Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones

Abstract

Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these goals. Within this contribution, we propose a novel integrated process model procedure to maximize the use of development data to optimize the Stage 1 process validation work flow. We generate an integrated process model based on available data and apply two innovative Monte Carlo simulation-based parameter sensitivity analysis linearization techniques to automate two quality by design activities: determining risk assessment severity rankings and establishing preliminary control strategies for critical process parameters. These procedures are assessed in a case study for proof of concept on a candidate monoclonal antibody bioprocess after process development, but prior to process characterization. The evaluation was successful in returning results that were used to support Stage I process validation milestones and demonstrated the potential to reduce the investigated parameters by up to 24% in process characterization, while simultaneously setting up a strategy for iterative updates of risk assessments and process controls throughout the process life-cycle to ensure a robust and efficient drug supply.

Specification-driven acceptance criteria for validation of biopharmaceutical processes

“…IPMs can be used to predict the out-ofspecification probability for a given set of process parameter setpoints. Another application is to set up a control strategy for process parameters by defining proven acceptable ranges (Taylor et al, 2021). The methodology described in this contribution links iACs to drug substance specification limits using an integrated process modelling approach.…”

“…The number of out-of-specification events was calculated according to Taylor et al (Taylor et al, 2021). A normal distribution was fit to the data.…”

Trendbericht Analytische Chemie 2022

“…Ebenso werden in Zukunft verstärkt gekoppelte, integrierte Prozessmodelle eingesetzt, um Real Time Release des Endprodukts vorherzusagen. 58) Thematisiert werden Lebenszyklen digitaler Zwillinge, automatisierte Workflows zu ihrer Adaptierung und ihre Übertragbarkeit durch Transfer-Learning-Strategien. Traditionelle Prozessanalysentechnik wird künftig mit digitalen Zwillingen kombiniert.…”

Towards Autonomous Process Control—Digital Twin for CHO Cell-Based Antibody Manufacturing Using a Dynamic Metabolic Model

“…In addition to high-throughput screening using miniaturized and parallelized cultivation [6][7][8], a mechanistic, predictive process model is available as an alternative process optimization method [9][10][11]. Compared with the experimental approach, this offers the advantage that many parameter combinations can be screened within a short time [12,13]. For later automation, the process model also serves as the basis of the digital twin [14].…”