Hybrid Modeling for Simultaneous Prediction of Flux, Rejection Factor and Concentration in Two-Component Crossflow Ultrafiltration

Krippl, Maximilian; Bofarull-Manzano, Ignasi; Duerkop, Mark; Dürauer, Astrid

doi:10.3390/pr8121625

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…For filtration steps, usually only theoretical models are available so there is a need for empirical small-scale technologies that can be used to establish processes with predictable scale-up performance. When new technologies or equipment (e.g., single pass TFF (Fuchs et al, 2023;Krippl et al, 2020Krippl et al, , 2021, two stage filtration (Burgstaller et al, 2019). multi stage counter current TFF (Jabra et al, 2019) are employed, it is important to establish scale-up principles and verify that the performance is predictable.…”

Section: Patient Safety and Process Robustnessmentioning

confidence: 99%

Status and future developments for downstream processing of biological products

Jungbauer,

Ferreira,

Butler

et al. 2024

Biotech & Bioengineering

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Governments and biopharmaceutical organizations aggressively leveraged expeditious communication capabilities, decision models, and global strategies to make a COVID‐19 vaccine happen within a period of 12 months. This was an unusual effort and cannot be transferred to normal times. However, this focus on a single vaccine has also led to other treatments and drug developments being sidelined. Society expects the pharmaceutical industry to provide an uninterrupted supply of medicines. However, it is often overlooked how complex the manufacture of these compounds is and what logistics are required, not to mention the time needed to develop new drugs. The overarching theme, therefore, is patient access and how we can help ensure access and extend it to low‐ and middle‐income countries. Despite unceasing efforts to make medications available to all patient populations, this must never be done at the expense of patient safety. A major fraction of the costs in biopharmaceutical manufacturing are for drug discovery, process development, and clinical studies. Infrastructure costs are very difficult to quantify because they often depend on whether a greenfield facility or an existing, depreciated facility is used or adapted for a new product. To accelerate process development concepts of platform process and prior knowledge are increasingly leveraged. While more traditional protein therapeutics continue to dominate the field, we are also experiencing the exciting emergence and evolution of other therapeutic formats (bispecifics, tetravalent mAbs, antibody‐drug conjugates, enzymes, peptides, etc.) that offer unique treatment options for patients. Protein modalities are still dominant, but new modalities are being developed that can be learned from including advanced therapeutics‐like cell and gene therapies. The industry must develop a model‐based strategy for process development and technologies such as continuous integrated biomanufacturing must be adopted. The overall conclusion is that the pandemic pace was unsustainable, focused on vaccine delivery at the expense of other modalities/disease targets, and had implications for professional and personal life (work‐life balance). Routinely reducing development time from 10 years to 1 year is nearly impossible to achieve. Environmental aspects of sustainable downstream processing are also described.

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Section: Patient Safety and Process Robustnessmentioning

confidence: 99%

Status and future developments for downstream processing of biological products

Jungbauer,

Ferreira,

Butler

et al. 2024

Biotech & Bioengineering

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“…Even though this hybrid modeling approach has been the state-of-the-art in other industries for many years, due to the higher complexity of biological processes, it has only gained interest during the last few years [14]. Even though hybrid modeling is increasingly adopted for downstream applications [15][16][17], the response surface modeling of process endpoints is still more commonly applied [18], and the full potential of hybrid process modeling applications in bioprocessing has not yet been realized.…”

Section: Introductionmentioning

confidence: 99%

Digital Twin Application for Model-Based DoE to Rapidly Identify Ideal Process Conditions for Space-Time Yield Optimization

et al. 2021

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The fast exploration of a design space and identification of the best process conditions facilitating the highest space-time yield are of great interest for manufacturers. To obtain this information, depending on the design space, a large number of practical experiments must be performed, analyzed, and evaluated. To reduce this experimental effort and increase the process understanding, we evaluated a model-based design of experiments to rapidly identify the optimum process conditions in a design space maximizing space-time yield. From a small initial dataset, hybrid models were implemented and used as digital bioprocess twins, thus obtaining the recommended optimal experiment. In cases where these optimum conditions were not covered by existing data, the experiment was carried out and added to the initial data set, re-training the hybrid model. The procedure was repeated until the model gained certainty about the best process conditions, i.e., no new recommendations. To evaluate this workflow, we utilized different initial data sets and assessed their respective performances. The fastest approach for optimizing the space-time yield in a three-dimensional design space was found with five initial experiments. The digital twin gained certainty after four recommendations, leading to a significantly reduced experimental effort compared to other state-of-the-art approaches. This highlights the benefits of in silico design space exploration for accelerating knowledge-based bioprocess development, and reducing the number of hands-on experiments, time, energy, and raw materials.

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