In order to support a model-based process design in ion-exchange chromatography, an adsorption equilibrium model was adapted to predict the protein retention behavior from the amino acid sequence and from structural information on the resin. It is based on the computation of protein resin interactions with a colloidal model and accounts for the contribution of each ionizable amino acid to the protein charge. As a verification of the protein charge model, the experimental titration curve of a monoclonal antibody was compared to its predicted net charge. Using this protein charge model in the computation of the protein-resin interactions, it is possible to predict the adsorption equilibrium constant (i.e. retention factor or Henry constant) with an explicit pH and salt dependence. The application of the model-based predictions for an in silico screening of the protein retention on various stationary phases or, alternatively, for the comparison of various monoclonal antibodies on a given cation-exchanger was demonstrated. Furthermore, considering the structural differences between charge variants of a monoclonal antibody, it was possible to predict their individual retention times. The selectivity between the side variants and the main isoform of the monoclonal antibody were computed. The comparison with the experimental data showed that the model was reliable with respect to the identification of the operating conditions maximizing the selectivity, i.e. the most promising conditions for a monoclonal antibody variant separation. Such predictions can be useful in reducing the experimental effort to identify the parameter space. (C) 2013 Elsevier B.V. All rights reserved.

The article describes how Quality by Design principles can be applied to the drug substance manufacturing process of an Fc fusion protein. First, the quality attributes of the product were evaluated for their potential impact on safety and efficacy using risk management tools. Similarly, process parameters that have a potential impact on critical quality attributes (CQAs) were also identified through a risk assessment. Critical process parameters were then evaluated for their impact on CQAs, individually and in interaction with each other, using multivariate design of experiment techniques during the process characterisation phase. The global multi-step Design Space, defining operational limits for the entire drug substance manufacturing process so as to ensure that the drug substance quality targets are met, was devised using predictive statistical models developed during the characterisation study. The validity of the global multi-step Design Space was then confirmed by performing the entire process, from cell bank thawing to final drug substance, at its limits during the robustness study: the quality of the final drug substance produced under different conditions was verified against predefined targets. An adaptive strategy was devised whereby the Design Space can be adjusted to the quality of the input material to ensure reliable drug substance quality. Finally, all the data obtained during the process described above, together with data generated during additional validation studies as well as manufacturing data, were used to define the control strategy for the drug substance manufacturing process using a risk assessment methodology.

A model was developed for the design of a monoclonal antibody charge variants separation process based on ion-exchange chromatography. In order to account for a broad range of operating conditions in the simulations, an explicit pH and salt concentration dependence has been included in the Langmuir adsorption isotherm. The reliability of this model was tested using experimental chromatographic retention times as well as information about the structural characteristics of the different charge variants, e.g. C-terminal lysine groups and deamidated groups. Next, overloaded isocratic elutions at various pH and salt concentrations have been performed to determine the saturation capacity of the ion-exchanger. Furthermore, the column simulation model was applied for the prediction of monoclonal antibody variants separations with both pH and salt gradient elutions. A good prediction of the elution times and peak shapes was observed, even though none of the model parameters was adjusted to fit the experimental data. The trends in the separation performance obtained through the simulations were generally sufficient to identify the most promising operating conditions. The predictive column simulation model thus developed in this work, including a set of parameters determined through specific independent experiments, was experimentally validated and offers a useful basis for a rational optimization of monoclonal antibody variants separation processes on ion-exchange chromatography.

PURPOSE:The purpose of this study was to evaluate the activity of CG53135 (FGF-20), a protein with in vitro mitogenic activity on epithelial and mesenchymal cells, in two in vivo models of oral mucositis (OM).EXPERIMENTAL DESIGN:Radiation or concomitant chemotherapy/radiation-induced OM was elicited in hamsters. Activity of CG53135 was assessed at different doses and regimens in the models. Bromodeoxyuridine (BrdUrd) incorporation and pharmacokinetic studies were also performed to correlate in vivo activity of CG53135 with exposure.RESULTS:In the hamster radiation model, administration of CG53135 (600 or 1200 micro g/day, i.p.) on days 3-15 resulted in a statistically significant (P < 0.001) reduction in days spent with severe mucositis. CG53135 administered at 12 mg/kg, i.p. (days 1-2 or 1-8) in the concomitant chemotherapy/radiation model resulted in a statistically significant (P < 0.001) reduction in severe mucositis. Maximal BrdUrd incorporation was observed in cheek pouch and jejunal tissues at 8 h, and peak plasma levels of CG53135 were reached 1 h after administration.CONCLUSIONS:CG53135 demonstrates potent, regimen-dependent activity in hamster models of OM. The activity was regimen dependent. BrdUrd incorporation studies confirmed that CG53135 had proliferative activity in vivo with a favorable pharmacokinetic profile. Based in part on work described herein, CG53135 has received approval from the United States Food and Drug Administration to be evaluated in a Phase I clinical trial of cancer patients at risk for developing OM.