This thesis concerns the development of new Nuclear Magnetic Resonance (NMR) methods for the analysis of complex systems such as mixtures and large carbohydrates. In both cases signal overlap in proton spectra is often problematic, hindering access to the information contained within a spectrum. Here, multiple methods are proposed to gain access to such information and simplify analysis. Diffusion experiments have become popular in the analysis of complex mixtures, allowing distinction between subspectra of individual components. However, these experiments are only feasible in cases of relatively well-resolved signals and large differences in diffusion rates between the components of a mixture. This work overcomes these limitations by exploiting different physical properties of nuclei such as relaxation and chemical shift evolution. Encoding 1H spin systems with the relaxation and/or chemical shift properties of 19F nuclei is shown to be useful in the analysis of mixtures with similar chemical structures such as fluorocorticosteroids and fluorosugars. In the worst cases of signal overlap, the effects of scalar couplings on spectra can be suppressed by using pure shift methods, achieving an order of magnitude increase in resolution. Combining pure shift methods with relaxation encoding is shown to be powerful in the analysis of mixtures of monosaccharides, allowing distinction between individual subspectra despite severe 1H spectral overlap. In addition, an efficient workflow is developed for the analysis of oligosaccharides. This workflow combines pure shift methods and automatic peak-picking routines with computational approaches to propose structural assignments for oligosaccharides, thus aiding in their analysis. The potential issue of low sensitivity when analysing fluorinated molecules present at low concentrations is overcome by sharing the significant hyperpolarisation of 19F nuclei, achieved by photo-chemically induced dynamic nuclear polarisation (photo-CIDNP), across multiple 1H nuclei.