Soft sensor based on Raman spectroscopy for the in-line monitoring of metabolites and polymer quality in the biomanufacturing of polyhydroxyalkanoates.

Polyhydroxyalkanoates (PHA) are among the most promising bio-based alternatives to conventional petroleum-based plastics. These biodegradable polyesters can in fact be produced by fermentation from bacteria like Cupriavidus necator, thus reducing the environmental footprint of the manufacturing process. However, ensuring consistent product quality attributes is a major challenge of biomanufacturing. To address this issue, the implementation of real-time monitoring tools is essential to increase process understanding, enable a prompt response to possible process deviations and realize on-line process optimization. In this work, a soft sensor based on in situ Raman spectroscopy was developed and applied to the in-line monitoring of PHA biomanufacturing. This strategy allows the collection of quantitative information directly from the culture broth, without the need for sampling, and at high frequency. In fact, through an optimized multivariate data analysis pipeline, this soft sensor allows monitoring cell dry weight, as well as carbon and nitrogen source concentrations with root mean squared errors (RMSE) equal to 3.71, 7 and 0.03 g/L, respectively. In addition, this tool allows the in-line monitoring of intracellular PHA accumulation, with an RMSE of 14 gPHA/gCells. For the first time, also the number and weight average molecular weights of the polymer produced could be monitored, with RMSE of 8.7E4 and 11.6E4 g/mol, respectively. Overall, this work demonstrates the potential of Raman spectroscopy in the in-line monitoring of biotechnology processes, leading to the simultaneous measurement of several process variables in real time without the need of sampling and labor-intensive sample preparations.

Role of the gradient slope during the product internal recycling for the multicolumn countercurrent solvent gradient purification of PEGylated proteins.

Protein PEGylation, i.e. functionalization with poly(ethylene glycol) chains, has been demonstrated an efficient way to improve the therapeutic index of these biopharmaceuticals. We demonstrated that Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) is an efficient process for the separation of PEGylated proteins (Kim et al., Ind. and Eng. Chem. Res. 2021, 60, 29, 10764-10776), thanks to the internal recycling of product-containing side fractions. This recycling phase plays a critical role in the economy of MCSGP as it avoids wasting valuable product, but at the same time impacts its productivity extending the overall process duration. In this study, our aim is to elucidate the role of the gradient slope within this recycling stage on the yield and productivity of MCSGP for two case-studies: PEGylated lysozyme and an industrially relevant PEGylated protein. While all the examples of MCSGP in the literature refer to a single gradient slope in the elution phase, for the first time we systematically investigate three different gradient configurations: i) a single gradient slope throughout the entire elution, ii) recycling with an increased gradient slope, to shed light on the competition between volume of the recycled fraction and required inline dilution and iii) an isocratic elution during the recycling phase. The dual gradient elution proved to be a valuable solution for boosting the recovery of high-value products, with the potential for alleviating the pressure on the upstream processing.

Design and economic investigation of a Multicolumn Countercurrent Solvent Gradient Purification unit for the separation of an industrially relevant PEGylated protein.

Conjugation of biopharmaceuticals to polyethylene glycol chains, known as PEGylation, is nowadays an efficient and widely exploited strategy to improve critical properties of the active molecule, including stability, biodistribution profile, and reduced clearance. A crucial step in the manufacturing of PEGylated drugs is the purification. The reference process in industrial settings is single-column chromatography, which can meet the stringent purity requisites only at the expenses of poor product recoveries. A valuable solution to this trade-off is the Multicolumn Countercurrent Solvent Gradient Purification (MCSGP), which allows the internal and automated recycling of product-containing side fractions that are typically discarded in the batch processes. In this study, an ad hoc design procedure was applied to the single-column batch purification of an industrially relevant PEGylated protein, with the aim of defining optimal collection window, elution duration and elution buffer ionic strength to be then transferred to the MCSGP. This significantly alleviates the design of the continuous operation, subjected to manifold process parameters. The MCSGP designed by directly transferring the optimal parameters allowed to improve the yield and productivity by 8.2% and 17.8%, respectively, when compared to the corresponding optimized batch process, ensuring a purity specification of 98.0%. Once the efficacy of MCSGP was demonstrated, a detailed analysis of its cost of goods was performed and compared to the case of single-column purification. To the best of our knowledge, this is the first example of a detailed economic investigation of the MCSGP across different manufacturing scenarios and process cadences of industrial relevance, which demonstrated not only the viability of this continuous technology but also its flexibility.

