Process analytical technology (PAT) for biopharmaceutical products

Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform

Pharmaceutical manufacturing is reliant upon bioprocessing approaches to generate the range of therapeutic products that are available today. The high cost of production, susceptibility to process failure, and requirement to achieve consistent, high-quality product means that process monitoring is paramount during manufacturing. Process analytic technologies (PAT) are key to ensuring high quality product is produced at all stages of development. Spectroscopy-based technologies are well suited as PAT approaches as they are non-destructive and require minimum sample preparation. This study explored the use of a novel attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy platform, which utilises disposable internal reflection elements (IREs), as a method of upstream bioprocess monitoring. The platform was used to characterise organism health and to quantify cellular metabolites in growth media using quantification models to predict glucose and lactic acid levels both singularly and combined. Separation of the healthy and nutrient deficient cells within PC space was clearly apparent, indicating this technique could be used to characterise these classes. For the metabolite quantification, the binary models yielded R 2 values of 0.969 for glucose, 0.976 for lactic acid. When quantifying the metabolites in tandem using a multi-output partial least squares model, the corresponding R 2 value was 0.980. This initial study highlights the suitability of the platform for bioprocess monitoring and paves the way for future in-line developments.

Is it advantageous to use quality by design (QbD) to develop nanoparticle-based dosage forms for parenteral drug administration?

Parenteral administration is one of the most commonly used drug delivery routes for nanoparticle-based dosage forms, such as lipid-based and polymeric nanoparticles. For the treatment of various diseases, parenteral administration include intravenous, subcutaneous, and intramuscular route. In drug development phase, multiparameter strategy with a focus on drug physicochemical properties and the specificity of the administration route is required. Nanoparticle properties in terms of size and targeted delivery, among others, are able to surpass many drawbacks of conventional dosage forms, but these unique properties can be a bottleneck for approval by regulatory authorities. Quality by Design (QbD) approach has been widely utilized in development of parenteral nanoparticle-based dosage forms. It fosters knowledge of product and process quality by involving sound scientific data and risk assessment strategies. A full and comprehensive investigation into the state of implementation and applications of the QbD approach in these complex drug products can highlight the gaps and challenges. In this review, the analysis of critical attributes and Design of Experiment (DoE) approach in different nanoparticulate systems, together with the proper utilization of Process Analytical Technology (PAT) applications are described. The essential of QbD approach for the design and development of nanoparticle-based dosage forms for delivery via parenteral routes is discussed thoroughly.

Adaptive modeling optimized by the data fusion strategy: Real-time dying cell percentage prediction using capacitance spectroscopy

The previous research showcased a partial least squares (PLS) regression model accurately predicting cell death percentages using in-line capacitance spectra. The current study advances the model accuracy through adaptive modeling employing a data fusion approach. This strategy enhances prediction performance by incorporating variables from the Cole-Cole model, conductivity and its derivatives over time, and Mahalanobis distance into the predictor matrix (X-matrix). Firstly, the Cole-Cole model, a mechanistic model with parameters linked to early cell death onset, was integrated to enhance prediction performance. Secondly, the inclusion of conductivity and its derivatives over time in the X-matrix mitigated prediction fluctuations resulting from abrupt conductivity changes during process operations. Thirdly, Mahalanobis distance, depicting spectral changes relative to a reference spectrum from a previous time point, improved model adaptability to independent test sets, thereby enhancing performance. The final data fusion model substantially decreased root-mean squared error of prediction (RMSEP) by around 50%, which is a significant boost in prediction accuracy compared to the prior PLS model. Robustness against reference spectrum selection was confirmed by consistent performance across various time points. In conclusion, this study illustrates that the data fusion strategy substantially enhances the model accuracy compared to the previous model relying solely on capacitance spectra.

What should next-generation analytical platforms for biopharmaceutical production look like?

Biotherapeutic products, particularly complex products such as monoclonal antibodies (mAbs), have as many as 20-30 critical quality attributes (CQAs), thereby requiring a collection of orthogonal, high-resolution analytical tools for characterization and making characterization a resource-intensive task. As discussed in this Opinion, the need to reduce the cost of developing biotherapeutic products and the need to adopt Industry 4.0 and eventually Industry 5.0 paradigms are driving a reappraisal of existing analytical platforms. Next-generation platforms will have reduced offline testing, renewed focus on online testing and real-time monitoring, multiattribute monitoring, and extensive use of advanced data analytics and automation. They will be more complex, more sensitive, resource lean, and more responsive compared with existing platforms.

Multi-dimensional technology - Recent advances and applications for biotherapeutic characterization

This review provides an overview of the latest advancements and applications in multi-dimensional liquid chromatography coupled with mass spectrometry (mD-LC-MS), covering aspects such as inter-laboratory studies, digestion strategy, trapping column, and multi-level analysis. The shift from an offline to an online workflow reduces sample processing artifacts, analytical variability, analysis time, and the labor required for data acquisition. Over the past few years, this technique has demonstrated sufficient maturity for application across a diverse range of complex products. Moreover, there is potential for this strategy to evolve into an integrated process analytical technology tool for the real-time monitoring of monoclonal antibody quality. This review also identifies emerging trends, including its application to new modalities, the possibility of evaluating biological activity within the mD-LC set-up, and the consideration of multi-dimensional capillary electrophoresis as an alternative to mD-LC. As mD-LC-MS continues to evolve and integrate emerging trends, it holds the potential to shape the next generation of analytical tools, offering exciting possibilities for enhanced characterization and monitoring of complex biopharmaceutical products.

