To achieve Agility in manufacturing – embrace Variability – Part 1
Posted 1644 days ago
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Increase in Vaccine Purity
Product Recovery Achieved
Faster Process Development
Wet-Lab Runs Required
Industry:
Life Sciences
Location:
USA
High cost of redundant wet-lab experiments
Limited value from in-silico characterization
Inadequate model accuracy for viral clearance
Insufficient data for reliable ML-based optimization
The vaccine purification optimization strategy led to an 11% increase in purity and 93% product recovery—exceeding historical targets. The team reduced wet-lab experiments by 40%, shortening development timelines and improving cost efficiency.
Unified lab, PAT, and process data streams to contextualize vaccine purification process insights in real time.
Simulated process outcomes and optimized purification setpoints with predictive in silico modeling.
Recommended optimal conditions using small-data ML, reducing manual iterations in biopharma purification process design.
Quartic helped us transition away from traditional development cycles. Their in-silico approach saved time, improved purity, and reduced experimentation.
