Skip to main content
SpringerLink
Log in

Investigation of Quantitative X-ray Microscopy for Assessment of API and Excipient Microstructure Evolution in Solid Dosage Processing

  • Research Article
  • Published:
AAPS PharmSciTech Aims and scope Submit manuscript

Abstract

Assessment and understanding of changes in particle size of active pharmaceutical ingredients (API) and excipients as a function of solid dosage form processing is an important but under-investigated area that can impact drug product quality. In this study, X-ray microscopy (XRM) was investigated as a method for determining the in situ particle size distribution of API agglomerates and an excipient at different processing stages in tablet manufacturing. An artificial intelligence (AI)–facilitated XRM image analysis tool was applied for quantitative analysis of thousands of individual particles, both of the API and the major filler component of the formulation, microcrystalline cellulose (MCC). Domain size distributions for API and MCC were generated along with the calculation of the porosity of each respective component. The API domain size distributions correlated with laser diffraction measurements and sieve analysis of the API, formulation blend, and granulation. The XRM analysis demonstrated that attrition of the API agglomerates occurred secondary to the granulation stage. These results were corroborated by particle size distribution and sieve potency data which showed generation of an API fines fraction. Additionally, changes in the XRM-calculated size distribution of MCC particles in subsequent processing steps were rationalized based on the known plastic deformation mechanism of MCC. The XRM data indicated that size distribution of the primary MCC particles, which make up the larger functional MCC agglomerates, is conserved across the stages of processing. The results indicate that XRM can be successfully applied as a direct, non-invasive method to track API and excipient particle properties and microstructure for in-process control samples and in the final solid dosage form. The XRM and AI image analysis methodology provides a data-rich way to interrogate the impact of processing stresses on API and excipients for enhanced process understanding and utilization for Quality by Design (QbD).

Graphical Abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Scheme 1
Fig. 4

Similar content being viewed by others

References

  1. Iacocca RG, Burcham CL, Hilden LR. Particle engineering: a strategy for establishing drug substance physical property specifications during small molecule development. J Pharm Sci. 2010;99(1):51–75.

    Article  CAS  Google Scholar 

  2. Leane M, Pitt K, Reynolds G. A proposal for a drug product manufacturing classification system (MCS) for oral solid dosage forms. Pharm Dev Technol. 2015;20(1):12–21. https://doi.org/10.3109/10837450.2014.954728.

    Article  CAS  PubMed  Google Scholar 

  3. Leane M, Pitt K, Reynolds GK, Dawson N, Ziegler I, Szepes A, et al. Manufacturing classification system in the real world: factors influencing manufacturing process choices for filed commercial oral solid dosage formulations, case studies from industry and considerations for continuous processing. Pharm Dev Technol. 2018;23(10):964–77. https://doi.org/10.1080/10837450.2018.1534863.

    Article  CAS  PubMed  Google Scholar 

  4. Kougoulos E, Smales I, Verrier HM. Towards integrated drug substance and drug product design for an active pharmaceutical ingredient using particle engineering. AAPS PharmSciTech. 2011;12(1):287–94.

    Article  CAS  Google Scholar 

  5. Ticehurst MD, Marziano I. Integration of active pharmaceutical ingredient solid form selection and particle engineering into drug product design. J Pharm Pharmacol. 2015;67(6):782–802. https://doi.org/10.1111/jphp.12375.

    Article  CAS  PubMed  Google Scholar 

  6. Hamad ML, Bowman K, Smith N, Sheng X, Morris KR. Multi-scale pharmaceutical process understanding: from particle to powder to dosage form. Chem Eng Sci. 2010;65(21):5625–38.

    Article  CAS  Google Scholar 

  7. Papageorgiou CD, Langston M, Hicks F, am Ende D, Martin E, Rothstein S, et al. Development of screening methodology for the assessment of the agglomeration potential of APIs. Org Process Res Dev. 2016;20(8):1500-1508. https://doi.org/10.1021/acs.oprd.6b00201.

