An integrated approach for the in vitro dosimetry of engineered nanomaterials: Relevant in vitro dose (RID) functions

Transcription

1 An integrated approach for the in vitro dosimetry of engineered nanomaterials: Relevant in vitro dose (RID) functions Joel Cohen, Zhaoxia Ji, Tian Xia, Philip Demokritou 1

2 Background (1 of 2) Development of cheap, accurate, and reproducible in vitro screening assays is a major goal for nano-eh&s research in the next decade 1 US National Academy of Science s Approach to Toxicity Testing in the 21 st Century 1,2 : Predictive in vitro tests that utilize toxicity pathways and mechanistic systems biology approaches High throughput screening approaches to facilitate testing of large batches of materials In vitro results to be confirmed in vivo 1. National Nanotechnology Initiative

3 Background (2 of 2) Challenges for in vitro nanotoxicology: Lack of harmonized (standardized and shared) dispersion preparation and characterization Discrepancies in the nanotoxicity literature may be lack of dosimetry considerations Administered vs delivered Mass concentration vs total surface area vs particle number Lack of tools available to take dosimetry into consideration 3

4 Integrated Approach for In Vitro Dosimetry Elements of approach: 1. Develop and use a harmonized protocol for ENM dispersion preparation 1 characterize ENM dispersion parameters which determine fate and transport in vitro: hydrodynamic diameter effective density 2 2. Utilize fate and transport numerical models for particles in suspension and estimate delivered to cells dose 3. Derive Relevant in vitro dose (RID) functions 3 as a tool for in vitro nanotoxicologists Simple mathematical functions link particle and in vitro properties to delivered dose metrics Present RID for large panel of ENMs under various cell culture conditions (mass concentration, cell culture media, well plate geometry, etc) 4. Validation of integrated approach for in vitro dosimetry with industrially relevant ENMs 1. Cohen et al Deloid and Cohen et al. in submission Cohen and Ji et al in preparation 4

5 1. ENM Dispersion Prep and Characterization: Agglomerate Diameter and Effective Density Utilize recently developed harmonized dispersion protocol 1 achieve reproducible, monodisperse, stable ENM suspensions Lack of efficient methods for measuring effective density for large panels of materials Cohen et al Deloid and Cohen et al. submitted 2013

6 1. ENM Dispersion Prep and Characterization: Harvard Volumetric Centrifugation Method (VCM) for Effective Density Features of VCM 1,2 : Fast easy to screen large panels of materials Inexpensive spin at low speeds using low cost common laboratory centrifuges Accurate >98% of particles are collected in pellet Measurements validated with gold standard AUC data Applicable for soluble and partially soluble ENMs Requires time-resolved dissolution analysis to determine M ENMsol Results significantly improve accuracy of fate and transport models r E = r media æ V pellet SF - M - M ö æ ENM ENMsol M ç + r ENM - M ENM ç ENMsol è r ENM ø è r ENM V pellet SF 1. Cohen and Deloid et al. submitted U.S. Provisional Patent Application 6 No. 61/661,895, filed June 20, 2012 ) ö ø

7 2. Model Fate and Transport of Particles In Vitro Transport of ENMs in liquid suspension determined by two fundamental transport mechanisms 1.Diffusion Stokes Einstein Equation: D = RT 3N A pmd 2.Sedimentation Stokes Law: V = g ( r - r E media )d 2 18m 7

8 2. Model Fate and Transport of Particles In Vitro Fate and transport models: In vitro sedimentation and diffusion dosimetry model (ISDD) 1 Currently available 1 dimensional numerical model Assumes homogenous conditions within cell culture well Assumes agglomerate density derived from unvalidated theoretical estimation for fractal materials Does not account mass loss and agglomerate transformations (effective density, hydrodyanamic diameter) due to dissolution over time Multidimensional computational fluid dynamics models Currently under development by our group at Harvard and others 2 Account for spatial variability of particle concentration over time Account for dynamic changes to agglomerate density, diameter and mass over time 1. Hinderliter et al Deloid et al. in preparation 8

9 3. A Tool for In Vitro Nanotoxicologists: Relevant In Vitro Dose Functions (RID) RID Function 1,2, : RID F=M,N,SA = AD i=m,n,sa *(1-e -a t ) Simple mathematical equations enable calculation as a function of exposure time (t): RID M : delivered mass (μg) RID N : delivered particle number (#) RID SA : delivered surface area (cm 2 ) 1. Cohen et al Cohen and Ji et al in preparation 9

10 3. A Tool for In Vitro Nanotoxicologists: Relevant In Vitro Dose Functions (RID) RID Function: RID F=M,N,SA = AD i=m,n,sa *(1-e -a t ) AD M =g A V Administered mass (μg): ϒ A = mass concentration (μg/ml) of ENM dispersion V= volume of ENM dispersion administered to cells Administered Dose Value: mass, particle number, surface area Administered particle number (#): r H = agglomerate radius (nm) ρ E = effective density (g/cm 3 ) AD N = æ ç è AD M 4 3 pr 3 H ö r ø e Administered surface area (cm 2 ): AD SA = ( 2 4pr ) H AD N Convert to delivered dose simply plug in ENM dispersion-specific values for: Agglomerate radius (r H ) Effective Density (ρ E ) Exposure time (t) 10 Deposition Constant (α)

