EMBIC CORP — Department of Health and Human Services SBIR Phase I: NIA
EMBIC CORP — SBIR Phase I award from Department of Health and Human Services.
- Amount
- $129,734
- Agency
- Department of Health and Human Services · National Institutes of Health
- Program / Phase
- SBIR · Phase I
- Topic
- NIA
- Solicitation
- PAS18-187
- NAICS
- —
- Place of performance
- CA
- Period
- 2019-08-01 → 2019-11-30
Description
PROJECT SUMMARYABSTRACT The goal of this study is to validate a pragmatic method to predict impending cognitive decline in earlystage Alzheimer s diseaseADpatientsprior to the development of hallmark symptomsWith the growing epidemic of AD dementiathe current focus of scientific research and clinical trials in Alzheimer s disease and related disordersADRDhas shifted toward intervention during the asymptomatic and earlystages of the diseaseHoweversuch early stage trials have struggled with an inability to identify and enroll subjects with no outward symptoms of cognitive declineIn additiononce treatments are approved to treat early stage ADRDidentifying asymptomatic patients will be a significant obstacle in the delivery of timely careThereforethere 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 therapiesOur preliminary studies have demonstrated that a Hierarchical Bayesian Cognitive ProcessingHBCPmodel of wordlist memoryWLMtest performance canquantify cognitive processes which are not captured by traditional scoring of assessments such as the AVLT or ADAS Cogor by recent composite measures such as the ADCOMSandaccurately classify cognitively normal individuals into two groupsthose whose latent cognitive processes indicate cognitively normal agingstableand those whose latent cognitive processes indicate progression to MCI ADprogressorUsing HBCP models to analyze WLM testswe will enable quantitative estimations of latent cognitive processes that predict impending cognitive decline due to ADRDSuccessful 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 subjectsThis technology will also facilitate timely clinical intervention for early stage ADRD patients when new treatments are approved PROJECT NARRATIVE The current focus of scientific researchclinical trialsand clinical care in Alzheimer s disease and related disordersADRDhas shifted toward intervention during asymptomatic and early stages of the diseaseHoweverthere are currently no pragmatic approaches for identifying cognitively normal subjects with impending cognitive declineThe proposed study will use a Hierarchical Bayesian Cognitive Processing model of wordlist memory task performance to enable quantitative estimations of latent cognitive processes that predict impending cognitive decline due to ADRD