Advertisement

Solid-State Pharmaceuticals: Solving Complex Problems in Preformulation and Formulation

  • Anthony J. Hickey
  • Hugh D. C. Smyth
Chapter
  • 18 Downloads
Part of the AAPS Introductions in the Pharmaceutical Sciences book series (AAPSINSTR)

Abstract

Pharmaceutical systems and products almost always include solid-state ingredients either during manufacture or as the dosage form itself. Thus preformulation and formulation of drug products is often critically dependent on the characterization and understanding of these physicochemical properties. Despite their seemingly simplicity, attributes like dissolution, particle shape, and powder flow can be exceedingly complex and often require nonlinear approaches for modeling, prediction, and analysis. This section provides examples both from static and dynamic processes encountered in pharmaceutical preformulation/formulation development.

Keywords

Physicochemical properties Dynamical systems Solubility Dissolution Fractal Monte Carlo Powder flow Powder mixing 

References

  1. Ahmad, A. M., Douglas Boudinot, F., Barr, W. H., Reed, R. C., & Garnett, W. R. (2005). The use of Monte Carlo simulations to study the effect of poor compliance on the steady state concentrations of valproic acid following administration of enteric-coated and extended release divalproex sodium formulations. Biopharmaceutics & Drug Disposition, 26(9), 417–425.Google Scholar
  2. Akbarieh, M., Dubuc, B., & Tawashi, R. (1987). Surface studies of calcium oxalate dihydrate single crystals during dissolution in the presence of urine. Scanning Microscopy, 1(3), 1397–1403.PubMedGoogle Scholar
  3. Akbarieh, M., & Tawashi, R. (1989). Surface studies of calcium oxalate dihydrate single crystals during dissolution in the presence of stone-formers’ urine. Scanning Microscopy, 3(1), 139–145. discussion 145–136.PubMedGoogle Scholar
  4. Amidon, G. L., Lennernas, H., Shah, V. P., & Crison, J. R. (1995). A theoretical basis for a biopharmaceutic drug classification: The correlation of in vitro drug product dissolution and in vivo bioavailability. Pharmaceutical Research, 12(3), 413–420.PubMedGoogle Scholar
  5. Aoshima, M., & Satoh, A. (2005). Two-dimensional Monte Carlo simulations of a colloidal dispersion composed of polydisperse ferromagnetic particles in an applied magnetic field. Journal of Colloid and Interface Science, 288(2), 475–488.PubMedGoogle Scholar
  6. Avnir, D., Carberry, J. J., Citri, O., Farin, D., Gratzel, M., & AJ, M. E. (1991). Fractal analysis of size effects and surface morphology effects in catalysis and electrocatalysis. Chaos, 1(4), 397–410.PubMedGoogle Scholar
  7. Avnir, D., & Farin, D. (1984). Molecular fractal surfaces. Nature, 308(5956), 261–263.Google Scholar
  8. Barnsley, M. F., & Rising, H. (1993). Fractals everywhere. Boston, MA: Academic Press Professional.Google Scholar
  9. Braatz, R. D., & Hasebe, S. (2002). Particle size and shape control in crystallization processes. AIChE Symposium, Series: Proceedings of the 6th International Conference on Chemical, Process Control.Google Scholar
  10. Carr, J. F., & Walker, D. M. (1967). An annular shear cell for granular materials. Powder Technology, 68(1), 369–373.Google Scholar
  11. Carr, R. L. (1965). Evaluating flow properties of solids. Chemical Engineer, 72, 163–168.Google Scholar
  12. Carstensen, J. T., & Franchini, M. (1993). The use of fractal geometry in pharmaceutical systems. Drug Development and Industrial Pharmacy, 19(1–2), 85–100.Google Scholar
