Evidence map›Paper›PMID 41563102›Full record

ReviewThe Biochemical journal2026

An expanded role for single-cell chemical genomics profiling in drug discovery.

Adeya Wyatt, Kevin Hoffer-Hawlik, Ross M Giglio, Elham Azizi, José L McFaline-Figueroa

Abstract readReview
In one paragraph

Review in The Biochemical journal, 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

5 authors.

Adeya WyattDepartment of Biomedical Engineering, Columbia University, New York, NY 10027, U.S.A.
Kevin Hoffer-HawlikDepartment of Biomedical Engineering, Columbia University, New York, NY 10027, U.S.A.
Ross M GiglioDepartment of Molecular Pharmacology and Therapeutics, Columbia University Medical Center, New York, NY 10032, U.S.A.
Elham AziziDepartment of Biomedical Engineering, Columbia University, New York, NY 10027, U.S.A.
José L McFaline-FigueroaDepartment of Biomedical Engineering, Columbia University, New York, NY 10027, U.S.A.ORCID 0000-0003-4387-1511

Funding

Defining gene-by-environment interactions using multiplex single-cell genomicsR35HG011941 · NHGRI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI MCFALINE-FIGUEROA, JOSE LUIS · 2021 to 2025
$2.5M
Machine learning methods for interpreting spatial multi-omics dataR01HG012875 · NHGRI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Elham Azizi · 2023 to 2026
$1.7M
Computational toolbox for spatial transcriptomic analysis of complex tissuesR21HG012639 · NHGRI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI AZIZI, ELHAM · 2023 to 2023
$435k
Allen Family Philanthropies - Paul G. Allen Frontiers Group Allen Distinguished Investigator AwardChan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation 2022-253560NHGRI NIH HHS R01 HG012875NHGRI NIH HHS R21 HG012639NHGRI NIH HHS R35 HG011941NIH HHS R01HG012875NIH HHS R21HG012639NIH HHS R35HG011941NSF 2146007
6 · The paper itself

Abstract

The integration of single-cell genomics into the chemical genetics paradigm is reshaping how researchers profile drug activity, prioritize lead candidates, and uncover new therapeutic opportunities. Traditional chemical genetic approaches, though instrumental in linking compounds to cellular phenotypes, often rely on bulk measurements that obscure important cellular heterogeneity and limit insight into mechanisms of action. By contrast, single-cell technologies offer a transformative view of how compounds influence diverse cell types and states, capturing nuanced molecular responses that further our understanding of efficacy, resistance, and polypharmacology. From cancer to neurodegenerative disorders and other disease contexts, single-cell chemical profiling enables a more precise annotation of drug-induced effects, revealing differential responses across cellular subpopulations. These methods help identify both beneficial and adverse outcomes that may not be readily predicted by a compound's structure or known targets, enhancing preclinical prioritization and supporting rational drug repurposing strategies. As these technologies mature, advances in multiplexing, multimodal profiling, and computational analysis are expanding their scalability and applicability to increasingly complex models. The resulting data-rich assays are poised to bridge critical gaps between compound screening and clinical relevance. This review highlights the evolution of chemical genomics toward single-cell resolution and outlines emerging opportunities to leverage these methods throughout the drug discovery pipeline, from early preclinical prioritization to late-stage repurposing, ultimately accelerating the development of safer, more effective therapies.

Indexed as

Drug DiscoveryGenomicsSingle-Cell AnalysisAnimalsHumansCRISPRdrug discovery and designfunctional genomicshigh-throughput screeningpharmacogenomics

Identifiers

PMID41563102
PMCPMC12905491

What OpenQuestion holds

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Registered trials

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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.