Holographic Characterization of Protein Aggregates Size, morphology - PowerPoint PPT Presentation

Holographic Characterization of Protein Aggregates Size, morphology and differentiation … one particle at a time (and fast) D. G. Grier, C. Wang, X. Zhong, & M. D. Ward New York University D. B. Ruffner & L. A. Philips Spheryx, Inc

Holographic Characterization Particle-resolved measurements of  Radius: subvisible range 200 nm to 10 m m  Refractive index: proxy for composition Useful for differentiation  Morphology Useful for differentiation Useful for analyzing aggregation mechanism  Concentration Divide observed counts by measured sample volume  Real-time processes 30 measurements/second Complete analysis in 10 minutes 2 2016 UMB-CERSI

So, what’s the problem? 3 2016 UMB-CERSI

Conventional Characterization (DLS) 40 PDMS spheres in water 0 500 1000 Malvern Zetasizer Nano ZS 4 2016 UMB-CERSI

Holographic Characterization 1.42 1.0 Relative Probability 1.41 Refractive Index 1.40 0.5 1.39 5,000 spheres one sphere 1.38 1.37 0 0.4 0.6 0.8 1.0 1.2 Radius Wang, et al. , Soft Matter 11 , 1062 (2015) 5 2016 UMB-CERSI

Holographic Tracking & Characterization Lorenz-Mie Microscopy Parameters 3D Position 𝒔 𝑞 (𝑢) Tracking 𝑏 𝑞 Radius Characterization Refractive Index 𝑜 𝑞 Lee et al. , Optics Express 15 , 18275 (2007) 6 2016 UMB-CERSI

Holographic Tracking & Characterization How Lorenz-Mie Microscopy works Incident plane wave: Scattered field: : position : radius : refractive index Focal plane Lee et al. , Optics Express 15 , 18275 (2007) 7 2016 UMB-CERSI

Holographic Tracking & Characterization How Lorenz-Mie Microscopy works Lee et al. , Optics Express 15 , 18275 (2007) 8 2016 UMB-CERSI

Holographic Tracking & Characterization How Lorenz-Mie Microscopy works Lorenz-Mie scattering coefficients for a sphere: • relative radius: • refractive index: Lee et al. , Optics Express 15 , 18275 (2007) 9 2016 UMB-CERSI

Lorenz-Mie Microscopy Lee et al. , Optics Express 15 , 18275 (2007) 10 2016 UMB-CERSI

Holographic Tracking & Characterization Independently verified performance Property Precision Range 100 × 100 × 100 𝜈 m 3 Δ𝒔 𝑞 ≤ 3 nm 3D Position Radius Δ𝑏 𝑞 ≤ 2 nm 200 nm − 20 𝜈 m Δ𝑜 𝑞 ≤ 10 −3 Refractive Index 1 − 5 10 3 mL −1 − 10 8 mL −1 Δ𝑑 𝑞 ≈ 𝑑 𝑞 Concentration NIST Traceable Particles 𝑒 𝑞 = 2 𝑏 𝑞 = 1.54 ± 0.05 𝜈 m 𝑜 𝑞 = 1.598 ± 0.005 Bangs Labs #12035 Krishnatreya et al. , Am. J. Phys. 82 , 23 (2014) 11 2016 UMB-CERSI

Holographic Tracking & Characterization Independently verified performance Property Precision Range 100 × 100 × 100 𝜈 m 3 Δ𝒔 𝑞 ≤ 3 nm 3D Position Radius Δ𝑏 𝑞 ≤ 2 nm 200 nm − 20 𝜈 m Δ𝑜 𝑞 ≤ 10 −3 Refractive Index 1 − 5 10 3 mL −1 − 10 7 mL −1 Δ𝑑 𝑞 ≈ 𝑑 𝑞 Concentration NIST traceable PS Measured flow volume (no calibration) Krishnatreya et al. , Am. J. Phys. 82 , 23 (2014) 12 2016 UMB-CERSI

Automated Holographic Characterization 1. Particles pass through laser beam in microfluidic channel 3. Compare measurement to scattering theory 2. Microscope records interference pattern 4. Comparison yields 5. Build statistics: : radius Each point : refractive index characterizes : 3D position one particle Size/refractive index distribution: for 2,500 spheres acquired in 10 minutes 13 2016 UMB-CERSI

Characterizing Colloidal Mixtures silica polystyrene Yevick, Hannel & Grier, Optics Express 22 , 22864 (2014) 14 2016 UMB-CERSI

Characterizing Protein Aggregates BSA in Tris + added salt Wang et al. , J. Pharm. Sci. 105 , 1074 (2016) 15 2016 UMB-CERSI

Differentiating Silicone Oil Droplets Wang et al. , J. Pharm. Sci. 105 , 1074 (2016) 16 2016 UMB-CERSI

Characterizing Protein & Contaminants Wang et al. , J. Pharm. Sci. 105 , 1074 (2016) 17 2016 UMB-CERSI

Effective Medium Theory Porous particle Material: Refractive index: Volume fraction: Medium: Refractive index: Effective refractive index: Lorentz-Lorenz factor: Cheong et al. , Soft Matter 7 , 6816 (2011) 18 2016 UMB-CERSI

Fractal Aggregates Volume fraction: Effective Medium Theory: Size-Index Scaling: Wang et al. , Soft Matter 12 , 8774 (2016) 19 2016 UMB-CERSI

Fractal Scaling of Protein Aggregates Bovine Serum Albumin Bovine Insulin Filamentary clusters Cluster-cluster aggregates Wang et al. , Soft Matter 12 , 8774 (2016) 20 2016 UMB-CERSI

Holographic Characterization of Human IgG 10 -1 10 -2 10 -3 silicone 10 -4 1 10 1 10 Large fractal dimension: compact clusters Differentiation between protein aggregates and silicone droplets Ruffner et al. , unpublished (2016) 21 2016 UMB-CERSI

Holographic Characterization  Detects, counts and characterizes subvisible protein aggregates in situ  Differentiates by composition & morphology  Fast, time-resolved measurements  Independently verified precision & accuracy  Minimal calibration 22 2016 UMB-CERSI

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Comparison with Industry Standard DLS (Malvern Zetasizer Nano) 1. Consistent mean radius results in common range 2. HVM also works for larger particles 3. HVM results have smaller (better) instrumental spread 4. HVM also yields refractive index (porosity) Cheong et al. , Opt. Express 17 , 13071 (2009) Cheong, Xiao, Pine & Grier, Soft Matter 7 , 6816 (2011) 24 2016 UMB-CERSI

So, what do our clusters look like? hologram fit 25 2016 UMB-CERSI

So, what do our clusters look like? hologram fit Holographic Deconvolution Microscopy Dixon et al., Opt. Express 19 , 16410 (2011) Chen et al. , J. Pharm. Sci. 105 , 1074 (2016) 26 2016 UMB-CERSI

So, what do our clusters look like? hologram fit 27 2016 UMB-CERSI

So, what do our clusters look like? hologram fit 28 2016 UMB-CERSI

So, what do our clusters look like? hologram fit 29 2016 UMB-CERSI