Research in radiotherapy for cancer treatment focuses on finding methods that can improve the compromise between tumour cell inactivation versus damage to the surrounding healthy tissue. As new radiation modalities such as proton therapy become accessible for everyday clinical practice, a better understanding of the variation in biological response of the tumour and healthy tissues would improve treatment planning to achieve optimal outcome. The development of radiobiological models capable of accurate predictions of biological effectiveness is needed. Existing radiation quality descriptors such as absorbed dose and LET are insufficient to explain variation in biological effectiveness for different treatment modalities. The stochastic nature of ionizing radiation creates discrete patterns of energy deposition (ED) sites which can now be analysed through sophisticated computer simulations (e.g. Monte Carlo track structure codes). This opens the possibility to develop a nanometre characterization of radiation quality based on the spatial cluster patterns of ED. The aim of this thesis is to investigate the track structure (ED spatial pattern) properties of several radiation qualities at a micro- and nanometric scale while exploring their influence in biological response through correlations with published experimental data. This work uses track structure data simulated for a set of 15 different radiation qualities: 4 commonly used brachytherapy sources, 6 different proton energies, 4 different carbon ion energies, and 60Co photons used as reference radiation for quantification of biological effectiveness. At a micrometre level, the behaviour of the microdosimetric spread in energy deposition for target sizes of the order of cell nuclei was analysed. The degree of the influence it had in the biological response was found to be negligible for photon sources but for protons and carbon ions the impact increased with decreasing particle energy suggesting it may be a confounding factor in biological response. Finally, this thesis outlines a framework for modelling the relative biological effectiveness based on the frequency distribution of cluster order as a surrogate for the nanometre classification for the physical properties of radiation quality. The results indicate that this frequency is a valuable descriptor of ionizing radiation. The positive correlation across the different types of ionizing radiation encourages further development of the framework by incorporating the behavior of the microdosimetric spread and expanding tests to other experimental datasets.