Continuous countercurrent chromatographic twin-column purification of oligonucleotides: The role of the displacement effect.

Oligonucleotides (ONs) are breaking through in the biopharmaceutical industry as a promising class of biotherapeutics. The main success of these molecules is due to their peculiar way of acting in the cellular process, regulating the gene expression and hence influencing the protein synthesis at a pretranslational level. Although the Food and Drug Administration (FDA) already approved a few ON-based therapeutics, their production cost strongly limits large-scale manufacturing: a situation that can be alleviated through process intensification. In this study, we address this problem by developing an efficient and continuous chromatographic purification process for ONs. In particular, we considered the chromatographic purification of an ON crude prepared by chemical synthesis using anion exchange resins. We demonstrate that in this system the competitive adsorption of the various species on the same sites of the resin leads to the displacement of the more weakly adsorbing species by the more strongly adsorbing ones. This phenomenon affects the behavior of the chromatographic units and it has been investigated in detail. Then, we developed a continuous countercurrent solvent gradient purification (MCSGP) process, which can significantly improve the productivity and buffer consumption compared to a classical single-column, batch chromatographic process.

Hybrid Models for the simulation and prediction of chromatographic processes for protein capture.

The biopharmaceutical industries are continuously faced with the pressure to reduce the development costs and accelerate development time scales. The traditional approach of heuristic-based or platform process-based optimization is soon getting obsolete, and more generalized tools for process development and optimization are required to keep pace with the emerging trends. Thus, advanced model-based methods that can reduce the can ensure accelerated development of robust processes with minimal experiments are necessary. Though mechanistic models for chromatography are quite popular, their success is limited by the need to have accurate knowledge of adsorption isotherms and mass transfer kinetics. As an alternative, in this work, a hybrid modeling approach is proposed. Thereby, the chromatographic unit behavior is learned by a combination of neural network and mechanistic model while fitting suitable experimental breakthrough curves. Since this approach does not require identifying suitable mechanistic assumptions for all the phenomena, it can be developed with lower effort. Thus, allowing the scientists to concentrate their focus on process development. The performance of the hybrid model is compared with the mechanistic Lumped kinetic Model for in-silico data and experiments conducted on a system of industrial relevance. The flexibility of the hybrid modeling approach results in about three times higher accuracies compared to Lumped Kinetic Model. This is validated for five different isotherm models used to simulate data, with the hybrid model showing about two to three times lower prediction errors in all the cases. Not only in prediction, but we could also show that the hybrid model is more robust in extrapolating across process conditions with about three times lower error than the LKM. Additionally, it could be demonstrated that an appropriately tailored formulation of the hybrid model can be used to generate representations for the underlying principles such as adsorption equilibria and mass transfer kinetics.

Analysis and optimal design of batch and two-column continuous chromatographic frontal processes for monoclonal antibody purification.

The increasing demand for efficient and robust processes in the purification of monoclonal antibodies (mAbs) has recently brought frontal chromatography to the forefront. Applied during the polishing step, it enables the removal of high molecular weight aggregates from the target product, achieving high purities. Typically, this process is operated in batch using a single column, which makes it intrinsically subjected to a purity-yield tradeoff. This means that high purities can only be achieved at the cost of lowering the product yield and vice versa. Recently, a two-column continuous implementation of frontal chromatography, referred to as Flow2, was developed. Despite being able of alleviating the purity-yield tradeoff typical of batch operations, the increase in the number of process parameters complicates its optimal design, with the risk of not exploiting its full potential. In this study, we developed an ad hoc design procedure (DP) suitable for the optimization of both batch frontal chromatography and Flow2 in terms of purity, yield, and productivity. This procedure provided similar results as a multiobjective optimization based on genetic algorithm but with lower computational effort. Then, batch and Flow2 operated at their optimal conditions were compared. Besides showing a more favorable Pareto front of yield and productivity at a specified purity, the Flow2 process demonstrated improved robustness compared to the batch process with respect to modifications in the loading linear velocity, washing buffer ionic strength and loading time, thus providing an appealing operation for integrated processes.

