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

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d1196912e185">Despite decades of translational research, translational stroke research has yield to no neuroprotective therapy. One major limitation is the remain focus on single-drug, single-target approaches, whilst we know that complex diseases are defined by multitarget modules which should be tackled simultaneously using integrative therapeutic strategies. Here, we propose a network-based approach for multi-target identification using human disease-associated genes linked to ischemic stroke, combined with a network pharmacology, drug repurposing strategy. Upon stroke, we validated an acute, in silico-based network pharmacology therapy in a preclinical stroke model, improving stroke outcome 24h after the ischemic event. To assess clinical safety, a triple drug combination of marketed drugs was repurposed and administered to healthy volunteers in a Phase I clinical trial followed by a Phase IIa study currently under evaluation. Beyond therapeutic innovation, understanding the systemic immune response post-stroke is critical for improving patient recovery. Therefore, a deep characterization of the blood systemic communication could reveal novel pathophysiological signatures given the tightly regulated immune response post-stroke. Circulating peripheral blood mononuclear cells (PBMCs) could, in fact, play a central role in mediating systemic inflammation, and thereby increasing the risk of secondary ischemic events and poor recovery. Due to their capacity to reflect broad systemic and dynamic changes, PBMCs could serve as a valuable alternative for biomarker discovery, offering the potential to cluster patients based on their molecular signatures. To explore this, we conducted the first in-depth comprehensive immunophenotyping study of PBMCs in ischemic stroke patients (CITE-sequencing) aiming to identify key mechanistic signatures modulated by the i) time after stroke, ii) treatment administered, iii) patient age, and iv) stroke severity. This integrative approach aims to bridge therapeutic development with precision medicine by elucidating targetable disease mechanisms based on redefined, individual patient responses.