Upskilling the cell therapy manufacturing workforce: design, implementation, and evaluation of a massive open online course.

Cell therapies have gained prominence as a promising therapeutic modality for treating a range of diseases. Despite the recent clinical successes of cell therapy products, very few formal training programs exist for cell therapy manufacturing. To meet the demand for a well-trained workforce, we assembled a team of university researchers and industry professionals to develop an online course on the principles and practice of cell therapy manufacturing. The course covers the basic cell and systems physiology underlying cell therapy products, in addition to explaining end-to-end manufacturing from cell acquisition through to patient treatment, industrialization, and regulatory processes. So far, over 10,000 learners have enrolled in the course, and over 90% of respondents to the course exit survey indicated that they were 'very likely' or 'likely' to recommend the course to a peer. In this paper, we discuss our experience in the collaborative design and implementation of the online course, as well as lessons learned from quantitative and qualitative student feedback. We believe that this course can serve as a model for how academia and industry can collaborate to create innovative, scalable training programs to meet the demands of the modern biotechnology workforce.

Mechanistic modeling explains the production dynamics of recombinant adeno-associated virus with the baculovirus expression vector system.

Current manufacturing processes for recombinant adeno-associated viruses (rAAVs) have less-than-desired yields and produce significant amounts of empty capsids. The increasing demand and the high cost of goods for rAAV-based gene therapies motivate development of more efficient manufacturing processes. Recently, the US Food and Drug Administration (FDA) approved the first rAAV-based gene therapy product manufactured in the baculovirus expression vector system (BEVS), a technology that demonstrated production of high titers of full capsids. This work presents a first mechanistic model describing the key extracellular and intracellular phenomena occurring during baculovirus infection and rAAV maturation in the BEVS. The model predictions are successfully validated for in-house and literature experimental measurements of the vector genome and of structural and non-structural proteins collected during rAAV manufacturing in the BEVS with the TwoBac and ThreeBac constructs. A model-based analysis of the process is carried out to identify the bottlenecks that limit full capsid formation. Vector genome amplification is found to be the limiting step for rAAV production in Sf9 cells using either the TwoBac or ThreeBac system. In turn, vector genome amplification is hindered by limiting Rep78 levels. Transgene and non-essential baculovirus protein expression in the insect cell during rAAV manufacturing also negatively influences the rAAV production yields.

Development and Application of a Data-Driven Signal Detection Method for Surveillance of Adverse Event Variability Across Manufacturing Lots of Biologics.

INTRODUCTION: Postmarketing drug safety surveillance research has focused on the product-patient interaction as the primary source of variability in clinical outcomes. However, the inherent complexity of pharmaceutical manufacturing and distribution, especially of biologic drugs, also underscores the importance of risks related to variability in manufacturing and supply chain conditions that could potentially impact clinical outcomes. We propose a data-driven signal detection method called HMMScan to monitor for manufacturing lot-dependent changes in adverse event (AE) rates, and herein apply it to a biologic drug. METHODS: The HMMScan method chooses the best-fitting candidate from a family of probabilistic Hidden Markov Models to detect temporal correlations in per lot AE rates that could signal clinically relevant variability in manufacturing and supply chain conditions. Additionally, HMMScan indicates the particular lots most likely to be related to risky states of the manufacturing or supply chain condition. The HMMScan method was validated on extensive simulated data and applied to three actual lot sequences of a major biologic drug by combining lot metadata from the manufacturer with AE reports from the US FDA Adverse Event Reporting System (FAERS). RESULTS: Extensive method validation on simulated data indicated that HMMScan is able to correctly detect the presence or absence of variable manufacturing and supply chain conditions for contiguous sequences of 100 lots or more when changes in these conditions have a meaningful impact on AE rates. Applying the HMMScan method to FAERS data, two of the three actual lot sequences examined exhibited evidence of potential manufacturing or supply chain-related variability. CONCLUSIONS: HMMScan could be utilized by both manufacturers and regulators to automate lot variability monitoring and inform targeted root-cause analysis. Broad application of HMMScan would rely on a well-developed data input pipeline. The proposed method is implemented in an open-source GitHub repository.

Machine learning-based detection of adventitious microbes in T-cell therapy cultures using long-read sequencing.

