insilicho 1.1.3

An insilico model for CHO cells

InSiliCHO

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.

• 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.

• 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.

Usage

This repo serves as a standalone package, available to install using (or added as a dependency) using:

pip install insilicho

Example

  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