A short presentation summarizing some of my PhD work focusing on antisolvent crystallization scale-up.

1. Multi-scale Characterization of Anti-solvent Crystallization Des O’Grady 1 December 15th 2008 School of Chemical and Bio-Process Engineering PhD Viva

2. Introduction Utilize a relatively neglected model system where sound chemical engineering principles can be applied to improve understanding Focus on key stages in the pharmaceutical drug development lifecycle Combine existing crystallization theory with in situ analytics and modern models to improve understanding Develop simple and effective techniques that can be used to improve industrial crystallization Implement a common sense scale-up protocol based on extensive laboratory-scale characterization 2

3. Introduction 1 Chapter 1 – Introduction Chapter 2 – Literature Review Chapter 3 – Solubility Chapter 4 – Mixing and MSZW Chapter 5 – Monitoring and Growth Chapter 6 – Scale-up 3

4. Chapter 3 – Solubility – Goals Generate solubility data for model system Investigate most suitable way to express anti-solvent solubility Assess feasibility of different techniques and cross-validate each method Calibrate ATR-FTIR probe Apply a theoretical model to measured solubility data 4

5. Simple Solubility Expression Traditional vs. “anti-solvent free” solubility expression 5 1. 2.

6. Gravimetric Analysis Two Gravimetric methods were used to measure solubility Solid analysis – mass of solute left in filter cake after drying Liquid Analysis – mass of solute remaining after filtrate was evaporated 6

7. FBRM Analysis “Polythermal” method was used to generate solubility information Solubility temperature was measured at a range of anti-solvent concentrations Anti-solvent concentration vs. solubility plot was then interpolated at 25ºC This method opens possibility of 3-dimensional solubility plot 7

8. ATR-FTIR Solubility Measurement Serial additions of solvent to saturated suspension at 25ºC Solubility point taken after 30 minute hold period Equilibrium achieved very quickly – dissolution kinetics are fast Potential for slow, continuous solvent addition to generate continuous solubility curve 8 Slight increase possibly due to temperature effect – heat of mixing

9. Overall Solubility Measurement Good agreement between 3 methods Accuracy of generated solubility curve is validated Liquid Analysis systematically underestimated the solubility 9

10. UNIQUAC Model UNIQUAC model follows observed solubility trends Predicts increase in solubility at low water concentrations 10

11. Introduction 1 Chapter 1 – Introduction Chapter 2 – Literature Review Chapter 3 – Solubility Chapter 4 – Mixing and MSZW Chapter 5 – Monitoring and Growth Chapter 6 – Scale-up 11

12. Chapter 3 – Solubility – Conclusions An accurate solubility curve has been generated and validated Liquid analysis underestimated solubility Increase in solubility observed at low water concentrations ‘Anti-solvent free’ solubility expression simplifies analysis MSZW and supersaturation simple to understand and define Analogous to cooling crystallization ATR-FTIR probe is calibrated Calibration model accuracy within 2% Supersaturation can be monitored during subsequent experiments UNIQUAC model generated Theoretical model fits measured data adequately 12

13. Introduction 1 Chapter 1 – Introduction Chapter 2 – Literature Review Chapter 3 – Solubility Chapter 4 – Mixing and MSZW Chapter 5 – Monitoring and Growth Chapter 6 – Scale-up 13

15. Develop a model to account for differences in the MSZW

17. Impact of Parameters on MSZW Impact of agitation, addition rate and addition location on MSZW Experiments were performed in triplicate – error bars are 95% confidence interval Some negative MSZW were observed – nucleation prior to saturation point Changing the addition location has the most significant impact 16

18. Chapter 4 – Mixing and MSZW – Interim Conclusions Wall addition location results in significant variability Variability worse at low agitation and fast addition rate Negative MSZWs observed at low agitation Typical widening of MSZW at high supersaturation generation rates not observed Impeller addition location results in little or no variability MSZW widens with increasing supersaturation generation rate Reducing agitation intensity results in a wider MSZW Rate and degree of anti-solvent incorporation needs to be studied Inadequate anti-solvent incorporation may result in locally high supersaturation A CFD model may help understand the differences between addition locations 17

19. CFD Model CFD models show velocity in z-direction (up-down) at liquid surface Close to the wall the velocity is upward – hindering anti-solvent incorporation Close to the impeller the velocity is downward – facilitating anti-solvent incorporation These models provide a model for the observed results Nucleation is hydrodynamically limited when anti-solvent is added at the wall 325rpm 475rpm wall wall wall impeller impeller wall impeller impeller 18

20. Nucleation kinetics 19 Classical nucleation kinetics are modified for an anti-solvent system Only experimental data gathered at the impeller location is considered A non-linear regression is used to estimate kinetic parameters – including an agitation parameter 3. 4. 5. x y kn = 1.9x10-3 n = 2.5 = 1.1 6.

