ReviewSeminars in liver disease2025
Integrated Patient Digital and Biomimetic Twins for Precision Medicine: A Perspective.
Review in Seminars in liver disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- MetALD Molecular Signatures: What We Know, What We Lack, and How to Move Forward Through Integrated Multi-Omics.Metabolites · 2026Review
- Artificial intelligence virtual extracellular vesicles (AIVEVs).Bioactive materials · 2026Review
- Article
- Article
- Scaling human liver microphysiological systems: implementing a higher-throughput liver acinus microphysiological system platform.Experimental biology and medicine (Maywood, N.J.) · 2026Article
- Liver Innervation in Health and Disease: Neuroimmune-Neurovascular Interface and Future Therapeutic Implications.Biomedicines · 2025Review
- Digital Twins in Translational Research and Health Care: An Anthropological Perspective.Ethics & human researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
A new paradigm for drug development and patient therapeutic strategies is required, especially for complex, heterogeneous diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD). Heterogeneity in MASLD patients is driven by genetics, various comorbidities, gut microbiota composition, lifestyle, environment, and demographics that produce multiple patient disease presentations and outcomes. Existing drug development methods have had limited success for complex, heterogeneous diseases like MASLD where only a fraction of patients respond to specific treatments, prediction of a therapeutic response is not presently possible, and the cost of the new classes of drugs is high. However, it is now possible to generate patient digital twins (PDTs) that are computational models of patients using clinomics and other "omics" data collected from patients to make various predictions, including responses to therapeutics. PDTs are then integrated with patient biomimetic twins (PBTs) that are patient-derived organoids or induced pluripotent stem cells that are then differentiated into the optimal number of organ-specific cells to produce organ experimental models. The PBTs mimic key aspects of the patient's pathophysiology, enabling predictions to be tested. In conclusion, integration of PTDs and PBTs has the potential to create a powerful precision medicine platform, yet there are challenges.
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What 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.