Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
Next-generation Alzheimer's therapeutics: target assessment and enablement at the Indiana University School of Medicine-Purdue University TREAT-AD Center.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Richardson Timothy I, Klein Rebecca C, Huang Kun, Zhang Jie, Mesecar Andrew D, Dage Jeffrey L, Clayton Brent, Lamb Bruce T, Palkowitz Alan D
Аннотация
The incidence of Alzheimer's disease (AD) continues to increase, despite decades of effort to develop disease-modifying therapies. In response, the National Institute on Aging (NIA) established the TaRget Enablement to Accelerate Therapy Development for Alzheimer's Disease (TREAT-AD) centers to address the gap between basic research and translational drug discovery. Situated within a robust AD research environment, the Indiana University School of Medicine (IUSM)-Purdue University TREAT-AD Center is one of two National Institutes of Health (NIH)-supported centers funded to accomplish this mission. With a focus on novel biological targets beyond amyloid and tau, our center has assembled the necessary components of a drug discovery engine: project and data management, bioinformatics and computational science, structural biology and biochemistry, assay development and pharmacology, and molecular design and synthesis of small molecules, antibodies, and oligonucleotides. Our objective is to deliver Target Enabling Packages (TEPs) within an open science framework, making data, methods, and research tools broadly accessible through the AD Knowledge Portal. HIGHLIGHTS: The Indiana University School of Medicine (IUSM)-Purdue TREAT-AD Center develops Target Enabling Packages (TEPs) to advance novel targets for the treatment of Alzheimer's disease (AD). The center is overseen by an administrative core and operates through four technical cores - bioinformatics, structural biology, assay development, and medicinal chemistry - within a milestone-driven and open science framework. Multi-omics, systems biology, and machine learning (ML) approaches guide the nomination of high-priority targets beyond amyloid and tau. Cross-core workflows provide structural insights into novel biological targets, validated assays, biomarkers, and molecular probes that enable lead optimization. All data, methods, and tools are openly shared through the AD Knowledge Portal to accelerate global efforts in AD drug discovery.