21. Predicting MSZW 20 Good agreement between measured MSZW and predicted values Clearly impeller speed plays a critical role in nucleation kinetics This kinetic model allows MSZWs to be predicted under certain hydrodynamic conditions 7. 8. kn = 1.9x10-3 n = 2.5 = 1.1

22. Chapter 4 – Mixing and MSZW - Conclusions Agitation, addition location, and addition rate all impact the MSZW A minor change in the feed location resulted in significant variability in the MSZW To ensure process robustness a slow addition rate, high agitation and optimal feed location should be chosen The CFD model indicates that anti-solvent incorporation is the limiting step Flow patterns in the vessel either facilitate or hinder anti-solvent incorporation Possible to model larger vessels and locate optimal feed location upon scale-up An agitation dependent nucleation model was developed Model predictions fitted the experimental data adequately Potential to predict MSZW under different mixing conditions at different scales 21

23. Introduction 1 Chapter 1 – Introduction Chapter 2 – Literature Review Chapter 3 – Solubility Chapter 4 – Mixing and MSZW Chapter 5 – Monitoring and Growth Chapter 6 – Scale-up 22

25. Understand crystallization mechanism with FBRM and PVM

27. Studying Process Consistency FBRM monitors the rate and degree of change to the particle count and dimension Crystal growth and nucleation is consistent across experiments FBRM trends indicate an initial primary nucleation event followed by growth 25 Nucleation zone Growth zone Point of nucleation Inflection point: primary nucleation complete

28. Understanding crystallization mechanism PVM in situ images provide instant size and morphology information Few fine crystals and little agglomeration after 30mins – growth dominates Mechanism of primary nucleation followed by growth is somewhat validated Needle width appears to be 20-80µm; Needle length appears to be 150- 500µm

29. Correlating FBRM and PVM FBRM distributions taken after 30mins again highlight consistency Unweighted distribution may be a good track of crystal width – mean~50µm Square weighted distribution may be a good track of crystal length – mean~180µm Crystal width? Crystal length?

30. Estimating Growth Rate - FBRM Crystal growth is tracked by trending the square weighted mean Considering the rate of change of this statistic a growth rate can be calculated Growth is initially fast but slows over time as supersaturation is consumed

31. Averaging over Three Runs Supersaturation and growth rates are averaged over three runs Consistent smooth trends are generated These can be combined to generate growth rate kinetics

32. Overall Growth Rate Kinetics Supersaturation is plotted against the FBRM growth rate to estimate kinetics The growth order of 1.1 is typical of organic systems G = 7.8ΔC1.1

33. Chapter 5 – Monitoring and Growth - Conclusions Suitable parameters were chosen to ensure a consistent process ATR-FTIR showed consistency in desupersaturation FBRM showed consistency in crystal nucleation and growth Crystallization mechanisms were revealed using FBRM and validated by PVM FBRM shows an initial primary nucleation followed by slow crystal growth PVM images after 30 mins confirm large well formed crystals with few fines The unweighted and square weighted distributions track crystal width and length respectively In situ growth rate kinetics were estimated using ATR-FTIR and FBRM Potential to implement feedback control using this method Possible to include breakage, agglomeration, secondary nucleation terms in model 31

34. Introduction 1 Chapter 1 – Introduction Chapter 2 – Literature Review Chapter 3 – Solubility Chapter 4 – Mixing and MSZW Chapter 5 – Monitoring and Growth Chapter 6 – Scale-up 32

36. Conserve particle size

37. Maintain a short cycle time

38. Achieve similar yield

39. Identify optimal addition locations using CFD model

40. Scale-up vessel is geometrically dissimilar

41. Also has baffles and a different impeller

42. Study process consistency at scale using in situ tools

43. How do FBRM trends compare between batches?

44. How doe FBRM trends compare between scales?1. Impeller Addition Location 2. Wall Addition Location 3. PVM 4. FBRM 5. Overflow

