BioTrillion

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

[BioTrillion @BioTrillion]

28 hours a week.

That’s how much clinician time @googlecloud says can disappear into paperwork and administrative work.

Its new Gemini for healthcare is built to reason across records, billing data, clinical guidance and other sources, then help execute multi-step workflows.

That raises a bigger HealthAI question:

What happens when those systems gain access not only to records, but to fresh objective physiology?

That is where smartphone biomarkers become another data layer for existing healthcare workflows.

#HealthcareAI #DigitalHealth #DigitalBiomarkers

https://t.co/9OzlYkafT9

[BioTrillion @BioTrillion]

Your voice may be becoming a vital sign.

In a 563-patient heart-failure study, Cordio Medical analyzed short daily voice recordings captured on smartphones. The system flagged heart-failure events an average of 24 days before clinical presentation, with 85% adherence.

The striking part isn’t voice itself.

It’s what software can extract from ordinary phone inputs.

The smartphone is quietly becoming a physiological sensor.

#DigitalHealth #DigitalBiomarkers #RemotePatientMonitoring #HealthcareAI #CardioTwitter

https://t.co/qEiqtykb6r

[BioTrillion @BioTrillion]

> 1 billion people live with hypertension. > 50% don’t know it.

@GoogleResearch is using ordinary smartwatch sensors plus AI to passively recognize persistent signs of high blood pressure, without cuff calibration.

That’s a meaningful shift.

The sensor doesn’t need to produce another exact number. It can help recognize a physiological pattern.

Sometimes the breakthrough isn’t a new sensor.

It’s learning to read the ones we already have.

#DigitalHealth #HealthcareAI #DigitalBiomarkers #Cardiology

https://t.co/8F4YKwtTjN

[BioTrillion @BioTrillion]

The scale tells you whether someone lost weight.

It doesn’t tell you what changed along the way.

@ouraring and @UCSanDiego are launching a multiyear study asking whether sleep, heart rate, activity and recovery data can help explain outcomes from GLP-1 treatment and bariatric surgery.

That makes the space between visits part of the clinical dataset.

Which between visit signals will prove most useful for understanding treatment response?

#ClinicalTrials #DigitalHealth #DigitalBiomarkers #Obesity

https://t.co/kmwiszlgab

[BioTrillion @BioTrillion]

Clinical-trial AI is going upstream.

@AstraZeneca and @Oracle are teaming up to use AI and real-world data to identify eligible trial participants and monitor safety signals.

Their first project will support hypertension research.

That moves AI from analyzing trials to helping operate them.

Recruitment determines who enters a trial.

Measurement determines what the trial can learn.

Which bottleneck deserves more attention?

#ClinicalTrials #Pharma #HealthcareAI #DigitalBiomarkers

https://t.co/6aGOvf59lO

[BioTrillion @BioTrillion]

An insurer just moved a lot further upstream than paying claims.

@pingan_group has launched an Alzheimer’s program spanning cognitive screening, genetic and biomarker testing, specialist care, rehabilitation and 24/7 contactless home monitoring.

That’s a very different definition of insurance.

The insurer of the future may look increasingly like a health-monitoring platform.

#DigitalHealth #Insurance #Alzheimers #DigitalBiomarkers

https://t.co/oJt4RQBV78

[BioTrillion @BioTrillion]

Personalized health AI has a dirty little secret:

It’s hungry.

The Verge spent ~ 100 days with @TwinHealthUS' digital twin. The system consumed CGM data, a smart scale, blood pressure readings, Apple Watch data, labs and daily logs.

The writer’s triglycerides dropped 70 mg/dL.

She also described real tracking fatigue.

That tension matters.

How much tracking will people tolerate before “personalized” starts to feel like a second job?

#PersonalizedMedicine #DigitalHealth #HealthcareAI #DigitalBiomarkers

https://t.co/oDbXfSgTOb

[BioTrillion @BioTrillion]

94% sensitivity. 67% specificity. From a consumer smartwatch.

A Stanford validation study of 147 adults found @Samsung Galaxy Watch 6 could screen for moderate-to-severe sleep apnea with high sensitivity.

