Abstract Number: Esoc2026a1836 Identification of an in Silico-Based Network Pharmacology Therapeutic Strategy Enhancing Long-Term Stroke Recovery

Abstract Background and aims Despite extensive preclinical work during decades, effective neuroprotective interventions have not yet reached clinical practice. Here, we introduce a systems medicine computational pipeline, designed to identify mechanistically related targets underlying the stroke pathomechanism. We propose a paradigm change evaluating an in silico-based multi-target, network pharmacology intervention in a murine model of focal cerebral ischaemia. Methods Male C57BL/6N mice underwent 30 minutes of transient middle cerebral artery occlusion (tMCAO) and were randomly allocated to receive either the network pharmacology treatment (NWPT) or vehicle control. Animals were sacrificed at days 3, 7, 14, 21 or 28 post-ischaemia. Prior to tissue collection, neuromotor function was assessed, alongside complementary analyses to characterise cerebral perfusion, thrombotic events, angiogenesis and gene expression profiles. Furthermore, TLR4 and S100A9 were determined as a potential biomarker and ELISA measurements were conducted to assess the concentration in patient plasma samples ≤ 72 h post-stroke. Results NWPT administration consistently improved neurological outcomes. Additionally, cerebral perfusion as well as angiogenic parameters were altered upon treatment initiation. Transcriptomic profiling revealed enhanced expression of genes associated with neuroprotection, while marked suppression of inflammatory pathways. TLR4 and S100A9 emerged as a promising biomarker panel for identifying the patient population most likely to benefit from our therapy, supporting a personalised treatment strategy. Conclusions Our systems medicine approach yields robust neuroprotection, suppresses inflammatory signalling, while enhancing neurotransmission, and reducing thrombotic burden after ischaemia. By promoting a synergistic therapeutic response alongside the potential of already approved drugs, this strategy offers a promising path towards clinical translation. Conflict of interest All authors: none