- Recorded load
- 40 g/L resin
- Residence time
- 2 min
- Protein loaded
- 40 mg
- Protein recovered
- 27.2 mg
Recovery68%
Below the study’s 80% criterion. Retained in the assessment.
Process characterization.
Configure and run process characterization (PC) studies in Seal, with protocols, results and assessments kept together. Trace each proposed operating range back to the experiments that support it.
Bring your study
How much can we load
without losing recovery?
A capture study with four corner conditions and three centre runs. Each execution keeps its protocol version, actual settings and results.
Load × residence time
Select a condition to inspect its execution.
20 g/L40 g/L
2 min
4 min
Centre runs30 g/L · 3 min
Inspect the configured study
Study PC-021 uses a 1 mL column and one load lot and resin lot. The protocol requests 20 and 40 g/L resin at 2 and 4 minutes, with three centre runs at 30 g/L and 3 minutes. The illustrative recovery criterion is ≥80%. Planned and recorded factor settings match in these seven records. Product-quality results and cross-lot confirmation are not supplied.
Higher load.
Different results.
At 40 g/L, recovery depends on which residence time was tested.
Protein recovery
━ 2 min┄ 4 min··· 80% study criterion
Centre runs30 g/L · 3 min
85%86%87%
Can we take the higher load forward?
neil
Check residence time with it.
At 40 g/L, the 2-minute run recovers 68%; the 4-minute run recovers 87%. The load effect differs between the two residence times.
I’d confirm the corner conditions and add quality results before selecting a range. These observations do not establish a proven range.
Inspect the source results
| Run | Load g/L | Time min | Recovery |
|---|---|---|---|
| PC-021-01 | 30 | 3 | 85% |
| PC-021-02 | 20 | 2 | 84% |
| PC-021-03 | 40 | 4 | 87% |
| PC-021-04 | 40 | 2 | 68% |
| PC-021-05 | 30 | 3 | 86% |
| PC-021-06 | 20 | 4 | 91% |
| PC-021-07 | 30 | 3 | 87% |
All seven runs are included. Centre replicates do not replace replication at the corners. The source values are assay-derived recovered protein mass divided by loaded protein mass.
Know what the study
actually covers.
Four corners, three centre runs, one material and resin lot. See the coverage before carrying a conclusion into the next study or scale.
Does the load effect repeat?
The centre runs give repeat observations at one condition. They do not establish repeatability at the four corners. Preserve the observed recovery difference and agree the replication needed to test it.
Return to the seven run results →Does recovery tell us about product quality?
Not on its own. This example contains no purity, aggregate or impurity-clearance results. Link the relevant pool samples and analytical evidence before drawing conclusions about critical quality attributes or parameter criticality.
Will the conclusion apply to another lot or scale?
These runs use one load lot and one resin lot on a 1 mL column. Record the scale-down model rationale, relevant equipment differences and material variability. Decide which additional evidence is needed for the intended manufacturing context.
What supports a proposed control?
Retain the exact analysis population, deviations, exclusions, model assumptions and diagnostics. A control proposal should reference the supporting studies, quality evidence, uncertainty and remaining risks—not only the best-looking run.
From finding
to follow-up protocol.
neil prepares the assessment and next study. Your scientists decide what to test, which criteria apply and when the protocol is ready.
Capture study follow-up
PC-021 · DraftConfirm the corners. Measure quality alongside recovery.
Scientific rationale
The higher-load runs differ by 19 percentage points in recovery. Retain both results and test whether the difference repeats.
PC-021-03 and PC-021-04 →Before the study can run
- Replication & run order
- To agree
- Quality responses & criteria
- To define
- Material & scale coverage
- To assess
Inspect the proposed follow-up protocol
- Design
- Confirm load × residence-time behaviour; agree replication and run order with the study statistician.
- Execution
- Record actual factor settings, material and resin lots, column history, deviations and linked pool samples.
- Responses
- Recovery plus the relevant quality attributes and reviewed analytical methods.
- Before execution
- Scientists agree the design, acceptance criteria and applicability questions. Test the configured workflow.
No approved range yet. The study’s recovery criterion is not a product-quality approval.
More than a study report.
For PD and MSAT teams characterizing culture, purification, formulation or other unit operations. Keep the experimental work and the control rationale connected.
Start with the uncertainty.
Connect prior knowledge and risk questions to the factors and quality attributes worth studying. Record where a scale-down model or platform assumption still needs confirmation.
Process development →Keep your analysis tools.
Use JMP, Minitab, R or Python alongside Seal. Retain the exact dataset, exclusions, model version and diagnostics behind the reviewed interpretation.
Connected systems →Carry decisions into execution.
Connect reviewed ranges and controls to the operating protocol and PPQ requirements. Preserve the evidence and unresolved risks behind each decision.
Process validation →Learn from the process in use.
Link later trends and deviations back to the characterization study. Reassess a conclusion when new evidence changes its basis; keep the earlier version.
Continued process verification →Questions from characterization teams.
Yes. Configure the study question, factor levels, run order, materials, sampling, calculations and review steps. Each run retains the protocol version, actual conditions, observations and source results. Test the workflow against its intended use before relying on the configured controls.
Specialist analysis can remain in JMP, Minitab, R, Python or another suitable tool. Connect the analysis dataset, exclusions, script or model version, diagnostics and outputs to the study records. The website chart is a comparison of fictional observations, not a fitted statistical model.
Explored conditions are those actually tested. A proposed operating range needs supporting performance evidence, uncertainty and applicability assessment. An approved range also has a reviewed rationale and authorised decision. A few passing observations do not establish a design space.
Connect a candidate process parameter to the critical quality attributes it may affect and the studies supporting that relationship. Critical process parameter (CPP) classification requires the relevant quality evidence and risk assessment. Recovery alone is not a substitute for critical quality attribute (CQA) evidence.
Record the source study, model suitability, materials, equipment, scale and relevant differences. Reuse depends on an applicability assessment and any necessary confirmation work. Similar operating settings do not demonstrate comparable process behaviour at another scale or site.
Carry reviewed parameter controls, sampling requirements, residual risks and supporting evidence into process performance qualification (PPQ). Link later continued process verification (CPV) trends and deviations back to the original characterization conclusion. New evidence can trigger reassessment without replacing the earlier record.