Evidence map›Paper›PMID 41476049›Full record

ArticleMicrosystems & nanoengineering2026

High-throughput combinatorial screening of antiplatelet drugs for personalized medicine.

Chenguang Wang, Wenjie Zhu, Jiawei Zhu, Tian Gao, Zheyi Jiang, Tiantian Zhang, Long Chen, Junfeng Zhang, Yifan Liu, Alex Chia Yu Chang

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Chenguang Wang *Department of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200011, Shanghai, China.
Wenjie Zhu *School of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
Jiawei ZhuSchool of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
Tian GaoSchool of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
Zheyi JiangDepartment of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200011, Shanghai, China.
Tiantian ZhangDepartment of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200011, Shanghai, China.
Long ChenSchool of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
Junfeng ZhangDepartment of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200011, Shanghai, China. zhangjf1222@sjtu.edu.cn.
Yifan LiuSchool of Physical Science and Technology, ShanghaiTech University, 201210, Shanghai, China. liuyf6@shanghaitech.edu.cn.ORCID http://orcid.org/0000-0002-2989-6280
Alex Chia Yu ChangDepartment of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 200011, Shanghai, China. alexchang@shsmu.edu.cn.ORCID http://orcid.org/0000-0001-9441-4033

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID41476049
PMCPMC12756261

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.