Many developing diseases signal themselves, pre-symptomatically and subtly, through non-molecular pathways in the form of physiological and behavioral "phenotypic signs."

BioEngine4D℠

Medical data is abundant.

However, it also tends to be siloed, unstructured, static, and even too abundant for human minds alone to optimally manage and process.  As a result, a massive amount of it is not adequately translating to improved health outcomes.

Diseases "signal" themselves through multiple modalities — molecular and non-molecular.

Many of these diseases develop while "signaling" themselves through non-molecular pathways, depending on the disease, typically as subtle, occasional, or intermittent physiological or behavioral "signs."  As humans, we subsequently observe these signs as symptoms, often later in a disease's stage, and sometimes too late.

The addition of LIFEdata℠ will provide more objective, passive, and continuous insights into our health.

We define LIFEdata as sensor-measured information digitally generated from life and around life.  We are connecting LIFEdata as learnable insights from expressions & environment to disease detection and prediction through machine learning and artificial intelligence.

The time dimension has been largely absent in our approaches to healthcare today.

Many developing diseases have a dynamic pattern of progression that can be more timely detected through continuous physiological and behavioral measures.  Timelier intervention, catalyzed by detection, will improve health and cost outcome ROI "return on (earlier) intervention".

Although advances in technology over the years have been able to radically disrupt most industries, there remains a gap within healthcare, and we believe many solutions and synergies exist locked within the Life setting.

Consumer smart devices with sensors that can capture LIFEdata are starting to rapidly populate our Life settings.  These digital devices provide individuals with the opportunity to contribute to and access novel healthcare innovations outside the Medical setting.  Even IoT home devices not originally purposed for healthcare applications can be a very valuable source of LIFEdata which will be processed by our technology platform.  We believe subtle and quantifiable, non-molecular and "digitizable" signals are under-discovered, but very insightful objective "markers" for many developing diseases and disorders.

Every new sensor released to market has the potential to generate novel LIFEdata measures and applications for healthcare.

Smartphones alone provide the Consumer a number of sensory modalities to passively generate LIFEdata.  New chips, hardware, and sensors coming to market will turn the smart devices in our Life setting into health tools.

We have only just begun to scratch the surface with the number of possibilities: n! / r! * (n − r)! ...

We are developing a life technology platform called BioEngine4D℠, powered by machine learning and AI, and fueled by passively streaming LIFEdata to digitally detect developing diseases.

We begin with the premise that every signal from life has the potential to be a "biomarker" weighted from 0 to 1, not 0 and 1.

Digital biomarkers are device-generated physiological and behavioral data points generated from digital smart devices that can be used to detect or predict certain health diseases and outcomes.

LIFEdata can become a digital biomarker when a relationship is drawn to a health-related clinical diagnostic or outcome.

We are developing digital biomarkers by algorithmically training BioEngine4D via machine learning and artificial intelligence — premised around clinically-known pathophysiologies.

BioEngine4D, fueled by medical data and LIFEdata, is being developed to enable, even enhance, the Consumer's current self-healthcare abilities.

As our users aggregate more types of LIFEdata, they can begin to serve as a central data portal and reposition themselves closer to the center of the healthcare paradigm.  We are developing BioEngine4D to enable us to digitally detect disease signs that are currently too subtle for an individual's or doctor's observational abilities, leading to more timely intervention.

Our solution is largely predicated on the novelty, complexity, and accuracy of BioEngine4D.  Moreover, BioEngine4D becomes maximally commercializable with a front-end App layer that is versatile for both Consumers or Medical professionals, intuitive to use, and value-additive to adopt.

Digital Disease Detection Has Begun.

Hundreds of engineers, years of R&D, and hundreds of millions of dollars were invested into the Apple Watch 4 ECG.  This was a major validating tailwind for BioTrillion and the market we’ve been predicting for next-gen healthcare:  digitally detecting developing diseases.

It's time to reimagine Healthcare solutions around accessibility, timeliness, and quantitatively enhanced outcomes.

Solutions that will make us realize our health had been in the dark 99% of the time in retrospect.

BioTrillion's mission is to transform Data from Life into Data for Life.