Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology—A Review

The release of the FDA’s guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.

Label-free detection and enumeration of Giardia cysts in agitated suspensions using in situ microscopy

Laboratory procedures performed in water treatment studies frequently require the characterization of (oo)cyst suspensions. Standard methods commonly used are laborious, expensive and time-consuming, besides requiring well-trained personnel to prepare samples with fluorescent staining and perform analysis under fluorescence microscopy. In this study, an easy cost-effective in situ microscope was assessed to acquire images of Giardia cysts directly from agitated suspensions without using any chemical labels or sample preparation steps. An image analysis algorithm analyzes the acquired images, and automatically enumerates and provides morphological information of cysts within 10 min. The proposed system was evaluated at different cyst concentrations, achieving a limit of detection of ~30 cysts/mL. The proposed system overcomes cost, time and labor demands by standard methods and has the potential to be an alternative technique for the characterization of Giardia cyst suspensions in resource-limited facilities, since it is independent of experts and free of consumables.

Cole-Cole modeling of real-time capacitance data for estimation of cell physiological properties in recombinant Escherichia coli cultivation

Real-time estimation of physiological properties of the cell during recombinant protein production would ensure enhanced process monitoring. In this study, we explored the application of dielectric spectroscopy to track the fed-batch phase of recombinant Escherichia coli cultivation for estimating the physiological properties, viz. cell diameter and viable cell concentration (VCC). The scanning capacitance data from the dielectric spectroscopy were pre-processed using moving average (MA). Later, it was modelled through a nonlinear theoretical Cole-Cole model and further solved using a global evolutionary genetic algorithm (GA). The parameters obtained from the GA were further applied for the estimation of the aforementioned physiological properties. The offline cell diameter and cell viability data were obtained from particle size analyzer and flow cytometry measurements to validate the Cole-Cole model. The offline VCC was calculated from the cell viability % from flow cytometry data and dry cell weight concentration (DCW). The Cole-Cole model predicted the cell diameter and VCC with an error of 1.03% and 7.72%, respectively. The proposed approach can enable the operator to take real-time process decisions in order to achieve desired productivity and product quality. This article is protected by copyright. All rights reserved.

Morphometric quantification of a pseudohyphae forming Saccharomyces cerevisiae strain using in situ microscopy and image analysis

Yeast morphology and counting are highly important in fermentation as they are often associated with productivity and can be influenced by process conditions. At present, time-consuming and offline methods are utilized for routine analysis of yeast morphology and cell counting using a haemocytometer. In this study, we demonstrate the application of an in situ microscope to obtain a fast stream of pseudohyphae images from agitated sample suspensions of a Saccharomyces cerevisiae strain, whose morphology in cell clusters is frequently found in the bioethanol fermentation industry. The large statistics of microscopic images allow for online determination of the principal morphological characteristics of the pseudohyphae, including the number of constituent cells, cell-size, number of branches, and length of branches. The distributions of these feature values are calculated online, constituting morphometric monitoring of the pseudohyphae population. By providing representative data, the proposed system can improve the effectiveness of morphological characterization, which in turn can help to improve the understanding and control of bioprocesses in which pseudohyphal-like morphologies are found.

In situ microscopy as online tool for detecting microbial contaminations in cell culture

Microbial contamination in mammalian cell cultures causing rejected batches is costly and highly unwanted. Most methods for detecting a contamination are time-consuming and require extensive off-line sampling. To circumvent these efforts and provide a more convenient alternative, we used an online in situ microscope to estimate the cell diameter of the cellular species in the culture to distinguish mammalian cells from microbial cells depending on their size. A warning system was set up to alert the operator if microbial cells were present in the culture. Hybridoma cells were cultured and infected with either Candida utilis or Pichia stipitis as contaminant. The warning system could successfully detect the introduced contamination and alert the operator. The results suggest that in situ microscopy could be used as an efficient online tool for early detection of contaminations in cell cultures.

An intelligent bioreactor system for the cultivation of a bioartificial vascular graft

Cardiovascular disease is the most common cause of death, accounting for 31% of deaths worldwide. As purely synthetic grafts implicate concomitant anticoagulation and autologous veins are rare, tissue-engineered vascular grafts are urgently needed. For successful in vitro cultivation of a bioartificial vascular graft, the suitable bioreactor should provide conditions comparable to vasculogenesis in the body. Such a system has been developed and characterized under continuous and pulsatile flow, and a variety of sensors has been integrated into the bioreactor to control parameters such as temperature, pressure up to 500 mbar, glucose up to 4.5 g/L, lactate, oxygen up to 150 mbar, and flow rate. Wireless data transfer (using the ZigBee specification based on the IEEE 802.15.4 standard) and multiple corresponding sensor signal processing platforms have been implemented as well. Ultrasound is used for touchless monitoring of the growing vascular structure as a quality control before implantation (maximally achieved ultrasound resolution 65 μm at 15 MHz). To withstand the harsh conditions of steam sterilization (120°C for 20 min), all electronics were encapsulated. With such a comprehensive physiologically conditioning, sensing, and imaging bioreactor system, all the requirements for a successful cultivation of vascular grafts are available now.

Monitoring of Microalgal Processes

Process monitoring, which can be defined as the measurement of process variables with the smallest possible delay, is combined with process models to form the basis for successful process control. Minimizing the measurement delay leads inevitably to employing online, in situ sensors where possible, preferably using noninvasive measurement methods with stable, low-cost sensors. Microalgal processes have similarities to traditional bioprocesses but also have unique monitoring requirements. In general, variables to be monitored in microalgal processes can be categorized as physical, chemical, and biological, and they are measured in gaseous, liquid, and solid (biological) phases. Physical and chemical process variables can be usually monitored online using standard industrial sensors. The monitoring of biological process variables, however, relies mostly on sensors developed and validated using laboratory-scale systems or uses offline methods because of difficulties in developing suitable online sensors. Here, we review current technologies for online, in situ monitoring of all types of process parameters of microalgal cultivations, with a focus on monitoring of biological parameters. We discuss newly introduced methods for measuring biological parameters that could be possibly adapted for routine online use, should be preferably noninvasive, and are based on approaches that have been proven in other bioprocesses. New sensor types for measuring physicochemical parameters using optical methods or ion-specific field effect transistor (ISFET) sensors are also discussed. Reviewed methods with online implementation or online potential include measurement of irradiance, biomass concentration by optical density and image analysis, cell count, chlorophyll fluorescence, growth rate, lipid concentration by infrared spectrophotometry, dielectric scattering, and nuclear magnetic resonance. Future perspectives are discussed, especially in the field of image analysis using in situ microscopy, infrared spectrophotometry, and software sensor systems.