Tableting & Scale up

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Changing tableting machines and scale up

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Tableting & Scale up

  1. 1. Changing Tableting Machines in Scale-Up and Production: Ramifications for SUPAC FDA CDER DPQR Seminar April 3, 2000 Michael Levin, Ph.D. Metropolitan Computing Corporation (MCC), East Hanover, NJ 07936
  2. 2. Page 2 MAKING A TABLET ! Die ! Upper punch ! Lower punch ! Upper compression roll ! lower compression roll ! Turret
  3. 3. Page 3 MAKING A TABLET UPPER PUNCH LOWER PUNCH UPPER PUNCH LOWER PUNCH LOWER PUNCH UPPER PUNCH LOWER PUNCH UPPER PUNCH LOWER PUNCH Apparent density Tapped density Deformation Fracture, Plastic Flow Fusion
  4. 4. Page 4 TABLETING PROCESS HARDNESS (bonding) DISSOLUTION (porosity) Adapted from K. Marshall (1999a) COMPACTION increase in mechanical strength (consolidation of particles) COMPRESSION reduction in bulk volume (displacement of gaseous phase)
  5. 5. Page 5 COMPRESSION MECHANISMS YESPARTLYVISCO-ELASTIC (starch) NONOBRITTLE (emcompress) YESPARTLYBRITTLE-PLASTIC (lactose) YESNOPLASTIC (avicel) NOYESELASTIC (rubber) TIME DEPENDENTREVERSIBLE Adapted from K. Marshall (1999a)
  6. 6. Page 6 COMPACTIBILITY PROFILE 0 2 4 6 8 0 5 10 15 20 Compaction Force (kN) Hardness(kP) starch avicel lactose emcompress Adapted from K. Marshall (1999a)
  7. 7. Page 7 0 20 40 60 80 100 0 5 10 15 20 Compaction Force (kN) Porosity(%) COMPRESSIBILITY PROFILE starch avicel lactose emcompress
  8. 8. Page 8 COMPACTIBILITY PROFILE 0 2 4 6 8 0 1 2 3 4 Compaction Force (kN) Hardness(kP) Avicel High speed Avicel Low speed
  9. 9. Page 9 0 20 40 60 80 100 0 1 2 3 Compaction Force (kN) Porosity(%) Avicel High speed Avicel Low speed COMPRESSIBILITY PROFILE
  10. 10. Page 10 0 5 10 15 20 25 30 35 40 0 2 4 6 8 10 12 14 16 18 20 22 24 26 specification specification POROSITY, HARDNESS AND DISSOLUTION Hardness (kP) t75% Dissolution (min) Porosity (%) Adapted from K. Marshall (1999a) SpeedForce
  11. 11. Page 11 FACTORS IN TABLETING Press Force Press Speed Hardness Porosity Surface Area Dissolution Disintegration
  12. 12. Page 12 Report and Recommendation of the USP Advisory Panel on Physical Test Methods: Compactibility Test K. Marshall (1999b) USP RECOMMENDATION ! Consolidation (Compactibility) area under hardness – log applied pressure plot ! Compressibility area under porosity – log applied pressure plot ! Compaction Rate Sensitivity area between two compactibility curves plots for two speeds that differ by a factor of 10
  13. 13. Page 13 Tableting Equipment
  14. 14. Page 14 Tableting Cycle
  15. 15. Page 15 DIFFERENCES IN TABLET PRESSES ! Mode of die fill (SUPAC IR/MR) G gravity G force feed G centrifugal G compression coating ! Mode of Compression G To constant thickness › Variations in porosity G To constant force › Variations in thickness ! Effect of Precompression
  16. 16. Page 16 DIFFERENCES IN TABLET PRESSES ! Effect of Speed G Hardness G Porosity G Temperature G Power of compaction G Lamination and capping G Disintegration time G Dissolution time
  17. 17. Page 17 Contact Time and Dwell Time Force Dwell Time Contact Time Compression Event Contact Time: when punch head is in contact with the wheel Dwell Time: when flat portion of punch head is in contact with the wheel
  18. 18. Page 18 Dwell Time Comparison for Rotary Pressesy Dwell Time, ms 0 10 20 30 40 50 60 70 80 Kilian T100 Fette PT 2090 IC Manesty Unipress Diamond Korsch PH106 Riva Piccola Manesty Betapress MCC Prester PRODUCTION PRESSES RESEARCH PRESSES Korsch PH336 Kilian TX40A Kikusui Libra2 Hata HT-AP38-SU MCC Presster
