# Predicting Impending Cognitive Decline in Cognitively Normal Individuals

> **NIH NIH R44** · MEDICAL CARE CORPORATION · 2020 · $837,630

## Abstract

PROJECT SUMMARY / ABSTRACT
The goal of this study is to validate a pragmatic method to predict impending cognitive decline in early-
stage Alzheimer’s disease (AD) patients, prior to the development of hallmark symptoms. With the
growing epidemic of AD dementia, the current focus of scientific research and clinical trials in Alzheimer’s
disease and related disorders (ADRD) has shifted toward intervention during the asymptomatic and early-
stages of the disease. However, such early-stage trials have struggled with an inability to identify and
enroll subjects with no outward symptoms of cognitive decline. In addition, once treatments are approved
to treat early-stage ADRD, identifying asymptomatic patients will be a significant obstacle in the delivery
of timely care. Therefore, there is an urgent need for a pragmatic method to predict impending decline in
cognitively normal subjects who could enroll in ADRD clinical trials and identify those who could
potentially benefit from treatment with future ADRD therapies.
Our preliminary studies have demonstrated that a Hierarchical Bayesian Cognitive Processing (HBCP)
model of wordlist memory (WLM) test performance can (1) quantify cognitive processes which are not
captured by traditional scoring of assessments such as the AVLT or ADAS-Cog, or by recent composite
measures such as the ADCOMS; and (2) accurately classify cognitively normal individuals into two
groups: those whose latent cognitive processes indicate cognitively normal aging (stable) and those
whose latent cognitive processes indicate progression to MCI/AD (progressor). Using HBCP models to
analyze WLM tests, we will enable quantitative estimations of latent cognitive processes that predict
impending cognitive decline due to ADRD.
Successful delivery of the proposed study will improve efficacy of ADRD drug development by expediting
enrollment and shortening trial duration and by quantifying changes in cognitive processes to
demonstrate meaningful treatment effects in asymptomatic subjects. This technology will also facilitate
timely clinical intervention for early-stage ADRD patients when new treatments are approved.

## Key facts

- **NIH application ID:** 10096896
- **Project number:** 4R44AG065126-02
- **Recipient organization:** MEDICAL CARE CORPORATION
- **Principal Investigator:** William Rodman Shankle
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $837,630
- **Award type:** 4N
- **Project period:** 2019-08-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10096896

## Citation

> US National Institutes of Health, RePORTER application 10096896, Predicting Impending Cognitive Decline in Cognitively Normal Individuals (4R44AG065126-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10096896. Licensed CC0.

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