The integration of computational and experimental methodologies, including digital twins and multiscale modeling, accelerates the translation of physiological principles into novel therapeutic strategies.
Historically, physiology has evolved from observational descriptions to the rigorous dissection of mechanisms. Today, we witness another transformation where experimental and computational methodologies are no longer separate disciplines, but rather interconnected strategies that are essential for navigating the nonlinear complexity of the heart. This Special Issue represents a maturation of the ‘Physiome Project’ vision (Loewe et al.; 2025): a quantitative, multi-scale description of physiological dynamics, now spanning from the metabolic state of a crossbridge to the haemodynamic flow in a fibrillating atrium. The contributions in this collection largely stem from the Cardiac Physiome Workshop 2024 in Freiburg, Germany. There, the community gathered to discuss the bidirectional crosstalk between theoretical foundations and specific clinical challenges, such as atrial fibrillation and drug safety. Indeed, we see a broadening of the use of models, which become predictive engines capable of exploring the design of novel therapies, the assessment of clinical risks in real time, and the scaling of physiology from molecule to organ. Thus, successful physiological insights now emerge from the iterative feedback between laboratory data and mathematical reconstruction. The interdisciplinary methodological frameworks highlighting this integration have been reviewed by Yang it is a key requirement for clinical safety and efficacy. Furthermore, the integration of machine learning and bioelectronics is enhancing our ability to reconstruct cardiac structure and modulate function in real time. The adoption of automated image analysis and autonomous closed-loop systems represents a practical shift towards more responsive physiological monitoring that remains grounded in the biophysical reality of the heart as a complex multicellular network. We hope that this Special Issue serves as both a comprehensive resource for the current community and a catalyst for the next generation of researchers. By continuing to close the gap between the analogue world and its digital representation, we can ensure that cardiac physiology remains at the forefront of the quest to understand, diagnose, treat, and ultimately prevent cardiovascular disease. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. No competing interests declared. V.T.: Conception or design of the work; Drafting the work or revising it critically for important intellectual content; Final approval of the version to be published; Agreement to be accountable for all aspects of the work. A.L.: Conception or design of the work; Drafting the work or revising it critically for important intellectual content; Final approval of the version to be published; Agreement to be accountable for all aspects of the work. The Cardiac Physiome Workshop 2024 in Freiburg, Germany, was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number 539 837 774. VT was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number 403 222 702 – SFB 1381, the Cluster of Excellence ‘Centre for Integrative Biological Signalling Studies’ (CIBSS) by the DFG under Germany's Excellence Strategy – EXC-2189 – 390 939 984, by the Hans A. Krebs Medical Scientist Programme, Faculty of Medicine, University of Freiburg, and by the Baden-Württemberg Stiftung—ArrhythMEC. AL acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number 507 828 355 and by the Leibniz ScienceCampus ‘Digital Transformation of Research’ with funds from the programme ‘Strategic Networking in the Leibniz Association’.
Timmermann et al. (Fri,) conducted a editorial in Cardiovascular disease. The integration of computational and experimental methodologies, including digital twins and multiscale modeling, accelerates the translation of physiological principles into novel therapeutic strategies.