Quantitative Mechanistic insights into Alzheimer’s Disease and Related Dementias

Alzheimer’s disease (AD) and related dementias (ADRD) remain major unmet medical needs, in part because disease mechanisms span multiple interacting pathways and because linking target engagement to meaningful clinical outcomes is challenging. Neuropharmacology increasingly relies on quantitative and mechanistic frameworks to connect biology, drug exposure, target modulation, biomarkers, and functional readouts across preclinical and clinical settings.This Research Topic will highlight mechanistic and model-informed advances in neuropharmacology that support therapeutic discovery and development for AD/ADRD. We welcome contributions using Quantitative Systems Pharmacology (QSP) and complementary quantitative approaches (e.g., mechanistic PK/PD, PBPK, disease progression models, network and systems biology models, trial simulation, and hybrid mechanistic + data-driven methods), mechanistic in vitro and animal experimental models, quantitative insights from epidemiological and -omics datasets, and related methodological advances. Submissions may address disease mechanisms, new drug discovery, drug mechanisms of action, translation across species, dose and regimen selection, patient stratification, biomarker-driven decision-making, and clinical outcomes.A particular emphasis will be placed on approaches that integrate diverse data streams, omics, imaging, fluid biomarkers, electrophysiology, digital outcomes, and clinical endpoints, to improve prediction of treatment response and to de-risk neurotherapeutic development.Topics of interest include, but are not limited to:- Mechanistic and QSP models linking amyloid, tau, neuroinflammation, synaptic dysfunction, neuronal network changes to disease trajectories, metabolic dysfunction (gut-brain axis), and mitochondrial dysfunction- Translational neuropharmacology models connecting exposure, BBB transport, target engagement, and downstream pharmacology- PK/PD and PBPK modeling for CNS drugs, including brain distribution, transporter effects, and formulation/delivery strategies- Experimental models including complex in vitro models (CIVM) and new approach methodologies (NAMs) investigating specific mechanisms of disease pathophysiology, such as aspects of proteinopathy, vascular dysfunction, and stem cell biology, which generate quantitative data- Analysis of large datasets, such as epidemiological or omics data, that generates quantitative mechanistic insights- Biomarkers and endpoints: quantitative links between target engagement and imaging/fluid/digital biomarkers (e.g., PET, plasma/CSF markers, neurophysiology)- Disease progression and heterogeneity: modeling subtypes, comorbidities (vascular/metabolic), and stage-dependent treatment effects- Trial simulation and design optimization: endpoint selection, adaptive designs and combination therapyTopic Editor Mark Schurdak holds stocks in Abbott Laboratories and AbbVie.Topic Editor Marissa Renardy is employed by GSK and holds stock in the company. Topic editors: Marissa Renardy, Suruchi Bakshi, Mark Schurdak, Shaina M Short Source: https://www.frontiersin.org/research-topics/78836/quantitative-mechanistic-insights-into-alzheimers-disease-and-related-dementias