Distinct and Quantitative Validation Method for Predictive Process Modeling with Examples of Liquid-Liquid Extraction Processes of Complex Feed Mixtures

Schmidt, A.; Strube, Jochen

doi:10.3390/pr7050298

Cited by 24 publications

(47 citation statements)

References 46 publications

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“…Due to the fact that the use of models is still sparse because of validation, Sixt et al established a workflow that ensures the development of valid physico-chemical models [49]. This has already been described in various papers and the execution was shown using the example of liquid-liquid [55] and solid-liquid extraction [49], chromatography [56], and cultivation [57].…”

Section: Modeling Of Precipitationmentioning

confidence: 99%

Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing

Lohmann

Strube

2020

Processes

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The demand on biologics has been constantly rising over the past decades and has become crucial in modern medicine. Promising approaches to cope with widespread diseases like cancer and diabetes are gene therapy, plasmid DNA, virus-like particles, and exosomes. Due to progress that has been made in upstream processing (USP), difficulties arise in downstream processing and demand for innovative solutions. This work focuses on the integration of precipitation using a quality by design (QbD) approach for process development. Selective precipitation is achieved with PEG 4000 resulting in an HCP depletion of ≥80% respectively to IgG. Dissolution was executed with a sodium phosphate buffer (pH = 5/50 mM) reaching an IgG recovery of ≥95%. However, the central challenge in process development is still an optimal process design, which is transferable for a broad molecular variety of new products. This is where rigorous modeling becomes vital in order to generate digital twins to support early-stage process development and reduce the experimental overhead. Therefore, a model development and validation concept for construction of a process model for precipitation is also presented.

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Section: Modeling Of Precipitationmentioning

confidence: 99%

Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing

Lohmann

Strube

2020

Processes

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“…This approach was already used for solid-liquid (phyto-) extraction [33], upstream fermentation of monoclonal antibodies [38], and aqueous two-phase liquid-liquid extraction of monoclonal antibodies [17].…”

Section: Stepmentioning

confidence: 99%

“…After that, a risk assessment is required. This might be done, for example, by aid of Ishikawa diagrams and failure mode and effect analysis, as presented in Figure 2 [7,17]. Although this step is not mandatory for process simulation, but part of quality-by-design, conclusions drawn here directly define the modelling task, the parameters that need to be covered with the model, and the level of detail needed.…”

Section: Introductionmentioning

confidence: 99%

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Distinct and Quantitative Validation Method for Predictive Process Modelling in Preparative Chromatography of Synthetic and Bio-Based Feed Mixtures Following a Quality-by-Design (QbD) Approach

Zobel-Roos¹,

Mouellef²,

Ditz³

et al. 2019

Processes

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Process development, especially in regulated industries, where quality-by-design approaches have become a prerequisite, is cost intensive and time consuming. A main factor is the large number of experiments needed. Process modelling can reduce this number significantly by replacing experiments with simulations. However, this requires a validated model. In this paper, a process and model development workflow is presented, which focuses on implementing, parameterizing, and validating the model in four steps. The presented methods are laid out to gain, create, or generate the maximum information and process knowledge needed for successful process development. This includes design of experiments and statistical evaluations showing process robustness, sensitivity of target values to process parameters, and correlations between process and target values. Two case studies are presented. An ion exchange capture step for monoclonal antibodies focusing on high accuracy and low feed consumption; and one case study for small molecules focusing on rapid process development, emphasizing speed of parameter determination.

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“…Simulation results can guide the design of commercial extraction systems [29]. A better quantitative understanding of the mass transfer mechanism is also needed to support decision-making in process design and evaluation and the operation of new product or commercial extraction systems [30,31].…”

Section: Introductionmentioning

confidence: 99%

A Mechanistic Model of Mass Transfer in the Extraction of Bioactive Compounds from Intact Sorghum Pericarp

et al. 2019

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The extraction of phytochemical compounds from intact red sorghum grains was developed as an alternative process for producing bioactive material in the pharmaceutical industry. A mechanistic model is needed to better understand the process and enable predictive simulations for designing commercial-scale extraction systems. This paper presents a mathematical model for predicting phytochemical concentrations in the solvent and inside the pericarp of the grain at different positions during the extraction. The model is based on the mass transfer mechanism from inside the pericarp to its solid surface by diffusion, and then from the surface to a solvent during the extraction of bioactive compounds. It was numerically solved while using finite-difference approximation. The parameters considered were effective diffusivity inside the pericarp (Dep), mass transfer coefficient from the pericarp surface to the solvent (kc), and distribution coefficient (H). The model simulates the extraction performance, including the yield and bioactive compounds’ concentrations in the extract and inside the pericarp at various positions and times. A sensitivity analysis of the changes in each involved parameter provided sufficient information for increasing the performance of the model. A validation test that compared the results of the simulation with those of established analytical solutions showed that the model has high accuracy. Hence, the model can be applied in quantitative evaluations to improve productivity in the pharmaceutical industry.

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Distinct and Quantitative Validation Method for Predictive Process Modeling with Examples of Liquid-Liquid Extraction Processes of Complex Feed Mixtures

Cited by 24 publications

References 46 publications

Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing

Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing

Distinct and Quantitative Validation Method for Predictive Process Modelling in Preparative Chromatography of Synthetic and Bio-Based Feed Mixtures Following a Quality-by-Design (QbD) Approach

A Mechanistic Model of Mass Transfer in the Extraction of Bioactive Compounds from Intact Sorghum Pericarp

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