Drug-delivery systems based on polymeric nanoparticles are useful for improving drug bioavailability and/or delivery of the active ingredient for example directly to the cancerous tumour. The physical and chemical characterization of a functionalized nanoparticle system is required to measure drug loading and dispersion but also to understand and model the rate and extent of drug release to help predict performance. Many techniques can be used, however, difficulties related to structure determination and identifying the precise location of the drug fraction make mathematical prediction complex and in many published examples the final conclusions are based on assumptions regarding an expected structure. Cryogenic scanning transmission electron microscopy imaging in combination with electron energy loss spectroscopy techniques are used here to address this issue and provide a multi-modal approach to the characterisation of a self-assembled polymeric nanoparticle system based upon a polylactic acid - polyethylene glycol (PLA-PEG) block copolymer containing a hydrophobic ion-pair between pamoic acid and an active pharmaceutical ingredient (API). Results indicate a regular dispersion of spherical nanoparticles of 88 ± 9 nm diameter. The particles are shown to have a multi-layer structure consisting of a 25 nm radius hydrophobic core of PLA and pamoic acid-API material with additional enrichment of the pamoic acid-API material within the inner core (that can be off-centre), surrounded by a 9 nm dense PLA-PEG layer all with a low-density PEG surface coating of around 10 nm thickness. This structure suggests that release of the API can only occur by diffusion through or degradation of the dense, 9 nm thick PLA-PEG layer either of which is a process consistent with the previously reported steady release kinetics of the API and counter ion from these nanoparticle formulations. Establishing accurate measures of product structure enables a link to performance by providing appropriate physical parameters for future mathematical modelling of barriers controlling API release in these nanoparticle formulations.