A model to capture CHO dynamics in-silico. An accompanying streamlit app to try the model out is available.
Model is based on the following primary sources:
- Pörtner, Ralf, ed. Animal Cell Biotechnology: Methods and Protocols. Vol. 2095. Methods in Molecular Biology. New York, NY: Springer US, 2020. https://doi.org/10.1007/978-1-0716-0191-4.
- Möller, Johannes, Tanja Hernández Rodríguez, Jan Müller, Lukas Arndt, Kim B. Kuchemüller, Björn Frahm, Regine Eibl, Dieter Eibl, and Ralf Pörtner. “Model Uncertainty-Based Evaluation of Process Strategies during Scale-up of Biopharmaceutical Processes.” Computers & Chemical Engineering 134 (March 2020): 106693. https://doi.org/10.1016/j.compchemeng.2019.106693.
Additional sources include:
-
Parolini, Dott Nicola, and Susanna Carcano. “A model for cell growth in batch bioreactors,” 2009, Thesis.
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Frahm, Björn. “Seed Train Optimization for Cell Culture.” In Animal Cell Biotechnology, edited by Ralf Pörtner, 1104:355–67. Methods in Molecular Biology. Totowa, NJ: Humana Press, 2014. https://doi.org/10.1007/978-1-62703-733-4_22.
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Möller, Johannes, Kim B. Kuchemüller, Tobias Steinmetz, Kirsten S. Koopmann, and Ralf Pörtner. “Model-Assisted Design of Experiments as a Concept for Knowledge-Based Bioprocess Development.” Bioprocess and Biosystems Engineering 42, no. 5 (May 2019): 867–82. https://doi.org/10.1007/s00449-019-02089-7.
This repo serves as a standalone package, available to install using (or added as a dependency) using:
pip install insilicho
from insilicho import run
def T(time):
"""returns temperature in degC"""
return 36.4
def F(time):
"""returns flow rate in L/hr"""
return 0.003
model = run.GrowCHO(
{"parameters": {"K_lys": "0.05 1/h"}},
feed_fn=F,
temp_fn=T,
)
model.execute(plot=True, initial_conditions={"V": "50 mL"})
final_vol = model.full_result.state[-1, 8]
print(final_V) # 0.914L