This work aims to develop a new human ventricular cardiomyocyte model, based on the O’Hara-Rudy model (ORd), to improve the inverse dependence of the action potential duration (APD) on the extracellular Ca2+ concentration ([Ca2+]o), and to set the extracellular K+ concentration ([K+]o) to the one used in vitro ([K+]o=4 mM experiments vs [K+]o=5.4 mM ORd). In addition, the new model will have to maintain all the well-reproduced properties of the original ORd model: APD rate dependence, APD restitution and current block effects. The differences between the Bartolucci2019 and ORd models are: - novel markovian formulation of the L-type Ca2+ current - markovian rapid delayed rectifier K+ current formulation published by the US Food and Drug Administration (FDA) - new formulation of the Ca2+ release from the sarcoplasmic reticulum - complete fine retuning of the model parameters. The Bartolucci2019 model is capable of simulating all the experimental data considered by ORd, with the correct [K+]o, together with a correct inverse APD-[Ca2+]o relationship. In addition to this, we used the Bartolucci2019 model as baseline to generate an experimentally-calibrated population of 1425 in silico ventricular cells, to study the occurrence of repolarization abnormalities in response to a strong IKr block: 89 models developed early after-depolarizations and 88 models failed to repolarize. We also challenged our in silico population with high rate stimulation to assess alternans occurrence, obtaining full adaptation in 897 models, 101 models developed alternans and 308 models failed to adapt to increasing pacing rate. Our results on Bartolucci2019 model indicate that we successfully improved the ORd, one of the most detailed, used and influent models in computational cardiology, by reproducing the APD-[Ca2+]o inverse relationship while keeping all the original model features tested in the appropriate experimentally-matched conditions. Furthermore, we demonstrated the Bartolucci2019 suitability as baseline for in silico population of models.