11 3. A Tool for In Vitro Nanotoxicologists: Relevant In Vitro Dose Functions (RID) Deposition Constant (α) describes ENM deposition over time for a given material-mediaconcentration-cell culture well plate system Derivation of α parameter: Model particle fate and transport over time Fit data to Gompertz sigmoidal function 1,2 : f (t) =1- e -a t Apply value to RID function to estimate delivered dosimetry for any exposure duration 1. Cohen et al Cohen and Ji et al in preparation

12 4. Validation of Methodology Neutron activated flame generated industrially relevant CeO 2, SiO 2 coated CeO 2, and ZnO ENMs Gamma emitting isotope 141 Ce and 65 ZnO easy to trace and quantify by gamma spectroscopy Measured passage of agglomerates across transwell insert with 3μm pores <2% particle loss on transwell membrane easy passage across 3μm pores 12

13 4. Validation of Methodology Close agreement (within 5%) between estimated and measured delivered doses 13

14 4. Validation of Methodology: Deposition Over Time Close agreement (within 5%) between estimated and measured delivered doses 14

15 Features of Integrated Approach for In Vitro Dosimetry Versatile method for improved dosimetry Agglomerating ENMs Non-agglomerating ENMs Ambient nanoparticles Combustion generated nanoparticles Metal and metal oxide ENMs Soluble and partially soluble ENMs Requires dissolution analysis in applicable media Can be used as a platform to investigate all types of nano-bio interactions in vitro Toxicity screens Cellular uptake Translocation across cellular monolayers Blood brain barrier, alveolar epithelium, etc 15

16 Case Study: Effect of Dosimetry on Nanotoxicology for 24 ENMs Applied integrated approach for 24 metal oxide ENMs previously characterized for toxicity and hazard ranking without dosimetry considerations 1 Objectives Derive RID functions for 24 ENMs Measured hydrodynamic diameter, effective density, deposition fraction parameter (α) for various conditions 2 : Two widely used cell culture media (BEGM, DMEM) Two mass concentration ranges (0-50ug/ml and ug/ml) Two well plate systems (96 well and 384 well plates) Evaluate implications of dosimetry for in vitro nanotoxicology 1. Zhang et al Cohen and Ji et al. in progress 16

17 Case Study: How to Use RID Functions Example: SiO 2 (d BET 13nm); BEGM media; 50μg/ml; 384 well plate 17

18 Effective Density; Hydrodynamic Diameter 18

19 α, 19

20 Relevant In Vitro Dose Functions (RID) Identify: SiO 2 (d BET 13nm); BEGM media; 50μg/ml; 384 well plate Values reported from tables: d H =182nm; ρ EV =1.23g/cm 3 ; α= 0.03 hours -1 ; γ=1.25 μg t=4 hours Delivered Dose values for 4 hour exposure period: RID M = 0.105μg RIS N =2.75x10 10 particles RID SA = 28.6cm 2 20

21 Implications for In Vitro Nanotoxicology: Effective Density and Agglomeration Influence Particle Delivery to Cells Challenge: high-throughput toxicity screens must account for dosimetry and differential mobility when comparing large libraries of NPs 21 (Cohen et al. submitted 2013)

22 Implications for In Vitro Nanotoxicology: Mass Concentration Influences Particokinetics Mass concentration influences hydrodynamic diameter Changes to hydrodynamic diameter influence particle delivery to cells 22

23 Implications for In Vitro Nanotoxicology: Ranking Toxicity of ENMs BEAS-2B bronchial epithelial cells exposed to CoO (d H =234nm; ρ EV =2.39g/cm 3 ) and Co 3 O 4 (d H =185nm; ρ EV =1.37g/cm 3 ) 1,2 When particokinetics are accounted for in the reported dose: Adminstered dose overestimates by >100% for Co 3 O 4 63μg/cm 2 vs 27μg/cm 2 Dose response curves appear more similar Differences in toxicity may be attributable to different delivered doses 1. Zhang et al Cohen and Ji et al. in progress 23

24 Conclusions Accurate reporting of dosimetry may improve validity and relevance of in vitro screens RID functions provide a simple tool for nanotoxicologists to take into consideration dosimetry RID functions can be derived by following our newly developed method: Comprehensive characterization of ENM transformations in liquid Agglomeration effective density (Harvard VCM, etc) 24

25 Acknowledgements Harvard School of Public Health Center for Nanotechnology and Nanotoxicology Dr Philip Demokritou Funding Sources: NIEHS grant (ES ) Dr Glen DeLoid Dr George Pyrgiotakis Dr Ramon Molina Dr Lester Kobzik Dr Joe Brain Dr John Godleski Dr George Sotiriou Dr Christa Watson Samuel Gass NSF grant (ID: ) University of California Los Angeles Center for Environmental Implications of Nanotechnology Dr Andre Nel Dr Tian Xia Dr Zhaoxia Ji 25

26 Questions? 26