It’s not a diagnosis. That’s what makes the story interesting.

Consumer devices are moving upstream into screening.

What matters most for population screening: sensitivity, specificity, or friction?

#DigitalHealth #SleepHealth #DigitalBiomarkers #HealthcareAI

https://t.co/YN1J2VMMMa

[BioTrillion @BioTrillion]

The interesting part of NeuroRPM Inc.’s latest move isn’t just the FDA clearance.

It’s where the data is going.

By integrating Parkinson’s monitoring into @athenahealth, tremor and dyskinesia data can move closer to the clinician’s normal workflow instead of living in a separate digital-health silo.

That may be the bigger test for digital biomarkers now:

Not “Can we measure it?”

But “Can we make the measurement easy enough to use routinely?”

@BioTrillion addresses that challenge by eliminating dedicated hardware and using smartphones to capture neuro and motor biomarkers.

For remote monitoring, workflow friction may matter just as much as sensor accuracy.

#RemotePatientMonitoring #Neurology #DigitalBiomarkers #NeuroTwitter

https://t.co/1GmWqvNsfW

[BioTrillion @BioTrillion]

Healthcare AI has a memory problem.

@HimsHersComms is building its weight-loss AI around longitudinal context: treatment history, medication dose, goals, clinician interactions, and what happened after earlier decisions.

A health recommendation without history is just a snapshot.

@BioTrillion's solution addresses the same problem in a different way.

@BioTrillion’s DigitalDoctor interprets changing physiological biomarker patterns together with relevant context.

For longitudinal care, which is harder: remembering the patient’s story, or measuring how the body is actually changing?

#HealthcareAI #DigitalHealth #Telehealth #PersonalizedMedicine

https://t.co/CMDfgFPkxk

[BioTrillion @BioTrillion]

A health sensor can work well and still fail at scale.

@Dexcom surveyed 2,500 people with Type 2 diabetes and 800+ healthcare professionals across 8 countries.

55% of patients reported limited CGM knowledge.
90% of clinicians cited coverage & reimbursement barriers.

That makes access part of the technology problem.

@BioTrillion addresses a different access barrier: hardware.

Its API/SDK can bring smartphone-based biomarker measurement into existing health workflows without requiring a separate dedicated device.

For digital health at scale, what is hardest to eliminate: reimbursement friction, knowledge gaps, or hardware burden?

#DigitalHealth #Diabetes #DigitalBiomarkers #HealthTech

https://t.co/CMDfgFOMHM

[BioTrillion @BioTrillion]

Wearable data is moving from wellness metric to healthcare outcome.

@Oura and @CounselHealth are joining @CMS’s ACCESS model to test whether continuous biometrics plus medical AI can improve chronic care at Medicare scale.

That puts biometrics inside a much harder test: measurably improving chronic care.

@BioTrillion approaches the measurement problem differently: objective biomarker capture without requiring a wearable or new device.

A 10-second #HealthySelfie scan captures 10 digital biomarkers through an API/SDK, using only a smartphone.

For chronic care at scale, which matters more: continuous passive monitoring, or much lower measurement friction?

#DigitalHealth #HealthcareAI #DigitalBiomarkers

https://t.co/EetwPHmvU1

[BioTrillion @BioTrillion]

What if the scans we already take can tell us more than we ever asked them to?

@Clairity’s FDA-authorized #AI model uses a standard mammogram not only to look for cancer today, but to help predict future breast-cancer risk.

That shift matters: familiar images can become new sources of health intelligence.

@BioTrillion is built around the same idea. A 10-second #HealthySelfie uses the smartphone camera to turn subtle physiological signals into objective biometrics.

If AI can reveal new health information from images we already capture, how many everyday sensors are still being underused?

#HealthcareAI #EarlyDetection #DigitalHealth #DigitalBiomarkers

https://t.co/I1MBub4aHg

[BioTrillion @BioTrillion]

What if the first sign of disease appears years before you feel anything?

@MayoClinic researchers are combining biological, environmental, and health data with #AI to find those early shifts before symptoms begin.

