Evidence map›Paper›PMID 41439866›Full record

ReviewBiomimetics (Basel, Switzerland)2025

Integrating New Approach Methodologies (NAMs) into Preclinical Regulatory Evaluation of Oncology Drugs.

Maryam Sadat Mirlohi, Tooba Yousefi, Amir Reza Aref, Amir Seyfoori

Abstract readReview
In one paragraph

Review in Biomimetics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. 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

4 authors.

Maryam Sadat MirlohiDepartment of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada.ORCID 0000-0001-6478-7146
Tooba YousefiDepartment of Clinical Biochemistry, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1985717413, Iran.
Amir Reza ArefMass General Cancer Center, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0002-5174-0522
Amir SeyfooriDepartment of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional animal-based preclinical models, including xenografts and genetically engineered mice, have been used for assessing pharmacodynamics, toxicity, efficacy, and safety for decades. Despite their limited ability to mimic human tumor heterogeneity, immune interactions, and microenvironmental complexity, over 90% of oncology candidates that succeed in animal studies fail in clinical trials. The New Approach Methodologies (NAMs), which include patient-derived organoids, organ-on-chip platforms, and AI-driven computational models, provide human-relevant solutions that can improve predictive validity, mechanistic insight, and ethics. Through these technologies, it will be possible to replicate tumor biology specific to patients, to support co-clinical trial designs, and to facilitate biomarker discovery while reducing animal testing. Several recent regulatory reforms, including the Food and Drug Administration (FDA) Modernization Act 2.0 and the European Medicines Agency's NAM qualification framework, have established clear pathways for the integration of validated NAMs into preclinical drug evaluation. Critically evaluating the scientific rationale, comparative performance, and regulatory context of key NAM platforms in oncology, this review highlights opportunities for synergistic integration, technical refinement, and global harmonization in order to accelerate the development of clinically effective cancer therapeutics based on preclinical findings.

Indexed as

drug developmentin vitro modelsNAMsoncology

Identifiers

PMID41439866
PMCPMC12730968

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.