Model-based monitoring of industrial reversed phase chromatography to predict insulin variants.

Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process- and product-related impurities. However, removing product-related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model-based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography. The system was described by a kinetic dispersive model with a modified Langmuir isotherm. Solely quality control analytical data on product and product variant concentrations were used to calibrate the model. This model-based monitoring approach was developed for an insulin purification process. Industrial materials were used in the separation of insulin and two insulin variants, one eluting at the product peak front and one eluting at the product peak tail. The model, fitted to analytical data, used one component to simulate each protein, or two components when a peak displayed a shoulder. This monitoring approach allowed the prediction of the elution patterns of insulin and both insulin variants. The results indicate the potential of using model-based monitoring in downstream polishing at industrial scale to take pooling decisions.

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.

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. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:923-930, 2017.

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.

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) m(2) /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.