Assuring that cell therapy products are safe before releasing them for use in patients is critical. Currently, compendial sterility testing for bacteria and fungi can take 7-14 days. The goal of this work was to develop a rapid untargeted approach for the sensitive detection of microbial contaminants at low abundance from low volume samples during the manufacturing process of cell therapies. We developed a long-read sequencing methodology using Oxford Nanopore Technologies MinION platform with 16S and 18S amplicon sequencing to detect USP <71> organisms and other microbial species. Reads are classified metagenomically to predict the microbial species. We used an extreme gradient boosting machine learning algorithm (XGBoost) to first assess if a sample is contaminated, and second, determine whether the predicted contaminant is correctly classified or misclassified. The model was used to make a final decision on the sterility status of the input sample. An optimized experimental and bioinformatics pipeline starting from spiked species through to sequenced reads allowed for the detection of microbial samples at 10 colony-forming units (CFU)/mL using metagenomic classification. Machine learning can be coupled with long-read sequencing to detect and identify sample sterility status and microbial species present in T-cell cultures, including the USP <71> organisms to 10 CFU/mL. IMPORTANCE This research presents a novel method for rapidly and accurately detecting microbial contaminants in cell therapy products, which is essential for ensuring patient safety. Traditional testing methods are time-consuming, taking 7-14 days, while our approach can significantly reduce this time. By combining advanced long-read nanopore sequencing techniques and machine learning, we can effectively identify the presence and types of microbial contaminants at low abundance levels. This breakthrough has the potential to improve the safety and efficiency of cell therapy manufacturing, leading to better patient outcomes and a more streamlined production process.

The ratio of nicotinic acid to nicotinamide as a microbial biomarker for assessing cell therapy product sterility.

Controlling microbial risks in cell therapy products (CTPs) is important for product safety. Here, we identified the nicotinic acid (NA) to nicotinamide (NAM) ratio as a biomarker that detects a broad spectrum of microbial contaminants in cell cultures. We separately added six different bacterial species into mesenchymal stromal cell and T cell culture and found that NA was uniquely present in these bacteria-contaminated CTPs due to the conversion from NAM by microbial nicotinamidases, which mammals lack. In cells inoculated with 1 × 104 CFUs/mL of different microorganisms, including USP <71> defined organisms, the increase in NA to NAM ratio ranged from 72 to 15,000 times higher than the uncontaminated controls after 24 h. Importantly, only live microorganisms caused increases in this ratio. In cells inoculated with 18 CFUs/mL of Escherichia coli, 20 CFUs/mL of Bacillus subtilis, and 10 CFUs/mL of Candida albicans, significant increase of NA to NAM ratio was detected using LC-MS after 18.5, 12.5, and 24.5 h, respectively. In contrast, compendial sterility test required >24 h to detect the same amount of these three organisms. In conclusion, the NA to NAM ratio is a useful biomarker for detection of early-stage microbial contaminations in CTPs.

Weighing the DNA Content of Adeno-Associated Virus Vectors with Zeptogram Precision Using Nanomechanical Resonators.

Quantifying the composition of viral vectors used in vaccine development and gene therapy is critical for assessing their functionality. Adeno-associated virus (AAV) vectors, which are the most widely used viral vectors for in vivo gene therapy, are typically characterized using PCR, ELISA, and analytical ultracentrifugation which require laborious protocols or hours of turnaround time. Emerging methods such as charge-detection mass spectroscopy, static light scattering, and mass photometry offer turnaround times of minutes for measuring AAV mass using optical or charge properties of AAV. Here, we demonstrate an orthogonal method where suspended nanomechanical resonators (SNR) are used to directly measure both AAV mass and aggregation from a few microliters of sample within minutes. We achieve a precision near 10 zeptograms which corresponds to 1% of the genome holding capacity of the AAV capsid. Our results show the potential of our method for providing real-time quality control of viral vectors during biomanufacturing.

Model-based control for column-based continuous viral inactivation of biopharmaceuticals.

