We are excited to announce that several SMASH-HCM partners will attend the Virtual Physiological Human (VPH 2026) conference and present project findings. We have a booth to present the SMASH-HCM project and answer questions. The conference is taking place 1–4 September in Milan, Italy. Additionally, our project partners will hold presentations and showcase posters.
There will be three presentations by Mark van Gils, Jari Hyttinen, and Marion Taconné:
Mark van Gils will present on “An Integrated Decision Support System for Hypertrophic Cardiomyopathy Disease Management.” As part of SMASH-HCM a decision support system (DSS) for hypertrophic cardiomyopathy (HCM) was developed. The DSS was co-created with healthcare professionals from three countries and combines multimodal patient data, mechanistic models and data-driven models within a digital twin platform. Its interface allows clinicians to explore signal, imaging and health record data alongside risk predictions and HCM management recommendations.
The next steps before clinical validation are further development to extend functionality with genetic data integration, patient similarity exploration, clustering visualisation, and explainable AI.
His presentation will take place Thursday 03.09.2026 at 9:18-9:30.
Jari Hyttinen will present the work of SMASH-HCM on developing a digital twin platform that integrates data and models across multiple biological scales. The SMASH-HCM approach brings together in-vitro and in-silico models, clinical data, ECG and genetic information, explainable AI to support deeper patient phenotyping, improved risk stratification and more personalised disease management. The models range from the cellular level to the whole heart and cardiovascular system. These are integrated into a three-level decision support solution designed to support both clinical decision making and patient self-management.
The work shows how multiscale digital twins could contribute to an improved and more individualized understanding of HCM, potentially providing the building blocks for similar approaches in other cardiovascular diseases.
Jari Hyttinen’s presentation will take place Thursday 03.09.2026 at 9:30-9:42.
Marion TACONNÉ will present work on a patient-specific digital twin for risk stratification in HCM, which is a collaboration between the SMASH-HCM partners from Politecnico di Milano and Tampere University. The study introduces an explainable AI-based clinical decision support system that combines multimodal patient data with machine learning to provide personalised and transparent risk predictions. Developed using data from more than 1,200 patients and externally validated in an independent cohort, the approach outperformed the conventional ESC risk score and showed that it could also track changes in individual patients’ risk over time.
By combining machine learning with explainable visualisations, the system aims to make AI-supported HCM risk assessment more interpretable and applicable in clinical practice.
Her presentation is taking place on Friday 04.09.2026 at 9:24-9:36.
There will be three posters presentations by Arthur Ben-Tolila, Nicole Anderton, and Olli Ylinen:
Arthur BEN-TOLILA will present on fast high-fidelity neural network surrogate for inference of a cardiovascular-baroreflex model. The team developed a fast multi-output machine learning surrogate to overcome the high computational demands of a detailed cardiovascular model used to study hypertrophic cardiomyopathy. The surrogate can rapidly predict 150 HCM-relevant physiological features from hundreds of model parameters while maintaining high accuracy and preserving the behaviour of the original simulator.
His poster slot is 11:00-13:00 on the 2nd of September, with a short presentation at 10:24.
Nicole Anderton will be presenting one poster that focuses on the development of a population of computational smooth muscle cell models that captures the biological variability observed in real vascular tissue. In doing this we provide a more realistic framework for studying vascular function. We further demonstrate how the population can be used to investigate the effects of L-type calcium channel blocker drugs across different virtual cells.
Her poster slot is 8:30-10:30 AM on the 3rd of September, with a short presentation at 12:45.
Olli Ylinen‘s poster will will present the work devevloped in SMASH-HCM on a machine learning surrogate model for human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CM). The model can accurately estimate key electrophysiological and contractile response while reducing computation time by around 1,000-fold on a CPU. This approach shows that large-scale in silico studies, including drug and disease modelling, and population modelling could be made considerably faster and more efficient.
His poster slot is 8:30-10:30 AM on the 3rd of September, with a short presentation at 10:24.
If you are attending the conference feel free to reach out to our project partners and connect!
You can find the detailed conference programme and presentation abstracts here: https://www.conftool.com/vph2026/sessions.php