Bioreactor Scale-Up Strategy: Key Concepts and Approaches
How does Graphtal’s expertise turn complex scale-up into a cost-efficient, data-driven process?
›Our
Bioreactor Scale-Up Focused Offerings:
•Mechanistic
Modelling for Scale-Up: Build first-principle models to
understand key process parameters and enable predictive scale performance.
•CFD-Based
Bioreactor Hybrid Modelling: Use Computational Fluid Dynamics to
simulate fluid flow, mixing(tm), and mass transfer (KLa) — critical for scaling
bioreactors with high accuracy and validated models.
•Data-Driven
Process Modelling: Harness historical prior knowledge and process data to
optimize scale-up strategies and uncover hidden process challenges.
•Hybrid
Modelling: Combine mechanistic and machine learning
models to accurately forecast performance across scales and bioreactor types.
•Regression Models: Efficiently explore process conditions at
pilot and commercial scale, reducing experimental burden and enabling scalable
design spaces.
•Machine
Learning for Predictive Scale-Up: Apply ML algorithms to anticipate
scale-up risks, optimize process settings, and ensure product quality at scale.
•Multivariate
Data Analysis (MVDA): Support consistent quality during
scale-up with advanced statistical analysis across batches and production
scales.
•Technology
Assessment, Software Tools, and Scale-Up Training: Evaluate new tools for scalability, and empower teams with specific trainings on scale up, scale down, modelling, and other digital scale-up strategies.
Tell Us About Your Project
Our team of experienced professionals at Graphtal is ready to transform your project from idea to
reality, ensuring alignment with your organisation goals through advanced data analytics and
predictive modelling.
Let's simplify your work