# LifeBio-ALZ: AI driven digital biomarker engine leveraging natural conversation to widely scale accessibility for early detection and assessment of Alzheimers disease progression

> **NIH NIH R43** · LIFEBIO INC · 2021 · $448,462

## Abstract

Alzheimer’s Disease (AD) is one of the most common forms of dementia to occur in elderly populations,
affecting over 30 million individuals worldwide. As the U.S. elderly population continues to increase, AD incidence
rises as well, as there is no neuroprotective therapy or cure. Common symptoms include memory loss, cognitive
impairment, disorientation, and psychiatric issues. Traditionally, diagnosis is achieved through a combination of
clinical criteria such as neurological examination, mental status tests & brain imaging. However, these strategies
are challenging for detection of early AD or patients with mild symptoms, specifically during the mild cognitive
impairment (MCI) stage. Mental status tests & subjective journals, kept by patients or caregivers, can track AD
progression, but have low sensitivity and reliability. The most strongly established biomarkers for AD, including
amyloid beta, tau protein, & phosphorylated tau, are all obtained thru CSF requiring invasive lumbar puncture.
 The LifeBio-ALZ technology will provide a convenient and accessible, yet comprehensive digital biomarker
and analytics suite to detect & assess Alzheimer’s progression. The platform will integrate a suite of assessment
domains all seamlessly captured through a single, patient-centric app that engages users in natural video chat
conversation via smart digital assistant. During brief, but regular sessions, an individual answers questions
following a smart sequence to evaluate awareness, engagement, cognition, reaction time, speech patterns, &
emotional state. The platform will record audio/video during the conversation. Type and timing of assessments,
as well as specific questions will be adaptively modulated based on AD stage, personal demographics and
previous analytics to minimize user burden while still providing rich data for algorithms. Quantitative features
across multiple domains will be extracted from digital speech and eye movements, and then used as inputs to
an AI engine to detect and assess Alzheimer’s’ disease progression. Data will be aggregated in secure cloud
storage with clinician access to dashboard visualization tools.
 Phase I will demonstrate core feasibility. Development will build on a strong tech foundation of an existing
LifeBio platform to increase likelihood of success. Currently, LifeBio is deployed in several formats including web,
phone, & mobile apps to record life histories of people reaching advanced age or facing life-threatening illnesses
or memory loss. Natural language processing tools parse information into life stories shared by family or used
by staff to personalize engagement in care facilities. While the existing tech provides a base, significant
enhancements will be executed in Phase I. More specifically, Phase I tasks will first update platform architecture
to integrate novel data domains, build on smart sequenced multidimensional questions, and enhance patient
workflow interfaces. Once the enhanced app passes all t...

## Key facts

- **NIH application ID:** 10381308
- **Project number:** 1R43AG076341-01
- **Recipient organization:** LIFEBIO INC
- **Principal Investigator:** Lisbeth Sanders
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $448,462
- **Award type:** 1
- **Project period:** 2021-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10381308

## Citation

> US National Institutes of Health, RePORTER application 10381308, LifeBio-ALZ: AI driven digital biomarker engine leveraging natural conversation to widely scale accessibility for early detection and assessment of Alzheimers disease progression (1R43AG076341-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10381308. Licensed CC0.

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