Parametric study of residence time distributions and granulation kinetics as a basis for process modeling of twin-screw wet granulation

Timo Plath* (Corresponding Author), Carolin Korte, Rakulan Sivanesapillai, Thomas Weinhart

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Twin-screw wet granulation is a crucial unit operation in shifting from pharmaceutical batch to continuous processes, but granulation kinetics as well as residence times are yet poorly understood. Experimental findings are highly dependent on screw configuration as well as formulation and therefore have limited universal validity. In this study an experimental design with a repetitive screw setup was conducted to measure the effect of specific feed load (SFL), liquid-to-solid ratio (L/S) and inclusion of a distributive feed screw on particle size distribution (PSD) and shape as well as residence time distribution of a hydrophilic Lactose/MCC based formulation. An intermediate sampling point was obtained by changing inlet ports along the screw axis. Camera-based particle size analysis (QICPIC) indicated no significant change of PSD between the first and second kneading section except for low L/S and low SFL where fines increase. Mean residence time was approximated as a bilinear fit of L/S and SFL. Moreover, large mass flow pulsations were observed by continuous camera measurements of residence time distribution and correlated to hold-up of the twin-screw granulator. These findings indicate fast granulation kinetics and process instabilities for high mean residence times, questioning current standards of two kneading compartments for wet granulation. The present study further underlines the necessity of developing a multiscale simulation approach including particle dynamics in the future.
Original languageEnglish
Number of pages17
JournalPharmaceutics
Publication statusSubmitted - 31 Mar 2021

Keywords

  • Twin-screw wet granulation
  • Residence time distribution
  • Design of experiments
  • Continuous manufacturing
  • Process modeling
  • Virtual prototyping

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