Anton Sellberg

Design and control of integrated chromatography column sequences

To increase the productivity in biopharmaceutical production, a natural step is to introduce integrated continuous biomanufacturing which leads to fewer buffer and storage tanks, smaller sizes of integrated unit operations, and full automation of the operation. The main contribution of this work is to illustrate a methodology for design and control of a downstream process based on integrated column sequences. For small scale production, for example, pre‐clinical studies, integrated column sequences can be implemented on a single chromatography system. This makes for a very efficient drug development platform. The proposed methodology is composed of four steps and is governed by a set of tools, that is presented, that makes the transition from batch separations to a complete integrated separation sequence as easy as possible. This methodology, its associated tools and the physical implementation is presented and illustrated on a case study where the target protein is separated from impurities through an integrated four column sequence. This article shows that the design and control of an integrated column sequence was successfully implemented for a tertiary protein separation problem.

Prediction of reversible IgG1 aggregation occurring in a size exclusion chromatography column is enabled through a model based approach

One important aspect of antibody separation being studied today is aggregation, as this not only leads to a loss in yield, but aggregates can also be hazardous if injected into the body. The aim of this study was to determine whether the methodology applied in the previous study could be used to predict the aggregation of a different batch of IgG1, and to model the aggregation occurring in a SEC column. Aggregation was found to be reversible. The equilibrium parameter was found to be 272 M‐1 and the reaction kinetic parameter 1.33 × 10‐5 s‐1, both within the 95% confidence interval of the results obtained in the previous work. The effective diffusivities were estimated to be 1.45 × 10‐13 and 1.90 10‐14 m2/s for the monomers and dimers, respectively. Good agreement was found between the new model and the chromatograms obtained in the SEC experiments. The model was also able to predict the decrease of dimers due to the dilution and separation in the SEC column during long retention times.

Discretized multi-level elution trajectory: A proof-of-concept demonstration

Biomolecular and pharmaceutical downstream processing is dominated by chromatographic separation, which is associated with high product quality, low capacity and high costs. The separation can be optimized to minimize the costs while achieving a high purity. This paper presents an experimental validation of a discretized multi-level elution (DiME) trajectory, implemented on commercially available chromatography equipment. The tertiary protein separation of ribonuclease A, cytochrome C and lysozyme was used as a case study. A mechanistic model was calibrated using step and linear gradient experiments. The model was simulated together with the state sensitivities with respect to model parameters, which was used in the Levenberg-Marquardt algorithm to fit the model response to the experimental data. The model was used to solve the dynamic optimization problem of maximizing the yield of cytochrome C given a 95% purity requirement, 1000s processing time and 50 salt concentration levels in the elution trajectory. The model was spatially discretized using finite volumes and temporally discretized using direct collocation. The corresponding non-linear programming problem was solved with IPOPT. Once the optimal salt trajectory was found it was experimentally implemented on an ÄKTA Pure using an OPC interface. The optimal trajectory was analyzed in-line by UV absorbance measurements and off-line by analysis of collected fractions. The results presented in this study show the successful experimental realization of DiME trajectories and how to use model calibration, optimization and control to realize DiME trajectories for any chromatography separation problem.

A Generic PAT Software Interface for On-Line Monitoring and Control of Chromatographic Separation Systems

This contribution presents a novel process analytical technology (PAT) software interface for online monitoring and control of commercial high-pressure liquid chromatography (HPLC) systems. The developed interface is an add-on to chromatography control software and uses industry-standard bidirectional communication protocols to link sensor technologies with the individual HPLC system components in an overall automation framework that facilitates data acquisition, central operation and control of all instruments. The interface is encoded in the Python™ scripting language and supports versatile data transfer to chromatography control software using either OPC (OLE for process control) or COM (component object model) technologies, which are both based on client/server architectures. By these means, the interface utilizes the flexibility of the high-level programming language for formulating optimal control strategies and enables (semantic) interoperability between the chromatography control software and user defined scripts as well as third-party scientific libraries and numerical packages. The advantages and applicability of the developed interface are highlighted through the implementation of a model-based iterative learning control strategy, in order to assure batch-to-batch repeatability, and open-loop optimal controlled elution trajectories on a commercial HPLC separation system. It is, however, noteworthy that the software interface is completely generic and constitutes a novel framework for implementing any PID control schemes as well as sequential optimal experimental design and model predictive control strategies.

Designing an autonomous integrated downstream sequence from a batch separation process - an industrial case study†

This work is a proof of concept of how a sequence of industrial batch separation steps together are used to form an integrated autonomous downstream process. The sequence in this case study consisted of an anion chromatography step, virus inactivation and finally a hydrophobic chromatography step. Moving from batch to integrated separation minimizes hold-up times, storage tanks, and required equipment. The conversion from batch to integrated mode is achieved by extracting operating points and separation data from batch chromatograms. The integrated separation process is realized on an ÄKTA Pure controlled by an open research software called Orbit, making it possible to operate complex process configurations including multiple steps. The results from this case study is the principle and method of the steps taken to automation, achieving a more continuous and efficient downstream process.

Multi-flowrate Optimization of the Loading Phase of a Preparative Chromatographic Separation

This contribution consists of a multi-flow rate optimization method to maximize the key performance indicators, yield, degree of resin utilization and productivity for a chromatographic loading step. The protein adsorption to the resin is modeled using a mechanistic column model with a steric mass action adsorption isotherm. The model was used to optimize the flow rate trajectories and the loading duration by using a simultaneous method where the controls and state variables were discretized using a direct and local collocation method on finite elements in the temporal dimension and a finite volume weighted essentially non-oscillatory scheme in the spatial dimension. The discretized nonlinear program was solved using an interior point method. The two and three dimensional pareto fronts for the multi-objective optimization are presented and the multi-flow rate strategy showed considerable improvement in all objectives at different points on the pareto front. (Less)

Development and Optimization of a Single Column Analog Model for a Multi-Column Counter-Current Solvent Gradient Purification Process

Abstract This contribution presents a modeling and optimization method for multi-column counter-current purification (MCSGP) processes. The model is based on conventional column models and by using the symmetric and cyclic steady state characteristics of the process a single column analog model was developed. The model have been used for dynamic optimization of the MCSGP process. The optimization was based on a simultaneous method where the control and state variables were discretized using a direct and local collocation method on finite elements in the temporal dimension and a finite volume weighted essentially non-oscillatory (WENO) scheme in the spatial dimension. The resulting nonlinear program (NLP) were solved using an interior point method. The case study presented shows that the zero-order hold elution trajectories, developed for single column batch operation, can be extended to semi-continuous multi-column chromatography with product recycling. The optimization results is composed of a set of operating conditions where the product was upgraded to 95% purity with 99% process yield.