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AI for Bioprocess Modelling: Technical Resource Library

Supporting process development professionals with modular technical training. A comprehensive resource for applying hybrid models to real-world datasets and mastering complex bioprocess simulation.

Challenges in Bioprocess Modeling

Explore the fundamental hurdles in bioprocess development, focusing on the "visibility gap" between surface-level measurements and the complex, hidden biological drivers that often lead to inefficient trial-and-error scaling.

Hybrid Modelling in Bioprocessing (I)

Addressing the Modeling Dilemma, this module introduces hybrid modeling as the "Golden Middle." We combine biological first principles with Knowledge-Informed AI to overcome the data limitations of traditional bioprocessing.

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Hybrid Modelling in Bioprocessing (II)

Breaks the bioprocess into modular "biological blocks" to model shifting physiological states - from growth to production and stress. This creates accurate Digital Twins that optimize process yields and ensure robust, scalable results.

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Use Case: Filamentous Fungi

Discover how hybrid modeling untangles the complex relationship between fungal morphology and broth viscosity to prevent metabolic shifts and oxygen limitations in large-scale fermentations.

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Use Case: E. coli

This case study demonstrates how modeling complex kinetics and population heterogeneity in E. coli optimized induction timing. Identifying the ideal biological window maximized productivity and achieved 10x improvements.

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Case Study: Pichia

See how dynamic model calibration and iDoE-based validation enabled a 40% increase in protein yield for Pichia pastoris by optimizing the transition from fed-batch to continuous multi-harvest protocols.

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