A comprehensive study in PAT-applications for a QbD-compliant development of continuous biopharmaceutical production

Conference Dates

September 17-21, 2017


The development of continuously operated integrated pharmaceutical production processes needs a tremendous expenditure. Beside the installation of a full-scale production, scale-down concepts are essential to meet the QbD-specifications of the FDA. In this presentation the surrounding PAT-field of such a plant for production of potential Malaria vaccines (shown in ICB I and ICB II) is discussed in order to create model based QbD-compliant strategies. This includes fully automated processing, global process monitoring with additional classical and spectroscopic measurement procedures including enhanced data processing and MVDA. A full-scope model of the plant allows an in-silico development of process control. The two-stage upstream line is scaled-down in a sixfold sequential/parallel operated bioreactor plant including flow analysis at-line measurements for substrates- and target protein-detection. This plant allows a fully automated simultaneous DoE-process optimization and identification of CPP-Critical Process Parameters. The DoE-model and Monte Carlo simulations create also the Design Space and the Control Space of QbD-production. Similar methods are used in the down-stream area for optimization of cyclic protein purification. These methods are applied with an AEKTAT avant which is developed especially for DoE. The main focus of the work lies on the development of a global MVDA-based monitoring system for biotechnological variables like cell mass, glycerol-, ammonium-, total secreted-, and target protein-concentration but also on the evaluation of process quality (reproducibility) of the running processes. Applications of NIR-, Raman-, and 2D-Fluorescence-Spectroscopy and the appropriate PLSR-modeling leads to a partly success. This was improved by using the nonlinear SVR-Support Vector-machine Regression. However, a MVDA-application with only classical process variables from agitation, aeration, temperature, feeding, pH, pO2, and process balances creates astonishing results in a satisfying bio-monitoring up to the on-line detection of the secreted target protein concentration. The quality of running processes was evaluated with a GB-Golden Batch approach. The GB-tunnel was created with data from QbD-conformed process courses and then used for an on-line observation and prediction of actual first principal components. A MPC-Model Predictive Control was also implemented in order to avoid a leaving of the GB-tunnel by correction of process set-points. These methods open the way to an on-line release of pharmaceutical products.

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