title: A Process Analytical Technology approach to near-infrared process control of pharmaceutical powder blending. Part III: Quantitative near-infrared calibration for prediction of blend homogeneity and characterization of powder mixing kinetics.
abstract: The Process Analytical Technology (PAT) initiative, undertaken by the Food and Drug Administration (FDA), paves the way for improvement of drug manufacturing through real-time measurements that allow better process understanding. This study is the third and final Part in a series of studies that represent an integrated approach for real-time blend uniformity assessment using near-infrared (NIR) technology. In this study, the development of a quantitative NIR model for prediction of blending end point is presented. Process signature was built into NIR calibration models by using blend samples that were collected from actual blend experiments under different processing conditions. Evaluation of various calibration algorithms including principal component regression (PCR), partial least squares (PLS), and multi-term linear regression (MLR) was performed. It was found that linear regression, using a single wavelength, yielded optimum calibration and prediction results. The blending profiles predicted by the NIR quantitative model correlated well to those determined by the UV reference analytical method. Characterization of intra-shell versus inter-shell powder mixing kinetics and its implication in sensor positioning was also performed and will be discussed.
authors.affiliation: Process Analytical Technology Group, Pharmaceutical Development Center of Excellence, Pharmaceutical Research Institute, Bristol-Myers Squibb, New Brunswick, New Jersey, USA.
authors.forename: Arwa S
authors.initials: AS
authors.lastname: El-Hagrasy
authors.forename: James K
authors.initials: JK
authors.lastname: Drennen
mesh_terms: D002138:Calibration; D002626:Chemistry, Pharmaceutical / Q000379:methods*; D007700:Kinetics; D007785:Lactose / Q000737:chemistry; D016018:Least-Squares Analysis; D016014:Linear Models; D000432:Methanol / Q000737:chemistry; D015999:Multivariate Analysis; D011208:Powders / Q000737:chemistry*; D020156:Salicylic Acid / Q000737:chemistry; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013678:Technology, Pharmaceutical
chemical_list: D011208:Powders; D007785:Lactose; D020156:Salicylic Acid; D000432:Methanol