How to Optimize Culture Media Using Fermentation Data | Constellab Bioprocess

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Full walkthrough of a medium optimization use case for Lactobacillus delbrueckii subsp. bulgaricus fermentation, using simulated data inspired by a published study (Tovilla-Coutino et al., 2022). We show how to load experimental data, visualize growth curves, extract kinetic features, and run multivariate analyses — all within the Constellab Bioprocess Dashboard, without writing a single line of code.

🔍 What You'll Learn:

Loading multi-file fermentor data (Info CSV, Raw Data CSV, Medium CSV, Follow-up ZIP)
Selecting samples and visualizing growth curves per medium
Configuring and running a quality check
Performing Medium PCA to explore compositional variability
Running PLS Regression and Random Forest to identify key medium components
Running Causal Effect analysis
Running Optimization module to predict the ideal medium formulation

💻 Explore the App:
Access the app directly here: https://constellab.community/apps/e1ec0c56-43a3-4b4d-a642-1ca4e555c8c9/constellab-bioprocess

🔗 Documentation: https://constellab.community/bricks/gws_plate_reader/latest/doc/use-cases/constellab-bioprocess/e20dbf4f-72d5-49ba-b71f-730fc6cf9b49

🎬 CHAPTERS
0:00 Introduction & Scientific Context
1:20 Loading the Data
2:08 Sample Selection & Visualization
3:20 Quality Check
4:00 Medium PCA and UMAP
4:46 Feature Extraction
5:30 Metadata Feature UMAP
5:56 PLS Regression and Random Forest Regression & VIP Scores
6:44 Causal Effect Analysis
6:58 Optimization & Conclusions

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Видео How to Optimize Culture Media Using Fermentation Data | Constellab Bioprocess канала Gencovery