Evaluating thrombosis risk and patient-specific treatment strategy using an atherothrombosis-on-chip model.

Platelets play an essential role in thrombotic processes. Recent studies suggest a direct link between increased plasma glucose, lipids, and inflammatory cytokines with platelet activation and aggregation, resulting in an increased risk of atherothrombotic events in cardiovascular patients. Antiplatelet therapies are commonly used for the primary prevention of atherosclerosis. Transitioning from a population-based strategy to patient-specific care requires a better understanding of the risks and advantages of antiplatelet therapy for individuals. This proof-of-concept study evaluates the potential to assess an individual's risk of forming atherothrombosis using a dual-channel microfluidic model emulating multiple atherogenic factors in vitro , including high glucose, high cholesterol, and inflammatory cytokines along with stenosis vessel geometry. The model shows precise sensitivity toward increased plasma glucose, cholesterol, and tumour necrosis factor-alpha (TNF-α)-treated groups in thrombus formation. An in vivo -like dose-dependent increment in platelet aggregation is observed in different treated groups, benefiting the evaluation of thrombosis risk in the individual condition. Moreover, the model could help decide the effective dosing of aspirin in multi-factorial complexities. In the high glucose-treated group, a 50 μM dose of aspirin could significantly reduce platelet aggregation, while a 100 μM dose of aspirin was required to reduce platelet aggregation in the glucose-TNF-α-treated group, which proves the model's potentiality as a tailored tool for customised therapy.