Biopharmaceuticals are drugs manufactured using cells that are genetically engineered to produce a therapeutic protein. A current trend in biomanufacturing is the replacement of hard-plumbed stainless steel vessels (where these cells are grown) with specialized, pre-sterilized, disposable plastic bags. While this move has significant environmental and cost benefits, the effect of plastics on the biomanufacturing process is not yet completely understood. Here we show that if a chemical compound formed by the breakdown of a common antioxidant additive to plastics leaches into the cell culture liquid, the growth of mammalian cells is strongly inhibited. Some of the factors that promote the generation of this compound, and the conditions that favor migration of the compound into process fluids, are explored here.

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis.

No abstract

No abstract

No abstract

No abstract

The paper explores scattering orthogonalization as a preprocessing technique to reduce physical interference and maintain chemical information in near-infrared (NIR) spectra of pharmaceutical tablets. Samples used in this study were tablets compressed at five compression forces; they were composed of theophylline, lactose, and microcrystalline cellulose (PH200). The NIR spectra were orthogonalized against the reduced scattering coefficients (representative of physical interference of scattering), and concentrations of all constituents were predicted. The robustness of predictions was compared to the widely employed standard normal variate (SNV) for the specificity of removing interference representative of physical parameter (such as tablet density). Group-wise cross-validation (groups were based upon similar chemical composition) and prediction demonstrated the enhanced robustness on prediction of chemical information via scattering orthogonalization in comparison to SNV. When compared to the SNV, scattering orthogonalization demonstrated an improved capacity to reduce physical interference while maintaining spectral variance attributable to chemical information. The improved capacity is expected to be useful for spectroscopy-based multivariate model calibration and continuous model update.

This is the third of a series of articles detailing the development of near-infrared spectroscopy methods for solid dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to develop a system for continuous calibration monitoring and formulate an appropriate strategy for calibration transfer. Indicators of high-flux noise (noise factor level) and wavelength uncertainty were developed. These measurements, in combination with Hotelling's T(2) and Q residual, are used to continuously monitor instrument performance and model relevance. Four calibration transfer techniques were compared. Three established techniques, finite impulse response filtering, generalized least squares weighting, and piecewise direct standardization were evaluated. A fourth technique, baseline subtraction, was the most effective for calibration transfer. Using as few as 15 transfer samples, predictive capability of the analytical method was maintained across multiple instruments and major instrument maintenance.