ArticleMicrosystems & nanoengineering2026
High-throughput combinatorial screening of antiplatelet drugs for personalized medicine.
Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
10 authors.
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Abstract
Cardiovascular disease (CVD) remains the leading cause of death worldwide. Platelet activation plays a critical role in arterial thrombotic events such as myocardial infarction. Although antiplatelet drugs are standard therapies, they are associated with risks including bleeding, gastrointestinal adverse effects, and drug resistance. Furthermore, substantial inter-individual variability in patient responses underscores the need for personalized antiplatelet regimens. These factors emphasize the importance of screening for optimal antiplatelet drugs and drug combinations tailored to individual patients. However, traditional platelet detection assays are reagent-hungry and low-throughput, making them unsuitable for high-throughput screening of antiplatelet agents. Here, we present the C-chip, a high-throughput platform for on-chip parallel screening of antiplatelet drug combinations. The C-chip miniaturizes individual screening reactions into picoliter-volume, color-coded droplets, enabling the generation of thousands of screening data points in a single experiment. We demonstrate that the C-chip can effectively identify the optimal combinations of three clinically relevant antiplatelet drugs: Aspirin, Tirofiban, and Ticagrelor. We further applied this platform to identify optimal drug combinations for five healthy volunteers, revealing marked inter-individual variability in antiplatelet drug responses.
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Registered trials
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