Industrial internet of things: What does it mean for the bioprocess industries?

Industrial Internet of Things (IIoT) is a system of interconnected devices that, via the use of various technologies, such as soft sensors, cloud computing, data analytics, machine learning and artificial intelligence, provides real-time insight into the operations of any industrial process from product conceptualisation, process optimisation and manufacturing to the supply chain. IIoT enables wide-scope data collection and utilisation, and reduces errors, increases efficiency, and provides an improved understanding of the process in return. While this novel solution is the pillar of Industry 4.0, the inherent operational complexity of bioprocessing arising from the involvement of living systems or their components in manufacturing renders the sector a challenging one for the implementation of IIoT. A large segment of the industry comprises the manufacturing of biopharmaceuticals and advanced therapies, some of the most valuable biotechnological products available, which undergo tight regulatory evaluations and scrutinization from product conceptualisation to patient delivery. Extensive process understanding is what biopharmaceutical industry strives for, however, the complexity of transition into a new mode of operation, potential misalignment of priorities, the need for substantial investments to facilitate transition, the limitations imposed by the downtime required for transition and the essentiality of regulatory support, render it challenging for the industry to adopt IIoT solutions to integrate with biomanufacturing operations. There is currently a need for universal solutions that would streamline the implementation of IIoT and overcome the widespread reluctance observed in the sector, which will recommend accessible implementation strategies, effective employee training and offer valuable insights in return to advance any processing and manufacturing operation within their respective regulatory frameworks

Advanced control strategies for bioprocess chromatography: Challenges and opportunities for intensified processes and next generation products

Recent advances in process analytical technologies and modelling techniques present opportunities to improve industrial chromatography control strategies to enhance process robustness, increase productivity and move towards real-time release testing. This paper provides a critical overview of batch and continuous industrial chromatography control systems for therapeutic protein purification. Firstly, the limitations of conventional industrial fractionation control strategies using in-line UV spectroscopy and on-line HPLC are outlined. Following this, an evaluation of monitoring and control techniques showing promise within research, process development and manufacturing is provided. These novel control strategies combine rapid in-line data capture (e.g. NIR, MALS and variable pathlength UV) with enhanced process understanding obtained from mechanistic and empirical modelling techniques. Finally, a summary of the future states of industrial chromatography control systems is proposed, including strategies to control buffer formulation, product fractionation, column switching and column fouling. The implementation of these control systems improves process capabilities to fulfil product quality criteria as processes are scaled, transferred and operated, thus fast tracking the delivery of new medicines to market

Computer-Aided Strategies for Determining the Amino Acid Composition of Medium for Chinese Hamster Ovary Cell-Based Biomanufacturing Platforms.

Chinese hamster ovary (CHO) cells are used for the production of the majority of biopharmaceutical drugs, and thus have remained the standard industry host for the past three decades. The amino acid composition of the medium plays a key role in commercial scale biologics manufacturing, as amino acids constitute the building blocks of both endogenous and heterologous proteins, are involved in metabolic and non-metabolic pathways, and can act as main sources of nitrogen and carbon under certain conditions. As biomanufactured proteins become increasingly complex, the adoption of model-based approaches become ever more popular in complementing the challenging task of medium development. The extensively studied amino acid metabolism is exceptionally suitable for such model-driven analyses, and although still limited in practice, the development of these strategies is gaining attention, particularly in this domain. This paper provides a review of recent efforts. We first provide an overview of the widely adopted practice, and move on to describe the model-driven approaches employed for the improvement and optimization of the external amino acid supply in light of cellular amino acid demand. We conclude by proposing the likely prevalent direction the field is heading towards, providing a critical evaluation of the current state and the future challenges and considerations

Digital twin of mRNA-based SARS-COVID-19 vaccine manufacturing towards autonomous operation for improvements in speed, scale, robustness, flexibility and real-time release testing

Supplying SARS-COVID-19 vaccines in quantities to meet global demand has a bottleneck in manufacturing capacity. Assessment of existing mRNA (messenger ribonucleic acid) vaccine processing shows the need for digital twins enabled by process analytical technology approaches to improve process transfers for manufacturing capacity multiplication, reduction of out-of-specification batch failures, qualified personnel training for faster validation and efficient operation, optimal utilization of scarce buffers and chemicals, and faster product release. A digital twin of the total pDNA (plasmid deoxyribonucleic acid) to mRNA process is proposed. In addition, a first feasibility of multisensory process analytical technology (PAT) is shown. Process performance characteristics are derived as results and evaluated regarding manufacturing technology bottlenecks. Potential improvements could be pointed out such as dilution reduction in lysis, and potential reduction of necessary chromatography steps. 1 g pDNA may lead to about 30 g mRNA. This shifts the bottleneck towards the mRNA processing step, which points out co-transcriptional capping as a preferred option to reduce the number of purification steps. Purity demands are fulfilled by a combination of mixed-mode and reversed-phase chromatography as established unit operations on a higher industrial readiness level than e.g., precipitation and ethanol-chloroform extraction. As a final step, lyophilization was chosen for stability, storage and transportation logistics. Alternative process units like UF/DF (ultra-/diafiltration) integration would allow the adjustment of final concentration and buffer composition before lipid-nano particle (LNP) formulation. The complete digital twin is proposed for further validation in manufacturing scale and utilization in process optimization and manufacturing operations. The first PAT results should be followed by detailed investigation of different batches and processing steps in order to implement this strategy for process control and reliable, efficient operation

Developing synthetic biology strategies for enhancing the efficiency of engineered cyanobacterial expression systems

