Inline Monitoring to Improve Purification of Biological Systems
Jack Shu
Technology and Application Consultant
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Outline
Bioprocess Workflow
Inline Particle Characterization Tools
Applications - Flocculation - Protein Crystallization
Examples of Other ‘Particle Applications’
Installations from Lab to Plant
Summary
Bioprocess Workflow
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Fermentation
Filtration and Centrifugation
Product Extraction
Purification Chromatography and / or
Crystallization
Upstream Downstream
Waste Treatment
Flocculation
Flocculation is a process where fine suspended particles aggregate to form larger flocs which settle from the liquid phase, reducing the turbidity of the solution
Widely used in clarification protocols in many industries - Wastewater clarification - Chemicals - Food - Pulp and paper production
Flocculation is becoming more widely used in downstream processing of high density cultures
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Flocculation in Bioprocesses
Flocculation improves the separations efficiency of high density, high product titer cultures
- Improve filtration rates - Reduce filtration volumes - Aggregate fine particles, reducing clarification steps - Followed by centrifugation, depth filtration and absolute filtration, flocculation
reduces the filter media required
Reported examples of reported flocculating agents chitosan diallyl dimethyl ammonium chloride (DADMAC) acrylamide acrylate copolymers quaternized polyamines
In pharmaceutical bioprocessing the flocculating agent should be: - non-mammalian (reduce the risk of prion contamination in therapeutic applications) - non-toxic and low in heavy metals - inexpensive
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Other Potential Particle Applications at Shire
Upstream processes - Microcarrier beads - Particulates >0.5 µm - Sparge bubbles
Protein extraction and purification - Centrifugation - Crystallization - Filtration Avoid clogging and breakthrough
Formulation - Aggregates / agglomerates, and characterization of any particles 0.5 µm – 2000 µm
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Particle Size Distribution and Filtration Efficiency
Fine particle count correlates directly to filtration efficiency
Tracking the fine particle count is easy with FBRM
Source: Optimization of Pharmaceutical Batch Crystallization for Filtration and scale-up, Brian K. Johnson, Carol Szeto, Omar Davidson and Art Andrews Presented at AIChE Annual Meeting, Los Angeles, CA, November 1997
Increase in Fines
Increase in Filtration Time
Product Quality and Process Efficiency
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Particle Size Distribution in Flocculation Studies
Improve separation efficiency during filtration or centrifugation Critical parameters include:
- Maximum floc size - Floc stability - Floc shear resistance - Optimum (amount of) flocculant addition - Bioprocess variability
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100
110
120
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140
150
160
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0 0.2 0.4 0.6 0.8
Mea
n Sq
uare
Wt (
1-10
00µm
)
Concentration (%)
Flocculant 1
Flocculant 2
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Outline
Bioprocess Workflow
Inline Particle Characterization Tools
Applications - Flocculation - Protein Crystallization
Examples of Other ‘Particle Applications’
Installations from Lab to Plant
Summary
PVM Technology Particle Vision and Measurement
FBRM Technology Focused Beam Reflectance Measurement
Inline Particle Characterization Tools
10 µm cells
Temperature G400 #/sec 0-20µm
Time
Chord Length (µm)
FBRM Method of Measurement
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ParticleTrackProbe Tube
Sapphire Window
Beam splitter
Rotating optics
Laser source fiber
Focused beam
Detection fiber
Cutaway view of ParticleTrack FBRM in-process probe
PVM image illustrating the view from the ParticleTrack probe window
Probe installed in process stream
FBRM Method of Measurement
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PVM image illustrating the view from the ParticleTrack probe window Enlarged view
Path of Focused Beam
Probe detects pulses of Backscattered light
And records measured Chord Lengths
FBRM Method of Measurement
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Path of Focused Beam
Enlarged view
Thousands of Chord Lengths are measured each second to produce the Chord Length Distribution
Enlarged view
Path of Focused Beam
Optimizing Flocculation in Real Time
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Unweighted Distribution
#/s <50 µm
#/s 50-1000 µm
Time (1 Measurement = 2 s)
Improve separation efficiency during filtration or centrifugation Critical parameters include
- Maximum floc size - Floc stability - Shear resistance - Optimum flocculant addition amount and rate of addition - Bioprocess variability
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Cou
nts
Dimension
Decreasing particle count
Time S
tatis
tic
In this example FBRM shows a significant decrease in total cell count
It also shows an increase in the mean cell size
This indicates that the cells are aggregating
t = 1 min t = 4 min t = 7 min
Increasing particle size
Flocculation of Cells and Cell Debris
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Outline
Bioprocess Workflow
Inline Particle Characterization Tools
Applications - Flocculation - Protein Crystallization
Examples of Other ‘Particle Applications’
Installations from Lab to Plant
Summary
Flocculation Studies
Understanding Flocculation: Particle Size, Filterability Presented by Anna Senczuk at AIChE Puget Sound Local Section Meeting, November 16, 2010 Amgen, WA Anna Senczuk’s slides available at: pugetsound.aiche.org/content/past-meetings
Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16th, 2010. pugetsound.aiche.org/content/past-meetings
Goals - Understand how flocculation works in Amgen’s (WA) processes - Could particle distribution analysis help optimize flocculation? - Is there a direct correlation between particle distribution and filterability?