  8. Schenck L, Koynov A, Cote A. Particle engineering at the drug substance, drug product interface: a comprehensive platform approach to enabling continuous drug substance to drug product processing with differentiated material properties. Drug Dev Ind Pharm. 2019;45(4):521–31. https://doi.org/10.1080/03639045.2018.1562467.

    Article  CAS  PubMed  Google Scholar 

  9. Birch M, Marziano I. Understanding and avoidance of agglomeration during drying processes: a case study. Org Process Res Dev. 2013;17(10):1359–66. https://doi.org/10.1021/op4000972.

    Article  CAS  Google Scholar 

  10. Beckmann W. Agglomeration during crystallization. Crystallization. Wiley-VCH; 2013. p. 75-84.

  11. Hsieh DS, Lindrud M, Huang M, Chan SH, Erdemir D, Engstrom JD. Mechanistic elucidation of hard agglomerate formation from drying kinetics in the integrated sorption chamber. Org Process Res Dev. 2018;22(5):608–17. https://doi.org/10.1021/acs.oprd.8b00052.

    Article  CAS  Google Scholar 

  12. Ticehurst MD, A. Basford P, I. Dallman C, M. Lukas T, V. Marshall P, Nichols G, et al. Characterisation of the influence of micronisation on the crystallinity and physical stability of revatropate hydrobromide. Int J Pharm. 2000;193(2):247-259.

  13. Brittain HG. Effects of mechanical processing on phase composition. J Pharm Sci. 2002;91(7):1573–80.

    Article  CAS  Google Scholar 

  14. Descamps M, Willart JF. Perspectives on the amorphisation/milling relationship in pharmaceutical materials. Adv Drug Deliv Rev. 2016;100:51–66. https://doi.org/10.1016/j.addr.2016.01.011.

    Article  CAS  PubMed  Google Scholar 

  15. Lin SY, Hsu CH, Ke WT. Solid-state transformation of different gabapentin polymorphs upon milling and co-milling. Int J Pharm. 2010;396(1-2):83–90. https://doi.org/10.1016/j.ijpharm.2010.06.014.

    Article  CAS  PubMed  Google Scholar 

  16. Wildfong PLD, Hancock BC, Moore MD, Morris KR. Towards an understanding of the structurally based potential for mechanically activated disordering of small molecule organic crystals. J Pharm Sci. 2006;95(12):2645–56.

    Article  CAS  Google Scholar 

  17. Llusa M, Sturm K, Sudah O, Stamato H, Goldfarb DJ, Ramachandruni H, et al. Effect of high shear blending protocols and blender parameters on the degree of API agglomeration in solid formulations. Ind Eng Chem Res. 2009;48(1):93–101. https://doi.org/10.1021/ie8007055.

    Article  CAS  Google Scholar 

  18. Chen H, Aburub A, Sun CC. Direct compression tablet containing 99% active ingredient -a tale of spherical crystallization. J Pharm Sci. 2019;108(4):1396–400. https://doi.org/10.1016/j.xphs.2018.11.015.

    Article  CAS  PubMed  Google Scholar 

  19. Chen H, Wang C, Kang H, Zhi B, Haynes CL, Aburub A, et al. Microstructures and pharmaceutical properties of ferulic acid agglomerates prepared by different spherical crystallization methods. Int J Pharm. 2020;574:118914. https://doi.org/10.1016/j.ijpharm.2019.118914.

    Article  CAS  PubMed  Google Scholar 

  20. Adi H, Larson I, Stewart P. Laser diffraction particle sizing of cohesive lactose powders. Powder Technol. 2007;179(1–2):90-4. https://doi.org/10.1016/j.powtec.2007.01.018.

  21. Ek R, Alderborn G, Nyström C. Particle analysis of microcrystalline cellulose: differentiation between individual particles and their agglomerates. Int J Pharm. 1994;111(1):43-50. https://doi.org/10.1016/0378-5173(94)90400-6.

