Effectiveness of Nurse-Led, Touch-Based Intervention in Improving Informal Caregivers' Engagement and Perceptions of Nurse Support During Neonatal Nursing Care: Protocol for Cluster Randomized Control

In the last decade, MODEL‐AD (Model Organism Development and Evaluation for Late‐Onset Alzheimer's Disease) has emerged as a cornerstone infrastructure for preclinical Alzheimer's disease (AD) research. Created in response to longstanding challenges in modeling late‐onset AD (LOAD), the IU/JAX/PITT MODEL‐AD Center comprises investigators from Indiana University (IU), The Jackson Laboratory (JAX), and the University of Pittsburgh (PITT), has delivered novel, genetically informed mouse models, a translationally relevant phenotyping pipeline, and a rigorous preclinical testing platform. This white paper reflects on the origins, accomplishments, and future trajectory of MODEL‐AD, and articulates why continued investment is both warranted and necessary. It is intended to support strategic discussions with funding agencies, guide future priorities, and serve as a clear articulation of the evolving mission of MODEL‐AD at a pivotal moment in the translational AD research landscape. By 2015, AD research had reached a breaking point. Nearly every drug candidate that showed promise in mouse models had failed in human trials. The core issue was poor translational relevance. Most existing models were built around transgenically expressed rare familial AD mutations, which are not representative of most patients with LOAD. These models failed to reflect the complexity and heterogeneity of the disease, often lacked thorough characterization, and produced inconsistent results across laboratories. Compounding the problem, there was no standardized pipeline for phenotyping or testing compounds in vivo, leaving the field without a reliable framework for validating therapeutic targets. At the same time, advances in human genetics were reshaping our understanding of LOAD. Large‐scale genome‐wide association studies (GWASs) and transcriptomic analyses were uncovering dozens of risk genes and molecular pathways linked to the disease. Yet these discoveries remained largely disconnected from model development. The insights weren't being translated into experimental systems that could support drug discovery or mechanistic research. In response, the National Institute on Aging (NIA) launched the MODEL‐AD program in 2016. Its mission was to address the translational gap by developing genetically relevant models based on human LOAD risk, implementing standardized and reproducible phenotyping pipelines, building infrastructure for rigorous and unbiased therapeutic testing, and making all tools and data openly accessible to the research community (). Since its launch, MODEL‐AD has fundamentally reshaped preclinical AD research. In less than a decade, the program has produced > 70 novel mouse models () that incorporate human genetic variants linked to LOAD. Key human genes that differ significantly between humans and mice (e.g., apolipoprotein E [], microtubule‐associated protein tau []) were introduced into the equivalent mouse gene locus by gene replacement (GR) strategies. Further, genetic risk variants (coding and non‐coding) that could be readily mapped to the equivalent mouse gene were engineered into mice using CRISPR/Cas9 technology. The program has developed both “base” models (consisting of, for instance, human , ε4, and humanized amyloid beta [Aβ] sequence),, as well as combinatorial models (incorporating variation in key risk genes such as triggering receptor expressed on myeloid cells 2 [], 1‐phosphatidylinositol‐4,5‐bisphosphate phosphodiesterase gamma‐2 [], ATP‐binding cassette sub‐family A member 7 [], methylenetetrahydrofolate reductase [], interleukin 1 receptor accessory protein [], etc.) to better reflect polygenic risk, aligning preclinical systems more closely with human disease biology. In some cases, models have been improved by the incorporation of environmental risk factors (e.g., high‐fat/high‐sugar diet, ) and prioritized models have been assessed from young to older ages.