Modern trends in downstream processing of biotherapeutics through continuous chromatography: The potential of Multicolumn Countercurrent Solvent Gradient Purification.

Single-column (batch) preparative chromatography is the technique of choice for purification of biotherapeutics but it is often characterized by an intrinsic limitation in terms of yield-purity trade-off, especially for separations containing a larger number of product-related impurities. This drawback can be alleviated by employing multicolumn continuous chromatography. Among the different methods working in continuous mode, in this paper we will focus in particular on Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) which has been specifically designed for challenging separations of target biomolecules from their product-related impurities. The improvements come from the automatic internal recycling of the impure fractions inside the chromatographic system, which results in an increased yield without compromising the purity of the pool. In this article, steps of the manufacturing process of biopharmaceuticals will be described, as well as the advantages of continuous chromatography over batch processes, by particularly focusing on MCSGP.

Model based strategies towards protein A resin lifetime optimization and supervision.

The high cost of protein A resins drives the biopharmaceutical industry to maximize its lifetime, which is limited by several processes, usually referred to as resin aging. In this work, two model based strategies are presented, aiming to control and improve the resin lifetime. The first approach, purely statistical, enables qualitative monitoring of the column state and prediction of column performance indicators (e.g. yield, purity and dynamic binding capacity) from chromatographic on-line data (e.g. UV signal). The second one, referred to as hybrid modeling, is based on a lumped kinetic model, which includes two aging parameters fitted on several resin cycling experimental campaigns with varying cleaning procedures (CP). The first aging parameter accounts for binding capacity deterioration (caused by ligand degradation, leaching, and pore occlusion), while the second accounts for a decreased mass transfer rate (mainly caused by fouling). The hybrid model provides important insights into the prevailing aging mechanism as a function of the different CPs. In addition, it can be applied to model based CP optimization and yield forecasting with the capability of state estimation corrections based on on-line process information. Both approaches show promising results, which could help to significantly extend the resin lifetime. This comes along with increased understanding, reduced experimental effort, decreased cost of goods, and improved process robustness.

From batch to continuous chromatographic purification of a therapeutic peptide through multicolumn countercurrent solvent gradient purification.

A twin-column Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) process has been developed for the purification of a therapeutic peptide, glucagon, from a crude synthetic mixture. This semi-continuous process uses two identical columns operating either in interconnected or in batch mode, thus enabling the internal recycle of the portions of the eluting stream which do not comply with purity specifications. Because of this feature, which actually results in the simulated countercurrent movement of the stationary phase with respect to the mobile one, the yield-purity trade-off typical of traditional batch preparative chromatography can be alleviated. Moreover, the purification process can be completely automatized. Aim of this work is to present a simple procedure for the development of the MCSGP process based on a single batch experiment, in the case of a therapeutic peptide of industrial relevance. This allowed to recover roughly 90% of the injected glucagon in a purified pool with a purity of about 90%. A comparison between the performance of the MCSGP process and the classical single column batch process indicates that percentage increase in the recovery of target product is +23% when transferring the method from batch conditions to MCSGP, with an unchanged purity of around 89%. This improvement comes at the expenses of a reduction of about 38% in productivity.

Current trends in the production of biodegradable bioplastics: The case of polyhydroxyalkanoates.

The global pollution caused by plastics and microplastics is stimulating intense research towards more environmentally friendly materials, preserving the remarkable application characteristics of the currently available polymers. Among these, polyhydroxyalkanoates (PHAs) have been hailed as the solution to replace conventional, oil-based plastics. Given their biodegradable nature and mechanical properties, their use can be envisioned in a wide range of applications reducing the environmental footprint. Several types of processes have been proposed for their production, which can be grouped in three main classes: (i) microbiological, (ii) enzymatic and (iii) chemical processes. Given the significant amount of literature available on this topic, this review aims to critically analyse what has been proposed so far in each of these classes, with specific reference to their potential to provide bioplastics that can actually replace the currently available materials. A comparison is made, based on the following aspects: achievable molecular structures (such as molecular weight and composition distributions), raw-material and production costs and availability of large-scale production technologies. Finally, some considerations and ideas on what should be further investigated and implemented to realize the economically sustainable production of PHA are brought forward.