  19. 19. Page 19 DIFFERENCES IN TABLET PRESSES ! Compression Roll Diameter ! Press Deformation Factor ! Tooling Geometry G porosity with tip curvature ! Instrumentation
  20. 20. Page 20 What can be measured on a tablet press? ! Compression ! Precompression ! Ejection ! Speed and turret position
  21. 21. Page 21 Compression Measurement FORCE SENSOR die COMPRESSION ROLL SERVO MOTOR WEIGHT ADJUSTMENT CAM TABLET THICKNESS ADJUSTMENT STRAIN GAUGES
  22. 22. Page 22 Compression Transducer FORCE SENSOR die
  23. 23. TABLET PRESS SIMULATION
  24. 24. Page 24 Functions:Functions: •• Load ControlLoad Control •• Position ControlPosition Control Hydraulic Compaction Simulator CROSSHEADS HYDRAULIC ACTUATOR COMPRESSION LOAD CELL PUNCHES AND DIE
  25. 25. Page 25 • Impossible to calculate • Pre-recorded data depends on (Force vs. Time)
  26. 26. Press brand, model, tooling
  27. 27. Press force and speed
  28. 28. Formulation
  29. 29. Instrumentation Load Control Profile Hydraulic Compaction Simulator
  30. 30. Page 26 •Pre-Recorded Data •Artificial Profiles •Theoretical Profiles (Punch Displacement vs. Time) Position Control Profile Hydraulic Compaction Simulator
  31. 31. Page 27 depends on
  32. 32. Press brand, model, tooling
  33. 33. Press force and speed
  34. 34. Formulation
  35. 35. Instrumentation Pre-Recorded Position Control Profile Hydraulic Compaction Simulator
  36. 36. Page 28
  37. 37. Sinusoid, saw-tooth, single-ended, etc.
  38. 38. Useful for basic compaction research
  39. 39. Useful for test standardization
  40. 40. Do not simulate tablet presses Artificial Position Control Profile Hydraulic Compaction Simulator
  41. 41. Page 29 Using Rippie & Danielson (1981) equation
  42. 42. Does not account for flat head
  43. 43. Does not account for punch deformation
  44. 44. Does not account for press deformation
  45. 45. In and out of an empty die Theoretical Position Control Profile Hydraulic Compaction Simulator
  46. 46. Page 30 ™ PRESS 1 PRESS 2 PRESS 3 Mechanical Compaction Simulator The New Generation Tablet Press Replicator
  47. 47. Page 31 ! mimic press geometry ! match press speed ! match tablet weight ! match tablet thickness ! match tooling ! control speed ! control force The Presster™
  48. 48. Page 32 CASE STUDY Correlations Between a Hydraulic Compaction Simulator, Instrumented Manesty Betapress and the PressterTM G. Venkatesh et al., AAPS Meeting, 1999
  49. 49. Page 33 PRODUCT QUALITY RESEARCH ! Data from G Instrumented Press G Compaction Simulator G The Presster ! Physical Tests for Submissions ! SUPAC Guidance ! Expert Systems ! Artificial Neural Networks ! Dimensional Analysis
  50. 50. DIMENSIONAL ANALYSIS
  51. 51. Page 35 DIMENSIONAL ANALYSIS Π-theorem Every physical relationship between n dimensional variables and constants can be reduced to a relationship between m=n-r mutually independent dimensionless groups, where r = number of dimensional units, i.e. rank of the dimensional matrix Buckingham (1914) Similarity: • Geometric • Kinematic • Dynamic For any two dynamically similar systems, all the dimensionless numbers necessary to describe the process have the same numerical value (Zlokarnik, 1998)
  52. 52. Page 36 DIMENSIONAL ANALYSIS Case Study: WET GRANULATION
  53. 53. Page 37
  54. 54. Page 38 Granulation End Point and Product Properties