  22. Shekunov BY, Chattopadhyay P, Tong HHY, Chow AHL. Particle size analysis in pharmaceutics: principles, methods and applications. Pharm Res. 2007;24(2):203–27. https://doi.org/10.1007/s11095-006-9146-7.

    Article  CAS  PubMed  Google Scholar 

  23. Tinke AP, Govoreanu R, Weuts I, Vanhoutte K, De Smaele D. A review of underlying fundamentals in a wet dispersion size analysis of powders. Powder Technol. 2009;196(2):102–14. https://doi.org/10.1016/j.powtec.2009.08.005.

    Article  CAS  Google Scholar 

  24. Lamberto DJ, Cohen B, Marencic J, Miranda C, Petrova R, Sierra L. Laboratory methods for assessing API sensitivity to mechanical stress during agitated drying. Chem Eng Sci. 2011;66(17):3868–75. https://doi.org/10.1016/j.ces.2011.05.016.

    Article  CAS  Google Scholar 

  25. Zhang S, Lamberto DJ. Development of new laboratory tools for assessment of granulation behavior during bulk active pharmaceutical ingredient drying. J Pharm Sci. 2014;103(1):152–60. https://doi.org/10.1002/jps.23762.

    Article  CAS  PubMed  Google Scholar 

  26. Gamble JF, Hoffmann M, Hughes H, Hutchins P, Tobyn M. Monitoring process induced attrition of drug substance particles within formulated blends. Int J Pharm. 2014;470(1-2):77–87. https://doi.org/10.1016/j.ijpharm.2014.04.028.

    Article  CAS  PubMed  Google Scholar 

  27. Gamble JF, Tobyn M, Hamey R. Application of image-based particle size and shape characterization systems in the development of small molecule pharmaceuticals. J Pharm Sci. 2015;104(5):1563–74. https://doi.org/10.1002/jps.24382.

    Article  CAS  PubMed  Google Scholar 

  28. Šašić S, Yu W, Zhang L. Monitoring of API particle size during solid dosage form manufacturing process by chemical imaging and particle sizing. Anal Methods. 2011;3(3):568–74. https://doi.org/10.1039/c0ay00562b.

    Article  CAS  PubMed  Google Scholar 

  29. Hoffmann M, Wray PS, Gamble JF, Tobyn M. Investigation into process-induced de-aggregation of cohesive micronised API particles. Int J Pharm. 2015;493(1-2):341–6. https://doi.org/10.1016/j.ijpharm.2015.07.073.

    Article  CAS  PubMed  Google Scholar 

  30. Skelbæk-Pedersen AL, Vilhelmsen TK, Wallaert V, Rantanen J. Investigation of the effects of particle size on fragmentation during tableting. Int J Pharm. 2020;576:118985. https://doi.org/10.1016/j.ijpharm.2019.118985.

    Article  CAS  PubMed  Google Scholar 

  31. Dave VS, Shahin HI, Youngren-Ortiz SR, Chougule MB, Haware RV. Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets. Int J Pharm. 2017;532(1):299–312. https://doi.org/10.1016/j.ijpharm.2017.09.009.

    Article  CAS  PubMed  Google Scholar 

  32. Crean B, Parker A, Roux DL, Perkins M, Luk SY, Banks SR, et al. Elucidation of the internal physical and chemical microstructure of pharmaceutical granules using X-ray micro-computed tomography, Raman microscopy and infrared spectroscopy. Eur J Pharm Biopharm. 2010;76(3):498–506. https://doi.org/10.1016/j.ejpb.2010.08.006.

    Article  CAS  PubMed  Google Scholar 

  33. Farber L, Tardos G, Michaels JN. Use of X-ray tomography to study the porosity and morphology of granules. Powder Technol. 2003;132(1):57–63. https://doi.org/10.1016/S0032-5910(03)00043-3.