@BioTrillion is built around the same missing window. One 10-second #HealthySelfie can capture objective neuro, cardio, and mobility biometrics from daily life, turning otherwise invisible physiology into measurable longitudinal data.

If disease changes the body before symptoms appear, why are we still waiting for symptoms to start measuring?

#PreventiveHealth #DigitalHealth #DigitalBiomarkers #HealthcareAI

https://t.co/src4i5nA7v

[BioTrillion @BioTrillion]

@KneuHealth just launched an FDA-cleared @AppleWatch tool that continuously measures tremor and dyskinesia in Parkinson’s.

That matters because Parkinson’s does not happen on a clinic schedule.

@BioTrillion is built around the same missing window, but without requiring a wearable. One 10-second #HealthySelfie can capture 10 objective biometrics across neuro, cardio, and mobility using the smartphone people already carry.

If symptoms change between visits, shouldn’t measurement live there too?

#DigitalHealth #Parkinsons #DigitalBiomarkers #AI

https://t.co/Tw1bENxGUv

[BioTrillion @BioTrillion]

@Oura’s IPO filing makes one thing hard to ignore:

Health data is becoming an asset class.

Nearly 42 billion hours of physiological data and about 5 million paid members point to a bigger shift from tracking what happened to predicting what happens next.

@BioTrillion shares that data thesis, but removes the ring. One 10-second #HealthySelfie turns the smartphone itself into a multi-biomarker sensor across neuro, cardio, and mobility.

If longitudinal physiology becomes one of #HealthcareAI’s most valuable assets, how much hardware should it really take to collect it?

#Wearables #AI #DigitalHealth #DigitalBiomarkers

https://t.co/kuBHA3aTOA

[BioTrillion @BioTrillion]

@FDA just authorized @Abbott’s Libre Duo, the first wearable to continuously measure both glucose and ketones in one device.

That matters because biology rarely speaks through a single signal.

@BioTrillion is built on the same multi-signal idea, but without adding another device. One 10-second #HealthySelfie can capture 10 objective biometrics across neuro, cardio, and mobility using the smartphone people already carry.

If two biomarkers together can change the clinical picture, what becomes possible when you can measure ten?

#DigitalHealth #DigitalBiomarkers #Diabetes #AI #Wearables

https://t.co/w2Bs70Nyp5

[BioTrillion @BioTrillion]

The founders of @Fitbit are back with @Luffu, an #AI-powered family health platform built to help people keep a closer eye on aging parents and children.

The bigger shift is clear: health AI is moving from tracking one person to understanding the people we care about most.

@BioTrillion approaches that future from another angle. #HealthySelfie captures objective biometrics in 10 seconds, while DigitalDoctor adds context and targeted questions, combining what the body shows with what a person reports.

If AI is becoming a family health companion, shouldn’t it understand both sides of the health story?

#DigitalHealth #HealthyAging #DigitalBiomarkers #HealthcareAI

https://t.co/L3Aan0VHlf

[BioTrillion @BioTrillion]

@FDA just put #DigitalBiomarkers closer to the center of drug development.

Its latest workshop focused on how digitally derived endpoints can turn continuous measurements into evidence regulators and trial teams can actually use.

@BioTrillion is building for that future: a 10-second #HealthySelfie can capture objective neuro, cardio, and mobility signals remotely, creating a new window into what happens between site visits.

Clinical trials are becoming more continuous.

Why should the endpoints still be episodic?

#ClinicalTrials #DigitalHealth #Pharma #AI

https://t.co/ZkuI0wmWt5

[BioTrillion @BioTrillion]

Proud to share that @BioTrillion has been selected to the @TechCrunch #StartupBattlefield200 - a handpicked cohort chosen from thousands of applicants around the world!

In San Francisco this October, we’ll showcase our years of hard work that can now transform the smartphone in 5B hands into an AI-powered health monitor.

Grateful to the TechCrunch Startup Battlefield team for the recognition.

https://t.co/e67IBTAJUk

#StartupBattlefield #TechCrunchDisrupt #HealthTech #DigitalHealth #AI