Basic regulatory science behind drug substance and drug product specifications of monoclonal antibodies and other protein therapeutics

In this review, we focus on providing basics and examples for each component of the protein therapeutic specifications to interested pharmacists and biopharmaceutical scientists with a goal to strengthen understanding in regulatory science and compliance. Pharmaceutical specifications comprise a list of important quality attributes for testing, references to use for test procedures, and appropriate acceptance criteria for the tests, and they are set up to ensure that when a drug product is administered to a patient, its intended therapeutic benefits and safety can be rendered appropriately. Conformance of drug substance or drug product to the specifications is achieved by testing an article according to the listed tests and analytical methods and obtaining test results that meet the acceptance criteria. Quality attributes are chosen to be tested based on their quality risk, and consideration should be given to the merit of the analytical methods which are associated with the acceptance criteria of the specifications. Acceptance criteria are set forth primarily based on efficacy and safety profiles, with an increasing attention noted for patient-centric specifications. Discussed in this work are related guidelines that support the biopharmaceutical specification setting, how to set the acceptance criteria, and examples of the quality attributes and the analytical methods from 60 articles and 23 pharmacopeial monographs. Outlooks are also explored on process analytical technologies and other orthogonal tools which are on-trend in biopharmaceutical characterization and quality control.

A Brief Introduction to Chemical Reaction Optimization

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

Current hurdles to the translation of nanomedicines from bench to the clinic

The field of nanomedicine has significantly influenced research areas such as drug delivery, diagnostics, theranostics, and regenerative medicine; however, the further development of this field will face significant challenges at the regulatory level if related guidance remains unclear and unconsolidated. This review describes those features and pathways crucial to the clinical translation of nanomedicine and highlights considerations for early-stage product development. These include identifying those critical quality attributes of the drug product essential for activity and safety, appropriate analytical methods (physical, chemical, biological) for characterization, important process parameters, and adequate pre-clinical models. Additional concerns include the evaluation of batch-to-batch consistency and considerations regarding scaling up that will ensure a successful reproducible manufacturing process. Furthermore, we advise close collaboration with regulatory agencies from the early stages of development to assure an aligned position to accelerate the development of future nanomedicines.

Flow chemistry for process optimisation using design of experiments

Implementing statistical training into undergraduate or postgraduate chemistry courses can provide high-impact learning experiences for students. However, the opportunity to reinforce this training with a combined laboratory practical can significantly enhance learning outcomes by providing a practical bolstering of the concepts. This paper outlines a flow chemistry laboratory practical for integrating design of experiments optimisation techniques into an organic chemistry laboratory session in which students construct a simple flow reactor and perform a structured series of experiments followed by computational processing and analysis of the results.

Transcriptome and proteome analysis of steady-state in a perfusion CHO cell culture process

Long-term continuous protein production can be reached by perfusion operation. Through the continuous removal of waste metabolites and supply of nutrients, steady-state (SS) conditions are achieved after a certain transient period, where the conditions inside the reactor are not only uniform in space but also constant in time. Such stable conditions may have beneficial influences on the reduction of product heterogeneities. In this study, we investigated the impact of perfusion cultivation on the intracellular physiological state of a CHO cell line producing a monoclonal antibody (mAb) by global transcriptomics and proteomics. Despite stable viable cell density was maintained right from the beginning of the cultivation time, productivity decrease, and a transition phase for metabolites and product quality was observed before reaching SS conditions. These were traced back to three sources of transient behaviors being hydrodynamic flow rates, intracellular dynamics of gene expression as well as metabolism and cell line instability, superimposing each other. However, 99.4% of all transcripts and proteins reached SS during the first week or were at SS from the beginning. These results demonstrate that the stable extracellular conditions of perfusion lead to SS also of the cellular level.

Application of Raman Spectroscopy and Univariate Modelling As a Process Analytical Technology for Cell Therapy Bioprocessing

Cell therapies offer unquestionable promises for the treatment, and in some cases even the cure, of complex diseases. As we start to see more of these therapies gaining market authorization, attention is turning to the bioprocesses used for their manufacture, in particular the challenge of gaining higher levels of process control to help regulate cell behavior, manage process variability, and deliver product of a consistent quality. Many processes already incorporate the measurement of key markers such as nutrient consumption, metabolite production, and cell concentration, but these are often performed off-line and only at set time points in the process. Having the ability to monitor these markers in real-time using in-line sensors would offer significant advantages, allowing faster decision-making and a finer level of process control. In this study, we use Raman spectroscopy as an in-line optical sensor for bioprocess monitoring of an autologous T-cell immunotherapy model produced in a stirred tank bioreactor system. Using reference datasets generated on a standard bioanalyzer, we develop chemometric models from the Raman spectra for glucose, glutamine, lactate, and ammonia. These chemometric models can accurately monitor donor-specific increases in nutrient consumption and metabolite production as the primary T-cell transition from a recovery phase and begin proliferating. Using a univariate modeling approach, we then show how changes in peak intensity within the Raman spectra can be correlated with cell concentration and viability. These models, which act as surrogate markers, can be used to monitor cell behavior including cell proliferation rates, proliferative capacity, and transition of the cells to a quiescent phenotype. Finally, using the univariate models, we also demonstrate how Raman spectroscopy can be applied for real-time monitoring. The ability to measure these key parameters using an in-line Raman optical sensor makes it possible to have immediate feedback on process performance. This could help significantly improve cell therapy bioprocessing by allowing proactive decision-making based on real-time process data. Going forward, these types of in-line sensors also open up opportunities to improve bioprocesses further through concepts such as adaptive manufacturing.

Expression of recombinant protein using Corynebacterium Glutamicum: progress, challenges and applications

Corynebacterium glutamicum (C. glutamicum) is a highly promising alternative prokaryotic host for recombinant protein expression, as it possesses several significant advantages over Escherichia coli (E. coli), the currently leading bacterial protein expression system. During the past decades, several experimental techniques and vector components for genetic manipulation of C. glutamicum have been developed and validated, including strong promoters for tightly regulating target gene expression, various types of plasmid vectors, protein secretion systems and methods of genetically modifying the host strain genome to improve protein production potential. This review critically discusses current progress in establishing C. glutamicum as a host for recombinant protein expression, and examines, in depth, some successful case studies of actual application of this expression system. The established "expression tool box" for developing novel constructs based on C. glutamicum as a host are also evaluated. Finally, the existing issues and solutions in process development with C. glutamicum as a host are specifically addressed.