480572 A Monte Carlo Model of Nanomaterial Toxicity
Monday, November 14, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Extended Abstract: File Not Uploaded
In the field of nanomedicne, tumor imaging agents such as quantum dots are introduced into the body by injecting metamaterials into the blood stream. In many cases, however, the kidney and liver will collect these nanomaterials and aggregate them preventing them from being removed from the body and increasing nanomaterial toxicity.
On the other hand, a vast majority of nanomaterials are removed through the kidneys; therefore, if we can prevent the nanoparticles that collect in the kidney from aggregating we can remove them from the body quickly and dramatically reduce their cytotoxicity. Previous strategies for optimizing the removal of nanoparticles have focused on “size optimization” or restricting the size of the particles to be less than 5.5nm. However, recent studies indicate that toxicity and removability depend more on seemingly irrelevant factors like shape, charge, bonding strength and a multitude of other variables. Although there is a lot of experimental data on nanomaterial toxicity, the sporadic dispersion of toxicity levels that depend on a variety of variables has created a high demand for an all-inclusive model to predict the toxicity of novel nanomaterials without expensive testing. This is epically important due to the nature of nanomaterials research, which frequently experiments with new compounds and structures.
Ideally, density functional theory can provide the most accurate model of nanomaterial toxicity, but the computational expense of this modeling technique encourages us to simplify the simulation using molecular dynamics. We can accomplish this by using density functional theory to characterize the chemical interactions between the nanomaterials and the body but then using molecular dynamics to account for size and shape. The randomness of the interactions between the nanomaterials and the cell membranes will be best captured though a Monte Carlo model.
Through using a Monte Carlo model of hard-spheres we have been able to show that nanomaterials are less likely to aggregate near the membranes of kidney cells. The implications of this experiment will act as a guide for developing clinically applicable nanomaterials and be included in the overall toxicity model that will unleash the medical capabilities of nanotechnology.