45. CFD Model – 70L CFD models show velocity in z-direction (up-down) at liquid surface The optimal feed location changes depending on the liquid volume At low volume the optimal feed location is close to the wall At high volume the optimal feed location is close the impeller 32 L 64 L 34 impeller wall impeller wall

46. Averaging over Three Runs Comparison of FBRM stats across batches Fines trends prove somewhat difficult to interpret at the start of each run Probe coating was evident at the start of Runs 2 & 3 Inadequate mixing and significant segregation was evident during Run 1 Probe coating

47. Averaging over Three Runs Comparison of stats across batches The coarse counts and mean square weight are both similar Growth kinetics are similar across all batches

48. Averaging over Three Runs FBRM endpoint comparison On the unweighted and square weighted distribution – endpoints are comparable Run 1 appears to be slightly different – possibly due reduced agitation intensity

49. Averaging over Three Runs FBRM endpoint comparison FBRM trends indicate that the growth and nucleation kinetics are similar However nucleation occurs earlier at the 70L scale

50. Averaging over Three Runs FBRM endpoint comparison On the unweighted and square weighted distribution – endpoints are comparable Run 1 appears to be slightly different – possibly due reduced agitation intensity

51. Averaging over Three Runs PVM endpoint comparison PVM images at both scales are comparable 70L 500 mL

52. Introduction 1 Chapter 1 – Introduction Chapter 2 – Literature Review Chapter 3 – Solubility Chapter 4 – Mixing and MSZW Chapter 5 – Monitoring and Growth Chapter 6 – Scale-up CONCLUSIONS 41

53. Conclusion Chapter 3 – Solubility Measurement for an Anti-Solvent System Using Gravimetric Analysis, ATR-FTIR and FBRM Simple Solubility Expression Novel FBRM Solubility Method Calibration of ATR-FTIR probe Solubility Measurement using ATR-FTIR Gravimetric Solubility Measurement UNIQAC Solubility Model Chapter 4 – The Effect of Mixing on the Metastable Zone Width in Anti-solvent Crystallization MSZW using FBRM and ATR-FTIR Impact of Process Conditions on MSZW MSZW Robustness and Repeatability CFD Model for Process Understanding Modified Nucleation Kinetics The Effect of Mixing on the Metastable Zone Width and Nucleation Kinetics In the Anti-solvent Crystallization of Benzoic Acid, Chemical Engineering Research and Design, Transactions IChemE part A, 85 (7) 945-953, 2007 Solubility Measurement for an Anti-solvent Crystallization System Using Gravimetric Analysis, ATR-FTIR and FBRM, Crystal Growth and Design, in press 42

54. Overview Chapter 5 – The Use of FBRM and ATR-FTIR to Monitor Anti-solvent Crystallization and Estimate Growth Kinetics Process Repeatability Study Choosing Optimal Process Parameters In situ Monitoring of Supersaturation In Situ Monitoring of Growth Rate In Situ Estimation of Growth Kinetics Chapter 6 – Scale-Up of Anti-solvent Crystallization Choose Optimal Process Conditions CFD Modeling to Reduce Experiments Optimization based on Initial Results Process Similarity Achieved Between Scales To Be Submitted – Journal of Crystal Growth To Be Submitted – Chemical Engineering Science 43

55. ATR-FTIR Calibration 40 calibration standards and 12 validation standards were used Average error of 1.4% (water concentration) and 1.8% (anti-solvent concentration) Offset of 4% in water – possibly due to two weak validation points 44

56. ATR-FTIR Calibration Calibration consistency was also validated Repeatability, agitation intensity, volume, hold time 45 Repeatability between standards Agitation Intensity Volume

57. ATR-FTIR Calibration Calibration consistency was also validated Repeatability, agitation intensity, volume, hold time 46

58. Chapter 5 – Monitoring and Growth – Setup Under-saturated solution held at 25ºC 75g ethanol, 75g water, 21g benzoic acid Addition rate 0.065gs-1 for 45 mins – followed by 15 min hold Agitation intensity 475rpm Addition location Impeller location (1) 47