Methods - FBRM - SHC filtration as an analytical method - Lipid assays (sieving and adsorptive properties of filters)
Flocculants
polyDADMAC (Polydiallyldimethylammonium chloride) Chitosan
Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16th, 2010. pugetsound.aiche.org/content/past-meetings
Tracking Flocculation Process with FBRM
0.08 % polyDADMAC
Increase in particle size over time
Source: Understanding Flocculation:Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16th, 2010. pugetsound.aiche.org/content/past-meetings
Tracking Flocculation in Real Time
0.08 % polyDADMAC
Fines counts decrease
Large particle counts increase
Source: Understanding Flocculation:Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16th, 2010. pugetsound.aiche.org/content/past-meetings
Effect of Flocculant Concentration on Floc Size
Visualize the change in particle distribution dependent on flocculating agent concentration
Flocculation with polyDADMAC
Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16th, 2010. pugetsound.aiche.org/content/past-meetings
Particle Size and Vmax
Particle size explains Vmax trend for settled supernatant
Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16th, 2010. pugetsound.aiche.org/content/past-meetings
Different Chemicals Result in Different Flocs
250 RPM
750 RPM 250
RPM
Source: Blanco et al. Flocculation Monitoring: Focused Beam Reflectance Measurement as a measurement tool. Can. J. Chem. Eng. 2002: 80(4):734-40
Determining the Type of Floc Formed with Each Flocculant
Stronger flocs under shear
Source: Blanco et al. Flocculation Monitoring: Focused Beam Reflectance Measurement as a measurement tool. Can. J. Chem. Eng. 2002: 80(4):734-40
Protein Crystals for the Delivery of Biopharmaceuticals Basu, S. K. Govardhan, C. P. Jung, C. W.; Margolin, A. L. Expert Opinion on Biological Therapy 2004, 4, 301-17.
Advantages of crystalline proteins:
- higher bioavailability - increased ease of handling - improved stability - reduced physical and chemical degradation, and hence maintaining the protein’s biological integrity during processing and storing - increased protection against proteolytic enzymes - may allow sustained release of the therapeutic agent, reducing the frequency of doses
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Protein Crystallization
Protein crystals for the delivery of biopharmaceuticals Basu, S. K. Govardhan, C. P. Jung, C. W.; Margolin, A. L. Expert opinion on biological therapy 2004, 4, 301-17.
Protein Crystallization
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Protein crystals for the delivery of biopharmaceuticals Basu, S. K. Govardhan, C. P. Jung, C. W.; Margolin, A. L. Expert opinion on biological therapy 2004, 4, 301-17.
Tracking protein crystallization process inline and in real-time
Inline real time crystallization process monitoring increased the efficiency of the process
Continued process monitoring provided insight into crystal breakage due to excessive agitation (data not presented)
Improved batch-to-batch consistency in the manufacture of crystallized proteins
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Outline
Bioprocess Workflow
Inline Particle Characterization Tools
Applications - Flocculation - Protein Crystallization
Examples of Other ‘Particle Applications’
Installations from Lab to Plant
Summary
Examples of Other ‘Particle Applications’
Particle agglomeration (protein, cells, cellular matter, etc.)
Optimizing number of cycles and cycle time for continuous centrifugation processes
Separation of cells (therapy) from debris while preserving the integrity of the cells
Maceration of cells to release inclusion bodies
Tracking bacterial sporulation processes
Tracking the size of sparge bubbles
29 Track changes to particle systems where the particles are larger than 0.5 µm
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Is it possible to predict viscosity by tracking bubble size and count during a fermentation?
Tracking Bubble Size Distribution in a Fermentation
High Viscosity Low Viscosity
- The low viscosity sample has a much larger number of bubbles than the high viscosity sample
- PVM brings immediate understanding to the differences between batches or points in the process
Comparing Chord Length Distributions from
FBRM
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Tracking Bubble Size Distribution in a Fermentation
- The low-viscosity sample has a bimodal distribution due to the presence of cells and a high number of bubbles
- FBRM distributions identify the regions of the chord length distribution that relate to changes in viscosity
More fine counts measured in high-viscosity sample
More coarse counts from bubbles in low-viscosity sample
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Choosing a statistic to track viscosity - Plotting viscosity against any of the
statistics below will provide a means to predict in-process viscosity using FBRM
Chord lengths on a number and volume-weighted basis
increase as viscosity decreases
When viscosity decreases, the population of fine counts decrease and the population
of coarse counts increase
Tracking Bubble Size Distribution in a Fermentation
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Outline
Bioprocess Workflow
Inline Particle Characterization Tools
Applications - Flocculation - Protein Crystallization
Examples of Other ‘Particle Applications’
Installations from Lab to Plant
Summary
Installations from Lab to Plant
Probe based technologies with no need for sampling or sample preparation
Instantaneous “real-time” response of particle systems to process changes
Installations in 10 mL to 20,000 L, and pipelines
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Outline
Bioprocess Workflow
Inline Particle Characterization Tools
Applications - Flocculation - Protein Crystallization
Examples of Other ‘Particle Applications’
Installations from Lab to Plant
Summary
Summary
Inline particle measurement with FBRM can be correlated to filtration parameters to improve overall separation throughput, and product recovery
Inline real time measurement enables users to quickly establish a robust separations process by determining:
- optimal polymer type - optimal polymer amount / addition rates - when the process has reached steady-state - floc strength, and optimize shear - adapt dosage as the incoming feed suspension changes
Real time process monitoring enables immediate detection of process deviations, and hence implementation of appropriate process control protocols to ensure high product recovery
FBRM and PVM can be used as a tech transfer tool during process scale up ensuring reproducibility and minimizing process failures