Cell culture process metabolomics together with multivariate data analysis tools opens new routes for bioprocess development and glycosylation prediction.

Multivariate latent variable methods have become a popular and versatile toolset to analyze bioprocess data in industry and academia. This work spans such applications from the evaluation of the role of the standard process variables and metabolites to the metabolomics level, that is, to the extensive number metabolic compounds detectable in the extracellular and intracellular domains. Given the substantial effort currently required for the measurement of the latter groups, a tailored methodology is presented that is capable of providing valuable process insights as well as predicting the glycosylation profile based on only four experiments measured over 12 cell culture days. An important result of the work is the possibility to accurately predict many of the glycan variables based on the information of three experiments. An additional finding is that such predictive models can be generated from the more accessible process and extracellular information only, that is, without including the more experimentally cumbersome intracellular data. With regards to the incorporation of omics data in the standard process analytics framework in the future, this works provides a comprehensive data analysis pathway which can efficiently support numerous bioprocessing tasks.

Hybrid-EKF: Hybrid model coupled with extended Kalman filter for real-time monitoring and control of mammalian cell culture.

In a decade when Industry 4.0 and quality by design are major technology drivers of biopharma, automated and adaptive process monitoring and control are inevitable requirements and model-based solutions are key enablers in fulfilling these goals. Despite strong advancement in process digitalization, in most cases, the generated datasets are not sufficient for relying on purely data-driven methods, whereas the underlying complex bioprocesses are still not completely understood. In this regard, hybrid models are emerging as a timely pragmatic solution to synergistically combine available process data and mechanistic understanding. In this study, we show a novel application of the hybrid-EKF framework, that is, hybrid models coupled with an extended Kalman filter for real-time monitoring, control, and automated decision-making in mammalian cell culture processing. We show that, in the considered application, the predictive monitoring accuracy of such a framework improves by at least 35% when developed with hybrid models with respect to industrial benchmark tools based on PLS models. In addition, we also highlight the advantages of this approach in industrial applications related to conditional process feeding and process monitoring. With regard to the latter, for an industrial use case, we demonstrate that the application of hybrid-EKF as a soft sensor for titer shows a 50% improvement in prediction accuracy compared with state-of-the-art soft sensor tools.

Oligonucleotides: Current Trends and Innovative Applications in the Synthesis, Characterization, and Purification.

Oligonucleotides (ONs) are gaining increasing importance as a promising novel class of biopharmaceuticals. Thanks to their fundamental role in gene regulation, they can be used to develop custom-made drugs (also called N-to-1) able to act on the gene expression at pre-translational level. With recent approvals of ON-based therapeutics by the Food and Drug Administration (FDA), a growing demand for high-quality chemically modified ONs is emerging and their market is expected to impressively prosper in the near future. To satisfy this growing market demand, a scalable and economically sustainable ON production is needed. In this paper, the state of the art of the whole ON production process is illustrated with the aim of highlighting the most promising routes toward the auspicated market-size production. In particular, the most recent advancements in both the upstream stage, mainly based on solid-phase synthesis and recombinant technology, and the downstream one, focusing on chromatographic techniques, are reviewed. Since ON production is projected to expand to the large scale, automatized multicolumn countercurrent technologies will reasonably be required soon to replace the current ones based on batch single-column operations. This consideration is supported by a recent cutting-edge application of continuous chromatography for the ON purification.

Design space and robustness analysis of batch and counter-current frontal chromatography processes for the removal of antibody aggregates.