    Article  CAS  Google Scholar 

  34. Fu X, Elliott JA, Bentham AC, Hancock BC, Cameron RE. Application of X-ray microtomography and image processing to the investigation of a compacted granular system. Part Part Syst Charact. 2006;23(3-4):229–36. https://doi.org/10.1002/ppsc.200601054.

    Article  Google Scholar 

  35. McGuire PA, Blackburn S, Holt EM. An X-ray micro-computed tomography study of agglomerate breakdown during the extrusion of ceramic pastes. Chem Eng Sci. 2007;62(22):6451–6. https://doi.org/10.1016/j.ces.2007.07.040.

    Article  CAS  Google Scholar 

  36. Schomberg AK, Diener A, Wunsch I, Finke JH, Kwade A. The use of X-ray microtomography to investigate the microstructure of pharmaceutical tablets: potentials and comparison to common physical methods. Int J Pharm. 2021;3:100090. https://doi.org/10.1016/j.ijpx.2021.100090.

    Article  CAS  Google Scholar 

  37. Wagner-Hattler L, Quebatte G, Keiser J, Schoelkopf J, Schleputz CM, Huwyler J, et al. Study of drug particle distributions within mini-tablets using synchrotron X-ray microtomography and superpixel image clustering. Int J Pharm. 2020;573:118827. https://doi.org/10.1016/j.ijpharm.2019.118827.

    Article  CAS  PubMed  Google Scholar 

  38. Fang L, Yin X, Wu L, He Y, He Y, Qin W, et al. Classification of microcrystalline celluloses via structures of individual particles measured by synchrotron radiation X-ray micro-computed tomography. Int J Pharm. 2017;531(2):658–67. https://doi.org/10.1016/j.ijpharm.2017.05.019.

    Article  CAS  PubMed  Google Scholar 

  39. Paleo P, Mirone A. Efficient implementation of a local tomography reconstruction algorithm. Adv Struct Chem Imaging. 2017;3(1):5. https://doi.org/10.1186/s40679-017-0038-1.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Vásárhelyi L, Kónya Z, Kukovecz Á, Vajtai R. Microcomputed tomography–based characterization of advanced materials: a review. Mater Today Adv. 2020;8. https://doi.org/10.1016/j.mtadv.2020.100084.

  41. Yost E, Chalus P, Zhang S, Peter S, Narang AS. Quantitative X-ray microcomputed tomography assessment of internal tablet defects. J Pharm Sci. 2019;108(5):1818–30. https://doi.org/10.1016/j.xphs.2018.12.024.

    Article  CAS  PubMed  Google Scholar 

  42. Nagapudi K, Zhu A, Chang DP, Lomeo J, Rajagopal K, Hannoush RN, et al. Microstructure, quality, and release performance characterization of long-acting polymer implant formulations with X-ray microscopy and quantitative AI analytics. J Pharm Sci. 2021. https://doi.org/10.1016/j.xphs.2021.05.016.

  43. Xi H, Zhu A, Klinzing GR, Zhou L, Zhang S, Gmitter AJ, et al. Characterization of spray dried particles through microstructural imaging. J Pharm Sci. 2020;109(11):3404–12. https://doi.org/10.1016/j.xphs.2020.07.032.

    Article  CAS  PubMed  Google Scholar 

  44. Zhang S, Stroud PA, Zhu A, Johnson MJ, Lomeo J, Burcham CL, et al. Characterizing the impact of spray dried particle morphology on tablet dissolution using quantitative X-ray microscopy. Eur J Pharm Sci. 2021;165:105921. https://doi.org/10.1016/j.ejps.2021.105921.

    Article  CAS  PubMed  Google Scholar 

  45. Zhang S, Byrnes AP, Jankovic J, Neilly J. Management, analysis, and simulation of micrographs with cloud computing. Microscopy Today. 2019;27(2):26–33. https://doi.org/10.1017/s1551929519000026.

    Article  Google Scholar 

  46. Nichols G, Byard S, Bloxham MJ, Botterill J, Dawson NJ, Dennis A, et al. A review of the terms agglomerate and aggregate with a recommendation for nomenclature used in powder and particle characterization. J Pharm Sci. 2002;91(10):2103–9. https://doi.org/10.1002/jps.10191.

