiomarkers

https://t.co/daFohfF8mS

[BioTrillion @BioTrillion]

@NatureReviewsDrugDiscovery reports wearables are rapidly reshaping #ClinicalTrials—enabling more real-world, participant-friendly monitoring and accelerating the rise of #DigitalBiomarkers as endpoints.

@BioTrillion pushes the same trend even further with no new hardware: a ~10-second smartphone scan improves compliance and reduces motion/lighting “taint,” producing cleaner longitudinal baselines for remote endpoints in trials. #Pharma #DCT #HealthAI

https://t.co/C4jSYZNe5b

[BioTrillion @BioTrillion]

A new @Nature analysis highlights the growing business case for adopting #digitalendpoints in #ClinicalTrials—because endpoints drive approval, trial economics, and ultimately payer decisions.

@BioTrillion is purpose-built for this shift: device-free digital biomarkers captured from a ~10-second smartphone scan, enabling higher compliance, cleaner real-world signals, and scalable trial participation—without shipping hardware. #DigitalBiomarkers #HealthAI #Pharma

https://t.co/Vt46tctGZl

[BioTrillion @BioTrillion]

In Consumer Healthcare, the highest priorities aren’t just accuracy—it’s also the user experience. Every second with a user is a privilege.

HealthySelfie™ is a ~10-second scan—while other camera-based platforms typically ask users to hold still ~30–60 seconds. A shorter scan is a real advantage:

Higher compliance → more people finish the scan, more often
Cleaner data → less motion fatigue + fewer lighting/drift artifacts
More consistent samples → less chance the environment “taints” the video
Better longitudinal baselines → more repeatable check-ins = stronger trend detection
Faster workflows → easier to embed in underwriting, telehealth intake, and trials

In digital biomarkers, the best model in the world can’t help if users don’t complete the scan.

Imagine when health-checks go from 1x per year to each time you unlock your phone: FaceID => HealthID 🚀

#DigitalHealth #DigitalBiomarkers #InsurTech #HealthAI

[BioTrillion @BioTrillion]

In Consumer Healthcare, the highest priorities aren’t just accuracy—it’s also the user experience. Every second with a user is a privilege.

HealthySelfie™ is a ~10-second scan—while other camera-based platforms typically ask users to hold still ~30–60 seconds. A shorter scan is a real advantage:

Higher compliance → more people finish the scan, more often
Cleaner data → less motion fatigue + fewer lighting/drift artifacts
More consistent samples → less chance the environment “taints” the video
Better longitudinal baselines → more repeatable check-ins = stronger trend detection
Faster workflows → easier to embed in underwriting, telehealth intake, and trials

In digital biomarkers, the best model in the world can’t help if users don’t complete the scan.

Imagine when health-checks go from 1x per year to each time you unlock your phone: FaceID => HealthID 🚀

#DigitalHealth #DigitalBiomarkers #InsurTech #HealthAI