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Artificial Intelligence Driven Digital Twin Framework for Real-Time Monitoring and Quality Control of GMP Stem Cell Manufacturing Processes with Nonlinear Bifurcation Analysis

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  • Khadija Sankoh

Abstract

This study develops a simulation-based artificial intelligence (AI) digital-twin framework for real-time monitoring and quality control of Good Manufacturing Practice (GMP) stem-cell manufacturing processes, with nonlinear bifurcation analysis used to identify loss-of-stability boundaries before conventional process limits are crossed. The supplied study dataset represents 60 manufacturing batches and 43,200 synchronized five-minute process states, including 14 online process variables and eight laboratory or soft-sensor critical quality attributes (CQAs).

Suggested Citation

  • Khadija Sankoh, 2026. "Artificial Intelligence Driven Digital Twin Framework for Real-Time Monitoring and Quality Control of GMP Stem Cell Manufacturing Processes with Nonlinear Bifurcation Analysis," International Journal of Innovative Science and Research Technology (IJISRT), IJISRT Publication, vol. 11(09), pages 947-958, September.
    • Handle: RePEc:cvr:ijisrt:2026:09:ijisrt26sep934
    DOI: https://doi.org/10.38124/ijisrt/26sep934
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