Analytical Tools for Reliable Detection and Characterization of Protein Particles. Alla Polozova Analytical Biochemistry, MedImmune

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1 Analytical Tools for Reliable Detection and Characterization of Protein Particles Alla Polozova Analytical Biochemistry, MedImmune

2 Outline What to expect: Types of particles which might be present in protein solutions Analytical toolbox: Methods for counting and characterization of particles Know-how: Common difficulties and problems Real life examples: Two case studies with monoclonal antibody solutions 2

3 Common Types of Particles in Protein Solutions Foreign particles Container material (polyethylene, polypropylene, rubber, etc) Leachables from filters and transfer lines (cellulose, silicone, etc) Protein-containing particles Protein only Mixed: extraneous material and protein Particle classification by size: 0.1 to 1 µm sub-micron particles 1 µm to 125±25 µm sub-visible particles greater than 125±25 µm visible particles 3

4 Particle Counting and Characterization Methods Particle counting and sizing methods Light Obscuration Microscopy (Optical and Electron) Flow Microscopy Light Scattering (Classic, Dynamic & Nanoparticle Tracking) Particle characterization methods (morphology, composition) Optical and Polarized Light Microscopy Flow Microscopy Chemical Microscopy > Fourier Transform Infra Red (FTIR) > Raman Scanning Electron Microscopy - Energy Dispersive Spectroscopy (SEM-EDS) Atomic Force Microscopy 4

5 Particle Counting with Light Obscuration Method Advantages: One particle at a time No assumptions about particle shape No assumptions about size distribution USP/EP method Size range: µm Limitations: Potential protein interference Not sensitive to transparent particles Sensitive to air/gas bubbles Suitable for clear samples only Requires large sample volumes (5-25 ml) 5

6 Particle Counting and Sizing by Optical Microscopy: Fast Screening Method Counting chamber Advantages: Fast screening in solution under native conditions Required volume is µl Can be combined with polarized light application for quick identification of foreign particles Limitations: Hemocytometer chamber High LOQ due to small volume imaged Microscope with differential interference contrast (DIC) optics to visualize transparent particles Not practical to use as a release method due to high LOQ Particles are analyzed by image processing software Size range µm 6

7 Particle Counting and Sizing with Flow Microscopy (FlowCAM) Combination of microscope and particle counter Size range: µm Advantages: Particles are viewed under native conditions Searchable image database enables particle classification and characterization Limitations: Limited flow cell size; large particles might be lost 7

8 Sub-Micron Particle Detection and Counting with NanoSight. Particles in stressed Mab solution Glass window metallic enclosure Size range: µm Advantages: Particle sizing is based on tracking of individual particles Particles are characterized under native conditions No artifacts and/or bias associated with static or dynamic light scattering No fitting or modeling involved Limitations: Only small volume is visualized, high LOQ Resolution in opalescent solutions is limited 8

9 Particle Characterization by FTIR Microscopy and SEM-EDS FTIR microscopy SEM-EDS X-ray detector C Si O FTIR microscope determines composition from IR spectra Not sensitive to inorganic materials Secondary structure of proteins in particles can be elucidated SEM-EDS determines elemental composition from X-ray spectra Not sensitive to organic materials 9

10 Common Problem with Light Obscuration Method: (1) Interference with Background Protein Protein particles in Mab A detected by light obscuration (HIAC) 10 um Particles/mL Predicted linear response um Particles/mL Concentration (mg/ml) In a set of stressed MAb A samples prepared by serial dilution, a clear deviation from expected response was observed Artificial decrease in counts was noted: above 5 mg/ml protein concentration for 5 um channels above 10 mg/ml protein concentration for 10 um channels 10

11 Common Problem with Light Obscuration: (2) Many Particles Are Not Detected Particles/mL Protein particles in Mab A detected by light obscuration (HIAC) Predicted linear response Particles/mL Protein particles in MAb A detected by microflow imaging (FlowCAM) Predicted linear response Concentration (mg/ml) Concentration (mg/ml) Light obscuration method detects >3-10 times less protein particles (depending on size) compared to flow microscopy Both methods deviate from predicted linear response at higher protein concentrations 11

12 Why Don t Particle Counters Work Well in Protein Solutions? Refractive index of Mab A solution Refractive index Projected loss in contrast between particles and solution dn (Particle-solution) Mab A concentration, mg/ml At higher protein concentration particles become invisible due to loss in contrast Performance of light obscuration instrument can be improved by calibration with protein-like particles 12

13 Case study 1: Sensitivity of Mab B to Handling Particle counts in Mab B solution were erratic and inconsistent Sensitivity of Mab B to sample handling history was suspected as a cause Systematic study of Mab B to dilution and filtration was carried out to confirm this suspicion 13

14 Particles in Mab B after Filtration Particle counts Increase in sub-micron particles determined by NanoSight 1.6E E E E E+00 5 min 30 min 90 min 1410 min Time after filtration Counts, particles/ml Particles in MAb B solution after filtration detected by FlowCAM 0 Particle volume, ppm Particle size, um particle volume Particle size, um 5 min 30 min 90 min 1140 min 5 min 30 min 90 min Growth of particles of all sizes was observed immediately after filtration Small particles converted to larger particles with time 14

15 Case Study 2 Many hand-filled vials with MAb C failed visual appearance test due to particles Investigation was carried out to determine the root cause of particle formation 15

16 Assessment of Sub-Visible Particle Counts Sub-visible particle counts by Light Obscuration Particle size, um Particles/container Placebo Drug substance Vialed drug product (formulation buffer) 10µm µm Amount of particles significantly increased after filling into vials Change in sub-visible particle counts with time determined by flow microscopy Particle size, Particles/mL um (ESD) 0 time point 6.5 weeks (5 o C) 1 µm 506, ,641 2 µm 249,977 69, µm 72,450 20, µm 1,420 2,245 After several weeks, counts of small particles decreased and counts of larger particles increased This suggests that over time, formation of new particles slows down or stops. Existing small particles may merge into larger particles 16

17 Characterization of Particles: Particles with Protein and Polypropylene Bands Second derivative of Amide I band Polypropylene Protein Amide I and II Intermolecular β-sheet Protein absorbed onto polypropylene particles formed intermolecular β- sheet aggregates 17

18 Characterization of Particles: Particles with Protein and Silicone Oil Bands Second derivative of Amide I band Silicone oil Protein Amide I and II Native β-sheet Protein absorbed onto silicone oil droplets retained native β-sheet structure 18

19 Case 2 Study Summary Multiple particles formed in MAb C solution filled into vials With time, the number of smaller particles decreased and the number of larger particles increased Several different particle types were observed: Protein only Protein + polypropylene Protein + silicone oil Particles with different secondary structure of proteins may form by different mechanisms Several different particle formation pathways might be present 19

20 Conclusions Characterization of particles in protein solutions has unique challenges Interference of background protein Fragile nature and transparency of particles Sample handling may result in formation of new particles Several orthogonal methods are needed for reliable characterization Counts and size: light obscuration, optical microscopy, micro-flow imaging, light scattering Composition: FTIR microscopy, SEM-EDS 20

21 Acknowledgements Yoen Joo Kim Vadim Frey Lisa Block Flaviu Gruia Ziping Wei Roja Anandakumar Steven Bishop Anju Parmar Chris Rankin Patricia Cash Mark Schenerman 21