Evidence map›Paper›PMID 41577171›Full record

ReviewDrug discovery today2026

Organoids in drug development: from predictive models to regulatory integration.

Xuyang Song, Xinrong Chen, Qing Chen, Hao Wang, Tao Zhang, Michael Z Liao, Chunhong Liu, Hongtao Yu, Yanning Hao, Guodong Gu and 4 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Drug discovery today, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

14 authors.

Xuyang SongDepartment of Clinical Pharmacology and DMPK, Adlai Nortye Ltd, 685 US Hwy 1, North Brunswick Township, NJ 08902, USA. Electronic address: song1927@gmail.com.
Xinrong ChenABC Toxicology Consulting, Potomac, MD 20854, USA.
Qing ChenClinical Microbiome Unit, Laboratory of Host Immunity Microbiome, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
Hao WangDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA.
Tao ZhangSchool of Pharmacy and Pharmaceutical Sciences, Binghamton University, State University of New York, PO Box 6000, Binghamton, NY 13902-6000, USA.
Michael Z LiaoThird Arc Bio, 727 Norristown Road, Building 8, Suite 320, Lower Gwynedd, PA 19002, USA.
Chunhong LiuHansoh Bio, 9900 Medical Center Drive, Suite 200, Rockville, MD 20850, USA.
Hongtao YuClinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gaithersburg, MD 20878, USA.
Yanning Hao10108 Vanderbilt Cir, Rockville, MD 20850, USA.
Guodong GuDuality Biologics, 233 Mount Airy Road, Room 182, Basking Ridge, NJ 07920, USA.
Zehua ChengDepartment of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford OX1 3QG, UK.
Zhiyao ZhuThermo Fisher Scientific, 5516 Falmouth Street, Suite 301 ABC, Richmond, VA 23230, USA.
Yongbin ZhangJoinn Laboratories, No.1 JOINN Road, Shaxi Town, Suzhou 215421, China.
Suchitra K HouriganClinical Microbiome Unit, Laboratory of Host Immunity Microbiome, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.

Funding

Understanding the role of the gut-brain axis in modulating Cadmium neurotoxicityR00ES034068 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Hao Wang · 2024 to 2026
$676k
Intramural NIH HHS Z99 AI999999NIEHS NIH HHS R00 ES034068
6 · The paper itself

Abstract

Organoids offer superior physiological relevance over traditional 2D and animal models. By recapitulating human tissue architecture, they enable predictive assessments of drug efficacy, toxicity, and pharmacokinetics (DMPK). Integrating artificial intelligence (AI)-driven modeling further expands their preclinical utility, particularly in oncology. Concurrently, regulatory agencies are establishing standards for organoid validation and qualification. In this review, we summarize current applications and discuss the scientific and regulatory requirements needed to bridge the translational gap. We emphasize that harmonized regulatory frameworks are essential to ensure scientific rigor and facilitate the broader adoption of organoid technologies in drug development.

Indexed as

Drug DevelopmentOrganoidsAnimalsArtificial IntelligenceHumansModels, Biologicalcomputational and AI-driven modelingDMPKmicro-physiological systemsorganoidsregulatory strategytoxicity assessmenttranslational research

Identifiers

PMID41577171
PMCPMC13000762

What Socratic holds

Textmetadata
LicenceTDM
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.