Benchtop NIR method development for continuous manufacturing scale to enable efficient PAT application for solid oral dosage form.

A Near Infrared (NIR) method was developed using a small benchtop feed frame system to quantify Saccharin potency in a powder blend during continuous manufacturing process. A 15-point Design of Experiments (DoE) was created based on the NIR spectral response and compositions of the formulation to develop a calibration set. The calibration set was designed to create compositional and raw material lots variation using minimum resources. The calibration experiments utilized around 0.5 kg Saccharin (Active Pharmaceutical Ingredient (API) surrogate) and 1.8 kg of excipients. Partial Least Square (PLS) modeling was used to develop a quantitative NIR method from the calibration data. The NIR method was implemented during 5 test batches in two different manufacturing sites across different potency levels at a continuous manufacturing platform for direction compression. Acceptable prediction performance was achieved from the NIR method at both sites. The NIR method was robust against changes in process scale and NIR instruments. The variance information built into the calibration set was found to be critical to successful model performance. This study shows a benchtop feed frame can be used for material sparing calibration method development without operating at a full-scale process line and applied across multiple sites, instruments at different potency levels.

A hybrid NIR-soft sensor method for real time in-process control during continuous direct compression manufacturing operations.

Near Infrared (NIR) spectroscopy is commonly utilized for continuous manufacturing as Process Analytical Technology (PAT) tool. This paper focus on a continuous direct compression manufacturing process, in which an NIR PAT probe is integrated into the tablet press feed frame and into the tablet diversion control system to ensure continuous monitoring of the potency and homogeneity of the blend within the process line. The quantification of NIR spectra is achieved through Partial Least-Squares (PLS) modeling, calibrated with offline analyzed tablet cores at different potency levels. Because the NIR measurements are often sensitive to sample physical properties caused by raw materials or process conditions, etc., adopting a data-driven approach will require a large amount of representative data throughout the method lifecycle. During the early stages of process development, whenever new uncaptured source of variability in the model space are encountered, the chemometric predictions can deviate from the offline reference, requiring frequent model updates. These deviations can be reduced by integrating process and physico-chemical knowledge in the on-line potency estimation. This paper presents a novel hybrid method combining the online NIR PLS and a potency soft sensor estimation, enabling a robust potency prediction whilst minimizing maintenance downtimes and facilitating cross-site method transfer.

An agile and robust in-line NIR potency deviation detection method for monitoring and control of a continuous direct compression process.

Near Infrared (NIR) method for blend potency estimation has been commonly used as an essential tool for process monitoring and control in continuous manufacturing of solid oral dosage forms. Robustness has been the main challenge for successful application of an NIR method, which often results in a long development time with frequent method update. Robustness deficiency often presents as an offset (bias) on the mean potency estimation. In this paper, the purpose of the NIR method has been redefined from estimating potency to potency deviation. This quantitative approach uses the mean centered potency to estimate potency deviations from the process mean, therefore, detects the non-conforming materials for continuous process monitoring and control. An NIR method was developed at the lab benchtop scale and directly deployed to a direct compression continuous manufacturing platform at Pfizer for mean centered potency estimation. The benchtop calibration provided a speedy and efficient NIR method development and the method showed enhanced robustness for estimating potency deviation in presence of wide process and raw material variations. Integrating with the mean centered approach, the NIR model from the lab could be implemented to different sites using different instruments without requiring model update for the established range of process conditions and raw material properties.