Fermentation Optimization
Maximizing Titers, Yields, and Productivity through Kinetic Modeling
The Science of Yield
Optimization at BioFlo goes beyond simple parameter tuning. We analyze the metabolic bottleneck of your strain by coupling stoichiometry with dynamic growth models.
Kinetic Characterization
Determining the fundamental growth limits of the culture using the Monod relationship:
\[ \mu = \mu_{max} \frac{S}{K_s + S} \]
Defining the saturation constant (\(K_s\)) to optimize nutrient feeding strategies.
Yield Quantification
Analyzing substrate-to-biomass (\(Y_{X/S}\)) and substrate-to-product (\(Y_{P/S}\)) conversion efficiencies:
\[ q_s = \frac{\mu}{Y_{X/S}^{max}} + m_s \]
Accounting for maintenance coefficients (\(m_s\)) during prolonged fed-batch phases.
Optimization Strategies
Our approach integrates multi-omics data with bioprocess variables to stabilize production:
- Fed-Batch Feeding Profiles: Designing exponential, constant, or \(DO\)-stat feeding regimes to prevent substrate inhibition (Crabtree effect).
- Gas Transfer Synchronization: Aligning Oxygen Transfer Rate (\(OTR\)) with the biological Oxygen Uptake Rate (\(OUR\)) to maintain metabolic flux.
- Media Formulation: Statistical Optimization (DoE) coupled with stoichiometric metabolic requirements.
Ready to Scale Your Process?
From lab-scale shake flasks to industrial-scale fermenters, we provide the modeling expertise to ensure consistency.
Consult with an Expert
Inquiries: ajit@bioflo.in