ArticleNature biotechnology2026
Digital twins of ex vivo human lungs enable accurate and personalized evaluation of therapeutic efficacy.
Article in Nature biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
Digital twins are an emerging concept in healthcare that envisions integration of molecular, physiological, functional and clinical data to create computational models of biological systems such as cells, organs and individuals. However, the lack of large, multimodal datasets has so far precluded the realization of comprehensive digital twins in medicine. Ex vivo lung perfusion (EVLP) allows the study of human lungs outside the body under physiological conditions and generates multimodal data from imaging, physiologic monitoring and molecular assays. Here we report lung digital twins developed from the largest known clinical EVLP dataset. We show that the digital twin framework accurately models >75 parameters spanning lung physiology, biochemistry, radiography, transcriptomics, metabolomics and proteomics. Furthermore, direct comparison to experimental data on EVLP lungs treated with alteplase demonstrates that digital twins can precisely assess therapeutic efficacy. Together, these results establish human lung digital twins developed using EVLP as a data-rich approach to improve the evaluation of therapeutic effects.
Identifiers
42082790What OpenQuestion holds
Registered trials
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.