Experiments relying on in vitro models or on animals are the basis for cardiovascular investigation. Nowadays, significant progress has been made. The development of computational techniques in fluid dynamics together with increasing performances of hardware found a promising field of applications in the framework of cardiovascular research [1,2]. However, modelling the hemodynamics with real physiological conditions of each patient, using principles of mathematics and engineering, is still a challenge. The achievement of a supporting tool to help in clinical reasoning may help cardiologists to better manage cardiovascular diseases (CAD). Our research team used, in the past, outlet pressure profiles defined in the literature as typical boundary conditions to model blood flow in arteries [1] and not specific for each patient. The imposition of pressure profiles at the outlet boundaries means a creation of pressure gradient along the artery which is not physiologically correct and accurate when the distribution of pressure is the desired solution such the Fractional Flow Reserve (FFR). Thus, the lumped-parameters model solves this problem and was recently implemented by the research team. This model finds accurate pressures in the coronary branches based on blood flow resistance. The goal is to obtain a non-invasive computed FFR and coronary hemodynamic descriptors, on-site and minimizing costs, through a software with the most accurate conditions as possible, assuming pressure profiles specific for each patient artery and viscoelastic property of blood [2]. The validation of the software has started, comparing the invasive FFR of the patient, provided by Vila Nova de Gaia/Espinho Hospital Center (Portugal), with the obtained computed FFR. After validation with many patient-specific cases, the research team will aim to create a software for local use (hospital), allowing a comprehensive assessment of CAD in an accessible, fast, reliable and non-invasive way, as well as cost reduction in the diagnosis and therapeutic guidance of patients with CAD. [1] N. Pinho et al. Medical & Biological Engineering & Computing, 57:715-729, 2019. [2] S.I.S. Pinto et al. International Journal of Non-Linear Mechanics, 123:103477, 2020.