  13. Castellanos, A., Valverde, J. M., & Quintanilla, M. A. (2002). Fine cohesive powders in rotating drums: Transition from rigid-plastic flow to gas-fluidized regime. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 65(6 Pt 1), 061301.PubMedGoogle Scholar
  14. Christofides, P. D. (2002). Model-Based Control of Particulate Processes (Vol. 14). Springer Science & Business Media., Dordrecht, Netherlands.Google Scholar
  15. Christov, I. C., Ottino, J. M., & Lueptow, R. M. (2010). Chaotic mixing via streamline jumping in quasi-two-dimensional tumbled granular flows. Chaos, 20(2), 023102.PubMedGoogle Scholar
  16. Concessio, N. M., & Hickey, A. J. (1997). Descriptors of irregular particle morphology and powder properties. Advanced Drug Delivery Reviews, 26(1), 29–40.PubMedGoogle Scholar
  17. Concessio, N. M., VanOort, M. M., Knowles, M. R., & Hickey, A. J. (1999). Pharmaceutical dry powder aerosols: Correlation of powder properties with dose delivery and implications for pharmacodynamic effect. Pharmaceutical Research, 16(6), 828–834.PubMedGoogle Scholar
  18. Crowder, T., & Hickey, A. (2006). Powder specific active dispersion for generation of pharmaceutical aerosols. International Journal of Pharmaceutics, 327(1–2), 65–72.PubMedGoogle Scholar
  19. Crowder, T., Hickey, A., Louey, M. D., & Orr, N. (2003). A guide to pharmaceutical particulate science. New York, NY: Informa Healthcare..Google Scholar
  20. D’Arcy, D. M., Corrigan, O. I., & Healy, A. M. (2005). Hydrodynamic simulation (computational fluid dynamics) of asymmetrically positioned tablets in the paddle dissolution apparatus: Impact on dissolution rate and variability. The Journal of Pharmacy and Pharmacology, 57(10), 1243–1250.PubMedGoogle Scholar
  21. D’Arcy, D. M., Corrigan, O. I., & Healy, A. M. (2006). Evaluation of hydrodynamics in the basket dissolution apparatus using computational fluid dynamics–dissolution rate implications. European Journal of Pharmaceutical Sciences, 27(2–3), 259–267.PubMedGoogle Scholar
  22. Daw, C. S., Finney, C. E. A., Vasudevan, M., van Goor, N. A., Nguyen, K., Bruns, D. D., … Yorke, J. A. (1995). Self-organization and Chaos in a fluidized bed. Physical Review Letters, 75(12), 2308.PubMedGoogle Scholar
  23. Dokoumetzidis, A., Kosmidis, K., Argyrakis, P., & Macheras, P. (2005). Modeling and Monte Carlo simulations in oral drug absorption. Basic & Clinical Pharmacology & Toxicology, 96(3), 200–205.Google Scholar
  24. Dokoumetzidis, A., & Macheras, P. (2006). A century of dissolution research: From Noyes and Whitney to the biopharmaceutics classification system. International Journal of Pharmaceutics, 321(1–2), 1–11.PubMedGoogle Scholar
  25. Dressman, J. B., Amidon, G. L., Reppas, C., & Shah, V. P. (1998). Dissolution testing as a prognostic tool for oral drug absorption: Immediate release dosage forms. Pharmaceutical Research, 15(1), 11–22.PubMedGoogle Scholar
  26. Egermann, H., Krumphuber, A., & Frank, P. (1992). Novel approach to estimate quality of binary random powder mixtures: Samples of constant volume. III: Range of validity of equation. Journal of Pharmaceutical Sciences, 81(8), 773–776.PubMedGoogle Scholar
  27. Faqih, A., Chaudhuri, B., Alexander, A. W., Davies, C., Muzzio, F. J., & Silvina Tomassone, M. (2006). An experimental/computational approach for examining unconfined cohesive powder flow. International Journal of Pharmaceutics, 324(2), 116–127.PubMedGoogle Scholar
  28. Farin, D., & Avnir, D. (1992). Use of fractal geometry to determine effects of surface morphology on drug dissolution. Journal of Pharmaceutical Sciences, 81(1), 54–57.PubMedGoogle Scholar
