Bridging Experimental Fermentation Data and Mechanistic Models Through Literature Synthesis

Project Details

• Student(s): Carolina Hakam
• Advisor(s): Dr. Elie Chalhoub; Co-contributor: Dr. Joanne Belovich, Professor, Chemical Engineering Department, Cleveland State University, Ohio, USA.
• Department: Chemical
• Academic Year(s): 2025-2026

Abstract

Fermentation processes are governed by complex biochemical and physiological interactions that vary widely across systems, yet a unified understanding of these dynamics is often hindered by fragmented experimental data. This study aims to integrate existing knowledge by conducting a comprehensive survey of the literature to compile, curate, and harmonize experimental datasets relevant to microbial fermentation. These data will form the basis for quantitative analyses, including identification of trends, sources of variability, and data‐driven insights into system behavior. 

Building on this foundation, we will develop a structured mechanistic model that captures the key metabolic, kinetic, and process-level interactions underlying fermentation performance. Model construction will be accompanied by systematic parameter estimation using aggregated literature data, followed by global and local sensitivity analyses to identify influential parameters and dominant mechanisms. Confidence intervals and uncertainty quantification techniques will be employed to assess the robustness of the fitted parameters and the predictive capability of the model.