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Importance of Raw Material Attributes for Modeling Ribbon and Granule Properties in Roller Compaction: Multivariate Analysis on Roll Gap and NIR Spectral Slope as Process Critical Control Parameters

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Abstract

This work is an extension of the earlier work from this laboratory aimed at identifying raw material properties critical to the modeling of granule and ribbon properties as part of the optimization of roller (RC) compaction processes. The utility of roll gap (RG) and near-infrared (NIR) signal, specifically, the spectral slope, as process critical control parameters (PCCPs) was also evaluated. Raw material tabletability, particle size, size distribution span, and tapped density were found to be most important factors for building robust predictive models. RG and NIR spectral slope in combination with RC operating parameters yielded models with good predictability for RC responses. Our results support the suitability of RG and NIR spectral slope as PCCPs in roller compaction, specifically, through ribbon density monitoring.

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Abbreviations

1/b :

Kawakita constant

a :

Kawakita constant

Bulk:

bulk density

C :

fractional powder volume reduction upon tapping

DoE:

design of experiment

Fall:

angle of fall

G/RM_PS:

ratio of granule to raw material particle size

G/RM_TTS:

ratio of granule to raw material tablet tensile strength

GMPS:

granule mean particle size

GTTS:

tensile strength of tablets made from granules

HFS:

horizontal feed screw speed

ICH:

International Conference on Harmonization

MCC:

microcrystalline cellulose

MCC Frac:

weight fraction of MCC in formulation

MgSt:

magnesium stearate

NIR:

near infrared

PAT:

process analytical technology

PC:

principal component

PCCP:

process critical control parameter

PLS:

partial least squares

PS:

particle size

QbD:

quality by design

RC:

roller compaction

RG:

roll gap

RMTTS:

raw material tablet tensile strength

RP:

roll pressure

RS:

roll speed

SF:

solid fraction

Span:

span in particle size distribution, \({\rm{Span = }}\frac{{X_{90} {\rm{ }} - {\rm{ }}X_{10} }}{{X_{50} }}\)

Tap:

tap density

VFS:

vertical feed screw speed

VIP:

variable importance on projection

V N :

powder volume after N taps

V o :

powder initial volume

ρ b :

powder bulk density

ρ t :

powder tap density

N :

number of taps

ε :

porosity

ρapp :

ribbon apparent density

σ t :

tensile strength

ρ T :

true density

References

  1. Soh JLP, Wang F, Boersen N, Pinal R, Peck GE, Cheney J, Valthorsson H, Pazdan J, Carvajal MT. Modeling the effects of raw material properties and operating parameters on ribbon and granule properties prepared in roller compaction using multivariate data analysis. Drug Dev Ind Pharm 2007 (in press).

  2. Hariharan M, Wowchuk C, Nkansah P, Gupta VK. Effect of formulation composition on the properties of controlled release tablets prepared by roller compaction. Drug Dev Ind Pharm 2004;30 (6):565–72.

    Article  PubMed  CAS  Google Scholar 

  3. Inghelbrecht S, Remon JP. Roller compaction and tableting of microcrystalline cellulose drug mixtures. Int J Pharm 1998a;161 (2):215–24.

    Article  CAS  Google Scholar 

  4. Cohn R, Heilig H, Delorimier A. Critical evaluation of the compactor. J Pharm Sci 1966;55 (3):328–31.

    Article  PubMed  CAS  Google Scholar 

  5. Inghelbrecht S, Remon JP. Reducing dust and improving granule and tablet quality in the roller compaction process. Int J Pharm 1998;171 (2):195–206.

    Article  CAS  Google Scholar 

  6. Johanson JR. A rolling theory for granular solids. J Applied Mech 1965;32:842–8.

    CAS  Google Scholar 

  7. Simon O, Guigon P. Correlation between powder-packing properties and roll press compact heterogeneity. Powder Tech 2003;130:257–64.

    Article  CAS  Google Scholar 

  8. Turkoglu M, Aydin I, Murray M, Sakr A. Modeling of a roller-compaction process using neural networks and genetic algorithms. Eur J Pharm Biopharm 1999;48 (3):239–45.

    Article  PubMed  CAS  Google Scholar 

  9. Dec RT, Zavaliangos A, Cunningham JC. Comparison of various modeling methods for analysis of powder compaction in roller press. Powder Tech 2003;130 (1–3):265–71.

    Article  CAS  Google Scholar 

  10. Gupta APG, Miller RW, Morris KR. Real-time near-infrared monitoring of content uniformity, moisture content, compact density, tensile strength, and young’s modulus of roller compacted powder blends. J Pharm Sci 2005;94 (7):1589–97.

    Article  PubMed  CAS  Google Scholar 

  11. Gupta APG, Miller RW, Morris KR. Nondestructive measurements of the compact strength and the particle-size distribution after milling of roller compacted powders by near-infrared spectroscopy. J Pharm Sci 2004;93 (4):1047–53.

    Article  PubMed  CAS  Google Scholar 

  12. Gupta APG, Miller RW, Morris KR. Influence of ambient moisture on the compaction behavior of microcrystalline cellulose powder undergoing uni-axial compression and roller-compaction: a comparative study using near-infrared spectroscopy. J Pharm Sci 2005;94 (10):2301–13.

    Article  PubMed  CAS  Google Scholar 

  13. Gupta APG, Miller RW, Morris KR. Effect of the variation in the ambient moisture on the compaction behavior of powder undergoing roller-compaction and on the characteristics of tablets produced from the post-milled granules. J Pharm Sci 2005;94 (10):2314–26.

    Article  PubMed  CAS  Google Scholar 

  14. Carr RL. Evaluating flow properties of solids. Chem Eng 1965;72:163–8.

    CAS  Google Scholar 

  15. Hausner HH. Friction conditions in a mass of metal powder. Int J Powder Metall 1967;3:7–13.

    Google Scholar 

  16. Ludde KH, Kawakita K. Die pulverkompression. Pharmazie 1967;21:93–403.

    Google Scholar 

  17. Beebe KR, Pell RJ, Seasholtz MB. Chemometrics—a practical guide. New York: Wiley; 1998. p. 280.

    Google Scholar 

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Acknowledgment

The authors thank the Consortium for the Advancement of Manufacturing of Pharmaceuticals (CAMP) for the funding of this work and especially Novartis Pharmaceuticals Corporation for providing the facilities where the roller compaction work was performed. Students from the Massachusetts Institute of Technology (MIT) Practice School are acknowledged for the help in the roller compaction. The assistance of Victor Hildebrand in the characterization work is also appreciated. A special gratitude is extended to Professor Rodolfo Romañach, University of Puerto Rico at Mayagüez, for stimulating discussions on this research.

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Correspondence to Rodolfo Pinal.

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Soh, J.L.P., Boersen, N., Carvajal, M.T. et al. Importance of Raw Material Attributes for Modeling Ribbon and Granule Properties in Roller Compaction: Multivariate Analysis on Roll Gap and NIR Spectral Slope as Process Critical Control Parameters. J Pharm Innov 2, 106–124 (2007). https://doi.org/10.1007/s12247-007-9013-z

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