  29. Fini, A., Fazio, G., Fernández-Hervás, M. J., Holgado, M. A., & Rabasco, A. M. (1996). Fractal analysis of sodium cholate particles. Journal of Pharmaceutical Sciences, 85(9), 971–975.PubMedGoogle Scholar
  30. Fini, A., Holgado, M. A., Rodriguez, L., & Cavallari, C. (2002). Ultrasound-compacted indomethacin/polyvinylpyrrolidone systems: Effect of compaction process on particle morphology and dissolution behavior. Journal of Pharmaceutical Sciences, 91(8), 1880–1890.PubMedGoogle Scholar
  31. Fuite, J., Marsh, R., & Tuszyński, J. (2002). Fractal pharmacokinetics of the drug mibefradil in the liver. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 66(2 Pt 1), 021904.PubMedPubMedCentralGoogle Scholar
  32. Fujiwara, M., Nagy, Z. K., Chew, J. W., & Braatz, R. D. (2005). First-principles and direct design approaches for the control of pharmaceutical crystallization. Journal of Process Control, 15(5), 493–504.Google Scholar
  33. Gilchrist, J. F., & Ottino, J. M. (2003). Competition between chaos and order: Mixing and segregation in a spherical tumbler. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 68(6 Pt 1), 061303.PubMedGoogle Scholar
  34. Grebogi, C., Ott, E., & Yorke, J. A. (1988). Unstable periodic orbits and the dimensions of multifractal chaotic attractors. Physical Review A, 37(5), 1711.Google Scholar
  35. Hausner, H. H. (1967). Friction conditions in a mass of metal powder. International Journal of Powder Metallurgy, 3, 7–13.Google Scholar
  36. Hickey, A., & Concessio, N. M. (1996). Chaos in rotating lactose beds. Particulate Science and Technology, 14(1), 15–25.Google Scholar
  37. Higuchi, T. (1961). Rate of release of medicaments from ointment bases containing drugs in suspension. Journal of Pharmaceutical Sciences, 50, 874–875.PubMedGoogle Scholar
  38. Hill, K. M., Khakhar, D. V., Gilchrist, J. F., McCarthy, J. J., & Ottino, J. M. (1999). Segregation-driven organization in chaotic granular flows. Proceedings of the National Academy of Sciences of the United States of America, 96(21), 11701–11706.PubMedPubMedCentralGoogle Scholar
  39. Holgado, M. A., Fernández‐Hervás, M. J., Rabasco, A. M., & Fini, A. (1995). Characterization study of a diclofenac salt by means of SEM and fractal analysis. International Journal of Pharmaceutics, 120(2), 157–167.Google Scholar
  40. Jartti, T. T., Kuusela, T. A., Kaila, T. J., Tahvanainen, K. U., & Välimäki, I. A. (1998). The dose-response effects of terbutaline on the variability, approximate entropy and fractal dimension of heart rate and blood pressure. British Journal of Clinical Pharmacology, 45(3), 277–285.PubMedPubMedCentralGoogle Scholar
  41. Johns, M. L., & Gladden, L. F. (2000). Probing ganglia dissolution and mobilization in a water-saturated porous medium using MRI. Journal of Colloid and Interface Science, 225(1), 119–127.PubMedGoogle Scholar
  42. Jorgensen, W. L., & Duffy, E. M. (2000). Prediction of drug solubility from Monte Carlo simulations. Bioorganic & Medicinal Chemistry Letters, 10(11), 1155–1158.Google Scholar
  43. Karalis, V., & Macheras, P. (2002). Drug disposition viewed in terms of the fractal volume of distribution. Pharmaceutical Research, 19(5), 696–703.PubMedGoogle Scholar
  44. Kaye, B. H. (1978). Specification of the ruggedness and/or texture of a fine particle profile by its fractal dimension. Powder Technology, 21(1), 1–16.Google Scholar
  45. Kaye, B. H. (1993). Chaos & complexity : Discovering the surprising patterns of science and technology. Weinheim, Germany, New York, NY: VCH.Google Scholar
  46. Kaye, B. H. (1994). A random walk through fractal dimensions. Weinheim, Germany/New York, NY: VCH.Google Scholar