Cyanobacteria are unique prokaryotic microbes performing oxygenic photosynthesis. They have inherent capacity of the direct conversion of solar energy, CO2 and water into carbonbased compounds. Scientists’ increasing abilities to engineer cyanobacterial cells makes them an attractive next-generation biotechnological host for sustainable production systems, independent of biomass-derived substrates. However, in order to develop commercially viable systems, the strategies for rational strain engineering and enhanced electron and carbon fluxes towards the specified target compounds should be improved by synthetic biology approaches. To date, the development of robust engineering tools for solar-driven cyanobacterial production systems has lagged considerably behind compared to more common heterotrophic microbial production platforms such as Escherichia coli and Saccharomyces cerevisiae. The focus of this thesis was to develop synthetic biology tools and strategies for cyanobacterium Synechocystis sp. PCC 6803 for efficient and predictable strain engineering and pathway design. The new synthetic biology tools established in this study include the characterisation of thirteen different ribosome binding sites (RBS) instrumental in adjusting the translational efficiency of synthetic pathways in Synechocystis. Nine different integration sites, both in the chromosome and endogenous plasmids, were validated for parallel and alternative expression of the gene of interest. Two expression vector backbones were designed and constructed for parallel and alternative expression strategies. A set of quantitative reporter markers were deployed as analytical tools which allowed the comparative evaluation of the expression of Synechocystis. An assembly system was adapted in Synechocystis for an accelerated pathway design and for a construction platform for expression cassettes or operons. In addition, a series of engineered Synechocystis strains were constructed to investigate whether the redirection of electron and carbon fluxes could enhance the photosynthetic electron flux towards the target end-product. This was accomplished by deleting the competing native flavodiiron protein–dependent electron transfer pathway and introducing an alternative sink for the excited electrons using sucrose as an end-product for electrons. This investigation revealed that a significant proportion of the electrons could be rescued and redirected towards the downstream biosynthetic reactions resulting in improved production efficiency. Furthermore, the potential use of acetate as supplementary carbon source for improving the cyanobacterial production system was addressed, and revealed to have a clear advantage for growth, especially under low light conditions. In summary, the results presented in this thesis provide new synthetic biology tools and engineering strategies for promoting the development of cyanobacteria-based cell factories; they also provide a better understanding of the endogenous regulatory systems in Synechocystis, as a part of the progress towards future biotechnological solutions that will generate sustainable carbon-based products directly from CO2

Single-Column Chromatography with Recycle Lag Analog to Simulated Moving Bed Processes

The chromatography steps dominate the Downstream Processing (DSP) costs of a new biopharmaceutical, which has propelled the biopharmaceutical industry to invest a lot of effort on their improvement in order to reduce the costs of the biopharmaceutical production. Liquid chromatography (LC) is currently the core technique within the DSP strategy for the purification of biopharmaceuticals. Although single-column batch chromatography is simpler to operate than continuous (multicolumn) chromatography, the latter has many advantages over the former, including improved purity, yield, and productivity. The main objective of this thesis is the development of a new chromatographic platform based on a novel single-column device that mimics the operation of multicolumn chromatography through ingenious management and recycling of the mixed fractions exiting the chromatographic column. The platform shares the benefits of the Simulated- Moving-Bed (SMB) technology. However, the newly developed process uses only a single chromatographic column. The conceptual design of the set-up and its mathematical model were successfully established. The laboratory prototype was built focusing on a simple, compact, and versatile design with small footprint. The binary separation of nucleosides by reversedphase chromatography was experimentally realized as proof of concept of the new system. An effort was made in 3D manufacturing of flow distributors and internals to ensure the proper operation of the recycle device and the improvement of its efficiency. A second case study—the capture step of monoclonal antibodies by affinity chromatography on protein A—was successfully used as a demonstration of the applicability of the newly developed process. The new system offers a more compact, less expensive, and simpler-to-operate alternative to multicolumn SMB chromatography. Depending on the efficiency of the recycle device, the single-column process can achieve the same purities as the analogous SMB unit while keeping the specific productivity constant. Moreover, the single-column chromatograph can be easily integrated into the existing downstream processing platforms of complex biopharmaceuticals

Engineering cell-free systems for synthetic biologists

Synthetic biology (synbio) has emerged as a transformative scientific field with immense potential to address a wide-range of global problems. A specific sub-field of synbio utilizes cellular biomolecular machinery outside of a living cell. In theory, these “cell-free” systems offer a simpler approach and unique features compared to cell-based systems for biotechnology development. However, in practice limited accessibility and poor protein synthesis capacity hinder the overall scope and application of cell-free synbio. To address these challenges, it was our goal to create new engineering tools that will help expand the overall utility of cell-free expression systems. Data presented here provides: 1) detailed methods for the in-house preparation of a cost-effective in vitro reconstituted cell-free system, 2) an in-depth proteomic analysis of the system building blocks as a tool to characterize the composition and inform optimization, and 3) an improvement to protein synthesis capacity by modifying the ribosome composition. Furthermore, a critical assessment of the regulatory landscape is provided, promoting the safe and responsible use of cell-free synbio

A model-based approach towards accelerated process development: A case study on chromatography

Process development is typically associated with lengthy wet-lab experiments for the identification of good candidate setups and operating conditions. In this paper, we present the key features of a model-based approach for the identification and assessment of process design space (DSp), integrating the analysis of process performance and flexibility. The presented approach comprises three main steps: (1) model development & problem formulation, (2) DSp identification, and (3) DSp analysis. We demonstrate how such an approach can be used for the identification of acceptable operating spaces that enable the assessment of different operating points and quantification of process flexibility. The above steps are demonstrated on Protein A chromatographic purification of antibody-based therapeutics used in biopharmaceutical manufacturing.Comment: Pre-print paper under revie