PAT

Data Science, Modeling, and Advanced PAT Tools Enable Continuous Culture

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Bioprocesses traditionally use (fed-)batch cell culture processes for production of recombinant proteins and therapeutics. In batch bioprocessing, material flow is discrete, with a hold step between two unit operations, and product is harvested only once for each unit operation. Batch processes have been studied extensively and optimized through numerous advancements in experimental design (1, 2), monitoring (3–5), measurement techniques (6–9), and control strategies (10–12). However, such processes require large facility footprints for equipment (13) as well as sterilization, load, and…

April 20, 2018

eBook: Of Microbrews and Medicines — Understanding Their Similarities and Differences in Bioprocessing Can Help Improve Yields and Quality While Reducing Cost

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Meeting a biopharmaceutical scientist or engineer who proclaims a love for brewing is not surprising. Perhaps it’s because of the challenge of mixing raw ingredients together and waiting patiently for the final product, maybe it’s the hands-on nature of the equipment or the data analytics entertainment, or it just might be the simple joy of creating something. Whatever attracts a scientist or engineer to making medicines and/or craft brews, a surprising number of principles hold true for both bioprocesses despite…

February 8, 2018

Integrated PAT Automated Feedback Control of Critical Process Parameters Using Modern In Situ Analytics

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Simply put, the best way to control a critical process parameter (CPP) is to measure that specific parameter, integrate the live signal into your control system, and apply a smart feedback algorithm for an automated control loop. The challenge in doing this for bioprocesses has been due, in part, to the complex, highly dynamic, and variable nature of the process along with the lack of robust, scalable, and multiformat (single-use or multiuse) technologies that can monitor (in real time) such…

November 17, 2017

Model Predictive Control for Bioprocess Forecasting and Optimization

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Automation hierarchy in bioprocess manufacturing consists of a regulatory layer, process analytics technology (PAT), and (potentially) a top-level model-predictive or supervisory layer. The regulatory layer is responsible for keeping typical process measurements such as temperature, pressure, flows, and pH on target. In some cases, spectral instrumentation in combination with multivariate analysis (MVA) can be configured to measure parameters such as glucose concentration. A cascade control structure can be set up when the nutrient flow setpoint is adjusted to maintain the…

November 17, 2017

CMC Forum: Evolution of Biopharmaceutical Control Strategy Through Continued Process Verification

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As defined in the ICH Q10 guideline, a control strategy is “a planned set of controls, derived from current product and process understanding, that assures process performance and product quality†(1). Every biopharmaceutical manufacturing process has an associated control strategy. FDA’s 2011 guidance for process validation (2) describes process validation activities in three stages (Figure 1). A primary goal of stage 1 is to establish a strategy for process control that ensures a commercial process consistently produces acceptable quality products.…

January 19, 2017

Mass Spectrometric Conjugate Characterization: Process Qualification of Recombinant Protein–Hapten Conjugation

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Conjugated protein biotherapeutics such as PEGylated proteins (with polyethylene glycol), antibody–drug conjugates (ADCs), and protein–haptens often present unique analytical challenges related to characterizing the conjugation aspect of their manufacturing processes. Analytical characterization of this class of proteins requires knowledge of the sites of conjugation, the degree of conjugation, and the drug-to-protein ratio. Here we present case studies in development of reliable methods based on mass spectrometry (MS) to characterize a protein–hapten drug substance during late-phase process validation. This protein is…

November 14, 2016

Analytics for Modern Bioprocess Development

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Twelve years ago, about the same time the US Food and Drug Administration was putting the finishing touches on its quality by design (QbD) and process analytical technology (PAT) guidelines, I wrote an article about breakthrough pharmaceutical educational programs. That article included the perspectives from a few members in academia of the future essential skills for pharmaceutical students. At the time, bioinformatics and computerized industrial process modeling were relatively new disciplines, but their importance in future manufacturing was clear. Several…

March 1, 2014

Essentials in Quality By Design

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Quality by design (QbD) is a systematic approach to drug development. It begins with predefined objectives and emphasizes product and process understanding and process control, all based on sound science, data-based decision making, and quality risk management (QRM). As introduced by the US Food and Drug Administration (FDA), QbD brings modern drug development methodologies to chemistry, manufacturing, and control (CMC) teams working on biologics, pharmaceuticals, and vaccines. The innovations associated with QbD are not so much the development concepts (which…

March 1, 2014

Design of Experiments for Fed-Batch Process Development in Shaken Cultures

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When designing a recombinant protein production process, a high number of parallel cultivations must be carried out. That task is typically performed using batch cultures in shake flasks or microwell plates, in which fermentation conditions are not monitored. To overcome that limitation, we combined the SensorDish Reader and Shake Flask Reader systems (from PreSens) with an enzymatic glucose delivery system (EnBase technology from BioSilta Oy) for Escherichia coli cultivations. Our objective was to determine whether SensorDish reader cultures would yield…

January 1, 2014

Responding to Life Sciences Manufacturing Industry Guidance

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Increasingly, life science manufacturing companies are applying technology to meet quality by design (QbD) goals. Organizations collect overflowing volumes of process data as part of programs designed to improve manufacturing variability and outcomes. Collecting valuable data is now an everyday task thanks to available software and process analytical technology (PAT) tools. The industry today, in fact, has focused so much on gathering data that it often has lost sight of an important fact: Data collection systems are valuable only if…

December 1, 2013