AI-integrated human-relevant alternatives to animal experimentation in drug development: Toward a predictive translational ecosystem, from in vitro and in silico models to clinical and real-world evidence.
- DOI
- 10.1177/02611929261492225
- Published
- 2026 Sep 25
- Container
- Alternatives to laboratory animals : ATLA
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1177/02611929261492225,
title = {AI-integrated human-relevant alternatives to animal experimentation in drug development: Toward a predictive translational ecosystem, from in vitro and in silico models to clinical and real-world evidence.},
author = {Amale PN and Tiwari DH},
year = {2026},
journal = {Alternatives to laboratory animals : ATLA},
doi = {10.1177/02611929261492225},
url = {https://doi.org/10.1177/02611929261492225}
}RIS
TY - JOUR TI - AI-integrated human-relevant alternatives to animal experimentation in drug development: Toward a predictive translational ecosystem, from in vitro and in silico models to clinical and real-world evidence. AU - Amale PN AU - Tiwari DH PY - 2026 JO - Alternatives to laboratory animals : ATLA DO - 10.1177/02611929261492225 UR - https://doi.org/10.1177/02611929261492225 ER -
APA
PN, A., & DH, T. (2026). AI-integrated human-relevant alternatives to animal experimentation in drug development: Toward a predictive translational ecosystem, from in vitro and in silico models to clinical and real-world evidence.. Alternatives to laboratory animals : ATLA. https://doi.org/10.1177/02611929261492225
Source records
- pubmed · retrieved 2026-09-25T18:15:40.250Z