  55. 55. Page 39 Relevance List for wet granulation: Dimensional analysis and application of the Buckingham theorem indicates that there are 4 dimensionless quantities that adequately describe the process: Ne (P) = P / (n3 d5) Newton Power Number Re = . d2 . n / Reynolds Number Fr = d2 . n / g Froude Number h/d ratio of characteristic lengths DIMENSIONAL ANALYSIS d - impeller diameter [L] h - height of granulation bed in the bowl g - gravitational constant [LT-2] η - dynamic viscosity [M L-1 T-1] ρ - specific density of particles [M L-5] n - impeller speed [T-1] P - power consumption [ML2T-5]
  56. 56. Page 40 Gral300 Gral150 Gral75 Gral25 Gral10 0.00 0.50 1.00 1.50 2.00 2.50 3.00 Froude Numbers for Collete-Gral High-Shear Mixers Wet Granulation
  57. 57. Page 41 PMA1800 PMA800 PMA600 PMA300 PMA150 PMA65 PMA25 PMA10 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Froude Numbers for Fielder High-Shear Mixers Wet Granulation
  58. 58. Page 42 P1250 P1000 P800 P600 P400 P250 P100 P50 P25 P10 0 0.5 1 1.5 2 Froude Numbers for Diosna High-Shear Mixers Wet Granulation
  59. 59. Page 43 VG-3000 VG-2000 VG-1000 VG-800 VG-600 VG-400 VG-200 VG-100 VG-50 VG-25 VG-10 VG-5 VG-1 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 Froude Numbers for Powrex High-Shear Mixers Wet Granulation
  60. 60. Page 44 VG-600 P600 PMA600 VG-200 P250 PMA300 Gral 300 VG-50 P50 PMA65 Gral 75 VG-10 P10 PMA10 Gral 10 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 Comparative Froude Numbers for High-Shear Mixers Wet Granulation
  61. 61. Page 45 DIMENSIONAL ANALYSIS Tableting 1. Geometric factors d - die diameter [L] h - tablet thickness [L] 2. Physical properties c = ΔV / (Δp V) - compressibility factor [M-1LT2] where V - volume of the tablet; p - applied pressure 3. Process parameters p - Compression pressure [ML-1T-2] s - Compression speed [LT-1] t - Contact time [T]
  62. 62. Page 46 DIMENSIONAL ANALYSIS Π1 = d / h Π2 = s • t / h Π3 = p • c Target quantity Predictor Equation hardness h [ML-1T-2] h • c = f(Π1, Π2, Π3) dissolution time θs [T] θs / t = f(Π1, Π2, Π3) By Buckingham’s Theorem, the Π set is These relationships are now awaiting an experimental confirmation on a range of presses and materials. The predictive power of the above relationships can have a vital role in the future of tableting scale-up.
  63. 63. Page 47 CURRENT SUPAC IR/MR ! Changes in batch size G Level 1 (equipment of same design and operating principles, vary in capacity up to a factor of 10 the size of the pilot batch) G Level 2 (equipment of same design and operating principles, vary in capacity beyond a factor of 10 the size of the pilot batch) ! Manufacturing Equipment Changes G Level 1 (equipment of same design and operating principles, may vary in capacity) G Level 2 (equipment of different design and operating principles) ! Manufacturing Process Changes G Level 1 (different operating conditions, such as operating speeds within original approved application ranges) G Level 2 (different operating conditions, such as operating speeds outside of original approved application ranges)
  64. 64. Page 48 ! Keith Marshall (Keith Marshall Associates) ! Gopi Venkatesh (SmithKline Beecham) ! Colleen Ruegger (Novartis) ! Marko Zlokarnik (Bayer Austria) Acknowledgements
  65. 65. Page 49 Special thanks to ! Neelima Phadnis, Ph. D. (SmithKline Beecham) for her valuable insight ! Lev Tsygan (MCC) for his contribution to Mixer characterization based on Froude numbers Acknowledgements

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