A cross-species drug-discovery platform to accelerate the identification of lifespan-extending interventions

Perez K, Schoenfeldt L, Phelps GB, Parras A, Morin J, Pinto C, Guilmot S, Oliveira T, Silveira M, Dolfi L, Ocampo A · 2026 · Cell Reports · Atlas ID PEREZ2026

What this study shows

An integrated high-throughput lifespan-screening platform spanning yeast, nematodes, flies, killifish and mice, evaluating >400 compounds across thousands of conditions using automated imaging and deep-learning death detection. Cross-species integration identifies geroprotectors active in multiple species and shows convergence on known and novel conserved longevity pathways. Methodological infrastructure for the question the Atlas keeps running into: which single-species lifespan results actually generalise. Note the abstract does not name individual hit compounds, so the specific standing of rapamycin/mTOR in this screen cannot be read off the abstract alone.

Abstract

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We develop an integrated, high-throughput platform to evaluate pharmacological lifespan-extending interventions across five model organisms spanning unicellular to mammalian biology including yeast, nematodes, fruit flies, killifish, and mice. By combining automated imaging, miniaturized assays, and deep-learning-based death detection, we evaluate over 400 compounds across thousands of conditions. In S. cerevisiae, a miniaturized PI/flow cytometry CLS assay enables scalable screening and identifies key assay confounders, while in C. elegans and D.

Read the full abstract on PubMed →

At a glance

Evidence type	A Animal model Marked A because it is an animal intervention or observation study measuring an organismal outcome (model: Five model organisms: S. cerevisiae, C. elegans, D. melanogaster, killifish, mice); the code names the system studied -- animal work can be rigorous and still not be human data.
Study type	4 - Animal Study
Model system	Five model organisms: S. cerevisiae, C. elegans, D. melanogaster, killifish, mice
Journal	Cell Reports
Year	2026
Peer reviewed	Yes
Record last updated	2026-10-01
Source	DOI 10.1016/j.celrep.2026.117897 · PMID 42671914

Extracted findings

These fields were extracted from the paper with AI assistance and have not been checked against the source. Read them as a pointer into the paper, not as curated claims; where they disagree with the curated summary above, the curated summary stands.

Intervention	>400 small-molecule compounds screened for lifespan extension
Target	Conserved longevity pathways (cross-species geroprotector screen)
Model	Yeast, C. elegans, D. melanogaster, killifish, mouse
Effect	Cross-species screening identifies multi-species geroprotectors and reveals convergence on conserved longevity pathways

In the Atlas

Cite this paper

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Perez, K., Schoenfeldt, L., Phelps, G. B., Parras, A., Morin, J., Pinto, C., Guilmot, S., Oliveira, T., Silveira, M., Dolfi, L., & Ocampo, A. (2026). A cross-species drug-discovery platform to accelerate the identification of lifespan-extending interventions. Cell Reports. https://doi.org/10.1016/j.celrep.2026.117897

@article{PEREZ2026,
  author       = {Perez, K. and Schoenfeldt, L. and Phelps, G. B. and Parras, A. and Morin, J. and Pinto, C. and Guilmot, S. and Oliveira, T. and Silveira, M. and Dolfi, L. and Ocampo, A.},
  title        = {{A cross-species drug-discovery platform to accelerate the identification of lifespan-extending interventions}},
  journal      = {Cell Reports},
  year         = {2026},
  doi          = {10.1016/j.celrep.2026.117897},
  note         = {PMID: 42671914},
}

Cite this Atlas record

The record is the Atlas's own work — the evidence label, the extracted findings and the links. It is cited as part of the dataset, not as the paper.

Barton, O. (2026). Oliver's mTOR Atlas (record PEREZ2026) [Data set]. https://mtor-atlas.org/study/PEREZ2026/ · Dataset DOI 10.5281/zenodo.22059963

@misc{atlas_PEREZ2026,
  author       = {Barton, Oliver},
  title        = {{Oliver's mTOR Atlas}, record PEREZ2026},
  howpublished = {Data set},
  year         = {2026},
  url          = {https://mtor-atlas.org/study/PEREZ2026/},
  doi          = {10.5281/zenodo.22059963}
}

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