Increasing molecular diversity and market competition requires biopharmaceutical manufacturers to intensify their processes. In this respect, frontal chromatography on cation exchange resins has shown its potential to effectively remove aggregates. However, yield losses during the wash step need to be accepted in order to ensure robust product quality. In this work, we present a novel counter-current frontal chromatography process called Flow2, which uses inline dilution during an interconnected wash phase to allow high monomer recovery without contaminating the product pool with impurities. Its model-based design spaces under purity and yield constraints are compared with those corresponding to traditional batch processes in terms of size and process attributes yield and productivity. The Flow2 process shows the largest extent of feasible operating points independent of feed conditions. Thereby, it allows the implementation of higher ionic strength wash, thus widening the range of operating conditions resulting in yields above 95% compared to batch processes. Productivities of batch and counter-current processes are the same at short regeneration times and equal residence time. However, long regeneration times, while influencing the size of the Flow2 design space, are not detrimental for its productivity resulting in twice as high values as obtained for the batch process. Furthermore, process robustness is evaluated by the ability of the process to maintain the required product quality when subjected to process parameter perturbations. It is found that the Flow2 process is able to retain a larger design space associated also with higher yields showing its ability to improve process attributes without sacrificing robustness at the same time.

Process-wide control and automation of an integrated continuous manufacturing platform for antibodies.

Integrated continuous manufacturing is entering the biopharmaceutical industry. The main drivers range from improved economics, manufacturing flexibility, and more consistent product quality. However, studies on fully integrated production platforms have been limited due to the higher degree of system complexity, limited process information, disturbance, and drift sensitivity, as well as difficulties in digital process integration. In this study, we present an automated end-to-end integrated process consisting of a perfusion bioreactor, CaptureSMB, virus inactivation (VI), and two polishing steps to produce an antibody from an instable cell line. A supervisory control and data acquisition (SCADA) system was developed, which digitally integrates unit operations and analyzers, collects and centrally stores all process data, and allows process-wide monitoring and control. The integrated system consisting of bioreactor and capture step was operated initially for 4 days, after which the full end-to-end integrated run with no interruption lasted for 10 days. In response to decreasing cell-specific productivity, the supervisory control adjusted the loading duration of the capture step to obtain high capacity utilization without yield loss and constant antibody quantity for subsequent operations. Moreover, the SCADA system coordinated VI neutralization and discharge to enable constant loading conditions on the polishing unit. Lastly, the polishing was sufficiently robust to cope with significantly increased aggregate levels induced on purpose during virus inactivation. It is demonstrated that despite significant process disturbances and drifts, a robust process design and the supervisory control enabled constant (optimum) process performance and consistent product quality.

Readily Adsorbable Thermoresponsive Polymers for the Preparation of Smart Cell-Culturing Surfaces on Site.

The efficacy of several cell therapy products is directly impacted by trypsinization, which can diminish the engrafting capacity of transplanted cells by cleaving cell surface receptors. Thermoresponsive surfaces can alleviate this drawback, enabling temperature-driven and enzyme-free cell harvesting. However, the production of thermoresponsive surfaces relies on dedicated and complex equipment, often involving protocols dependent on high surface activation energies that prevent the development of scalable and universal platforms. In this work, we developed thermoresponsive copolymers incorporating styrene units that enable the copolymer adsorption on tissue culture polystyrene surfaces from an alcoholic solution in a short time, regardless of the vessel size and geometry, and without any particular equipment. In this way, the procedure can be performed with minimal effort by the end user on any surface. The thermoresponsive copolymers were synthesized via reversible addition-fragmentation chain transfer polymerization, providing high control over the polymer microstructure, a key parameter for tuning its cloud point and architecture. Block copolymers comprising a thermoresponsive segment and a polystyrene block exhibited optimal adhesion on conventional cell culture surfaces and permitted a more efficient temperature-mediated harvesting of adipose-derived stromal cells and Chinese hamster ovary cells compared to their statistical counterparts. To expand the application of this polymer deposition protocol to serum-free cell culture, we also considered the polymer modification with the tripeptide arginine-glycine-aspartic acid, known to promote the cell adhesion to synthetic substrates. The incorporation of this peptide enabled the collection in serum-free conditions of intact cell sheets from surfaces prepared shortly before their usage.

