Probabilistic clinical studies and deterministic physiology: building a Monte Carlo bridge with the "Frank" project.

Authors

Felipe Coelho Argolo, Arthur Vasconcelos de Luna Freire, Larrie Rabelo Laporte, Guilherme Moreira Magnavita, Luís Cláudio Lemos Correia

Published in

Einstein (Sao Paulo, Brazil). Volume 24. Issue spe1. Pages eAE2239. Epub Oct 19, 2026.

Abstract

To resolve the apparent paradox between deterministic physiological laws and probabilistic clinical outcomes by framing clinical variability as epistemic uncertainty within a complex, non-linear system, demonstrating how deterministic mechanisms can account for empirical distributions and outcome heterogeneity.
We developed the "Frank" project, a 0-dimensional computational agent-based model (ABM) of human cardiovascular hemodynamics implemented in Julia (Agents.jl). Using Monte Carlo simulations (n=100), myocardial infarction was modeled by varying initial conditions, specifically sampling the infarction area from a Gaussian distribution along with systemic compliance. Cardiogenic shock was defined by a systolic arterial pressure <90mmHg and a cardiac index <2.2L/min/m2, with parameters evaluated via grid search against literature incidence benchmarks (5-10%).
The simulation produced hemodynamically stable, physiologically sound boundary parameters and pressure-volume loops. When initialized with a mean infarction area of 35±5% and systemic compliance of 1.5±0.3mL/mmHg, the model yielded a 7\% incidence of cardiogenic shock, closely matching empirical data. A strong linear inverse correlation was observed between infarction area and post-infarction systolic blood pressure (mean 93.96mmHg).
Stochastic-appearing clinical trial outcomes can emerge from deterministic physiological systems characterized by sensitivity to initial parameters and hidden variables. The "Frank" framework establishes a Monte Carlo bridge between mechanistic physiology and epidemiological statistics, offering an approach to explore outcome heterogeneity and refine clinical trial interpretation and patient stratification.

PMID:
42912034
Bibliographic data and abstract were imported from PubMed on 24 Oct 2026.

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