Lieu, D. K. | Search bioRxiv

bioRxiv2025

Digital Twin for the Win: Personalized Cardiac Electrophysiology

Individual variability shapes how diseases manifest, how patients respond to therapy, and how rare phenotypes arise. Conventional experimental approaches obscure variation by averaging, which limits mechanistic insight and predictive accuracy. We present a computational framework that builds digital twins of human-induced pluripotent stem cell-derived cardiomyocytes from a single optimized voltage clamp experiment. The framework depends on massive synthetic datasets comprising simulated cells that span broad ionic and electrophysiological ranges. These synthetic data make it possible to control parameters precisely, explore biological variability comprehensively, and train models beyond the limits of experimental data. A neural network trained on synthetic data then inferred biophysical parameters from experimental recordings from live cells, reproducing distinct electrophysiological features. Our study unites computational modeling, data simulation, and learning to enable scalable, precise, individualized cardiac electrophysiology modeling and can be readily extended to any electrically active cell type.

physiology↗

bioRxiv2024

Reversal of contractile defects by mediating calcium homeostasis in human mini-heart models of heart failure with preserved ejection fraction (HFpEF) leads to first-in-human gene therapy clinical trial

AimsHeart failure with preserved ejection fraction (HFpEF), is a global health problem lacking disease-modifying therapeutic options, reflecting a lack of predictive models for preclinical drug testing. Aligned with FDA Modernization Act 2.0, we aimed to create the first in vitro human-specific mini-heart models of HFpEF, and to test the efficacy of a candidate gene therapy to improve cardiac kinetics and correct the disease phenotype. Methods and ResultsHealthy human pluripotent stem cell-derived ventricular cardiomyocytes were used to bioengineer beating cardiac tissue strips and pumping cardiac chambers. When conditioned with transforming growth factor-{beta}1 and endothelin-1, these mini-heart models exhibited signature disease phenotypes of significantly elevated diastolic force and tissue stiffness, and slowed contraction and relaxation kinetics, with no significant deficit in systolic force or ejection fraction versus unconditioned controls. Bioinformatic analysis of bulk RNA sequencing data from HFpEF mini-heart models and patient ventricular samples identified downregulation of SERCA2a of the calcium signalling pathway as a key differentially expressed gene. After dosage optimization, AAV-mediated expression of SERCA2a abrogated the disease phenotype and improved the cardiac kinetics in HFpEF mini-Hearts. ConclusionsThese findings contributed to FDA approval of an ongoing first-in-human gene therapy clinical trial for HFpEF, with Fast Track designation. We conclude that such human-based disease-specific mini-heart platforms are relevant for target discovery and validation that can facilitate clinical translation of novel cardiac therapies. Translational PerspectiveHeart failure with preserved ejection fraction (HFpEF) is a significant and growing global health concern lacking disease-modifying therapeutic options, reflecting inadequate preclinical models of the disease. Aligned with FDA Modernization Act 2.0, we created the first in vitro human-specific mini-heart models of HFpEF, demonstrated phenotypic disease characteristics of elevated stiffness and slowed kinetics, showed transcriptomic consistency with HFpEF patient data, identified SERCA2a as a key downregulated gene, performed dosing titration of SERCA2a gene therapy, and showed improvement of cardiac kinetics post-treatment. The findings contributed to FDA approval of an ongoing first-in-human gene therapy clinical trial for HFpEF.

bioengineering↗