Development of Mammalian Cell Perfusion Cultures at Lab Scale: From Orbitally Shaken Tubes to Benchtop Bioreactors.

This chapter introduces the necessary concepts to develop mammalian cell perfusion cultures for the expression of therapeutic proteins at lab scale. We highlight the operation of the orbitally shaken tubes and of a classical glass vessel reactor system coupled to an external alternating tangential flow (ATF) device. Two different experiments can be performed in the shake-tube system: (1) the VCDmax experiment exploring the maximum achievable viable cell density at a given medium exchange rate and (2) the VCDSS experiment for the prediction of process performance at constant viable cell density and a given medium exchange rate for the design of the benchtop bioreactor process. In addition, the operation of the benchtop system is discussed containing start-up and control procedures for a long-term production run.

Modeling the nonlinear behavior of a bioactive peptide in reversed-phase gradient elution chromatography.

The thermodynamic behavior of octreotide, a cyclic octapeptide with important pharmaceutical functions, has been simulated under reversed-phase gradient elution conditions. To this end, adsorption behavior was firstly investigated in isocratic conditions, under a variety of water/acetonitrile + 0.02% (v/v) trifluoroacetic acid (TFA) mixtures as mobile phase by using a Langmuir isotherm. Organic modifier was varied in the range between 23 and 28% (v/v). Adsorption isotherms were determined by means of the so-called Inverse Method (IM) with a minimum amount of peptide. The linear solvent strength (LSS) model was used to find the correlation between isotherm parameters and mobile phase composition. This study contributes to enlarge our knowledge on the chromatographic behavior under nonlinear gradient conditions of peptides. In particular, it focuses on a cyclic octapeptide.

Bioprocessing in the Digital Age: The Role of Process Models.

In this age of technology, the vision of manufacturing industries built of smart factories is not a farfetched future. As a prerequisite for Industry 4.0, industrial sectors are moving towards digitalization and automation. Despite its tremendous growth reaching a sales value of worth $188 billion in 2017, the biopharmaceutical sector distinctly lags in this transition. Currently, the challenges are innovative market disruptions such as personalized medicine as well as increasing commercial pressure for faster and cheaper product manufacturing. Improvements in digitalization and data analytics have been identified as key strategic activities for the next years to face these challenges. Alongside, there is an emphasis by the regulatory authorities on the use of advanced technologies, proclaimed through initiatives such as Quality by Design (QbD) and Process Analytical Technology (PAT). In the manufacturing sector, the biopharmaceutical domain features some of the most complex and least understood processes. Thereby, process models that can transform process data into more valuable information, guide decision-making, and support the creation of digital and automated technologies are key enablers. This review summarizes the current state of model-based methods in different bioprocess related applications and presents the corresponding future vision for the biopharmaceutical industry to achieve the goals of Industry 4.0 while meeting the regulatory requirements.

Understanding mAb aggregation during low pH viral inactivation and subsequent neutralization.

Monoclonal antibodies (mAbs) and related recombinant proteins continue to gain importance in the treatment of a great variety of diseases. Despite significant advances, their manufacturing can still present challenges owing to their molecular complexity and stringent regulations with respect to product purity, stability, safety, and so forth. In this context, protein aggregates are of particular concern due to their immunogenic potential. During manufacturing, mAbs routinely undergo acidic treatment to inactivate viral contamination, which can lead to their aggregation and thereby to product loss. To better understand the underlying mechanism so as to propose strategies to mitigate the issue, we systematically investigated the denaturation and aggregation of two mAbs at low pH as well as after neutralization. We observed that at low pH and low ionic strength, mAb surface hydrophobicity increased whereas molecular size remained constant. After neutralization of acidic mAb solutions, the fraction of monomeric mAb started to decrease accompanied by an increase on average mAb size. This indicates that electrostatic repulsion prevents denatured mAb molecules from aggregation under acidic pH and low ionic strength, whereas neutralization reduces this repulsion and coagulation initiates. Limiting denaturation at low pH by d-sorbitol addition or temperature reduction effectively improved monomer recovery after neutralization. Our findings might be used to develop innovative viral inactivation procedures during mAb manufacturing that result in higher product yields.