Abstract Number: Esoc2026a2444 an Integrative Systems Medicine Framework for Ischemic Stroke: In Silico-Based Target Identification, Network Pharmacology, and Immune Mechanistic Redefinition

Abstract Background and aims Despite decades of translational research, stroke research has not yielded an effective neuroprotective therapy. A key major limitation has been the remain focus on single-drug, single-target interventions, despite growing recognition that stroke is a complex disease defined by multi-target modules which should be tackled using mechanistic drug combination. In parallel, post-stroke outcomes are critically influenced by systemic immune responses, yet these remain insufficiently characterized. Circulating peripheral blood mononuclear cells (PBMCs) represent a central mediator of systemic inflammation and may contribute to secondary ischemic events and poor recovery, while also offering an accessible window into disease biology. Methods We here developed a network-based pipeline for multi-target identification using human stroke-associated genes combined with a network pharmacology therapeutic approach. In parallel, we implemented a transcriptomic biomarker discovery approach using CITE-sequencing of PBMCs from stroke patients to capture systemic immune dynamics. Results Our in silico-based network pharmacology therapy improved outcomes in a preclinical stroke model 24h after post-ischemia. To assess clinical safety, a repurposed triple drug combination was evaluated in healthy volunteers (Phase I) followed by a Phase IIa study demonstrating a favourable safety profile in acute stoke patients. Due to the capacity of PBMCs to reflect broad systemic and dynamic changes, we conducted the first in-depth comprehensive immunophenotyping study in ischemic stroke patients, identifying key mechanistic signatures modulated by time post-stroke, treatment, and severity. Conclusions This integrative approach aims to bridge therapeutic development with precision medicine by elucidating targetable disease mechanisms based on redefined, individual patient responses. Conflict of interest None of the authors have anything to disclose