Evidence map›Paper›PMID 41550661›Full record

ReviewPharmaceutical science advances2025

The applications of single-cell multiomics in drug screening.

Qingming Xue, Hanyu Hu, Ruogu Wang, Fei Wu, Haiqing Xiong

Abstract readReview
In one paragraph

Review in Pharmaceutical science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Qingming XueState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Hanyu HuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Ruogu WangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Fei WuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Haiqing XiongState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell multiomics (scMultiomics) technologies and methods encompassing transcriptomics, genomics, epigenomics, proteomics, and metabolomics, together with associated computational tools have profoundly revolutionized disease research, enabling unprecedented dissection of cellular heterogeneity and dynamic biological responses. The use of scMultiomics technologies to study drug drug screening, actions and responses has not only unlocked novel avenues in precision drug screening but also transformed our understanding of how small molecules target specific cell types in cancer treatment, as well as their connections to disease etiology and progression from a high-resolution view of their functional diversity. In this review, we systematically explore how scMultiomics technologies develop and drive advancements in drug screening. With a specific focus on the applications in target identification, drug response, and drug resistance, we highlight how scMultiomics can link cellular-level insights with individualized drug screening, which in turn promises actionable strategies to improve therapeutic precision in drug development.

Indexed as

Drug resistanceDrug responseDrug screeningscMultiomics

Identifiers

PMID41550661
PMCPMC12710029

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.