  47. Keller, T. H., Pichota, A., & Yin, Z. (2006). A practical view of ‘druggability’. Current Opinion in Chemical Biology, 10(4), 357–361.PubMedGoogle Scholar
  48. Khakhar, D. V., McCarthy, J. J., Gilchrist, J. F., & Ottino, J. M. (1999). Chaotic mixing of granular materials in two-dimensional tumbling mixers. Chaos, 9(1), 195–205.PubMedGoogle Scholar
  49. Kosmidis, K., Argyrakis, P., & Macheras, P. (2003). A reappraisal of drug release laws using Monte Carlo simulations: The prevalence of the Weibull function. Pharmaceutical Research, 20(7), 988–995.PubMedGoogle Scholar
  50. Kosmidis, K., & Macheras, P. (2007). Monte Carlo simulations for the study of drug release from matrices with high and low diffusivity areas. International Journal of Pharmaceutics, 343(1–2), 166–172.PubMedGoogle Scholar
  51. Kosmidis, K., & Macheras, P. (2008). Monte Carlo simulations of drug release from matrices with periodic layers of high and low diffusivity. International Journal of Pharmaceutics, 354(1–2), 111–116.PubMedGoogle Scholar
  52. Kosmidis, K., Rinaki, E., Argyrakis, P., & Macheras, P. (2003). Analysis of Case II drug transport with radial and axial release from cylinders. International Journal of Pharmaceutics, 254(2), 183–188.PubMedGoogle Scholar
  53. Kuu, W. Y., & Chilamkurti, R. (2003). Determination of in-process limits during parenteral solution manufacturing using Monte Carlo simulation. PDA Journal of Pharmaceutical Science and Technology, 57(4), 263–276.PubMedGoogle Scholar
  54. Lee, Y. S., Poynter, R., Podczeck, F., & Newton, J. M. (2000). Development of a dual approach to assess powder flow from avalanching behavior. AAPS PharmSciTech, 1(3), E21.PubMedGoogle Scholar
  55. Leuenberger, H., Leu, R., & Bonny, J. D. (1992). Application of percolation theory and fractal geometry to tablet compaction. Drug Development and Industrial Pharmacy, 18(6–7), 723–766.Google Scholar
  56. Li, B., & Siegel, R. A. (2000). Global analysis of a model pulsing drug delivery oscillator based on chemomechanical feedback with hysteresis. Chaos, 10(3), 682–690.PubMedGoogle Scholar
  57. Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 46(1–3), 3–26.PubMedGoogle Scholar
  58. Liu, J. G., & Nie, Y. F. (2001). Fractal scaling of effective diffusion coefficient of solute in porous media. Journal of Environmental Sciences (China), 13(2), 170–172.Google Scholar
  59. Lüdde, K. H., & Kawakita, K. (1966). Die Pulverkompression. Pharmazie, 21, 393–403.Google Scholar
  60. Luerkens, D. W. (1991). Theory and application of morphological analysis : Fine particles and surfaces. Boca Raton, FL: CRC Press.Google Scholar
  61. Macheras, P. (1996). A fractal approach to heterogeneous drug distribution: Calcium pharmacokinetics. Pharmaceutical Research, 13(5), 663–670.PubMedGoogle Scholar
  62. Macheras, P., & Argyrakis, P. (1997). Gastrointestinal drug absorption: Is it time to consider heterogeneity as well as homogeneity? Pharmaceutical Research, 14(7), 842–847.PubMedPubMedCentralGoogle Scholar
  63. Manai, G., Delogu, F., & Rustici, M. (2002). Onset of chaotic dynamics in a ball mill: Attractors merging and crisis induced intermittency. Chaos, 12(3), 601–609.PubMedGoogle Scholar
  64. Marsh, R. E., & Riauka, T. A. (2007). Modeling fractal-like drug elimination kinetics using an interacting random-walk model. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 75(3 Pt 1), 031902.PubMedGoogle Scholar
  65. Marsh, R. E., & Tuszynski, J. A. (2006). Fractal Michaelis-Menten kinetics under steady state conditions: Application to mibefradil. Pharmaceutical Research, 23(12), 2760–2767.PubMedPubMedCentralGoogle Scholar
