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

整合患者数字孪生和仿生孪生以进行精准医疗:一个视角

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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.

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