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…
Process development and biomanufacturing in the biopharmaceutical industry have evolved extensively over the past 10 years. More tools are available to study process variables to enable more efficient and productive processes, speed development, and reduce costs. High powered microcontrollers are embedded in laboratory devices to carry out complex tasks. Recently, users have started working with microcontrollers such as Raspberry Pi for personal projects. As personal computer power has accelerated multiplefold,leading to high processing power and compact, high-capacity memory readily available…
Managing large amounts of data presents biopharmaceutical companies of all sizes with the need to adopt more efficient ways to handle the ongoing influx of information. At KNect365’s September 2017 Cell and Gene Therapy conference in Boston, Lisa Graham (founder and chief executive officer of Alkemy Innovation, Inc. in Bend, OR) spoke about the need for data management, data analysis, and process monitoring systems to evolve. Although she was speaking at a cell therapy event, her points are applicable to…
A strong connection between turbidity and total suspended solids (TSS) has been linked in the past to measuring well defined particles in processes. Optical density probes have seen wide adoption in the biotechnology industry for monitoring cell growth within a bioreactor, whereas in-line turbidity sensors have been used to monitor filter performance. Turbidity measurements offer a rapid quantification of suspended solids but have not been used in the biotechnology industry for chromatographic resins. In this study, turbidity measured with equipment developed by PendoTECH was used with novel continuous chromatography technology developed by Chromatan…
There is ever increasing pressure for the biopharmaceutical industry to drive toward higher efficiency and lower costs. Compared to the past, target markets for many drugs typically are becoming smaller, and so-called blockbuster drugs are becoming more the exception than the rule. Regulatory agencies have continued to increase the pressure on drug makers to meet increasing quality standards and accept higher levels of responsibility. Furthermore, customer pricing, healthcare markets, and recent biopharmaceutical pricing scandals all add incentives toward more efficient…
In commercial-scale biopharmaceutical manufacturing, downstream chromatography steps are still a bottleneck and contribute to significant operational costs (1, 2). Some of those costs are inherent (e.g., resins, large buffer quantities, and cleaning) whereas others are avoidable (e.g., product loss due to rejected lots or deviations that result in production downtime). Maintaining efficient and robust chromatography process performance is therefore critical for minimizing operating costs. To do so, we introduce a simple and one-point multiparameter technique (SOP-MPT) for monitoring chromatographic process…
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…
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…
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…
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…