Process Concepts*

Kaspereit, Malte; Schmidt–Traub, H.

doi:10.1002/9783527816347.ch5

Cited by 3 publications

(7 citation statements)

References 130 publications

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“…The Chromatography Analysis and Design Toolkit (CADET) is a fast and accurate solver and chromatogram simulator that covers a wide range of models, including GRM variants such as GRM2D and reduced variants of the lumped rate model (Leweke and Lieres 2018;Leweke et al, 2020;Narayanan et al, 2021b). Commercially available counterparts include Cytiva's GoSilico Chromatography Modeling Software (Briskot et al, 2021) and ChromWorks from YPSOFacto (Kaspereit and Schmidt-Traub 2020;Schmölder and Kaspereit 2020) 5 . TABLE 1 List of mass transport models and adsorption kinetic models for the mechanistic modeling of the protein transport and adsorption during chromatography-based purification processes.…”

Section: Mechanistic Modelsmentioning

confidence: 99%

The use of predictive models to develop chromatography-based purification processes

Bernau

Knödler

Emonts

et al. 2022

Front. Bioeng. Biotechnol.

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Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

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Section: Mechanistic Modelsmentioning

confidence: 99%

The use of predictive models to develop chromatography-based purification processes

Bernau

Knödler

Emonts

et al. 2022

Front. Bioeng. Biotechnol.

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show abstract

“…Starting points of the boundaries for pure extract and raffinate products are point a (H 1 ,H 1 ) and point b (H 2 ,H 2 ), respectively. At the first step, the difference between the m-values of zones 2 and 3 is increased by Δm 23 (1) . The initial points for the pure extract boundary screening can be obtained from the previous step result, a 0…”

Section: Triangle Theory and Iterativementioning

confidence: 99%

“…(1) = (m 2,min (0) , m 2,min (0) + Δm 23 (1) ) and b 0 (1) = (m 3,max (0) , Δm 23 (1) , m 3,max (0) ) where m 2,min (0) = H 1 and m 3,max…”

Section: Triangle Theory and Iterativeunclassified

“…= min(q 1,1,2 (1) /c 2,1,1 (1) ). These screening steps are repeated until m 2,min (k) > m 3,max (k) − Δm 23 (k) .…”

Section: Triangle Theory and Iterativementioning

confidence: 99%

“…In preparative chromatography, the application of classical batch elution is still the prevailing technology. Several more complicated modes of operation were developed in order to overcome the limitations of batch chromatography with respect to productivity, recovery, and solvent economy . Among these modes the periodically operated multicolumn simulated moving bed (SMB) process is particularly productive.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Numerical Short-Cut Design of Simulated Moving Bed Chromatography for Multicomponent Nonlinear Adsorption Isotherms: Nonstoichiometric Langmuir Model

Lee

Kienle

Seidel‐Morgenstern

2021

Ind. Eng. Chem. Res.

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For the fine chemical and pharmaceutical industries, simulated moving bed (SMB) chromatography is a very promising separation process. Because of its structural and operational complexity this periodically operated multicolumn process is not easy to design and optimize. In the 1990s, Storti, Mazzotti, and Morbidelli exploited the potential of the equilibrium theory and developed a now well-established short-cut design method for the conventional four-zone SMB processes. The concept, which is known as the “triangle theory”, provides explicit design rules for a small set of nonlinear adsorption isotherm models and the case of processing binary feed mixtures. For the sake of extending the triangle theory to multicomponent systems, we introduce in this work a numerical short-cut method. The iterative method will be illustrated to design a conventional four-zone SMB process for the separation of quaternary mixtures obeying nonstoichiometric Langmuir isotherms. The results will be validated by comparing predicted internal concentration profiles with the results of additionally carried out true moving bed simulations.

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Advanced In-Line Purification Technologies in Multistep Continuous Flow Pharmaceutical Synthesis

Lei

Ang

2023

Org. Process Res. Dev.

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Continuous flow synthesis is a widely used method for synthesizing fine chemicals due to its benefits such as process intensification, improved reproducibility, and the ability to perform otherwise impossible transformations. Multistep continuous flow synthesis (MCFS) simplifies the synthesis of complex molecules by telescoping multiple steps into a streamlined and potentially automated process, reducing human efforts and time. Despite these advantages, challenges such as solid formation, solvent and reagent incompatibilities, and intermediate purification difficulties limit the development of MCFS. Overcoming these challenges will accelerate the innovative development of MCFS, thereby leading to enhanced multistep synthesis. This Perspective highlights representative examples of complex molecule production enabled by MCFS, where various in-line purification technologies were utilized during the flow processes.

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Process Concepts*

Cited by 3 publications

References 130 publications

The use of predictive models to develop chromatography-based purification processes

The use of predictive models to develop chromatography-based purification processes

Numerical Short-Cut Design of Simulated Moving Bed Chromatography for Multicomponent Nonlinear Adsorption Isotherms: Nonstoichiometric Langmuir Model

Advanced In-Line Purification Technologies in Multistep Continuous Flow Pharmaceutical Synthesis

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