Completed Heart, Stroke & Blood Bones, Joints & Muscles

Human in silico clinical trials in post myocardial infarction: mechanistic investigations into phenotypic electromechanical variability and response to treatment

In plain English

AI plain-English summary

Doctors cannot reliably predict which heart attack survivors will suffer a fatal arrhythmia or develop heart failure, because the standard risk marker—ejection fraction—misses many high-risk patients and wrongly flags others. This project builds thousands of personalised computer models of damaged human hearts, simulating both electrical and mechanical behaviour from the level of individual ion channels up to the whole organ. By running virtual clinical trials on these models, the researcher aims to identify the specific electromechanical mechanisms that determine why two patients with similar damage can have completely different outcomes. If successful, the work could transform how clinicians stratify risk after a heart attack, replacing a single crude measurement with a detailed, patient-specific profile that predicts both arrhythmic danger and mechanical decline. This would allow doctors to target expensive treatments—such as implantable defibrillators or drugs that modify heart contraction—only to those who will actually benefit, while sparing low-risk patients from unnecessary procedures. The approach also offers a platform for testing new pharmacological interventions in silico before moving to human trials, potentially accelerating drug development for post-infarction care.

View original technical description
The population of patients with ventricular damage following survival of myocardial infarction (MI) is rising, owing to the increased prevalence of coronary artery disease and improvements in treatment. Post-MI patients suffer from permanent myocardial damage, and this increases risk of sudden death and cardiac mechanical dysfunction, with potential progression to heart failure. Arrhythmic risk stratification is conducted using ventricular ejection fraction, a mechanical marker. However, a significant number of sudden deaths occur in patients with relatively preserved ejection fraction, and patients with low ejection fraction often do not experience serious arrhythmic events. In this Fellowship, I propose to unravel key mechanisms explaining phenotypic variability in post-MI, focusing on the interplay between electrophysiological and mechanical ventricular abnormalities, and their modulation by pharmacological interventions. I propose a Systems Biomedicine approach based on human ventricular computer modelling and simulation of coupled mechanical and electrophysiological function, in iteration with experimental and clinical studies. We will construct populations of thousands of human ventricular electromechanical post-MI models from ionic to whole-organ dynamics, calibrated and validated using rich experimental and clinical datasets. We will conduct in silico clinical trials to dissect key factors determining arrhythmic risk and degree of mechanical dysfunction post-MI, and effects of pharmacological interventions.

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Researchers

Rodriguez (EPMC Awardee)

Related Research

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Original classification

Senior Research Fellowship Renewal

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