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Path Catalog
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This learning path reviews and updates the core competencies of bioprocess engineering for graduate students, focusing on recent advances and emerging technologies. It covers advanced bioprocess design, modeling, automation, and regulatory considerations to support career development.
This advanced learning path guides bioprocess engineering students through the integration of core knowledge areas—bioreactor design, kinetics, downstream processing, and scale-up. It emphasizes the interconnectedness of these topics to prepare learners for real-world bioprocess development and optimization.
This learning path provides a systematic introduction to the biological foundations of biotechnology, covering cell biology, microbiology, and molecular biology. It is designed for bioprocess engineering and biology students at the university level, progressing from fundamental cellular concepts to molecular mechanisms and their applications.
This learning path provides a systematic foundation in chemical engineering principles applied to bioprocesses, covering stoichiometry, thermodynamics, transport phenomena, reaction kinetics, and bioreactor design. It integrates these principles with biochemical and biological fundamentals to enable the analysis and design of bioprocess unit operations.
This advanced graduate-level path equips bioprocess engineers and synthetic biology students with the knowledge to understand and implement biofoundry workflows. It covers the foundational principles of synthetic biology, the core design-build-test-learn cycle, and the automation, high-throughput, and data integration strategies that define modern biofoundries.
This graduate-level learning path systematically covers the design, construction, and optimization of synthetic biological systems for bioprocess applications. It integrates molecular biology fundamentals, genetic circuit design, metabolic engineering, and bioprocess scale-up considerations. The path emphasizes both theoretical understanding and practical application, preparing learners to engineer microbes for industrial production.
This advanced learning path equips bioprocess engineers and data scientists with the knowledge to model, simulate, and apply AI to bioprocesses. Starting with core bioprocess engineering and modeling, it progresses through mechanistic and data-driven modeling, then integrates them into digital twins. The path culminates in a capstone project where learners build and validate a digital twin for a bioreactor process.
This advanced graduate-level path provides a systematic understanding of single-use (disposable) bioprocessing technologies. It covers the foundational principles, key unit operations, integration strategies, and the challenges and considerations for implementing single-use systems in biopharmaceutical manufacturing.
This advanced graduate-level path equips bioprocess engineering students with the knowledge to design, operate, and intensify continuous bioprocessing systems. It covers fundamental principles, process design, operational challenges, and intensification strategies, integrating both upstream and downstream processing.
This learning path guides bioprocess engineering students through the principles and practices of scaling up bioprocesses from laboratory to pilot scale. It covers bioreactor fundamentals, scale-up criteria, pilot plant operations, and data analysis to enable successful scale-up experiments.