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Optimization of critical quality attributes in continuous twin-screw wet granulation via design space validated with pilot scale experimental data. | LitMetric

AI Article Synopsis

  • * They developed regression models to predict outcomes like motor torque, granule properties, and tablet quality, revealing that all these factors are significantly impacted by the three variables studied.
  • * The TSWG process was optimized to produce granules with a specific diameter of 150μm and a 95% yield, and a design space was established to ensure quality control, which was further validated through successful experiments.

Article Abstract

In this study, the influence of key process variables (screw speed, throughput and liquid to solid (L/S) ratio) of a continuous twin screw wet granulation (TSWG) was investigated using a central composite face-centered (CCF) experimental design method. Regression models were developed to predict the process responses (motor torque, granule residence time), granule properties (size distribution, volume average diameter, yield, relative width, flowability) and tablet properties (tensile strength). The effects of the three key process variables were analyzed via contour and interaction plots. The experimental results have demonstrated that all the process responses, granule properties and tablet properties are influenced by changing the screw speed, throughput and L/S ratio. The TSWG process was optimized to produce granules with specific volume average diameter of 150μm and the yield of 95% based on the developed regression models. A design space (DS) was built based on volume average granule diameter between 90 and 200μm and the granule yield larger than 75% with a failure probability analysis using Monte Carlo simulations. Validation experiments successfully validated the robustness and accuracy of the DS generated using the CCF experimental design in optimizing a continuous TSWG process.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5525546PMC
http://dx.doi.org/10.1016/j.ijpharm.2017.04.055DOI Listing

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