In situ process analytical technology for real time viable cell density and cell viability during live-virus vaccine production

Viable cell density (VCD) and cell viability (CV) are key performance indicators of cell culture processes in biopharmaceutical production of biologics and vaccines. Traditional methods for monitoring VCD and CV involve offline cell counting assays that are both labor intensive and prone to high variability, resulting in sparse sampling and uncertainty in the obtained data. Process analytical technology (PAT) approaches offer a means to address these challenges. Specifically, in situ probe-based measurements of dielectric spectroscopy (also commonly known as capacitance) can characterize VCD and CV continuously in real time throughout an entire process, enabling robust process characterization. In this work, we propose in situ dielectric spectroscopy as a PAT tool for real time analysis of live-virus vaccine (LVV) production. Dielectric spectroscopy was collected across 25 discreet frequencies, offering a thorough evaluation of the proposed technology. Correlation of this PAT methodology to traditional offline cell counting assays was performed, in which VCD and CV were both successfully predicted using dielectric spectroscopy. Both univariate and multivariate data analysis approaches were evaluated for their potential to establish correlation between the in situ dielectric spectroscopy and offline measurements. Univariate analysis strategies are presented for optimal single frequency selection. Multivariate analysis, in the form of partial least squares (PLS) regression, produced significantly higher correlations between dielectric spectroscopy and offline VCD and CV data, as compared to univariate analysis. Specifically, by leveraging multivariate analysis of dielectric information from all 25 spectroscopic frequencies measured, PLS models performed significantly better than univariate models. This is particularly evident during cell death, where tracking VCD and CV have historically presented the greatest challenge. The results of this work demonstrate the potential of both single and multiple frequency dielectric spectroscopy measurements for enabling robust LVV process characterization, suggesting that broader application of in situ dielectric spectroscopy as a PAT tool in LVV processes can provide significantly improved process understanding. To the best of our knowledge, this is the first report of in situ dielectric spectroscopy with multivariate analysis to successfully predict VCD and CV in real time during live virus-based vaccine production.

Application of Formulation Principles to Stability Issues Encountered During Processing, Manufacturing, and Storage of Drug Substance and Drug Product Protein Therapeutics

The field of formulation and stabilization of protein therapeutics has become rather extensive. However, most of the focus has been on stabilization of the final drug product. Yet, proteins experience stress and degradation through the manufacturing process, starting with fermentaition. This review describes how formulation principles can be applied to stabilize biopharmaceutical proteins during bioprocessing and manufacturing, considering each unit operation involved in prepration of the drug substance. In addition, the impact of the container on stabilty is discussed as well.

Process engineering of natural killer cell-based immunotherapy

Cell therapy offers the potential for curative treatment of cancers. Although T cells have been the predominantly used cell type, natural killer (NK) cells have attracted great attention owing to their ability to kill cancer cells and because they are naturally suitable for allogeneic applications. Upon stimulation by cytokines or activation by a target cell, NK cells proliferate and expand their population. These cytotoxic NK cells can be cryopreserved and used as an off-the-shelf medicine. The production process for NK cells thus differs from that of autologous cell therapies. We briefly outline key biological features of NK cells, review the manufacturing technologies for protein biologics, and discuss their adaptation for developing robust NK cell biomanufacturing processes.

Continuous multi-membrane chromatography of large viral particles

Continuous multi-column chromatography (CMCC) has been successfully implemented to address biopharmaceutical biomolecule instability, to improve process efficiency, and to reduce facility footprint and capital cost. This paper explores the implementation of a continuous multi-membrane chromatography (CMMC) process, using four membrane units, for a large viral particle in just few weeks. CMMC improves the efficiency of the chromatography step by enabling higher loads with smaller membranes for multiple cycles of column use and enables steady-state continuous bioprocessing. The separation performance of CMMC was compared to a conventional batch chromatographic capture step used at full manufacturing scale. The product step yield was 80% using CMMC versus 65% in batch mode while increasing slightly the relative purity. Furthermore, the total amount of membrane area required for the CMMC approach was approximately 10% of the area needed for batch operation, while realizing similar processing times. Since CMMC uses smaller membrane sizes, it can take advantage of the high flow rates achievable for membrane chromatography that are not typically possible at larger membrane scales due to skid flow rate limitations. As such, CMMC offers the potential for more efficient and cost-effective purification trains.

Automated quality analysis in continuous downstream processes for small-scale applications

Development of integrated, continuous biomanufacturing (ICB) processes brings along the challenge of streamlining the acquisition of data that can be used for process monitoring, product quality testing and process control. Manually performing sample acquisition, preparation, and analysis during process and product development on ICB platforms requires time and labor that diverts attention from the development itself. It also introduces variability in terms of human error in the handling of samples. To address this, a platform for automatic sampling, sample preparation and analysis for use in small-scale biopharmaceutical downstream processes was developed. The automatic quality analysis system (QAS) consisted of an ÄKTA Explorer chromatography system for sample retrieval, storage, and preparation, as well as an Agilent 1260 Infinity II analytical HPLC system for analysis. The ÄKTA Explorer system was fitted with a superloop in which samples could be stored, conditioned, and diluted before being sent to the injection loop of the Agilent system. The Python-based software Orbit, developed at the department of chemical engineering at Lund university, was used to control and create a communication framework for the systems. To demonstrate the QAS in action, a continuous capture chromatography process utilizing periodic counter-current chromatography was set up on an ÄKTA Pure chromatography system to purify the clarified harvest from a bioreactor for monoclonal antibody production. The QAS was connected to the process to collect two types of samples: 1) the bioreactor supernatant and 2) the product pool from the capture chromatography. Once collected, the samples were conditioned and diluted in the superloop before being sent to the Agilent system, where both aggregate content and charge variant composition were determined using size-exclusion and ion-exchange chromatography, respectively. The QAS was successfully implemented during a continuous run of the capture process, enabling the acquisition of process data with consistent quality and without human intervention, clearing the path for automated process monitoring and data-based control.

An adaptive soft-sensor for advanced real-time monitoring of an antibody-drug conjugation reaction

In the production of antibody-drug conjugates (ADCs), the conjugation reaction is a central step defining the final product composition and, hence, directly affecting product safety and efficacy. To enable real-time monitoring, spectroscopic sensors in combination with multivariate regression models have gained popularity in recent years. The extended Kalman filter (EKF) can be used as so-called soft-sensor to fuse sensor predictions with long-horizon forecasts by process models. This enables the dynamic update of the current state and provides increased robustness against experimental noise or model errors. Due to the uncertainty associated with sensor and process models in biopharmaceutical applications, the deployment of such soft-sensors is challenging. In this study, we demonstrate the combination of an uncertainty-aware sensor model with a kinetic reaction model using an EKF to monitor a site-directed ADC conjugation reaction. As the sensor model, a Gaussian process regression model is presented to realize a time-variant determination of the sensor uncertainty. The EKF fuses the time-discrete predictions of the amount of conjugated drug from the sensor model with the time-continuous predictions from the kinetic model. While the ADC species are not distinguishable by on-line recorded UV/Vis spectra, the developed soft-sensor is able to dynamically update all relevant reaction species. It could be shown that the use of time-variant process and sensor noise computation approaches improved the performance of the EKF and achieved a reduction of the prediction error of up to 23% compared with the kinetic model. The developed framework proved to enhance robustness against noisy sensor measurements or wrong model initialization and was successfully transferred from batch to fed-batch mode. In future, this framework could be implemented for model-based process control and be adopted for other ADC conjugation reaction types.

Yeast extracts from different manufacturers and supplementation of amino acids and micro elements reveal a remarkable impact on alginate production by A. vinelandii ATCC9046

BACKGROUND

In research and production, reproducibility is a key factor, to meet high quality and safety standards and maintain productivity. For microbial fermentations, complex substrates and media components are often used. The complex media components can vary in composition, depending on the lot and manufacturing process. These variations can have an immense impact on the results of biological cultivations. The aim of this work was to investigate and characterize the influence of the complex media component yeast extract on cultivations of Azotobacter vinelandii under microaerobic conditions. Under these conditions, the organism produces the biopolymer alginate. The focus of the investigation was on the respiration activity, cell growth and alginate production.

RESULTS

Yeast extracts from 6 different manufacturers and 2 different lots from one manufacturer were evaluated. Significant differences on respiratory activity, growth and production were observed. Concentration variations of three different yeast extracts showed that the performance of poorly performing yeast extracts can be improved by simply increasing their concentration. On the other hand, the results with well-performing yeast extracts seem to reach a saturation, when their concentration is increased. Cultivations with poorly performing yeast extract were supplemented with grouped amino acids, single amino acids and micro elements. Beneficial results were obtained with the supplementation of copper sulphate, cysteine or a combination of both. Furthermore, a correlation between the accumulated oxygen transfer and the final viscosity (as a key performance indicator), was established.

CONCLUSION

The choice of yeast extract is crucial for A. vinelandii cultivations, to maintain reproducibility and comparability between cultivations. The proper use of specific yeast extracts allows the cultivation results to be specifically optimised. In addition, supplements can be applied to modify and improve the properties of the alginate. The results only scratch the surface of the underlying mechanisms, as they are not providing explanations on a molecular level. However, the findings show the potential of optimising media containing yeast extract for alginate production with A. vinelandii, as well as the potential of targeted supplementation of the media.

Real-time in situ monitoring of CRM-197 and polysaccharide conjugation reaction by fluorescence spectroscopy

Aims: Process analytical technology (PAT) is increasingly being adopted within the pharmaceutical industry to build quality into a process. Development of PAT that provides real-time in situ analysis of critical quality attributes are highly desirable for rapid, improved process development. Conjugation of CRM-197 with pneumococcal polysaccharides to produce a desired pneumococcal conjugate vaccine is a significantly intricate process that can tremendously benefit from real-time process monitoring. Methods: In this work, a fluorescence-based PAT methodology is described to elucidate CRM-197-polysacharide conjugation kinetics in real time. Results & conclusion: In this work, a fluorescence-based PAT methodology is described to elucidate CRM-197-polysacharide conjugation kinetics in real time.

Near-infrared spectroscopy based monitoring of all 20 amino acids in mammalian cell culture broth

The biopharmaceutical industry extensively employs Chinese hamster ovary (CHO) cell culture for monoclonal antibody production. Amino acids represent an essential source of nutrients in all CHO cell culture media, and their concentration is known to significantly impact cell viability, titre, and monoclonal antibody critical quality attributes. In this study, a robust Fourier transform near-infrared spectroscopy (FT-NIR) based quantification method has been developed for of all 20 amino acids (0-24 mM), as well as concentrations of glucose (0-6.7 mg mL^-1), lactate (0-2.7 mg mL^-1), and trastuzumab (0-2.5 mg mL^-1) in the CHO cell culture. Near infra-red absorbance spectrum in the range of 4000-11,000 cm^-1 were acquired, and spectra pre-processing through smoothening and derivatives were employed to enhance key characteristic signals. High-performance liquid chromatography with pre-column derivatization was used as the orthogonal analytical tool for quantification. Principal component analysis and partial least squares regression were employed for region selection and calibration model development, respectively. The results demonstrate that a good calibration statistic with the acceptable coefficient of determinations for both calibration (R_c² = 0.94-0.99) and prediction (R_p² = 0.83-0.98) could be achieved, along with high RPD values (>3) for all components except alanine (2.4). The external validation study also exhibited a satisfactory outcome (R_EV² = 0.89-0.99, RMSE = 0.04-1.04), validating the model's ability to predict the concentrations of the respective species. The calibration models were successfully applied for at-line monitoring of two perfusion runs on a 10 L scale. To our knowledge, this is the first application where NIR spectroscopy-based measurement of all 20 amino acids in mammalian cell culture samples has been demonstrated. The proposed tool can play a critical role as biopharma manufacturers implement continuous processing as well as for facilitating process analytical technology-based control of mammalian cell culture processes.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Continuous integrated manufacturing for biopharmaceuticals: A new paradigm or an empty promise?

