The number of facilities that offer tumor treatment with particle therapy has been increasing substantially over the past decades. The dose distribution deposited by ions, and for the heaviest, their higher biological effectiveness, make them more interesting to destroy localized tumors while sparing healthy tissues. Such an effectiveness is quantified through the RBE (relative biological effectiveness), which is a complex function of multiple parameters like cell line, cell cycle stage, radiation quality and irradiation conditions. Therefore, determining the value of RBE for every scenario is a challenging task that requires modeling to comply with the demands of a clinical environment. Several solutions have already been developed and a few are currently used in treatment planning [1-4]. Nevertheless, despite the progress these models have allowed, they present some shortcomings [5-7] that may limit their improvement. We present thereby a new approach that gathers some principles of the existing ones and addresses some of their weaknesses. The innovative features of NanoxTM are that it is fully based on statistical physics, taking in particular into account the fluctuations in energy deposition at multiple scales, and that it introduces the concept of a chemical dose. The latter is chosen as a parameter defined at the cell scale to represent the induction of cell death by “non-local” events as the accumulation of cellular oxidative stress or sublethal lesions induced by the produced radical species. Such “non-local” events are complementary to the so-called “local” events, which take place at a very localized (nanometric) scale. The “local” events are considered as lethal since a single event can cause cell death. The cell survival predicted by NanoxTM for V79 cell line was compared with experimental results for photons, protons and carbon ions, and even others like neon and argon ions. A good agreement was found in all cases. In particular, the model is able to describe the effectiveness of ions, including the overkill effect at higher LET values. Moreover, NanoxTM can reproduce the typical shoulder in cell survival curves. This was possible due to the introduction of the “non-local” events, through the chemical dose, which varies with LET. It is worthwhile to note that such results were obtained through the adjustment of a reduced number of free parameters. The first results of NanoxTM, obtained for V79 cell line, give us confidence that this model has potential for application in a clinical scenario in the context of particle therapy. Although it requires the tuning of only a few free parameters, NanoxTM is based on solid principles and a thorough mathematical implementation, which renders this approach simple but reliable for application in clinical practice.