Inline Monitoring to Improve Purification of Biological Systems

Transcription

1 Inline Monitoring to Improve Purification of Biological Systems Jack Shu Technology and Application Consultant

2 Outline Bioprocess Workflow Inline Particle Characterization Tools Applications - Flocculation - Protein Crystallization Examples of Other Particle Applications Installations from Lab to Plant Summary 2

3 Bioprocess Workflow Fermentation Filtration and Centrifugation Product Extraction Purification Chromatography and / or Crystallization Waste Treatment Upstream Downstream 3

4 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 4

5 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 5

6 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 6

7 Particle Size Distribution and Filtration Efficiency Product Quality and Process Efficiency Fine particle count correlates directly to filtration efficiency Tracking the fine particle count is easy with FBRM Increase in Fines Increase in Filtration Time 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

8 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 170 Mean Square Wt (1-1000µm) Flocculant 1 Flocculant Concentration (%)

9 Outline Bioprocess Workflow Inline Particle Characterization Tools Applications - Flocculation - Protein Crystallization Examples of Other Particle Applications Installations from Lab to Plant Summary 9

10 Inline Particle Characterization Tools FBRM Technology Focused Beam Reflectance Measurement PVM Technology Particle Vision and Measurement Temperature G400 #/sec 0-20µm Time Chord Length (µm) 10 µm cells

11 FBRM Method of Measurement Cutaway view of ParticleTrack FBRM in-process probe PVM image illustrating the view from the ParticleTrack probe window Laser source fiber Detection fiber Beam splitter Rotating optics ParticleTrack Probe Tube Focused beam Sapphire Window Probe installed in process stream 11

12 FBRM Method of Measurement Enlarged view PVM image illustrating the view from the ParticleTrack probe window Path of Focused Beam Probe detects pulses of Backscattered light And records measured Chord Lengths 12

13 FBRM Method of Measurement Enlarged view Path of Focused Beam of Focused Beam Thousands of Chord Lengths are measured each second to produce the Chord Length Distribution 13

14 Optimizing Flocculation in Real Time Unweighted Distribution #/s <50 µm #/s 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 14

15 Flocculation of Cells and Cell Debris Decreasing particle count t = 1 min t = 4 min t = 7 min Counts Statistic Increasing particle size Dimension Time 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 15

16 Outline Bioprocess Workflow Inline Particle Characterization Tools Applications - Flocculation - Protein Crystallization Examples of Other Particle Applications Installations from Lab to Plant Summary 16

17 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 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) Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16 th, pugetsound.aiche.org/content/past-meetings

18 Flocculants polydadmac (Polydiallyldimethylammonium chloride) Chitosan Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16 th, pugetsound.aiche.org/content/past-meetings

19 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 16 th, pugetsound.aiche.org/content/past-meetings

20 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 16 th, pugetsound.aiche.org/content/past-meetings

21 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 16 th, pugetsound.aiche.org/content/past-meetings

22 Particle Size and V max Particle size explains V max trend for settled supernatant Source: Understanding Flocculation: Particle Size, Filterability, Anna Senczuk, Amgen WA Presented at AIChE Puget Sound Local Section Meeting, November 16 th, pugetsound.aiche.org/content/past-meetings

23 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

24 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

25 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, 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 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,

26 Protein Crystallization 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 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,

27 Outline Bioprocess Workflow Inline Particle Characterization Tools Applications - Flocculation - Protein Crystallization Examples of Other Particle Applications Installations from Lab to Plant Summary 28

28 29 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 Track changes to particle systems where the particles are larger than 0.5 µm

29 Tracking Bubble Size Distribution in a Fermentation Is it possible to predict viscosity by tracking bubble size and count during 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 30

30 Tracking Bubble Size Distribution in a Fermentation Comparing Chord Length Distributions from FBRM More fine counts measured in high-viscosity sample More coarse counts from bubbles in low-viscosity sample - 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 31

31 Tracking Bubble Size Distribution in a Fermentation 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 32

32 Outline Bioprocess Workflow Inline Particle Characterization Tools Applications - Flocculation - Protein Crystallization Examples of Other Particle Applications Installations from Lab to Plant Summary 33

33 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

34 Outline Bioprocess Workflow Inline Particle Characterization Tools Applications - Flocculation - Protein Crystallization Examples of Other Particle Applications Installations from Lab to Plant Summary 35

35 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

36 Thank You Contact information: cell: