Downstream Process Development Research Articles

Glimpsing the future of AAV analytical innovation

Wei Zhang is a Senior Scientist and heading Downstream Processing Group (DSP) in Bioprocessing Technology Institute (BTI), Agency for Science, Technology and Research (A*STAR) in Singapore. Her team focuses on the downstream process development and product analytics of a variety of novel biotherapeutics, ranging from monoclonal antibodies, bispecific antibodies to viral vectors and nucleic acid therapies. Her team is also committed to work towards intensified and continuous downstream processing. Her team in BTI actively collaborate with dozens of biopharmaceutical companies and bioprocessing solution providers worldwide, including both leading industrial players and local SMEs.

High-throughput, automated analysis of viral vector titer and process-related impurities accelerates downstream process development of AAV-based gene therapies

Watch the video or read the poster to learn:How to use a single, automated platform for both viral vector titer and impurity analysisWhy fully automated, microfluidic immunoassays provide a time- and sample-saving alternative to ELISA techniquesHow to deploy a strategy for shortening analysis time, reducing sample volume, and dramatically increasing walkaway timeJustine Collet-Brose after graduating from the University of Grenoble Alpes (France) in Biotechnological Medicines and Management, Justine worked 6 years in a Swiss Biotech company developing therapeutic antibodies. Having had the chance to support a biotherapeutic program from the preclinical phase to the FDA market approval, she then decided to join Gyros Protein Technologies as Field Application Specialist supporting customers in Europe on various bioanalytical area including bioprocess, preclinical/clinical development, vaccines and cell and gene therapies. With more than 10 years of experience on the Gyrolab technology, she recently joined the Product and Market Management team to keep contributing to address academia and industry needs in the development of innovative treatments.

Quality by Design in Downstream Process Development of Romiplostim

Background: Downstream processing of therapeutic recombinant proteins expressed as the inclusion bodies (IBs) in E. coli is quite challenging. This study aimed to use the quality by design approach for developing the multi-step downstream process of a structurally complex therapeutic Fc-Peptide fusion protein, romiplostim. Methods: For development of a successful downstream process, risk analysis and experimental designs were used to characterize the most critical quality attributes (CQAs) and effects of process parameters on these quality attributes. Results: The solubilization of IBs was optimized by design of experiment on three parameters with a focus on solubility yield, which resulted in >75% increase of the target protein solubilization. The pH of sample was identified as CQA in anion exchange chromatography that might have an impact on achieving >85% host cell proteins removal and >90% host cell DNA reduction. In the refolding step, process parameters were screened. Cystine/cysteine ratio, pH, and incubation time identified as CPPs were further optimized using Box-Behnken analysis, which >85% of the target protein was refolded. The design space for further purification step by HIC was mapped with a focus on high molecular weight impurities. After polishing by gel filtration, the final product's biological activity showed no statistically significant differences among the groups received romiplostim and Nplate®, as the reference product. Conclusion: This research presents a precise and exhaustive model for mapping the design space in order to describe and anticipate the link between the yield and quality of romiplostim and its downstream process parameters.

An accelerated approach for mechanistic model based prediction of linear gradient elution ion-exchange chromatography of proteins

With growing demands for therapeutic monoclonal antibodies, in silico downstream process development based on mechanistic modeling of chromatography separation process is being increasingly used for process optimization and process characterization. Application of mechanistic modeling in biopharmaceutical industry has been sparse due to the significant investment of time and resources that are required for performing model calibration. Mechanistic modeling of the chromatography process involves a large number of mass transport and binding parameters and their initial input values are required for simulations. These input values of column parameters can be easily obtained either from experiments or from empirical correlations available in literature. On the other hand, obtaining the model input valves for binding kinetic parameters is usually a cumbersome process as it involves performing batch experiments which are not only tedious but also require significant quantities of purely isolated main product and its related impurities, which is challenging as the product related impurities are typically present in smaller quantities and hence are difficult to obtain as pure species. In the present work, a mechanistic model that is based on the general rate model coupled with extended Langmuir binding model has been used for prediction of linear gradient elution peaks of monoclonal antibody on cation exchanger chromatography. The present work describes an accelerated approach for obtaining the input values for binding kinetic parameters in the extended Langmuir binding model from the two Yamamoto coefficient A and B values obtained by Yamamoto method directly from the model calibration linear gradient elution runs of different gradient slopes and at low to moderate protein loadings. The equations that can relate the two coefficients to the extended Langmuir model equation binding kinetic parameters were derived. Therefore, once A and B are determined, the binding kinetic parameter values were determined straightforward, thereby avoiding the problem of multiple solutions for the model parameters. The estimated binding parameters were successfully validated from isocratic elution experiments performed at low loading. What we demonstrate is that the proposed approach allows us to estimate binding kinetic parameters in a significantly more efficient and accelerated manner than presently used approaches, thereby accelerating development and implementation of mechanistic modeling for process chromatography.

Exploring the potential of machine learning for more efficient development and production of biopharmaceuticals.

Principles of Industry 4.0 direct us to predict how pharmaceutical operations and regulations may exist with automation, digitization, artificial intelligence (AI), and real time data acquisition. Machine learning (ML), a sub-discipline of AI, involves the use of statistical tools to extract the desired information either through understanding the underlying patterns in the information or by development of mathematical relationships among the critical process parameters (CPPs) and critical quality attributes (CQAs) of biopharmaceuticals. ML is still in its infancy for directly supporting the quality-by-design based development and manufacturing of biopharmaceuticals. However, adoption of ML-based models in place of conventional multi-variate-data-analysis (MVDA) is increasing with the accumulation of large-scale data. This has been majorly contributed by the real-time monitoring of process variables and quality attributes of products through the implementation of process analytical technology in biopharmaceutical manufacturing. All aspects of healthcare, from drug design to product distribution, are complex and multidimensional. Thus, ML-based approaches are being applied to achieve sophistication, accuracy, flexibility and agility in all these areas. This review discusses the potential of ML for addressing the complex issues in diverse areas of biopharmaceutical development, such as biopharmaceuticals design and assessment of early stage development, upstream and downstream process development, analysis, characterization and prediction of post-translational modifications (PTMs), formulation, and stability studies. Moreover, the challenges in acquisition, cleaning and structuring the bioprocess data, which is one of the major hurdles in implementation of ML in biopharma industry, have also been discussed. Regulatory perspectives on implementation of AI/ML in the biopharma sector have also been briefly discussed. This article is a bird's eye view on the recent developments and applications of ML in overcoming the challenges for adopting "Industry - 4.0" in the biopharma industry.

Recent Advances and Future Directions in Downstream Processing of Therapeutic Antibodies.

Despite the advent of many new therapies, therapeutic monoclonal antibodies remain a prominent biologics product, with a market value of billions of dollars annually. A variety of downstream processing technological advances have led to a paradigm shift in how therapeutic antibodies are developed and manufactured. A key driver of change has been the increased adoption of single-use technologies for process development and manufacturing. An early-stage developability assessment of potential lead antibodies, using both in silico and high-throughput experimental approaches, is critical to de-risk development and identify molecules amenable to manufacturing. Both statistical and mechanistic modelling approaches are being increasingly applied to downstream process development, allowing for deeper process understanding of chromatographic unit operations. Given the greater adoption of perfusion processes for antibody production, continuous and semi-continuous downstream processes are being increasingly explored as alternatives to batch processes. As part of the Quality by Design (QbD) paradigm, ever more sophisticated process analytical technologies play a key role in understanding antibody product quality in real-time. We should expect that computational prediction and modelling approaches will continue to be advanced and exploited, given the increasing sophistication and robustness of predictive methods compared to the costs, time, and resources required for experimental studies.

Bayesian optimization using multiple directional objective functions allows the rapid inverse fitting of parameters for chromatography simulations

The modeling of chromatographic separations can speed up downstream process development, reducing the time to market and corresponding development costs for new products such as pharmaceuticals. However, calibrating such models by identifying suitable parameter values for mass transport and sorption is a major, time-consuming challenge that can hinder model development and improvement. We therefore designed a new approach based on Bayesian optimization (BayesOpt) and Gaussian processes that reduced the time required to compute relevant chromatography parameters by up to two orders of magnitude compared to a multistart gradient descent and a genetic algorithm. We compared the three approaches side by side to process several internal and external datasets for ion exchange chromatography (based on a steric mass action isotherm) and hydrophobic interaction chromatography (a modified version of a recently published five-parameter isotherm) as well as different input data types (gradient elution data alone vs gradient elution and breakthrough data). We found that BayesOpt computation was consistently faster than the other approaches when using either single-core or 12-cores computer processing units. The error of the BayesOpt parameter estimates was higher than that of the competing algorithms, but still two orders of magnitude less than the variability of our experimental data, indicating BayesOpts applicability for chromatography modeling. The low computational demand of BayesOpt will facilitate rapid model development and improvement even for large datasets (e.g., > 100 proteins) and increase its suitability for research laboratories or small and medium enterprises lacking access to dedicated mainframe computers.

Recent advances to accelerate purification process development: A review with a focus on vaccines

The safety requirements for vaccines are extremely high since they are administered to healthy people. For that reason, vaccine development is time-consuming and very expensive. Reducing time-to-market is key for pharmaceutical companies, saving lives and money. Therefore the need is raised for systematic, general and efficient process development strategies to shorten development times and enhance process understanding. High throughput technologies tremendously increased the volume of process-related data available and, combined with statistical and mechanistic modeling, new high throughput process development (HTPD) approaches evolved. The introduction of model-based HTPD enabled faster and broader screening of conditions, and furthermore increased knowledge. Model-based HTPD has particularly been important for chromatography, which is a crucial separation technique to attain high purities. This review provides an overview of downstream process development strategies and tools used within the (bio)pharmaceutical industry, focusing attention on (protein subunit) vaccine purification processes. Subsequently high throughput process development and other combinatorial approaches are discussed and compared according to their experimental effort and understanding. Within a growing sea of information, novel modeling tools and artificial intelligence (AI) gain importance for finding patterns behind the data and thereby acquiring a deeper process understanding.

Thinking big: the need for innovation in the production of lentivirus-based cell and gene therapies

<b>Elisa Manzotti</b>, Founder, BioInsights, speaks to <b>Hanna Leinonen, John Moscariello, Lee DaviesScott Cross </b>and <b>Will Junker</b> <div class="authors authors-lg"><div class="author"><div class="author-img"><img src="https://cdn.insights.bio/uploads/H Leinonen copy.jpg" data-image="1"></div><div class="author-det"><h3 class="author-name">Hanna Leinonen</h3><h5 class="author-title">Senior Scientist, Kuopio Center for Gene and Cell Therapy</h5> Hanna M. Leinonen holds a PhD in Molecular Medicine from the University of Eastern Finland (2014). She has 15 years’ experience on lentiviral vectors and 6 years’ experience on bioprocessing. She is currently working as a Senior Scientist in Kuopio Center for Gene and Cell Therapy (Finland) focusing on development of upstream processing for viral vectors (lentivirus, adenovirus, AAV). </div></div></div><div class="authors authors-lg"><div class="author"><div class="author-img"><img src="https://cdn.insights.bio/uploads/26118d9d52f34a12859025a3d5f4aabc.jpg" data-image="1"></div><div class="author-det"><h3 class="author-name">John Moscariello</h3><h5 class="author-title">Executive Director, Viral Vector and Gene Editing Process Development, Bristol Myers Squibb</h5> John Moscariello currently serves as Executive Director of Viral Vector and Gene Editing Process Development at Bristol-Myers Squib (BMS). At BMS, John’s group develops viral vector processes that enable rapid timelines to generate clinical viral vectors as well as the development and characterization of commercial viral vector processes. Prior to his work at BMS, John was the Vice President of Process Development at AGC Biologics where his team was responsible cell line development, upstream and downstream process development, analytical and formulation development, and technical support for AGC Biologic’s commercial manufacturing facility and supported development activities from generating processes for Toxicology/Phase 1 supply up to and including commercialization and post-approval process support. John is very active in the biotechnology community. He is on the Scientific Advisory Board for various conferences, including the BioProcess International conference series, and the CBI conference series on achieving efficient facilities and the next frontier of single-use technologies. John obtained his Ph.D. in Chemical and Biological Engineering from the University of Wisconsin-Madison, and his B.Eng. in Chemical Engineering from the University of Delaware. </div></div></div><div class="authors authors-lg"><div class="author"><div class="author-img"><img src="https://cdn.insights.bio/uploads/Lee Davies 1.jpg" data-image="1"></div><div class="author-det"><h3 class="author-name">Lee Davies</h3><h5 class="author-title">Director, Process Research &amp; Development, Oxford Biomedica</h5><p class="oneComWebmail-MsoNormal"><i>As Director of Process Research and Development, Lee helps drive development, innovation and improvements in&nbsp;</i><i>world-class lentiviral vector manufacturing processes,&nbsp;</i><i>applying scientific and engineering principles to all aspects of upstream and downstream process development, including process optimisation and scale-up, technology transfer to GMP manufacturing and process characterisation to support chemistry, manufacturing and controls (CMC) regulatory submissions.&nbsp;</i><i>As part of&nbsp;the</i><i>&nbsp;Process Research and Development team, Lee works</i><i>&nbsp;at the&nbsp;cutting edge of gene therapy, ensuring its applicability to the needs of the wider gene and cell therapy community. The team’s mission covers the&nbsp;</i><i>life cycle of gene therapies, taking</i><i>&nbsp;processes from the early phase development work through to&nbsp;fully optimised large scale, GMP-ready processes, manufacturing and commercialisation.&nbsp;</i><i>Prior to joining Oxford Biomedica 6 years ago, Lee worked at the University of Oxford as a postdoctoral researcher and obtained a D.Phil in Gene Therapy for Cystic Fibrosis.</i> </div></div></div><div class="authors authors-lg"><div class="author"><div class="author-img"><img src="https://cdn.insights.bio/uploads/Scott_122321_WebReady copy.jpg" data-image="1"></div><div class="author-det"><h3 class="author-name">Scott Cross</h3><h5 class="author-title">Senior Principal, Dark Horse Consulting</h5> Scott has over 20 years experience working with viral vectors, vaccines, and biologics in GMP environments. He has been responsible for cleanroom design, build out and commissioning of vector facilities, as well as the oversight of viral vector, cell therapy, fill finish and manufacturing support departments. Scott started his career at Merck and Co. where he worked on the development of an Adenovirus-based HIV vaccine and later, the development, optimization, and validation of release assays for live virus vaccines. He then moved to Indiana University (IU) where he managed the IU Vector Production Facility (IUVPF), overseeing GMP production and testing of Lentiviral and Retroviral vectors for the IUVPF and the National Gene Vector Laboratories (NGVL). While at the IUVPF he also managed the design, build and commissioning of a new viral vector GMP production and testing facility. After leaving the IUVPF, Scott joined Cincinnati Children’s Hospital Medical Center (CCHMC) managing the GMP Vector Production Facility, Viral Vector Core, and the Aseptic Processing Labs. Scott then moved to the University of Florida where he was the Director of Cell Therapy, Fill Finish and Manufacturing Support Operations for Florida Biologix and Brammer Bio. He was also responsible for the design of two new fill finish suites. Most recently, Scott served as Vice President of Vector Operations at Orchard Therapeutics where he was one of the original ten members and responsible for viral vector development, GMP vector production, plasmid production, oversight of 10 CDMOs, due diligence, and facility design. </div></div></div><div class="authors authors-lg"><div class="author"><div class="author-img"><img src="https://cdn.insights.bio/uploads/Will Junker headshot copy.jpg" data-image="1"></div><div class="author-det"><h3 class="author-name">Will Junker</h3><h5 class="author-title">Head of Vector Manufacturing Quality, Kite Pharma</h5> Will Junker is Head of Vector Quality and oversees the operation of QC, QA and QE to bring Kite’s vector manufacturing facility on line through licensure. Before this role, Will built Kite’s Quality Engineering function globally. His 35 year career in BioPharma includes 13 years at AstraZeneca and 15 years at Aventis/Sanofi as well as a few years at Baxter BioScience in technical/quality roles of increasing responsibility. </div></div></div>

Ultrastructural elucidation of lignin macromolecule from different growth stages of Chinese pine

Understanding of the morphological changes at different growth stages and lignin accumulation pattern for pine biomass plays the key role in facilitating the further development of value-added utilization and downstream conversion processes. This work systematically revealed the morphological change and lignin accumulation pattern in Chinese pine branches cell walls via confocal Raman microscopy (CRM) technology. Meanwhile, the structural characteristics of isolated lignin samples from different growth stages were synthetically characterized by nuclear magnetic resonance (NMR) and gel permeation chromatography (GPC) techniques. The results indicated that the content of pith in adult pine new branch was bigger than juvenile trees. With the increase of physiological age, the branches in adult pine could accumulate more lignin both in overall content and the concentration of cell corner middle layer. Moreover, the significantly increases of molecular weights and the β-O-4, β-β linkages content revealed that the lignin macromolecule of pine would polymerize faster in the adult stage (14, 35 years). The panorama generated from the structural and chemical features of pine native lignin not only benefited to understand the biosynthetic pathways and lignin macromolecules structural variation in plant cell walls from different growth stages but also contributed to the valorization and deconstruction of biomass.

Limosilactobacillus fermentum from buffalo milk is suitable for potential biotechnological process development and inhibits Helicobacter pylori in a gastric epithelial cell model

Probiotics are living microorganisms that give beneficial health effects while consumed, and each strain possesses diverse and unique properties and also different technological characteristics that affect its ability to be produced at large scale. Limosilactobacillus fermentum is a widely studied member of probiotics, however, few data are available on the development of fermentation and downstream processes for the production of viable biomasses for potential industrial applications.In the present study a novel L. fermentum strain was isolated from buffalo milk and used as test example for biotechnological process development. The strain was able to produce up to 109 CFU/mL on a (glucose based) semi-defined medium deprived of animal-derived raw materials up to the pilot scale (150 L), demonstrating improved results compared to commonly used, although industrially not suitable, media rich of casein and beef extract. The study of strain behavior in batch experiments indicated that the highest concentration of viable cells was reached after only 8 h of growth, greatly shortening the process. Moreover, initial concentrations of glucose in the medium above 30 g/L, if not supported by higher nitrogen concentrations, reduced the yield of biomass and increased production of heterolactic fermentation by-products. Biomass concentration via microfiltration on hollow fibers, and subsequent spray-drying allowed to recover about 5.7 × 1010CFU/gpowder of viable cells, indicating strain resistance to harsh processing conditions.Overall, these data demonstrate the possibility to obtain and maintain adequate levels of viable L. fermentum cells by using a simple approach that is potentially suitable for industrial development. Moreover, since often exopolysaccharides produced by lactobacilli contribute to the strain's functionality, a partial characterization of the EPS produced by the newly identified L. fermentum strain was carried out.Finally, the effect of L. fermentum versus H. pylori in a gastric epithelial cell model was evaluated demonstrating its ability to stimulate the response of the immune system and displace the infective agent.

Accelerating process development with at-line concentration measurement

Currently, the most used methods for adeno-associated viral (AAV) vector quantitative analysis are qPCR or ddPCR and ELISA assays, along with analytical ultracentrifugation (AUC) and transmission electron microscopy (TEM). The time to results when using these methods can range from days to several weeks, and the acceptable tolerance range is high. Rapid, reliable in-process testing offers a significant benefit to AAV downstream process development and can be achieved with Slope Spectroscopy&#174; utilizing Variable Pathlength Technology (VPT). The CTech™ SoloVPE&#174; System, when used at-line in one or more stages of a process, can help to quickly identify process characteristics, provide key insights, and allow for process optimization in minutes. VPT has enabled at-line measurement of concentration by eliminating the need for sample dilution or manipulation and delivering rapid and highly accurate real-time results.

Fucoxanthin from Algae to Human, an Extraordinary Bioresource: Insights and Advances in up and Downstream Processes.

Fucoxanthin is a brown-colored pigment from algae, with great potential as a bioactive molecule due to its numerous properties. This review aims to present current knowledge on this high added-value pigment. An accurate analysis of the biological function of fucoxanthin explains its wide photon absorption capacities in golden-brown algae. The specific chemical structure of this pigment also leads to many functional activities in human health. They are outlined in this work and are supported by the latest studies in the literature. The scientific and industrial interest in fucoxanthin is correlated with great improvements in the development of algae cultures and downstream processes. The best fucoxanthin producing algae and their associated culture parameters are described. The light intensity is a major influencing factor, as it has to enable both a high biomass growth and a high fucoxanthin content. This review also insists on the most eco-friendly and innovative extraction methods and their perspective within the next years. The use of bio-based solvents, aqueous two-phase systems and the centrifugal partition chromatography are the most promising processes. The analysis of the global market and multiple applications of fucoxanthin revealed that Asian companies are major actors in the market with macroalgae. In addition, fucoxanthin from microalgae are currently produced in Israel and France, and are mostly authorized in the USA.

Smart process development: Application of machine-learning and integrated process modeling for inclusion body purification processes.

The development of a biopharmaceutical production process usually occurs sequentially, and tedious optimization of each individual unit operation is very time-consuming. Here, the conditions established as optimal for one-step serve as input for the following step. Yet, this strategy does not consider potential interactions between a priori distant process steps and therefore cannot guarantee for optimal overall process performance. To overcome these limitations, we established a smart approach to develop and utilize integrated process models using machine learning techniques and genetic algorithms. We evaluated the application of the data-driven models to explore potential efficiency increases and compared them to a conventional development approach for one of our development products. First, we developed a data-driven integrated process model using gradient boosting machines and Gaussian processes as machine learning techniques and a genetic algorithm as recommendation engine for two downstream unit operations, namely solubilization and refolding. Through projection of the results into our large-scale facility, we predicted a twofold increase in productivity. Second, we extended the model to a three-step model by including the capture chromatography. Here, depending on the selected baseline-process chosen for comparison, we obtained between 50% and 100% increase in productivity. These data show the successful application of machine learning techniques and optimization algorithms for downstream process development. Finally, our results highlight the importance of considering integrated process models for the whole process chain, including all unit operations.

Application of inline variable pathlength technology for rapid determination of dynamic binding capacity in downstream process development of biopharmaceuticals.

Determination of dynamic binding capacity (DBC) for capture purification chromatographic step is usually the first experiment to be performed during downstream process development of biopharmaceuticals. In this work, we investigated the application of inline variable pathlength technology using FlowVPE for rapid determination of DBC on affinity resins for protein capture and proved its comparability with offline titer methods. This work also demonstrated that variable pathlength technology for DBC determination can be successfully applied to different classes of monoclonal antibodies and fusion proteins. This enabled rapid screening of affinity resins and optimization of the capture chromatography step. Hence, use of inline variable pathlength technology eliminated the dependency on offline titer data, traditionally used for DBC determination and accelerated overall process development timelines with less cost.

Accelerating downstream analytical testing for gene therapy

Watch the video or read the poster to learn: The benefits of rapid, reliable in-process testing for AAV downstream process development How utilizing Slope Spectroscopy can remove or automate multiple process stepsGene therapy case studies demonstrating use of the SoloVPE System to make real-time decisions for viral vector applicationsHarald Ehlen has been with Repligen for almost 2 years, supporting Biopharma analytical development, GMP implementation, and QC validation of Slope Spectroscopy&#174; methods and instruments for rapid bioprocess analytics. Prior to working with Repligen, he gathered 6 years of experience as Senior Pharma Analytics Application Specialist and Bioproduction Application Specialist supporting Biopharma QC and Analytical Development. He graduated in Biology at the University of Cologne where he also retrieved a PhD in Physiological Chemistry and then spent several years as scientist studying the physiology, pathogenesis, and development of the skeletal system before moving to the biotech industry. When not in the lab, you can find Harald enjoying playing guitar or spending time with his wife and two children.

Serial fractionation of spent brewer's yeast protein hydrolysate by ultrafiltration: A peptide-rich product with low RNA content

Spent brewer's yeast (SBY) application as a new source of peptides depends on the development of proper downstream processes. This work aimed to separate yeast hydrolysate peptides from sugars and ribonucleic acids (RNA) by a 3-step designed fractionation process using ceramic ultra and nanofiltration following two sequences: (1) 50, 8 and 1 kDa and (2) 15, 8 and 1 kDa molecular weight cut-off (MWCO) membranes. In step one, 15 kDa MWCO membrane retained more components and increased performance of subsequent steps, when compared to 50 kDa. Peptide composition of the initial hydrolysate was gradually changed until 90% of the peptides smaller than 1 kg mol −1 were found in the final permeate. Fractionation increased peptide purity regarding RNA and total sugars up to 1.7 and 2.7-fold, respectively. Innovative protein-rich ingredients from SBY residue with an RNA content as low as 1.4% were produced by membrane separation technology. High quality ingredients presented different peptide profiles and great potential in food and pharmaceutical industries applications. • Efficient RNA reduction was achieved using membrane separation technology. • RNA content in protein-rich fraction was as low as 1.4% (dry weight). • Membranes of 15–1 kDa range were adapted to spent yeast ultrafiltration. • Protein purity of obtained fractions increased 1.7 and 2.7-fold for RNA and sugars. • A fraction with bioactive potential (65% of the peptides < 1 kg mol −1 ) was produced.

Bota Biosciences

Bota Biosciences, a start-up with a scheme to engineer enzymes as catalysts for making small molecules, closed a series B financing round totaling $100 million in July. It is one of several firms aiming to engineer enzymes and microorganisms for green manufacturing that received significant funding this year, but Bota can be distinguished from the pack. The company has its eyes on more than enzyme design and fermentation. It has an information technology–enabled process of developing microbial strains and enzymes that can be scaled up to aid the production of food, nutrition products, drugs, and other products. And while many players in the field specialize in early design steps, Bota seeks to follow through to production. Bota’s eyes, CEO Cheryl Cui says, are on the end product. “Instead of just focusing on what’s in the lab, we also try to move as quickly as we can into downstream process development

Identification and classification of host cell proteins during biopharmaceutical process development.

As significant improvements in volumetric antibody productivity have been achieved by advances in upstream processing over the last decade, and harvest material has become progressively more difficult to recover with these intensified upstream operations, the segregation of upstream and downstream processing has remained largely unchanged. By integrating upstream and downstream process development, product purification issues are given consideration during the optimization of upstream operating conditions, which mitigates the need for extensive and expensive clearance strategies downstream. To investigate the impact of cell culture duration on critical quality attributes, CHO-expressed IgG1 was cultivated in two 2L bioreactors with samples taken on days 8, 10, 13, 15, and 17. The material was centrifuged, filtered and protein A purified on a 1ml HiTrap column. Host cell protein (HCP) identification by mass spectrometry (MS) was applied to this system to provide insights into cellular behavior and HCP carryover during protein A purification. It was shown that as cultivation progressed from day 8 to 17 and antibody titer increased, product quality declined due to an increase in post-protein A HCPs (from 72 to 475 peptides detected by MS) and a decrease in product monomer percentage (from 98% to 95.5%). Additionally, the MS data revealed an increase in the abundance of several classes of post-protein A HCPs (e.g., stress response proteins and indicators of cell age), particularly on days 15 and 17 of culture, which were associated with significant increases in total overall HCP levels. This provides new insight into the specific types of HCPs that are retained during mAb purification and may be used to aid process development strategies.

Recent Developments in the Downstream Processing of Phycobiliproteins from Algae: A Review

Algae (both micro and macro) have gained huge attention in the recent past for their high commercial value products. They are the source of various biomolecules of commercial applications ranging from nutraceuticals to fuels. Phycobiliproteins are one such high-value low volume compounds that are mainly obtained from micro and macroalgae. In order to tap the bioresource, a significant amount of work has been carried out for large scale production of algal biomass. However, work on downstream processing aspects of phycobiliproteins (PBPs) from algae is scarce, especially in the case of macroalgae. There are many difficulties in cell wall disruption of both micro and macro algae because of their cell wall structure and compositions. At the same time, there are several challenges in the purification of phycobiliproteins. The current review article focuses on the recent developments in downstream processing of phycobiliproteins (mainly phycocyanins and phycoerythrins) from micro and macroalgae. The current status, recent advancements and potential technologies (that are under development) are summarised in this review article besides providing future directions for the present research area.