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Upstream Processing

Optimize and Monitor Upstream Bioprocessing with Data-Driven Insights

Inconsistent upstream conditions can lead to suboptimal protein expression, metabolic imbalances, and inefficient production yields—threatening process efficiency. Without process insights into key metabolites and protein titers, manufacturers risk costly batch failures, poor scalability, and unpredictable bioreactor performance.

A proactive approach helps biopharma companies gain complete control over upstream processing by combining near real time information with expert-driven data interpretation. The dataset below illustrates how critical parameters—glucose consumption, lactate production, amino acid metabolism, and phosphoric acid depletion—impact protein expression over time. Identifying these shifts early enables proactive process adjustments, improving yield and consistency. Example Insight: At T3, protein titer reaches its peak (see also raw spectra: increase of Amide I and Amide II bands (1500 - 1750 cm⁻¹)), but phosphoric acid depletion and metabolic byproducts suggest potential nutrient limitations. A data-driven approach ensures that culture conditions remain optimized throughout the process....

Unlock the full potential of your upstream process. Reduce variability, maximize yield, and accelerate bioprocess development with expert-driven analytics. This kind of dataset can be generated without the need of any complex chemometric model generation. CLADE's Data Driven DOSIM algorithm enables you to turn four minute mesurements into data driven insights virtually instantly.

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Attribute T_0 T_1 T_2 T_3
Protein Concentration [mg/ml] 0 Gene
expression
induced
0 2 22
Glucose [mg/ml] 5.7 0.1 0.2 0.4
Lactate [mg/ml] 0.01 0 0.03 0.02
Asparagine [mg/ml] 0 0.5 0.8 1.4
Isoleucing [mg/ml] 0 0.1 0.5 0.9
Glutamine [mg/ml] 0.2 0.5 0.7 1.0
Citric Acid [mg/ml] 1.8 1.7 0.8 1.3
Ammonia [mg/ml] 1.2 1.4 1.2 1.4
Phosphoric Acid [mg/ml] 10 8 5 1

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