This project aims to investigate the interactions between blood plasma proteins and therapeutic nanoparticle agents. Their interaction has been scarcely documented in the past, yet remains poorly understood and their interacting structures are yet to be elucidated. Achieving this would represent a significant advancement towards nanoparticle-targeted therapeutics and give us insight into designing inhibitory medications against conditions such as deep-vein thrombosis, ischemic strokes and Alzheimers disease. The interaction between nanoparticles and immune system plasma proteins are typically regarded as transient and non-specific. While this is beneficial for normal bodily function, it poses challenges for cryo-EM data processing. From initial screening experiments, our micrographs display pure and homogenous particle distribution, however with heterogenous protein conformations due to the non-specific interactions with the nanoparticles. Standard EM processing software is inadequate to resolve these natural sample properties, therefore we further aim to employ neural network machine learning software, such as CryoDRGN, to assist with density map construction of heterogenous particles. Due to the novel and frontier research, simply revealing the interacting nanoparticle-plasma protein structures will be sufficient for an initial publication in a high impact journal. However, the field is extremely active, and we are thus hoping to expedite progress by gaining quick access to the world-class computational and data storage resources at Tetralith.