Batch low-pH hold is a common processing step to inactivate enveloped viruses for biologics derived from mammalian sources. Increased interest in the transition of biopharmaceutical manufacturing from batch to continuous operation resulted in numerous attempts to adapt batch low-pH hold to continuous processing. However, control challenges with operating this system have not been directly addressed. This article describes a low-cost, column-based continuous viral inactivation system constructed with off-the-shelf components. Model-based, reaction-invariant pH controller is implemented to account for the nonlinearities with Bayesian estimation addressing variations in the operation. The residence time distribution is modeled as a plug flow reactor with axial dispersion in series with a continuously stirred tank reactor, and is periodically estimated during operation through inverse tracer experiments. The estimated residence time distribution quantifies the minimum residence time, which is used to adjust feed flow rates. Controller validation experiments demonstrate that pH and minimum residence time setpoint tracking and disturbance rejection are achieved with fast and accurate response and no instability. Viral inactivation testing demonstrates tight control of logarithmic reduction values over extended operation. This study provides tools for the design and operation of continuous viral inactivation systems in service of increasing productivity, improving product quality, and enhancing patient safety.

Mechanistic model for production of recombinant adeno-associated virus via triple transfection of HEK293 cells.

Manufacturing of recombinant adeno-associated virus (rAAV) viral vectors remains challenging, with low yields and low full:empty capsid ratios in the harvest. To elucidate the dynamics of recombinant viral production, we develop a mechanistic model for the synthesis of rAAV viral vectors by triple plasmid transfection based on the underlying biological processes derived from wild-type AAV. The model covers major steps starting from exogenous DNA delivery to the reaction cascade that forms viral proteins and DNA, which subsequently result in filled capsids, and the complex functions of the Rep protein as a regulator of the packaging plasmid gene expression and a catalyst for viral DNA packaging. We estimate kinetic parameters using dynamic data from literature and in-house triple transient transfection experiments. Model predictions of productivity changes as a result of the varied input plasmid ratio are benchmarked against transfection data from the literature. Sensitivity analysis suggests that (1) the poorly coordinated timeline of capsid synthesis and viral DNA replication results in a low ratio of full virions in harvest, and (2) repressive function of the Rep protein could be impeding capsid production at a later phase. The analyses from the mathematical model provide testable hypotheses for evaluation and reveal potential process bottlenecks that can be investigated.

Cellular pathways of recombinant adeno-associated virus production for gene therapy.

Recombinant adeno-associated viruses (rAAVs) are among the most important vectors for in vivo gene therapies. With the rapid development of gene therapy, current rAAV manufacturing capacity faces a challenge to meet the emerging demand for these therapies in the future. To examine the bottlenecks in rAAV production during cell culture, we focus here on an analysis of cellular pathways of rAAV production, based on an overview of assembly mechanisms first in the wild-type (wt) AAV replication and then in the common methods of rAAV production. The differences analyzed between the wild-type and recombinant systems provide insights into the mechanistic differences that may correlate with viral productivity. Based on these analyses, we identify potential barriers to high productivity of rAAV and discuss future directions for improvement to meet the emerging needs set by the growth of rAAV-based therapy and the needs of patients.

Standards efforts and landscape for rapid microbial testing methodologies in regenerative medicine.

The Standards Coordinating Body for Gene, Cell, and Regenerative Medicines and Cell-Based Drug Discovery (SCB) supports the development and commercialization of regenerative medicine products by identifying and addressing industry-wide challenges through standards. Through extensive stakeholder engagement, the implementation of rapid microbial testing methods (RMTMs) was identified as a high-priority need that must be addressed to facilitate more timely release of products. Since 2017, SCB has coordinated efforts to develop standards for this area through surveys, weekly meetings, workshops, leadership in working groups and participation in standards development organizations. This article describes the results of these efforts and discusses the current landscape of RMTMs for regenerative medicine products. Based on discussions with stakeholders across the field, an overview of traditional culture-based methods and limitations, alternative microbial testing technologies and current challenges, fit-for-purpose rapid microbial testing and case studies, risk-based strategies for selection of novel rapid microbial test methods and ongoing standards efforts for rapid microbial testing are captured here. To this end, SCB is facilitating several initiatives to address challenges associated with rapid microbial testing for regenerative medicine products. Two documentary standards are under development: an International Organization for Standardization standard to provide the framework for a risk-based approach to selecting fit-for-purpose assays primarily intended for cell and gene therapy products and an ASTM standard guide focused on sampling methods for microbial testing methods in tissue-engineered medical products. Working with the National Institute of Standards and Technology, SCB expects to facilitate the process of developing publicly available microbial materials for inter-laboratory testing. These studies will help collect the data necessary to facilitate validation of novel rapid methods. Finally, SCB has been working to increase awareness of, dialog about and participation in efforts to develop standards in the regenerative medicine field.

