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Open Access
CC BY 4.0 · Semin Liver Dis
DOI: 10.1055/a-2649-1560
Review Article

Integrated Patient Digital and Biomimetic Twins for Precision Medicine: A Perspective

Mark T. Miedel
1   Department of Pharmacology and Chemical Biology, Organ Pathobiology and Therapeutics Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
,
Mark E. Schurdak
2   Department of Computational and Systems Biology, Organ Pathobiology and Therapeutics Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
,
Andrew M. Stern
2   Department of Computational and Systems Biology, Organ Pathobiology and Therapeutics Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
,
Alejandro Soto-Gutierrez   *
3   Department of Pathology, Center for Transcriptional Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
,
Eric von Strobl   *
4   Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
,
Jaideep Behari   *
5   Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
,
D. Lansing Taylor   *
2   Department of Computational and Systems Biology, Organ Pathobiology and Therapeutics Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
› Institutsangaben
Funding We would like to acknowledge the following grants from the National Institutes of Health: 5UG3TR003289-02 (D.L. Taylor, J. Behari, A. Soto-Gutierrez), S10OD12269 (D.L. Taylor), 5RO1DK135606-02 (M. Miedel and A. Soto-Gutierrez), 4UH3TR004124-04 (M. Miedel), Pittsburgh Liver Research Center- (P30DK120531-06 (Monga), 1U2CTR004863-01 (D.L. Taylor, M.E. Schurdak, M. Miedel, A. Soto-Gutierrez, L. Vernetti), U24TR002632 (D.L. Taylor, M.E. Schurdak, A. Gough), 5R01CA255809 (J. Behari). We would also like to acknowledge research support from the following companies: Simulations Plus with an SBIR for predicting liver injury from biologics in our human liver MPS.
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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.

Keywords

patient digital twins - patient biomimetic twins - precision medicine - organoids - induced pluripotent stem cells - microphysiological systems - pathophysiology of complex diseases - biomarker discovery

* Co-Senior Authors.


Supplementary Material



Publikationsverlauf

Accepted Manuscript online:
04. Juli 2025

Artikel online veröffentlicht:
23. Juli 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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