Each year, hundreds of thousands of patients undergo cardiovascular procedures that are planned using medical imaging. These images capture anatomy, but cannot predict how the chosen device will actually interact with blood flow in an individual patient's heart.
This limitation is becoming a major challenge for both patient selection and treatment selection. Today, one question matters more than ever:What quality of life can we offer our patients?
Today's planning tools aren't designed to answer that question, and SciFluid's predictive models are precisely built to fill that gap, by transforming medical images into predictive insights for clinicians.
Turning medical imaging into patient‑specific predictions.
SciFluid is a French deeptech company working at the intersection of engineering and medicine. Born from pioneering research in high-fidelity predictive simulation at the M2P2 laboratory of Aix Marseille University, SciFluid develops patient-specific predictive technologies to help physicians and medical device companies better understand, anticipate, and optimize medical device performance and cardiac interventions.
Our technology combines patient-specific digital twins, advanced multiphysics simulation, and explainable AI to reproduce cardiac biomechanics and blood flow with high fidelity.
We develop clinical decision support software that enables heart teams to simulate and compare multiple treatment scenarios before intervention. Our predictive models go beyond conventional imaging and planning tools by estimating the physiological impact of each treatment option before the procedure. The technology is currently in active development and validation, ahead of coming regulatory clearance.
We help medical device companies optimize cardiovascular devices through high-fidelity computational simulation, including heart valves prostheses, ventricular assist devices, stents, and more. Our platform accelerates R&D by enabling faster iteration across a wider range of designs than bench or animal testing alone, while generating complementary in-silico data. We also support regulatory submissions by providing quantitative evidence aligned with FDA, CE, ISO, and ASME V&V40 expectations.
SciFluid was born from years of academic research in high-fidelity computational simulation and a shared ambition to bring predictive technologies into everyday cardiovascular care. We are a complementary co-founder team committed to delivering a technology that can truly support clinical decision-making and accelerate device innovation.
Medical device companies, clinicians, researchers, investors: interested in collaborating with SciFluid? You can contact us at:
SciFluid is growing rapidly, and so is this website. More content, demonstrations, and clinical updates are coming soon.