  66. Martin-Landrove, M., Pereira, D., Caldeira, M. E., Itriago, S., & Juliac, M. (2007). Fractal analysis of tumoral lesions in brain. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, 1306–1309.Google Scholar
  67. Mihranyan, A., & Stromme, M. (2007). Solubility of fractal nanoparticles. Surface Science, 601(2), 315–319.Google Scholar
  68. Montgomery, M. J., Beringer, P. M., Aminimanizani, A., Louie, S. G., Shapiro, B. J., Jelliffe, R., & Gill, M. A. (2001). Population pharmacokinetics and use of Monte Carlo simulation to evaluate currently recommended dosing regimens of ciprofloxacin in adult patients with cystic fibrosis. Antimicrobial Agents and Chemotherapy, 45(12), 3468–3473.PubMedPubMedCentralGoogle Scholar
  69. Moon, S. J., Swift, J. B., & Swinney, H. L. (2004). Role of friction in pattern formation in oscillated granular layers. Physical Review E, 69(3), 031301.Google Scholar
  70. Muzzio, F. J., Goodridge, C. L., Alexander, A., Arratia, P., Yang, H., Sudah, O., & Mergen, G. (2003). Sampling and characterization of pharmaceutical powders and granular blends. International Journal of Pharmaceutics, 250(1), 51–64.PubMedGoogle Scholar
  71. Narambuena, C. F., Ausar, F. S., Bianco, I. D., Beltramo, D. M., & Leiva, E. P. (2005). Aggregation of casein micelles by interactions with chitosans: A study by Monte Carlo simulations. Journal of Agricultural and Food Chemistry, 53(2), 459–463.PubMedGoogle Scholar
  72. Ottino, J. M., & Khakhar, D. V. (2002). Open problems in active chaotic flows: Competition between chaos and order in granular materials. Chaos, 12(2), 400–407.PubMedGoogle Scholar
  73. Pang, K. S., Weiss, M., & Macheras, P. (2007). Advanced pharmacokinetic models based on organ clearance, circulatory, and fractal concepts. The AAPS Journal, 9(2), E268–E283.PubMedPubMedCentralGoogle Scholar
  74. Papadopoulou, V., Kosmidis, K., Vlachou, M., & Macheras, P. (2006). On the use of the Weibull function for the discernment of drug release mechanisms. International Journal of Pharmaceutics, 309(1–2), 44–50.PubMedGoogle Scholar
  75. Peppas, N. A. (1985). Analysis of Fickian and non-Fickian drug release from polymers. Pharmaceutica Acta Helvetiae, 60(4), 110–111.PubMedGoogle Scholar
  76. Pereira, L. M. (2010). Fractal pharmacokinetics. Computational and Mathematical Methods in Medicine, 11(2), 161–184.PubMedGoogle Scholar
  77. Persson, E. M., Gustafsson, A. S., Carlsson, A. S., Nilsson, R. G., Knutson, L., Forsell, P., … Abrahamsson, B. (2005). The effects of food on the dissolution of poorly soluble drugs in human and in model small intestinal fluids. Pharmaceutical Research, 22(12), 2141–2151.PubMedGoogle Scholar
  78. Rawlings, J. B., Miller, S. M., & Witkowski, W. R. (1993). Model identification and control of solution crystallization processes: A review. Industrial & Engineering Chemistry Research, 32(7), 1275–1296.Google Scholar
  79. Roncaglia, R., Mannella, R., & Grigolini, P. (1994). Fractal properties of ion channels and diffusion. Mathematical Biosciences, 123(1), 77–101.PubMedGoogle Scholar
  80. Rowe, R. C., York, P., Colbourn, E. A., & Roskilly, S. J. (2005). The influence of pellet shape, size and distribution on capsule filling–a preliminary evaluation of three-dimensional computer simulation using a Monte-Carlo technique. International Journal of Pharmaceutics, 300(1–2), 32–37.PubMedGoogle Scholar
  81. Sanz, E., & Marenduzzo, D. (2010). Dynamic Monte Carlo versus Brownian dynamics: A comparison for self-diffusion and crystallization in colloidal fluids. The Journal of Chemical Physics, 132(19), 194102.PubMedGoogle Scholar
