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. Pure component approaches, such as iterative optimization technology (IOT), have a reduced calibration burden for PAT applications. The IOT algorithm is dependent on several assumptions, including the harmonization of spectral collection conditions for pure component and mixture spectra. Collecting pure components under identical conditions to mixture spectra does not guarantee accurate predictions, and not all pure components are suitable for individual processing. This IOT assumption must be addressed to facilitate IOT application in PAT systems. In this work, IOT predicted API potency from in-line NIR spectra using combinations of stagnant and dynamic pure component spectra. A small number of mixture samples called a development set guided the selection of representative pure component spectral sets. Several model performance metrics from the development set predictions identified optimal pure component spectral sets for prediction of test sets. The combination of IOT and a development set generated accurate API potency predictions and potentiates the application of IOT in challenging pharmaceutical manufacturing settings. The IOT assumption of similar collection conditions should not be regarded as an assumption, but rather a consideration that the pure component spectral collection conditions should be representative of the mixture spectra to ensure appropriate predictions.

Application of a wavelength angle mapper for variable selection in iterative optimization technology predictions of drug content in pharmaceutical powder mixtures.

Process analytical technology (PAT) is an essential tool within pharmaceutical manufacturing to ensure consistent quality and maintain process control. Near-infrared (NIR) spectroscopy is one of the most popular PAT techniques, particularly for monitoring active pharmaceutical ingredient (API) concentrations. To interpret the spectral outputs of NIR spectroscopy, advanced multivariate models are required. Calibration-free models such as iterative optimization technology (IOT) algorithms are increasingly of interest, due primarily to their reduced material and time burdens. Variable/wavelength selection is a common method to improve prediction performance and robustness for IOT by focusing on spectral regions with the most relevant information. However, currently proposed wavelength selection approaches rely on training sets for optimization, therefore reducing or removing the advantages of IOT over empirical calibration-dependent models. In this work, a true calibration-free wavelength selection method is proposed based on measuring the difference between individual wavelengths of a mixture spectra and the net analyte signals via a wavelength angle mapper (WAM). An extension of the WAM utilizing a spectral window of wavelength instead of individual wavelengths, called SWAM, was also developed. However, the SWAM method does require a small training set to optimize wavelength selection parameters. The WAM and SWAM methods showed similar prediction performance for API in pharmaceutical powder blends when compared against other calibration-dependent models and the base IOT algorithm.

Strategies for controlling afucosylation in monoclonal antibodies during upstream manufacturing.

Core fucosylation is a highly prevalent and significant feature of N-glycosylation in therapeutic monoclonal antibodies produced by mammalian cells where its absence (afucosylation) plays a key role in treatment safety and efficacy. Notably, even slight changes in the level of afucosylation can have a considerable impact on the antibody-dependent cell-mediated cytotoxicity. Therefore, implementing control over afucosylation levels is important in upstream manufacturing to maintain consistent quality across batches of product, since standard downstream processing does not change afucosylation. In this review, the influences and strategies to control afucosylation are presented. In particular, there is emphasis on upstream manufacturing culture parameters and media supplementation, as these offer particular advantages as control strategies over alternative approaches such as cell line engineering and chemical inhibitors. The review discusses the relationship between the afucosylation influences and the underlying cellular metabolism to promote increased process understanding. Also, briefly highlighted is the value of empirical and mechanistic models in evaluating and designing control methods for core fucosylation.

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. In the present study, the application of two pure component approaches, classical least squares (CLS) models and iterative optimization technology (IOT) algorithms, to pharmaceutical powder blends in a continuous feed frame was considered. The approaches were compared from both a model performance and practical implementation perspective. IOT were found to demonstrate superior performance in predicting drug content compared to CLS. The practical implementation of each modelling approach was also given consideration.

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). However, the development of PLS can be burdensome due to the time and resource intensive requirements of calibration. To overcome this challenge, calibration-free/minimal calibration approaches have become of increasing interest. Iterative optimization technology (IOT) algorithms are a favorable calibration-free/minimal calibration approach with only the requirement of pure component spectra for successful active pharmaceutical ingredient (API) quantification. IOT algorithms were utilized to monitor potency trends (qualitative) and API content (quantitative) in a CM system and compared to a traditional PLS model. To overcome the reduced prediction performance of IOT during non-steady state conditions, a novel wavelength method based on variable importance in projection scores was employed. Overall, the success and value of IOT algorithms for application in CM settings was demonstrated.

Metabolic trends of Chinese hamster ovary cells in biopharmaceutical production under batch and fed-batch conditions.

Extensive knowledge of Chinese hamster ovary (CHO) cell metabolism is required to improve process productivity and culture performance in biopharmaceutical manufacturing. However, CHO cells show a dynamic metabolism during culturing in batch and fed-batch bioreactors. CHO cell metabolism is generally described as taking place in three stages: exponential growth phase, stationary phase, and death phase. This review aims to summarize the trends of central metabolism for CHO cells during each stage. Additional insights into how culture conditions are related to phase transitions and force metabolic rewiring are provided. Understanding of CHO cell metabolism lends itself to improving culture qualities by, for example, identifying sources of toxic byproducts and pathways for cellular engineering. In summary, this review describes the changes in CHO cell central metabolism over the course of the culture.

Rapid serum-free/suspension adaptation: Medium development using a definitive screening design for Chinese hamster ovary cells.

The biopharmaceutical industry prefers to culture the mammalian cells in suspension with a serum-free media (SFM) due to improved productivity and process consistency. However, mammalian cells preferentially grow as adherent cells in a complete medium (CM) containing serum. Therefore, cells require adaptation from adherence in CM to suspension culture in SFM. This work proposes an adaptation method that includes media supplementation during the adaption of Chinese hamster ovary cells. As a result, the adaptation was accelerated compared to the traditional repetitive subculturing. Ca2+ /Mg2+ supplementation significantly reduced the doubling time compared to the adaptation without supplementation during the adaptation of adherent cells from 100% CM to 75% CM (p < 0.05). Furthermore, a definitive screening design (DSD) was applied to select essential nutrients during the adaptation from 10% CM to 0% CM. The main effects of Ca2+ and Dulbecco's modified essential medium (DMEM) were found significant to both viable cell density and viability at harvest. Additionally, the interaction term between Ca2+ and DMEM was found significant, which highlights the ability of DSD to capture interaction terms. Eventually, the media supplementation method resulted in adaptation SFM in 27 days, compared to the previously reported 66 days. Additionally, the membrane surface integrin expression was found significantly decreased when adherent cells were adapted to suspension. Moreover, the Ca2+ /Mg2+ supplementation correlated with faster integrin recovery after trypsinization. However, faster integrin recovery did not contribute to the accelerated cell growth when subculturing from 100% CM to 75% CM.