Continuous integrated bioprocessing has elicited considerable interest from the biopharma industry for the many purported benefits it promises. Today many major biopharma manufacturers around the world are engaged in the development of continuous process platforms for their products. In spite of great potential, the path toward continuous integrated bioprocessing remains unclear for the biologics industry due to legacy infrastructure, process integration challenges, vague regulatory guidelines, and a diverging focus toward novel therapies. In this article, we present a review and perspective on this topic. We explore the status of the implementation of continuous integrated bioprocessing among biopharmaceutical manufacturers. We also present some of the key hurdles that manufacturers are likely to face during this implementation. Finally, we hypothesize that the real impact of continuous manufacturing is likely to come when the cost of manufacturing is a substantial portion of the cost of product development, such as in the case of biosimilar manufacturing and emerging economies.

FcγRIIIA affinity chromatography complements conventional functional characterization of rituximab

Analytical and functional characterization of batches of biologics/biosimilar products are imperative towards qualifying them for pre-clinical and clinical investigations. Several orthogonal strategies are employed to characterize the functional attributes of these drugs. However, the use of conventional techniques for online monitoring of functional attributes is not feasible. Liquid chromatography is one of the crucial unit operations during the downstream processing of biopharmaceuticals. In this work, we have demonstrated the utility of FcγRIIIA affinity chromatography as an independent quantitative functional characterization tool. FcγRIIIA affinity chromatography aided in sequential elution of Rituximab glycoform mixtures, based on varying levels of galactosylation, and thereby the affinity for the receptor protein. The predominant glycans present in the three Rituximab glycoform mixture peaks were G0F, G1F, and G2F, respectively. Dissociation rate constants were derived from the chromatographic elution profiles by the peak profiling method, for the control and glucose stress conditions. The glucose stress conditions did not result in unfavorable binding kinetics of Rituximab and FcγRIIIA. The dissociation rate constants of the glycoform mixture 2, predominantly consisting of G1F, were similar to the dissociation rate constants obtained by surface plasmon resonance. Moreover, the glycosylation profiles obtained from chromatographic estimation can be corroborated with the ADCC activity. However, the ex vivo ADCC reporter assay indicated that there was an increase in the effector activity with increasing glucose stress. Thus, FcγRIIIA affinity chromatography permitted three independent assessments via a single analysis. Such approaches can be utilized as potential process analytical technology (PAT) tools in the biosimilar development process.

Calibration-free PAT: Locating selective crystallization or precipitation sweet spot in screenings with multi-way PARAFAC models

When developping selective crystallization or precipitation processes, biopharmaceutical modalities require empirical screenings and analytics tailored to the specific needs of the target molecule. The multi-way chemometric approach called parallel factor analysis (PARAFAC) coupled with ultraviolet visible light (UV/Vis) spectroscopy is able to predict specific concentrations and spectra from highly structured data sets without the need for calibration samples and reference analytics. These calculated models can provide exploratory information on pure species spectra and concentrations in all analyzed samples by representing one model component with one species. In this work, protein mixtures, monoclonal antibodies, and virus-like particles in chemically defined and complex solutions were investigated in three high-throughput crystallization or precipitation screenings with the aim to construct one PARAFAC model per case. Spectroscopic data sets of samples after the selective crystallization or precipitation, washing, and redissolution were recorded and arranged into a four-dimensional data set per case study. Different reference analytics and pure species spectra served as validation. Appropriate spectral preprocessing parameters were found for all case studies allowing even the application of this approach to the third case study in which quantitative concentration analytics are missing. Regardless of the modality or the number of species present in complex solutions, all models were able to estimate the specific concentration and find the optimal process condition regarding yield and product purity. It was shown that in complex solutions, species demonstrating similar phase behavior can be clustered as one component and described in the model. PARAFAC as a calibration-free approach coupled with UV/Vis spectroscopy provides a fast overview of species present in complex solution and of their concentration during selective crystallization or precipitation, washing, and redissolution.

Development of process analytical tools for rapid monitoring of live virus vaccines in manufacturing

In the development of end-to-end large-scale live virus vaccine (LVV) manufacturing, process analytical technology (PAT) tools enable timely monitoring of critical process parameters (CPP) and significantly guide process development and characterization. In a commercial setting, these very same tools can enable real time monitoring of CPPs on the shop floor and inform harvest decisions, predict peak potency, and serve as surrogates for release potency assays. Here we introduce the development of four advanced PAT tools for upstream and downstream process monitoring in LVV manufacturing. The first tool explores the application of capacitance probes for real time monitoring of viable cell density in bioreactors. The second tool utilizes high content imaging to determine optimum time of infection in a microcarrier process. The third tool uses flow virometry (or nanoscale flow cytometry) to monitor total virus particle counts across upstream and downstream process steps and establishes a robust correlation to virus potency. The fourth and final tool explores the use of nucleic acid dye staining to discriminate between “good” and “damaged” virus particles and uses this strategy to also monitor virus aggregates generated sometimes during downstream processing. Collectively, these tools provide a comprehensive monitoring toolbox and represent a significantly enhanced control strategy for the manufacturing of LVVs.

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.

Bridging the gap between fundamental research and product development of long acting injectable PLGA microspheres

INTRODUCTION

Long acting Injectable PLGA microspheres have gained more and more interest and attention in the field of life cycle management of pharmaceutical products due to their biocompatibility and biodegradability. So far, a multitude of trial-and-error experiments at lab scale have been used for establishing the correlation relationship between critical process parameters, critical material attributes and critical quality attributes. However, few published studies have elaborated on the development of PLGA microspheres from an industrial perspective.

AREAS COVERED

In this review, the scale-up feasibility of translational technologies of PLGA microspheres manufacturing have been evaluated. Additionally, state-of-the-art of technologies and facilities in PLGA development have been summarized. Meanwhile, the industrial knowledge matrix of PLGA microspheres development and research are establishing which provide comprehensive insight for understanding properties of PLGA microspheres as controlled/sustained release vehicle.

EXPERT OPINION

There is still big gap between fundamental research in academic institute and product development in pharmaceuticals. Therefore, the difference and connection between them should be identified gradually for better understanding of PLGA microspheres development.

In situ Raman spectroscopy for real time detection of cysteine

Cysteine serves a wide range of important biological and chemical functions and may have an association to neurodegenerative disease and cancer. Rapid, accurate analytical methods for cysteine detection are thus highly desirable. In this work, we report an investigation into the utility of in situ Raman spectroscopy as a Process Analytical Technology (PAT) for real time monitoring of cysteine. Cysteine concentrations are tracked in real time using Raman spectroscopy across a range of pharmaceutically-relevant concentrations, demonstrating the capability of Raman spectroscopy detection for in situ cysteine monitoring. The concentration range over which this analytical methodology can be applied is successfully established. As such, the results herein serve as a proof-of-principle investigation to demonstrate and evaluate the capabilities of a real time Raman spectroscopic approach for in situ cysteine detection, thus informing the range of important chemical and biological processes to which this approach can be applied. To the best of our knowledge, this is the first report of in situ Raman spectroscopy for real time monitoring of dynamically changing cysteine process concentrations.

Utilizing in situ spectroscopic tools to monitor ketal deprotection processes

The use of protection groups to shield a functional group during a synthesis is employed throughout many reactions and organic syntheses. The role of a protection group can be vital to the success of a reaction, as well as increase reaction yield and selectivity. Although much work has been done to investigate the addition of a protection group, the removal of the protection group is just as important - however, there is a lack of methods employed within the literature for monitoring the removal of a protection group in real time. In this work, the process of removing, or deprotecting, a ketal protecting group is investigated. Process analytical technology tools are incorporated for in situ analysis of the deprotection reaction of a small molecule model compound. Specifically, Raman spectroscopy and Fourier transform infrared spectroscopy show that characteristic bands can be used to track the decrease of the reactant and the increase of the expected products over time. To the best of our knowledge, this is the first report of process analytical technology being used to monitor a ketal deprotection reaction in real time. This information can be capitalized on in the future for understanding and optimizing pharmaceutically-relevant deprotection processes and downstream reactions.

In situ real time monitoring of emulsification and homogenization processes for vaccine adjuvants

Adjuvants are commonly employed to enhance the efficacy of a vaccine and thereby increase the resulting immune response in a patient. The activity and effectiveness of emulsion-based adjuvants has been heavily studied throughout pharmaceuticals; however, there exists a lack in research which monitors the formation of a stable emulsion in real time. Process analytical technology (PAT) provides a solution to meet this need. PAT involves the collection of in situ data, thereby providing real time information about the monitored process as well as increasing understanding of that process. Here, three separate PAT tools - optical particle imaging, in situ particle analysis, and Raman spectroscopy - were used to monitor two key steps involved in the formation of a stable emulsion product, emulsification and homogenization, as well as perform a stability assessment. The obtained results provided new insights-particle size decreases during emulsification and homogenization, and molecular changes do not occur during either the emulsification or homogenization steps. Further, the stability assessment indicated that the coarse emulsion product obtained from the emulsification step is stable over the course of 24 hours when mixed. To the best of our knowledge, this is the first report of an analytical methodology for in situ, real time analysis of emulsification and homogenization processes for vaccine adjuvants. Using our proposed analytical methodology, an improved understanding of emulsion-based vaccine adjuvants can now be achieved, ultimately impacting the ability to develop and deliver successful pharmaceuticals.

Microbial technologies for biotherapeutics production: Key tools for advanced biopharmaceutical process development and control

Current trends in the biopharmaceutical market such as the diversification of therapies as well as the increasing time-to-market pressure will trigger the rethinking of bioprocess development and production approaches. Thereby, the importance of development time and manufacturing costs will increase, especially for microbial production. In the present review, we investigate three technological approaches which, to our opinion, will play a key role in the future of biopharmaceutical production. The first cornerstone of process development is the generation and effective utilization of platform knowledge. Building processes on well understood microbial and technological platforms allows to accelerate early-stage bioprocess development and to better condense this knowledge into multi-purpose technologies and applicable mathematical models. Second, the application of verified scale down systems and in silico models for process design and characterization will reduce the required number of large scale batches before dossier submission. Third, the broader availability of mathematical process models and the improvement of process analytical technologies will increase the applicability and acceptance of advanced control and process automation in the manufacturing scale. This will reduce process failure rates and subsequently cost of goods. Along these three aspects we give an overview of recently developed key tools and their potential integration into bioprocess development strategies.

Process monitoring of polysaccharide deketalization for vaccine bioconjugation development using in situ analytical methodology

Pneumococcal conjugate vaccines (PCVs) are formed by bioconjugation of a carrier protein to the purified capsular polysaccharide (Ps) from multiple serological strains of Streptococcus pneumoniae. The associated bioconjugation chemistry relies on initial selective modifications to the Ps backbone structure. Among these modifications, removal of a ketal functional group, termed deketalization, is one that is important for pharmaceutical PCV production. Herein, we report a process monitoring investigation into the deketalization of a polysaccharide relevant to PCV process development. We have applied process analytical technology (PAT) for in situ process monitoring to study the deketalization reaction in real time. We find that in situ FTIR spectroscopy elucidates multiple classes of reaction kinetics, one of which correlates strongly with the deketalization reaction of interest. This PAT approach to real time reaction monitoring offers the possibility of improved process monitoring in the pharmaceutical production of PCVs. To our knowledge, this report represents the first PAT investigation into Ps deketalization. Our findings suggest that broader application of PAT to the chemical modifications associated with PCV bioconjugation, as well as other pharmaceutically relevant bioconjugation processes, carries the power to enhance process understanding, control, and efficiency through real time process monitoring.

Systematic assessment of process analytical technologies for biologics

The application of process analytical technology (PAT) for biotherapeutic development and manufacturing has been employed owing to technological, economic, and regulatory advantages across the industry. Typically, chromatographic, spectroscopic, and/or mass spectrometric sensors are integrated into upstream and downstream unit operations in in-line, on-line, or at-line fashion to enable real-time monitoring and control of the process. Despite the widespread utility of PAT technologies at various unit operations of the bioprocess, a holistic business value assessment of PAT has not been well addressed in biologics. Thus, in this study, we evaluated PAT technologies based on predefined criteria for their technological attributes such as enablement of better process understanding, control, and high-throughput capabilities; as well as for business attributes such as simplicity of implementation, lead time, and cost reduction. The study involved an industry-wide survey, where input from subject matter industry experts on various PAT tools were collected, assessed, and ranked. The survey results demonstrated on-line liquid Chromatography (LC), in-line Raman, and gas analysis techniques are of high business value especially at the production bioreactor unit operation of upstream processing. In-line variable path-length UV/VIS measurements (VPE), on-line LC, multiangle light scattering (MALS), and automated sampling are of high business value in Protein A purification and polishing steps of the downstream process. We also provide insights, based on our experience in clinical and commercial manufacturing of biologics, into the development and implementation of some of the PAT tools. The results presented in this study are intended to be helpful for the current practitioners of PAT as well as those new to the field to gauge, prioritize and steer their projects for success.

Proton-transfer-reaction mass spectrometry (PTR-MS) for online monitoring of glucose depletion and cell concentrations in HEK 293 gene therapy processes

Objectives

The applicability of proton-transfer-reaction mass spectrometry (PTR-MS) as a versatile online monitoring tool to increase consistency and robustness for recombinant adeno-associated virus (rAAV) producing HEK 293 bioprocesses was evaluated. We present a structured workflow to extract process relevant information from PTR-MS data.

Results

Reproducibility of volatile organic compound (VOC) measurements was demonstrated with spiking experiments and the process data sets used for applicability evaluation consisted of HEK 293 cell culture triplicates with and without transfection. The developed data workflow enabled the identification of six VOCs, of which two were used to develop a soft sensor providing better real-time estimates than the conventional capacitance sensor. Acetaldehyde, another VOC, provides online process information about glucose depletion that can directly be used for process control purposes.

Conclusions

The potential of PTR-MS for HEK 293 cell culture monitoring has been shown. VOC data derived information can be used to develop soft sensors and to directly set up new process control strategies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10529-021-03205-y.

Critical Analysis of cGMP Large-Scale Expansion Process in Bioreactors of Human Induced Pluripotent Stem Cells in the Framework of Quality by Design

Human induced pluripotent stem cells (hiPSCs) are manufactured as advanced therapy medicinal products for tissue replacement applications. With this aim, the feasibility of hiPSC large-scale expansion in existing bioreactor systems under current good manufacturing practices (cGMP) has been tested. Yet, these attempts have lacked a paradigm shift in culture settings and technologies tailored to hiPSCs, which jeopardizes their clinical translation. The best approach for industrial scale-up of high-quality hiPSCs is to design their manufacturing process by following quality-by-design (QbD) principles: a scientific, risk-based framework for process design based on relating product and process attributes to product quality. In this review, we analyzed the hiPSC expansion manufacturing process implementing the QbD approach in the use of bioreactors, stressing the decisive role played by the cell quantity, quality and costs, drawing key QbD concepts directly from the guidelines of the International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use.

In-line monitoring and endpoint determination of percolation process of herbal medicine using ultraviolet spectroscopy combined with convolutional neural network

OBJECTIVES

As a common step in the herbal medicine production process, percolation usually lacks effective process monitoring methods and is often conducted with fixed process parameters. In this study, an in-line ultraviolet (UV) spectroscopy was used for monitoring the Caulis Sinomenii percolation process.

METHODS

The spectra and concentration data of 156 percolation samples from five batches were collected. Convolutional neural networks (CNNs) were used to develop quantitative calibration models. The mean squared error (MSE), mean absolute percentage error (MAPE) and mean absolute error (MAE) were compared to select the proper loss function for developing the CNN models. Meanwhile, partial least square regression (PLSR) was also used to develop calibration models for performance comparison.

KEY FINDINGS

The CNN models with MAPE or MAE as the loss function could provide accurate predictions for all samples. However, CNN models adopting MSE as the loss function tended not to predict low-concentration samples accurately. The CNN models mostly achieved satisfactory results without any preprocessing techniques and surpassed PLSR models in all the performance metrics.

CONCLUSIONS

An in-line UV spectroscopy system combining the CNN algorithm was implemented to monitor the percolation process of Caulis Sinomenii. The system can accurately determine the endpoint of the percolation process.

Characterization of cell cycle and apoptosis in Chinese hamster ovary cell culture using flow cytometry for bioprocess monitoring

Chinese hamster ovary (CHO) cells are by far the most important mammalian cell lines used for producing antibodies and other therapeutic proteins. It is critical to fully understand their physiological conditions during a bioprocess in order to achieve the highest productivity and the desired product quality. Flow cytometry technology possesses unique advantages for measuring multiple cellular attributes for a given cell and examining changes in cell culture heterogeneity over time that can be used as metrics for enhanced process understanding and control strategy. Flow cytometry-based assays were utilized to examine the progression of cell cycle and apoptosis in three case studies using different antibody-producing CHO cell lines in both fed-batch and perfusion bioprocesses. In our case studies, we found that G0/G1 phase distribution and early apoptosis accumulation responded to subtle changes in culture conditions, such as pH shifting or momentary glucose depletion. In a perfusion process, flow cytometry provided an insightful understanding of the cell physiological status under a hypothermic condition. More importantly, these changes in cell cycle and apoptosis were not detected by a routine trypan blue exclusion-based cell counting and viability measurement. In summary, integration of flow cytometry into bioprocesses as a process analytical technology tool can be beneficial for establishing optimum process conditions and process control.

Method development for mono- and disaccharides monitoring in cell culture medium by capillary and microchip electrophoresis

The rapidly growing, competitive biopharmaceutical market requires tight bioprocess monitoring. An integrated, automated platform for the routine online/at-line monitoring of key factors in the cell culture medium could greatly improve process monitoring. Mono- and disaccharides, as the main energy and carbon source, are one of these key factors. A CE-LIF method was developed for the analysis of several mono- and disaccharides, considering requirements and restrictions for analysis in an integrated, automated monitoring platform, such as the possibility for miniaturization to microchip electrophoresis. Analysis was performed after fluorescent derivatization with 8-aminopyrene-1,3,6-trisulfonic acid. The derivatisation reaction and the separation BGE were optimized using design of experiments. The developed method is applicable to the complex matrix of cell culture medium and proved transferable to microchip electrophoresis.

Prediction of Residual Curing Capacity of Melamine-Formaldehyde Resins at an Early Stage of Synthesis by In-Line FTIR Spectroscopy

Melamine-formaldehyde (MF) resins are widely used as surface finishes for engineered wood-based panels in decorative laminates. Since no additional glue is applied in lamination, the overall residual curing capacity of MF resins is of great technological importance. Residual curing capacity is measured by differential scanning calorimetry (DSC) as the exothermic curing enthalpy integral of the liquid resin. After resin synthesis is completed, the resulting pre-polymer has a defined chemical structure with a corresponding residual curing capacity. Predicting the residual curing capacity of a resin batch already at an early stage during synthesis would enable corrective measures to be taken by making adjustments while synthesis is still in progress. Thereby, discarding faulty batches could be avoided. Here, by using a batch modelling approach, it is demonstrated how quantitative predictions of MF residual curing capacity can be derived from inline Fourier Transform infrared (FTIR) spectra recorded during resin synthesis using partial least squares regression. Not only is there a strong correlation (R² = 0.89) between the infrared spectra measured at the end of MF resin synthesis and the residual curing capacity. The inline reaction spectra obtained already at the point of complete dissolution of melamine upon methylolation during the initial stage of resin synthesis are also well suited for predicting final curing performance of the resin. Based on these IR spectra, a valid regression model (R² = 0.85) can be established using information obtained at a very early stage of MF resin synthesis.

Determination of protein concentration in downstream biomanufacturing processes by in-line index of refraction

Protein concentration determination is a necessary in-process control for the downstream operations within biomanufacturing. As production transitions from batch mode to an integrated continuous bioprocess paradigm, there is a growing need to move protein concentration quantitation from off-line to in-line analysis. One solution to fulfill this process analytical technology need is an in-line index of refraction (IoR) sensor to measure protein concentration in real time. Here the performance of an IoR sensor is evaluated through a series of experiments to assess linear response, buffer matrix effects, dynamic range, sensor-to-sensor variability, and the limits of detection and quantitation. The performance of the sensor was also tested in two bioprocessing scenarios, ultrafiltration and capture chromatography. The implementation of this in-line IoR sensor for real-time protein concentration analysis and monitoring has the potential to improve continuous bioprocess manufacturing.

Bioprocess Control: Current Progress and Future Perspectives

Typical bioprocess comprises of different unit operations wherein a near optimal environment is required for cells to grow, divide, and synthesize the desired product. However, bioprocess control caters to unique challenges that arise due to non-linearity, variability, and complexity of biotech processes. This article presents a review of modern control strategies employed in bioprocessing. Conventional control strategies (open loop, closed loop) along with modern control schemes such as fuzzy logic, model predictive control, adaptive control and neural network-based control are illustrated, and their effectiveness is highlighted. Furthermore, it is elucidated that bioprocess control is more than just automation, and includes aspects such as system architecture, software applications, hardware, and interfaces, all of which are optimized and compiled as per demand. This needs to be accomplished while keeping process requirement, production cost, market value of product, regulatory constraints, and data acquisition requirements in our purview. This article aims to offer an overview of the current best practices in bioprocess control, monitoring, and automation.

At-Line Reversed Phase Liquid Chromatography for In-Process Monitoring of Inclusion Body Solubilization

Refolding is known as the bottleneck in inclusion body (IB) downstream processing in the pharmaceutical industry: high dilutions leading to large operating volumes, slow refolding kinetics and low refolding yields are only a few of the problems that impede industrial application. Solubilization prior to refolding is often carried out empirically and the effects of the solubilizate on the subsequent refolding step are rarely investigated. The results obtained in this study, however, indicate that the quality of the IB solubilizate has a severe effect on subsequent refolding. As the solubilizate contains chaotropic reagents in high molarities, it is commonly analyzed with sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). SDS-PAGE, however, suffers from a long analysis time, making at-line analytical implementation difficult. In this study, we established an at-line reversed phase liquid chromatography method to investigate the time-dependent quality of the solubilizate. To verify the necessity of at-line solubilization monitoring, we varied the essential solubilization conditions for horseradish peroxidase IBs. The solubilization time was found to have a major influence on subsequent refolding, underlining the high need for an at-line analysis of solubilization. Furthermore, we used the developed reversed phase liquid chromatography method for an in-process control (IPC). In conclusion, the presented reversed phase liquid chromatography method allows a proper control of IB solubilization applicable for tailored refolding.

Pharmaceutical Excipients Enhance Iron-Dependent Photo-Degradation in Pharmaceutical Buffers by near UV and Visible Light: Tyrosine Modification by Reactions of the Antioxidant Methionine in Citrate Buffer

PURPOSE

To evaluate the effect of excipients, including sugars and amino acids, on photo-degradation reactions in pharmaceutical buffers induced by near UV and visible light.

METHODS

Solutions of citrate or acetate buffers, containing 1 or 50 μM Fe³⁺, the model peptides methionine enkephalin (MEn), leucine enkephalin (LEn) or proctolin peptide (ProP), in the presence of commonly used amino acids or sugars, were photo-irradiated with near UV or visible light. The oxidation products were analyzed by reverse-phase HPLC and HPLC-MS/MS.

RESULTS

The sugars mannitol, sucrose and trehalose, and the amino acids Arg, Lys, and His significantly promote the oxidation of peptide Met to peptide Met sulfoxide. These excipients do not increase the yields of hydrogen peroxide, suggesting that other oxidants such as peroxyl radicals are responsible for the oxidation of peptide Met. The addition of free Met reduces the oxidation of peptide Met, but, in citrate buffer, causes the addition of Met oxidation products to Tyr residues of the target peptides.

CONCLUSIONS

Commonly used excipients enhance the light-induced oxidation of amino acids in model peptides.

Control of surge tanks for continuous manufacturing of monoclonal antibodies

Surge tanks are critical but often overlooked enablers of continuous bioprocessing. They provide multiple benefits including dampening of concentration gradients and allowing process resumption efforts in case of equipment failure or unexpected deviations, which can occur during a continuous campaign of weeks or months. They are also useful in enabling steady-state operation across a continuous train by facilitating mass balance between unit operations such as chromatography which have periodic loading and elution cycles. In this paper, we propose a design of a system of surge tanks for a monoclonal antibody (mAb) production process consisting of cell culture, clarification, capture chromatography, viral inactivation, polishing chromatography, and single-pass ultrafiltration and diafiltration. A Python controller has been developed for robust control of the continuous train. The controller has four layers, namely data acquisition, process scheduling, deviation handling, and real-time execution. A set of general guidelines for surge tank placement and sizing have been proposed together with process control strategies based on the design space of the individual unit operations, failure modes analysis of the different equipment, and expected variability in the process feed streams for both fed-batch and perfusion bioreactors. The control system has been successfully demonstrated for several continuous runs of up to 36 h in duration and is able to leverage surge tanks for robust control of the continuous train in the face of product variability as well as process errors while maintaining critical quality attributes. The proposed set of strategies for surge tank control are adaptable to most continuous processing setups for mAbs, and together form the first framework that can fully realize the benefits of surge tanks in continuous bioprocessing.

Development of a rapid polarized total synchronous fluorescence spectroscopy (pTSFS) method for protein quantification in a model bioreactor broth

Protein quantification during bioprocess monitoring is essential for biopharmaceutical manufacturing and is complicated by the complex chemical composition of the bioreactor broth. Here we present the early-stage development and optimization of a polarized total synchronous fluorescence spectroscopy (pTSFS) method for protein quantification in a hydrolysate-protein model (mimics clarified bioreactor broth samples) using a standard benchtop laboratory fluorometer. We used UV transmitting polarizers to provide wider range pTSFS spectra for screening of the four different TSFS spectra generated by the measurement: parallel (||), perpendicular (⊥), unpolarized (T) intensity spectra and anisotropy maps. TSFS_|| (parallel polarized) measurements were the best for protein quantification compared to standard unpolarized measurements and the Bradford assay. This was because TSFS_|| spectra had a better analyte signal to noise ratio (SNR), due to the anisotropy of protein emission. This meant that protein signals were better resolved from the background emission of small molecule fluorophores in the cell culture media. SNR of >5000 was achieved for concentrations of bovine serum albumin/yeastolate 1.2/10 g L^-1 with TSFS_|| . Optimization using genetic algorithm and interval partial least squares based variable selection enabled reduction of spectral resolution and number of excitation wavelengths required without degrading performance. This enables fast (<3.5 min) online/at-line measurements, and the method had an LOD of 0.18 g L^-1 and high accuracy with a predictive error of <9%.