Information Technology

Development and Application of a Simple and One-Point Multiparameter Technique: Monitoring Commercial-Scale Chromatography Process Performance

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…

Multitiered Automation for Improved Efficiency of Bioprocess Analytics

The first biopharmaceutical, human insulin, was approved for use in 1982 (1). The biopharmaceutical market continues to exhibit healthy growth now, with the number of yearly patent applications increasing by 25% annually since 1995 (2). The total pharmaceutical R&D pipeline has more than doubled since the beginning of the century (Figure 1), much of that attributable to the biologics industry segment. As this industry has matured, new platform methods have emerged, and competition has increased. Consequently, the pressures of speed,…

eBook: Using Modern In Situ Analytics and PAT for Automated Feedback Control of Critical Process Parameters

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…

Using Data and Advanced Analytics to Improve Chromatography and Batch Comparisons

With all the hype surrounding the industrial Internet of Things (IoT), cloud computing, and digital transformations, the most important information technology factors still are data and the connections of sensors, systems, and applications that generate, store, find, and use those data to obtain operational intelligence. Data volumes are increasing rapidly, and they will continue to do so. The ability to find and make sense of data to obtain intelligence that improves process outcomes is more important than ever. For clinical-…

Single-Use Sensors and Control and Data Acquisition Tools to Streamline Bioprocess Development

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…

Big Biotech Data: Implementing Large-Scale Data Processing and Analysis for Bioprocessing

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…

eBook: Bioprocess and Analytical Laboratories — Proving the Power of Data in Drug Development

Analytics pervade the entire biopharmaceutical development process — from protein characterization through biomanufacturing process optimization to final-product formulation and clinical testing. Every technical article in BPI requires data to back up the statements made, whether the topic is upstream/production, downstream processing, product development, or otherwise focused. And never mind publishing: Even more detailed documentation is required for regulatory submissions. If a company can’t back up the choices made and results obtained in development, manufacturing, and testing of its biopharmaceutical product,…

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

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…

Addressing the Challenge of Complex Buffer Management: An In-Line Conditioning Collaboration

Preparation and storage of buffers is a challenge for biopharmaceutical companies developing protein-based pharmaceuticals. The need for volumes of buffer to purify increasing upstream titers have become a major bottleneck in biopharmaceutical downstream processing. Italian biopharmaceutical company Kedrion Biopharma collects and fractionates blood plasma to produce plasma-derived therapeutic products for treating and preventing serious diseases, disorders, and conditions such as hemophilia and immune-system deficiencies. To expand its offerings and include the immunoglobulin G fractionate of blood plasma (IgG, an antibody…

Accelerating Process Development Through Flexible Automated Workflows

Synthace began as a bioprocess optimization company in 2011, spun out of University College, London. The company worked on multifactorial approaches with 15–30 factors simultaneously instead of seven or eight. The work investigated genetic strain engineering factors alongside process parameters, defining deep interactions between the way strains were designed and the way they were treated in bioprocesses. Those complex experiments gave unique insight into the complexities of biological processes, but they were exceptionally taxing to plan and carryout manually. Automation…