A broad European industry/academic consortium, Inno4Vac, has developed a robust, open-source modeling platform that unifies upstream and downstream models and predicts product stability, all within a single environment. Unlike many open-source modeling programs, this one, called CADET-Hub, doesn’t need mad programming skills to use.
As Reinhard Liebers, PhD, a project manager at the European Vaccine Initiative, tells GEN, this work shows “that mechanistic modeling, digital twins, and stability prediction can be integrated into one collaborative platform to accelerate bioprocess development, improve process understanding, and reduce experimental workload.”
CADET-Hub is an integrated, modular, cloud-based modeling platform designed to help the biotech industry especially vaccine manufacturers quickly reconfigure their manufacturing platforms in response to emerging demands such as quickly-mutating pathogens. Its developers add that it can be used to help optimize a broad spectrum of bioprocesses.
Integration and ease of use—even for non-programmers—are standout features for this new platform. A key motivation for developing CADET-Hub was “to make the setting up and fine-tuning of biomanufacturing processes more efficient as well as reduce the technical overhead of setting up local software environments for bioprocess modeling,” according to a team led by Eric von Lieres, PhD, head of modeling and simulation at Forschungszentrum Jülich, and Liebers, in a recent paper. Therefore, each of the modules is web-based “in principle, with options for local deployment if desired, and a graphical user interface under development,” they tell GEN.
The upstream models are based on computational fluid dynamics and metabolic models for bioreactor simulations. The downstream models offer insights into centrifugation, filtration, and chromatography. CADET-Hub includes a dedicated stability forecasting model.
The research around CADET-Hub supports a shift from empirical trial-and-error development toward predictive, data-driven biomanufacturing with integrated upstream, downstream, control, and stability models,” Liebers says.
Case studies
The team of authors around Liebers and von Lieres tested CADET-Hub under three scenarios.
As a way to model anion exchange capture of a recombinant subunit vaccine, they report that it functioned effectively as a collaborative workflow to share experimental data and mechanistic models, capturing meaningful nonlinear and multicomponent effects.
When modeling downstream filtration using ion exchange chromatography, CADET-Hub used explicit storage vessel models to close local material balances and transfer component concentrations in a structured way. It showed how upstream variability “can be propagated downstream to predict its impact on subsequent unit operations.” But, they add, “Experimental validation of the filtration model is still required.”
For process optimization and control, they point out, “Vaccine production requires a combination of sequence control and nonlinear model predictive control.” Overall, the case study showed a 50% improvement in upstream yield and a 20% improvement in downstream productivity that is attainable through model-based optimization.
To predict product stability under various conditions, the scientists combined hierarchical and advanced kinetic models within a Bayesian framework. They produced a “robust estimation of vaccine shelf life,” while meeting regulatory expectations and ICH Q12 principles.
“The next steps are to expand CADET-Hub toward fully end-to-end digital bioprocess models; to improve scalability, industrial deployment, and user interfaces; and to continue regulatory validation and adoption,” Liebers says.
CADET-Hub was created as part of the Inno4Vac vaccine development project and received funding from the Innovative Medicines Initiative/European Union/European Federation of Pharmaceutical Industries and Associations (IMI2/EU/EFPIA).
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