    Article  CAS  PubMed  Google Scholar 

  47. Williams RO III, Sriwongjanya M, Barron MK. Compaction properties of microcrystalline cellulose using tableting indices. Drug Dev Ind Pharm. 1997;23(7):695–704.

    Article  CAS  Google Scholar 

  48. Skelbæk-Pedersen A, Vilhelmsen T, Wallaert V, Rantanen J. Quantification of fragmentation of pharmaceutical materials after tableting. J Pharm Sci. 2019;108(3):1246–53. https://doi.org/10.1016/j.xphs.2018.10.040.

    Article  CAS  PubMed  Google Scholar 

  49. Skelbæk-Pedersen AL, Anuschek M, Vilhelmsen TK, Rantanen J, Zeitler JA. Non-destructive quantification of fragmentation within tablets after compression from scattering analysis of terahertz transmission measurements. Int J Pharm. 2020;588:119769. https://doi.org/10.1016/j.ijpharm.2020.119769.

    Article  CAS  PubMed  Google Scholar 

  50. Wang J, Wen H, Desai D. Lubrication in tablet formulations. Eur J Pharm Biopharm. 2010;75(1):1–15.

    Article  Google Scholar 

  51. Ahlgren P. The application of microcrystalline cellulose in pharmaceutical tablet-making. Nord Pulp Pap Res J. 1995;10(1):12–6.

    Article  CAS  Google Scholar 

  52. Doelker E. Comparative compaction properties of various microcrystalline cellulose types and generic products. Drug Dev Ind Pharm. 2008;19(17-18):2399–471. https://doi.org/10.3109/03639049309047196.

    Article  Google Scholar 

  53. Tobyn MJ, McCarthy GP, Staniforth JN, Edge S. Physicochemical comparison between microcrystalline cellulose and silicified microcrystalline cellulose. Int J Pharm. 1998;169(2):183–94. https://doi.org/10.1016/S0378-5173(98)00127-6.

    Article  CAS  Google Scholar 

  54. Westermarck S, Juppo AM, Kervinen L, Yliruusi J. Microcrystalline cellulose and its microstructure in pharmaceutical processing. Eur J Pharm Biopharm. 1999;48(3):199–206. https://doi.org/10.1016/S0939-6411(99)00051-X.

    Article  CAS  PubMed  Google Scholar 

  55. Obae K, Iijima H, Imada K. Morphological effect of microcrystalline cellulose particles on tablet tensile strength. Int J Pharm. 1999;182(2):155–64.

    Article  CAS  Google Scholar 

  56. Unknown. Cellulose, Microcrystalline. In: al Se, editor. Handbook of pharmaceutical excipients. Ninth ed. Royal Pharmaceutical Press. 2021.

  57. Gamble JF, Chiu W-S, Tobyn M. Investigation into the impact of sub-populations of agglomerates on the particle size distribution and flow properties of conventional microcrystalline cellulose grades. Pharm Dev Technol. 2011;16(5):542–8. https://doi.org/10.3109/10837450.2010.495395.

    Article  CAS  PubMed  Google Scholar 

  58. Battista OA. Technology of cellulose and its derivatives. Microcrystalline cellulose. High Polym. 1971;5:1265–76.

    CAS  Google Scholar 

  59. Gustafsson C, Lennholm H, Iversen T, Nystroem C. Evaluation of surface and bulk characteristics of cellulose I powders in relation to compaction behavior and tablet properties. Drug Dev Ind Pharm. 2003;29(10):1095–107.

    Article  CAS  Google Scholar 

  60. Thoorens G, Krier F, Leclercq B, Carlin B, Evrard B. Microcrystalline cellulose, a direct compression binder in a quality by design environment--a review. Int J Pharm. 2014;473(1-2):64–72. https://doi.org/10.1016/j.ijpharm.2014.06.055.

