R01AG076234

Computational Drug Repurposing for AD/ADRD with Integrative Analysis of Real World Data and Biomedical Knowledge - Abstract

Alzheimer's Disease (AD) and AD-related Dementia (AD/ADRD) is the 6th leading cause of death in the United States (US) – an aging-related neurodegenerative disease with a complex pathogenic mechanism affecting an estimated 6.2 million Americans in 2021.

Both the pathogenic mechanism and pathophysiology of AD/ADRD are complex, creating difficulties in finding effective new treatment or prevention strategies, despite significant investments in the last decade.

On the other hand, the proliferation of large Clinical Research Networks (CRNs) with real-world data (RWD), such as Electronic Health Records (EHRs), claims, and billing data among others, offer unique opportunities to generate real-world evidence (RWE) that will have direct translational impacts on AD/ADRD.

In the past, RWD such as EHRs have limited use for AD/ADRD drug repurposing and primarily used only for validating and evaluating the hypotheses generated by molecular level predictions of AD/ADRD repurposing agents, partially due to a number of key methodological gaps:

1. The lack of integration with existing rich biological and pathophysiological knowledge of AD/ADRD for hypothesis generation.
2. The lack of validated computable phenotyping (CP) and natural language processing (NLP) algorithms and tools that can accurately define the study populations, extract key relevant patient characteristics and meaningful outcomes (e.g., MMSE scores to determine severity).
3. The lack of consideration on the heterogeneity of the disease (i.e., AD/ADRD subtypes).
4. The lack of recognition of the inherent biases in RWD and the need for applying causal inference principles.

The goal of this project is to develop a comprehensive machine learning-based causal inference framework for generating high-throughput and high-quality drug repurposing hypotheses for AD/ADRD by integrating heterogeneous information sources.

There are three aims in this project. Aim 1 aims at developing computable phenotypes to extract key patient characteristics and outcomes relevant to AD/ADRD drug repurposing studies from RWD. Aim 2 aims at developing a learning-based causal inference framework for generating drug repurposing hypotheses from RWD, a deep knowledge embedding framework for generating drug repurposing hypotheses from biomedical knowledge bases (BKB), and a mutual information enhancement framework that combines the information from both RWD and BKB to further improve the quality of the generated hypotheses. Aim 3 aims at validating the generated hypotheses with diverse data sources and approaches.

The project will leverage the patient data from two large Clinical Research Networks (CRNs) contributing to the National Patient-Centered Clinical Research Network (PCORnet) – covering approximately 15 million Floridians and 11 million New Yorkers.

The developed algorithms and software will be open-sourced and widely disseminated within the CRNs and the AD/ADRD research communities.

Weill Medical College Of Cornell University

TO ENCOURAGE BIOMEDICAL, SOCIAL, AND BEHAVIORAL RESEARCH AND RESEARCH TRAINING DIRECTED TOWARD GREATER UNDERSTANDING OF THE AGING PROCESS AND THE DISEASES, SPECIAL PROBLEMS, AND NEEDS OF PEOPLE AS THEY AGE. THE NATIONAL INSTITUTE ON AGING HAS ESTABLISHED PROGRAMS TO PURSUE THESE GOALS. THE DIVISION OF AGING BIOLOGY EMPHASIZES UNDERSTANDING THE BASIC BIOLOGICAL PROCESSES OF AGING. THE DIVISION OF GERIATRICS AND CLINICAL GERONTOLOGY SUPPORTS RESEARCH TO IMPROVE THE ABILITIES OF HEALTH CARE PRACTITIONERS TO RESPOND TO THE DISEASES AND OTHER CLINICAL PROBLEMS OF OLDER PEOPLE. THE DIVISION OF BEHAVIORAL AND SOCIAL RESEARCH SUPPORTS RESEARCH THAT WILL LEAD TO GREATER UNDERSTANDING OF THE SOCIAL, CULTURAL, ECONOMIC AND PSYCHOLOGICAL FACTORS THAT AFFECT BOTH THE PROCESS OF GROWING OLD AND THE PLACE OF OLDER PEOPLE IN SOCIETY. THE DIVISION OF NEUROSCIENCE FOSTERS RESEARCH CONCERNED WITH THE AGE-RELATED CHANGES IN THE NERVOUS SYSTEM AS WELL AS THE RELATED SENSORY, PERCEPTUAL, AND COGNITIVE PROCESSES ASSOCIATED WITH AGING AND HAS A SPECIAL EMPHASIS ON ALZHEIMER'S DISEASE. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.

93.866 - Aging Research

National Institute on Aging (NIA) [HHS - NIH]

New York, New York 100654805 United States

Single Zip Code

Translational Bioinformatics Approaches to Advance Drug Repositioning and Combination Therapy Development for Alzheimers Disease (R01 Clinical Trial Optional) (PAR-20-156)

Amendment Since initial award the total obligations have increased 283% from $807,473 to $3,089,899.