In this study, we established a robust feed-forward control model for the tableting process\nby partial least squares regression using the near-infrared (NIR) spectra and physical attributes of\nthe granules to be compressed. The NIR spectra of granules are rich in information about chemical\nattributes, such as the compositions of any ingredients and moisture content. Polymorphism and\npseudo-polymorphism can also be quantitatively evaluated by NIR spectra. We used the particle\nsize distribution, flowability, and loose and tapped density as the physical attributes of the granules.\nThe tableting process was controlled by the lower punch fill depth and the minimum distance between\nthe upper and lower punches at compression, which were specifically related to the tablet weight\nand thickness, respectively. The feed-forward control of the process would be expected to provide\nsome advantages for automated and semi-automated continuous pharmaceutical manufacturing.\nAs a result, our model, using a combination of NIR spectra and the physical attributes of granules\nto control the distance between punches, resulted in respectable agreement between the predicted\nprocess parameters and actual settings to produce tablets of the desired thickness.
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