Implications Of The Caacb Virus Contamination In Biomanufacturing Project For Cell Therapy Manufacturers

Adventitious agent contamination of cell culture-based biomanufacturing operations for the production of protein and monoclonal antibody biotherapeutics are infrequent, but when they do occur, they are very costly, impact manufacturing operations, and can potentially impact patient safety and product supply. In response to this need, the MIT Consortium on Adventitious Agent Contamination in Biomanufacturing (CAACB) began the confidential collection and analysis of industry-wide viral contamination data with an emphasis on “lessons learned”. This presentation will cover the learnings from this study, including identified industry risks and best practices to mitigate those risks. Some of the key findings which have significant implications to the emerging cell therapy industry are: 1) Raw materials, including non-animal-based raw materials, may be a potential source of viral contamination and stringent raw material testing and vendor selection and auditing programs are critical. 2) Traditional viral tests, including in vitro testing and PCR, have contributed to false-positive events, which may take extended times to resolve prior to release of raw materials, process intermediates, or final product. 3) The time frames needed for viral testing in general, and for investigation of positive viral tests, can range from weeks to months, and are not compatible with the requirements for near real-time release testing for some cell therapy products. 4) Viral testing programs, and potential investigations of positive results, are quite expensive, and application to the autologous cell therapy space will be challenging

Mechanistic modeling to predict titers and infected cells in the two-stage continuous production of a viral vaccine

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Biomanufacturing and testbed development for the continuous production of monoclonal antibodies

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Modeling Framework to Evaluate Vaccine Strategies against the COVID-19 Pandemic

SARS-CoV-2, with an infection fatality rate between 0.5 and 1%, has spread to all corners of the globe and infected millions of people. While vaccination is essential to protect against the virus and halt community transmission, rapidly making and delivering safe and efficacious vaccines presents unique development, manufacturing, supply chain, delivery, and post-market surveillance challenges. Despite the large number of vaccines in or entering the clinic, it is unclear how many candidates will meet regulatory requirements and which vaccine strategy will most effectively lead to sustained, population-wide immunity. Interviews with experts from biopharmaceutical companies, regulatory and multilateral organizations, non-profit foundations, and academic research groups, complemented with extensive literature review, informed the development of a framework for understanding the factors leading to population-wide immunity against SARS-CoV-2, in particular considering the role of vaccines. This paper presents a systems-level modeling framework to guide the development of analytical tools aimed at informing time-critical decisions to make vaccines globally and equitably accessible. Such a framework can be used for scenario planning and evaluating tradeoffs across access strategies. It highlights the diverse and powerful ways in which data can be used to evaluate future risks and strategically allocate limited resources

Models to inform neutralizing antibody therapy strategies during pandemics: the case of SARS-CoV-2

Background: Neutralizing antibodies (nAbs) against SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) can play an important role in reducing impacts of the COVID-19 pandemic, complementing ongoing public health efforts such as diagnostics and vaccination. Rapidly designing, manufacturing and distributing nAbs requires significant planning across the product value chain and an understanding of the opportunities, challenges and risks throughout. Methods: A systems framework comprised of four critical components is presented to aid in developing effective end-to-end nAbs strategies in the context of a pandemic: (1) product design and optimization, (2) epidemiology, (3) demand and (4) supply. Quantitative models are used to estimate product demand using available epidemiological data, simulate biomanufacturing operations from typical bioprocess parameters and calculate antibody production costs to meet clinical needs under various realistic scenarios. Results:In a US-based case study during the 9-month period from March 15 to December 15, 2020, the projected number of SARS-CoV-2 infections was 15.73 million. The estimated product volume needed to meet therapeutic demand for the maximum number of clinically eligible patients ranged between 6.3 and 31.5 tons for 0.5 and 2.5 g dose sizes, respectively. The relative production scale and cost needed to meet demand are calculated for different centralized and distributed manufacturing scenarios. Conclusions: Meeting demand for anti-SARS-CoV-2 nAbs requires significant manufacturing capacity and planning for appropriate administration in clinical settings. MIT Center for Biomedical Innovation’s data-driven tools presented can help inform time-critical decisions by providing insight into important operational and policy considerations for making nAbs broadly accessible, while considering time and resource constraints

A warm-start digital CRISPR/Cas-based method for the quantitative detection of nucleic acids

Nucleic acids-based molecular diagnostic tools incorporating the CRISPR/Cas system are being developed as rapid and sensitive methods for pathogen detection. However, most CRISPR/Cas-based diagnostics lack quantitative detection ability. Here, we report Warm-Start RApid DIgital Crispr Approach (WS-RADICA) for the rapid, sensitive, and quantitative detection of nucleic acids. WS-RADICA detected as little as 1 copy/μl SARS-CoV-2 RNA in 40 min (qualitative detection) or 60 min (quantitative detection). WS-RADICA can be easily adapted to various digital devices: two digital chips were evaluated for both DNA and RNA quantification, with linear dynamic ranges of 0.8-12777 copies/μL for DNA and 1.2-18391 copies/μL for RNA (both R2 values > 0.99). Moreover, WS-RADICA had lower detection limit and higher inhibitor tolerance than a bulk RT-LAMP-Cas12b reaction and similar performance to RT-qPCR and RT-dPCR. To prove its performance on nucleic acids derived from live virus, WS-RADICA was also validated to detect and quantify human adenovirus and herpes simplex virus. Given its speed, sensitivity, quantification capability, and inhibitor tolerance, WS-RADICA shows great promise for a variety of applications requiring nucleic acid quantification

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

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