A state of the art in LNP structural determination method is small angle neutron scattering (SANS) with contrast-variation to give information on the 3D compositional distribution of different lipids and RNA. Small angle X-ray scattering (SAXS) is used to probe the internal phase of LNPs and the interactions between RNA and ionisable lipids in the LNP core. NMR is also used to provide structural insights. The Cryo-OrbiSIMS depth profiling capability presented here is complementary to these techniques. It is a de novo approach that does not require a preconceived model, knowledge of the identity of the lipids or deuterium labelling of components. These attributes would be particularly useful in the analysis of organic nanoparticles comprising more complex component mixtures derived from natural products. This also makes it amenable to the analysis of real-world over model formulations requiring labelling. The analysis throughput can be of the order of 20 depth profiles per hour, making this compatible with high throughput LNP formulation structure-activity investigations and discovery campaigns. Recent advancements in artificial intelligence (AI) that connect lipid chemistry to in vivo performance in high throughput LNP discovery campaigns can be enhanced by incorporating insights on surface structure and composition. These advances in analytics and AI have the potential to facilitate LNP prediction based on formulation composition, which can subsequently inform in vivo efficacy and clinical effectiveness.