    Article  CAS  PubMed  Google Scholar 

  61. Badawy SIF, Gray DB, Hussain MA. A study on the effect of wet granulation on microcrystalline cellulose particle structure and performance. Pharm Res. 2006;23(3):634–40. https://doi.org/10.1007/s11095-005-9555-z.

    Article  CAS  PubMed  Google Scholar 

  62. Diarra H, Mazel V, Busignies V, Tchoreloff P. Investigating the effect of tablet thickness and punch curvature on density distribution using finite elements method. Int J Pharm. 2015;493(1-2):121–8. https://doi.org/10.1016/j.ijpharm.2015.07.030.

    Article  CAS  PubMed  Google Scholar 

  63. Kadiri MS, Michrafy A. The effect of punch’s shape on die compaction of pharmaceutical powders. Powder Technol. 2013;239:467–77. https://doi.org/10.1016/j.powtec.2013.02.022.

    Article  CAS  Google Scholar 

  64. Martin NL, Schomberg AK, Finke JH, Abraham TG, Kwade A, Herrmann C. Process modeling and simulation of tableting-an agent-based simulation methodology for direct compression. Pharmaceutics. 2021;13(7). https://doi.org/10.3390/pharmaceutics13070996.

  65. Gamble JF, Tobyn M, Zhang S, Zhu A, Salplachta J, Matula J, et al. Characterization of the morphological nature of hollow spray dried dispersion particles using X-ray submicron-computed tomography. AAPS PharmSciTech. 2021;23(1):40. https://doi.org/10.1208/s12249-021-02184-7.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors acknowledge Jia Liu for conducting the HPLC assay studies.

Author information

Authors and Affiliations

  1. DigiM Solution LLC, 500 West Cummings Park, Suite 3650, Woburn, MA, 01801, USA

    Aiden Zhu, Paul E. Luner, Joshua Lomeo & Shawn Zhang

  2. Small Molecule Pharmaceutical Sciences, Genentech, Inc., 1 DNA Way, South San Francisco, California, USA

    Chen Mao & Chi So

  3. Triform Sciences LLC, Waterford, Connecticut, USA

    Paul E. Luner

  4. F. Hoffmann-La Roche AG, Konzern-Hauptsitz, Grenzacherstrasse 124, CH-4070, Basel, Switzerland

    Stephanie Marchal

Authors
  1. Aiden Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chen Mao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paul E. Luner
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joshua Lomeo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chi So
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Stephanie Marchal
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Shawn Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Chen Mao and Chi So developed the conception of the work, conducted the formulation experiments, and analyzed the formulation data; Stephanie Marchal conducted the particle size analysis and SEM characterization data on the API; Paul Luner consolidated the information contributed by all the authors and compiled it into a cohesive single document. He was also responsible for writing and editing and discussing with authors regarding the information they provided for its clarity. Aiden Zhu and Joshua Lomeo conducted XRM image acquisition and data analysis on formulation samples; Shawn Zhang contributed to the initial conception of the work, designed the XRM approaches utilized, and provided detailed input to the writing of the manuscript. All authors reviewed and approved the final manuscript. Chen Mao and Shawn Zhang agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Corresponding authors

Correspondence to Chen Mao or Shawn Zhang.

Ethics declarations

Conflict of Interest

The authors have no conflicts of interest to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. At the time of publication, Chen Mao and Chi So are employed by Genentech Inc.; Stephanie Marchal is employed by Hoffman La Roche; Aiden Zhu, Joshua Lomeo, and Shawn Zhang are employed by DigiM Solutions LLC; Paul Luner is a part-time contractor for DigiM Solution LLC.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, A., Mao, C., Luner, P.E. et al. Investigation of Quantitative X-ray Microscopy for Assessment of API and Excipient Microstructure Evolution in Solid Dosage Processing. AAPS PharmSciTech 23, 117 (2022). https://doi.org/10.1208/s12249-022-02271-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1208/s12249-022-02271-3

KEY WORDS

Search

Navigation