Development of iterative optimization technology: Selecting pure component spectra using a small-scale feed frame simulator.

The application of spectroscopic process analytical technology (PAT) for in-line data collection offers advantages to modern pharmaceutical manufacturing. Partial least squares (PLS) models are the preferred approach for predicting API potency from PAT data, particularly near-infrared (NIR) spectra. However, the calibration burden of PLS models is sometimes considered prohibitive.

Comparison Between Pure Component Modeling Approaches for Monitoring Pharmaceutical Powder Blends with Near-Infrared Spectroscopy in Continuous Manufacturing Schemes.

Near-infrared (NIR) spectroscopy has become an important process analytical technology (PAT) for monitoring and implementing control in continuous manufacturing (CM) schemes. However, NIR requires complex multivariate models to properly extract the relevant information and the traditional model of choice, partial least squares, can be unfavorable on account of its high material and time investments for generating calibrations. To account for this, pure component-based approaches have been gaining attention due to their higher flexibility and ease of development.

Development of calibration-free/minimal calibration wavelength selection for iterative optimization technology algorithms toward process analytical technology application.

As continuous manufacturing (CM) processes are developed, process analytical technology (PAT) via NIR spectroscopy has become an integral tool in process monitoring. NIR spectroscopy requires the deployment of complex multivariate models to extract the relevant information. The model of choice for the pharmaceutical industry is Partial Least Squares (PLS).

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.

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.

Multivariate Spectroscopic Method Lifecycle Management as Part of the Quality Management System.

Multivariate model based spectroscopic methods require model maintenance through their lifecycle. A survey conducted by the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) in 2019 showed that regulatory reporting categories for the model related changes can be a hurdle for the routine use of these types of methods. This article introduces industry best practices on multivariate method and model lifecycle management within the Pharmaceutical Quality System.

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.

First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing.

This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and In Vitro Release and Dissolution Testing (IVRDT). The intent of this manuscript is to show recent progress in the field of in vitro predictive dissolution modeling and to provide recommended general approaches to developing in vitro predictive dissolution models for both early- and late-stage formulation/process development and batch release. Different modeling approaches should be used at different stages of drug development based on product and process understanding available at those stages.

Designing a calibration set in spectral space for efficient development of an NIR method for tablet analysis.

Designing a calibration set is the first step in developing a multivariate spectroscopic calibration method for quantitative analysis of pharmaceutical tablets. This step is critical because successful model development depends on the suitability of the calibration data. For spectroscopic-based methods, traditional concentration based techniques for designing calibration sets are prone to have redundant information while simultaneously lacking necessary information for a successful calibration model.

In-line monitoring and optimization of powder flow in a simulated continuous process using transmission near infrared spectroscopy.

In-line monitoring of continuous powder flow is an integral part of the continuous manufacturing process of solid oral dosage forms in the pharmaceutical industry. Specifically, monitoring downstream from loss-in-weight (LIW) feeders and/or continuous mixers provides important data about the state of the process. Such measurements support control of the process and thereby enhance product quality.