Building the quality into pellet manufacturing environment - Feasibility study and validation of an in-line quantitative near infrared (NIR) method

TY - JOUR

T1 - Building the quality into pellet manufacturing environment - Feasibility study and validation of an in-line quantitative near infrared (NIR) method

AU - Mantanus, Jérôme

AU - Ziémons, Eric

AU - Rozet, Eric

AU - Streel, Bruno

AU - Klinkenberg, Régis

AU - Evrard, Brigitte

AU - Rantanen, Jukka Tapio

AU - Hubert, Philippe

PY - 2010/12/15

Y1 - 2010/12/15

N2 - The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non-invasively interface a dispersive NIR spectrometer with four realistic particle streams existing in the pellets manufacturing environment. Regardless of the particle stream characteristics investigated, NIR together with Principal Component Analysis (PCA) was able to classify the samples according to their active content. Further, one of these particle stream interfaces was non-invasively investigated with a FT-NIR spectrometer. A predictive model based on Partial Least Squares (PLS) regression was able to determine the active content of pharmaceutical pellets. The NIR method was finally validated with an external validation set for an API concentration range from 80 to 120% of the targeted active content. The prediction error of 0.9% (root mean standard error of prediction, RMSEP) was low, indicating the accuracy of the NIR method. The accuracy profile on the validation results, an innovative approach based on tolerance intervals, demonstrated the actual and future performance of the in-line NIR method. Accordingly, the present approach paves the way for real-time release-based quality system.

AB - The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non-invasively interface a dispersive NIR spectrometer with four realistic particle streams existing in the pellets manufacturing environment. Regardless of the particle stream characteristics investigated, NIR together with Principal Component Analysis (PCA) was able to classify the samples according to their active content. Further, one of these particle stream interfaces was non-invasively investigated with a FT-NIR spectrometer. A predictive model based on Partial Least Squares (PLS) regression was able to determine the active content of pharmaceutical pellets. The NIR method was finally validated with an external validation set for an API concentration range from 80 to 120% of the targeted active content. The prediction error of 0.9% (root mean standard error of prediction, RMSEP) was low, indicating the accuracy of the NIR method. The accuracy profile on the validation results, an innovative approach based on tolerance intervals, demonstrated the actual and future performance of the in-line NIR method. Accordingly, the present approach paves the way for real-time release-based quality system.

KW - Former Faculty of Pharmaceutical Sciences

U2 - 10.1016/j.talanta.2010.09.009

DO - 10.1016/j.talanta.2010.09.009

M3 - Journal article

C2 - 21111138

SN - 0039-9140

VL - 83

SP - 305

EP - 311

JO - Talanta

JF - Talanta

IS - 2

ER -