Analytical methods for process and product characterization of recombinant adeno-associated virus-based gene therapies.

The optimization of upstream and downstream processes for production of recombinant adeno-associated virus (rAAV) with consistent quality depends on the ability to rapidly characterize critical quality attributes (CQAs). In the context of rAAV production, the virus titer, capsid content, and aggregation are identified as potential CQAs, affecting the potency, purity, and safety of rAAV-mediated gene therapy products. Analytical methods to measure these attributes commonly suffer from long turnaround times or low throughput for process development, although rapid, high-throughput methods are beginning to be developed and commercialized. These methods are not yet well established in academic or industrial practice, and supportive data are scarce. Here, we review both established and upcoming analytical methods for the quantification of rAAV quality attributes. In assessing each method, we highlight the progress toward rapid, at-line characterization of rAAV. Furthermore, we identify that a key challenge for transitioning from traditional to newer methods is the scarcity of academic and industrial experience with the latter. This literature review serves as a guide for the selection of analytical methods targeting quality attributes for rapid, high-throughput process characterization during process development of rAAV-mediated gene therapies.

Viral contamination in biologic manufacture and implications for emerging therapies.

Recombinant protein therapeutics, vaccines, and plasma products have a long record of safety. However, the use of cell culture to produce recombinant proteins is still susceptible to contamination with viruses. These contaminations cost millions of dollars to recover from, can lead to patients not receiving therapies, and are very rare, which makes learning from past events difficult. A consortium of biotech companies, together with the Massachusetts Institute of Technology, has convened to collect data on these events. This industry-wide study provides insights into the most common viral contaminants, the source of those contaminants, the cell lines affected, corrective actions, as well as the impact of such events. These results have implications for the safe and effective production of not just current products, but also emerging cell and gene therapies which have shown much therapeutic promise.

Cyberbiosecurity in Advanced Manufacturing Models.

Cybersecurity for the production of safe and effective biopharmaceuticals requires the attention of multiple stakeholders, including industry, governments, and healthcare providers. Cyberbiosecurity breaches could directly impact patients, from compromised data privacy to disruptions in production that jeopardize global pandemic response. Maintaining cybersecurity in the modern economy, where advanced manufacturing technologies and digital strategies are becoming the norm, is a significant challenge. Here, we highlight vulnerabilities in present and future biomanufacturing paradigms given the dependence of this industry sector on proprietary intellectual property, cyber-physical systems, and government-regulated production environments, as well as movement toward advanced manufacturing models. Specifically, we (1) present an analysis of digital information flow in a typical biopharmaceutical manufacturing value chain; (2) consider the potential cyberbiosecurity risks that might emerge from advanced manufacturing models such as continuous and distributed systems; and (3) provide recommendations for risk mitigation. While advanced manufacturing models hold the potential for reducing costs and increasing access to more personalized therapies, the evolving landscape of the biopharmaceutical enterprise has led to growing concerns over potential cyber attacks. Gaining better foresight on potential risks is key for implementing proactive defensive principles, framing new developments, and establishing a permanent security culture that adapts to new challenges while maintaining the transparency required for regulated production of safe and effective medicines.

Comparability: manufacturing, characterization and controls, report of a UK Regenerative Medicine Platform Pluripotent Stem Cell Platform Workshop, Trinity Hall, Cambridge, 14-15 September 2015.

This paper summarizes the proceedings of a workshop held at Trinity Hall, Cambridge to discuss comparability and includes additional information and references to related information added subsequently to the workshop. Comparability is the need to demonstrate equivalence of product after a process change; a recent publication states that this 'may be difficult for cell-based medicinal products'. Therefore a well-managed change process is required which needs access to good science and regulatory advice and developers are encouraged to seek help early. The workshop shared current thinking and best practice and allowed the definition of key research questions. The intent of this report is to summarize the key issues and the consensus reached on each of these by the expert delegates.