Advanced computational modeling for in vitro nanomaterial dosimetry

Abstract

BackgroundAccurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Correctly and consistently quantifying what cells “see,” during an in vitro exposure requires standardized preparation of stable ENM suspensions, accurate characterizatoin of agglomerate sizes and effective densities, and predictive modeling of mass transport. Earlier transport models provided a marked improvement over administered concentration or total mass, but included assumptions that could produce sizable inaccuracies, most notably that all particles at the bottom of the well are adsorbed or taken up by cells, which would drive transport downward, resulting in overestimation of deposition.MethodsHere we present development, validation and results of two robust computational transport models. Both three-dimensional computational fluid dynamics (CFD) and a newly-developed one-dimensional Distorted Grid (DG) model were used to estimate delivered dose metrics for industry-relevant metal oxide ENMs suspended in culture media. Both models allow simultaneous modeling of full size distributions for polydisperse ENM suspensions, and provide deposition metrics as well as concentration metrics over the extent of the well. The DG model also emulates the biokinetics at the particle-cell interface using a Langmuir isotherm, governed by a user-defined dissociation constant, KD, and allows modeling of ENM dissolution over time.ResultsDose metrics predicted by the two models were in remarkably close agreement. The DG model was also validated by quantitative analysis of flash-frozen, cryosectioned columns of ENM suspensions. Results of simulations based on agglomerate size distributions differed substantially from those obtained using mean sizes. The effect of cellular adsorption on delivered dose was negligible for KD values consistent with non-specific binding (> 1 nM), whereas smaller values (≤ 1 nM) typical of specific high-affinity binding resulted in faster and eventual complete deposition of material.ConclusionsThe advanced models presented provide practical and robust tools for obtaining accurate dose metrics and concentration profiles across the well, for high-throughput screening of ENMs. The DG model allows rapid modeling that accommodates polydispersity, dissolution, and adsorption. Result of adsorption studies suggest that a reflective lower boundary condition is appropriate for modeling most in vitro ENM exposures.Electronic supplementary materialThe online version of this article (doi:10.1186/s12989-015-0109-1) contains supplementary material, which is available to authorized users.

Toxicological implications of released particulate matter during thermal decomposition of nano-enabled thermoplastics

“…This was made possible by utilizing the integrated in-vitro dosimetry platform recently developed by the authors, which enables estimation of delivered to cell dose rate as a function of exposure time (Cohen, et al, 2013; Cohen et al , 2015; DeLoid, et al, 2014; DeLoid, et al, 2015), (Pal et al , 2015a); (Palza, 2015). Using this integrated, multistep methodology, the fraction deposited of each LCPM colloid as a function of time was derived and the necessary administered concentration was adjusted across different LCPM colloids in order to bring at the same level, the delivered to cell doses across various particle systems.…”

“…The recently developed, integrated Harvard In Vitro dosimetric platform was used to convert administered LCPM doses to delivered cell doses as a function of exposure time (Cohen et al , 2014b; DeLoid et al , 2015). This method consists of two highly integrated steps: 1) LCPM dispersion preparation and characterization (described above) (Cohen, et al, 2013; Cohen et al , 2014a); and 2) use of advanced fate and transport numerical models to estimate the settling of formed agglomerates as a function of exposure time.…”

“…This method consists of two highly integrated steps: 1) LCPM dispersion preparation and characterization (described above) (Cohen, et al, 2013; Cohen et al , 2014a); and 2) use of advanced fate and transport numerical models to estimate the settling of formed agglomerates as a function of exposure time. The recently developed at Harvard Distorted Grid (DG) model was utilized (DeLoid, et al, 2015) to calculate numerically the fraction of administered particles deposited on the small airway epithelial cell surface as a function of time, f D (t), for all LCPM suspensions. The volume weighted agglomerate hydrodynamic diameter, d H , as measured by DLS, and the effective density of ENM agglomerates suspended in cell culture media, as measured by the Harvard volumetric centrifugation method (DeLoid, et al, 2014), were used as inputs to the numerical fate and transport model to calculate the concentrations at the bottom of well, fraction deposited, and the mass per surface area.…”

Preparation, characterization, and in vitro dosimetry of dispersed, engineered nanomaterials

“…This in vitro hazard and bioactivity assessment approach has been widely and successfully used for industrial and environmental chemicals, as well as for drug candidates 39,40 . However, because ENMs in suspension are subject to ENM- and media-specific physicochemical transformations that affect their fate and transport, and thus the dose delivered to cells as a function of exposure time 33,36,37,41,42 , it is not suitable for assessment of colloidal suspensions of ENMs.…”

The role of the food matrix and gastrointestinal tract in the assessment of biological properties of ingested engineered nanomaterials (iENMs): State of the science and knowledge gaps

“…Furthermore, these pristine ENMs are usually incubated a culture medium that contains serum proteins, which results in protein corona formation and agglomeration that will affect the bioactivity and biological properties of the nanoparticles (Cohen et al , 2013; Lundqvist et al , 2011; Monopoli et al , 2011b; Tenzer et al , 2013; Walkey and Chan, 2012). In addition, these simple cellular models ignore the effects of agglomeration on the mass transport and dosimetry of the iENMs, thereby resulting in erroneous and difficult to interpret dose-response data (Cohen et al , 2015; Cohen et al , 2014b; DeLoid et al , 2014; DeLoid et al , 2015). Consequently, the interfacial properties and agglomeration state of the iENMs are not physiologically relevant and may be very different from what the intestinal cells would encounter in real life.…”