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Connect evidence
Connect campaign runs with feed, material lots, metabolites, viability and reactor events.
01
← All modalities
CHO · MAB
Monoclonal antibodies
Bring cell-culture records, process conditions, downstream recovery and analytical outcomes into one scientific context. Compare runs, investigate changes and evaluate the next process scenario using the evidence that supports it.
CHO · mAbMonoclonal antibodies
OUTCOMES TRACKEDTiterrecoveryproduct quality
MODALITY-SPECIFIC PROCESS INTELLIGENCE
Connect culture performance to final product quality.
01Cell culture
02Harvest
03Purification
04Quality
FOCUS AREA · Cell culture
Culture development
Compare growth, viability, feed, nutrients and product accumulation across clones and culture conditions.
01
EVIDENCE · MODELS · DECISIONS
Keep every conclusion connected.
Evidence in Bio Hub
- Cell growth and viability
- Feed, metabolites and reactor conditions
- Chromatography, recovery and quality assays
Models in Bio Twin
- Culture kinetics and hybrid prediction
- Feed and operating-window comparisons
- Scale-dependent process assessment
Scientific decisions
- Compare media and feed strategies
- Investigate titer or quality shifts
- Assess transfer and scale-up scenarios
Process outcomes to evaluate: Titer · recovery · product quality
SOFT SENSORS
Estimate what you cannot continuously measure.
Explore process-specific estimates of biomass, metabolites, product titer and purification performance using scientific models and available process measurements.
Explore BioMedAna Soft Sensors ↗EXAMPLE INVESTIGATION
Why did titer decline while the nominal setpoints stayed the same?
02/ 04
Compare context
Compare the affected cohort with representative historical runs and aligned process phases.
02
03/ 04
Evaluate explanations
Evaluate plausible growth, nutrient and transport explanations; use calibrated model scenarios where appropriate.
03
04/ 04
Review next steps
Prepare a traceable comparison and recommend the experiment or measurement that would distinguish the hypotheses.
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Bio Agents can coordinate the scientific work across evidence and models, while Bio OS preserves governance and human review. The configured workflow determines which tasks and models are available.
Bring us this process challenge ↗EVALUATION & SCOPE
Make the demonstration specific.
Evaluate model fitness against independent runs, the intended operating range and the specific output. A model of titer does not automatically validate predictions of glycosylation or other quality attributes.
What evidence should we bring?
Cell growth and viability. Feed, metabolites and reactor conditions. Chromatography, recovery and quality assays. Include the process question, relevant run context and the analytical methods used to assess the outcome.
How do models support the workflow?
Culture kinetics and hybrid prediction. Feed and operating-window comparisons. Scale-dependent process assessment. Scope and evaluation criteria are defined for your process, data and intended decision.
What should we validate before using the results?
Evaluate model fitness against independent runs, the intended operating range and the specific output. A model of titer does not automatically validate predictions of glycosylation or other quality attributes.
EXPLORE OTHER MODALITIES
ENTERPRISE USE CASE
Investigating a CHO process transfer across manufacturing sites
A transfer investigation connecting matched batch cohorts, temperature-transition timing and a product-specific quality panel.
Explore the complete use case ↗Balancing mAb titer and quality from the next experiment to scale-up
Follow a CHO fed-batch development decision from strong titer and variable quality through experiment selection, a pilot-scale surprise and a targeted confirmation plan.
Explore the complete use case ↗From Batch Variability to Predictable Biomanufacturing
How BioMedAna helps MSAT teams investigate batch variability, assess process risks and evaluate manufacturing scenarios using scientific models and AI.
Explore the complete use case ↗