  82. Schroder, M., & Kleinebudde, P. (1995). Structure of disintegrating pellets with regard to fractal geometry. Pharmaceutical Research, 12(11), 1694–1700.PubMedGoogle Scholar
  83. Shah, K. R., Badawy, S. I., Szemraj, M. M., Gray, D. B., & Hussain, M. A. (2007). Assessment of segregation potential of powder blends. Pharmaceutical Development and Technology, 12(5), 457–462.PubMedGoogle Scholar
  84. Shinbrot, T., Alexander, A., Moakher, M., & Muzzio, F. J. (1999). Chaotic granular mixing. Chaos, 9(3), 611–620.PubMedGoogle Scholar
  85. Siepmann, J., & Peppas, N. A. (2001). Modeling of drug release from delivery systems based on hydroxypropyl methylcellulose (HPMC). Advanced Drug Delivery Reviews, 48(2–3), 139–157.PubMedGoogle Scholar
  86. Siepmann, J., & Siepmann, F. (2013). Mathematical modeling of drug dissolution. International Journal of Pharmaceutics, 453(1), 12–24.PubMedGoogle Scholar
  87. Sjoberg, B., & Mortensen, K. (1997). Structure and thermodynamics of nonideal solutions of colloidal particles: Investigation of salt-free solutions of human serum albumin by using small-angle neutron scattering and Monte Carlo simulation. Biophysical Chemistry, 65(1), 75–83.PubMedGoogle Scholar
  88. Tromelin, A., Gnanou, J. C., Andrès, C., Pourcelot, Y., & Chaillot, B. (1996). Study of morphology of reactive dissolution interface using fractal geometry. Journal of Pharmaceutical Sciences, 85(9), 924–928.PubMedGoogle Scholar
  89. Tromelin, A., Hautbout, G., & Pourcelot, Y. (2001). Application of fractal geometry to dissolution kinetic study of a sweetener excipient. International Journal of Pharmaceutics, 224(1–2), 131–140.PubMedGoogle Scholar
  90. Venables, H. J., & Wells, J. I. (2001). Powder mixing. Drug Development and Industrial Pharmacy, 27(7), 599–612.PubMedGoogle Scholar
  91. Walker, D. M. (1966). An approximate theory for pressures and arching in hoppers. Chemical Engineering Science, 21, 975–997.Google Scholar
  92. Wang, T. Y., Sheng, Y. J., & Tsao, H. K. (2009). Donnan potential of dilute colloidal dispersions: Monte Carlo simulations. Journal of Colloid and Interface Science, 340(2), 192–201.PubMedGoogle Scholar
  93. Warnken, Z., Smyth, H. D. C., & Williams, R. O. (2016). Route-specific challenges in the delivery of poorly water-soluble drugs. In R. O. Williams III et al. (Eds.), Formulating poorly water soluble drugs (AAPS advances in the pharmaceutical sciences series) (Vol. 22, pp. 1–39).Google Scholar
  94. Weidler, P. G., Degovics, G., & Laggner, P. (1998). Surface roughness created by acidic dissolution of synthetic goethite monitored with SAXS and N2-adsorption isotherms. Journal of Colloid and Interface Science, 197(1), 1–8.PubMedGoogle Scholar
  95. Weisstein, E. W. (2010). “Fractal.” Retrieved August 18, 2010, from http://mathworld.wolfram.com/Fractal.html.
  96. Xie, L., Wu, H., Shen, M., Augsburger, L. L., Lyon, R. C., Khan, M. A., … Hoag, S. W. (2008). Quality-by-design (QbD): Effects of testing parameters and formulation variables on the segregation tendency of pharmaceutical powder measured by the ASTM D 6940-04 segregation tester. Journal of Pharmaceutical Sciences, 97(10), 4485–4497.PubMedGoogle Scholar
  97. Zook, J. M., & Iftekharuddin, K. M. (2005). Statistical analysis of fractal-based brain tumor detection algorithms. Magnetic Resonance Imaging, 23(5), 671–678.PubMedGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2020

Authors and Affiliations

  • Anthony J. Hickey
    • 1
  • Hugh D. C. Smyth
    • 2
  1. 1.RTI InternationalResearch Triangle ParkUSA
  2. 2.College of PharmacyThe University of Texas at AustinAustinUSA

Personalised recommendations