Publications by authors named "M Kunzelmann"
Article Synopsis
- * It introduces the Life-Cycle-Design of Experiments (LDoE) methodology, which integrates various data and enhances model predictions by allowing for flexible design adjustments during the development process.
- * The LDoE approach consolidates all experimental data into one cohesive model, enabling timely identification of critical process parameters, which can lead to more effective and efficient process development.
Article Synopsis
- The study presents a new type of infectivity assay that uses label-free bright-field imaging to track changes in cell shape due to virus infection.
- This kinetic infectious virus titer (KIT) assay allows for quick analysis of viral titers, showing results within 24 hours and demonstrating high accuracy with low variability across samples.
- The KIT assay is versatile enough to be applied to various viruses and could significantly improve the efficiency of virus testing in both pharmaceutical and academic settings.
Article Synopsis
- Robust potency assays are crucial for biotherapeutic analytics and Design of Experiment (DoE) approaches help analyze how different assay parameters affect these assays.
- Current methods evaluate specific assay features in isolation, making it hard to understand their combined effects.
- The proposed functional DoE approach models the relationships between assay features, optimizing assay design through a multivariate desirability, which enhances the understanding and reliability of biotherapeutic analytics.
Specification-driven acceptance criteria for validation of biopharmaceutical processes.
Front Bioeng Biotechnol
September 2022
Intermediate acceptance criteria are the foundation for developing control strategies in process validation stage 1 in the pharmaceutical industry. At drug substance or product level such intermediate acceptance criteria for quality are available and referred to as specification limits. However, it often remains a challenge to define acceptance criteria for intermediate process steps.
View Article and Find Full Text PDFMaximizing 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.
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