Lots. Trends. Deviations. Yields. APQR. Every number, and the rows it counts.
The review is counted on the record itself, every lot in the period, and each number opens to the rows it counts. Neil drafts; QA signs.
Line 2, Aug to Nov
Line 2's review
Aug to NovBlubber Biologics is a fictional plant.
A shift is found lot by lot.
The feed track rose 0.7 A over five lots, and no limit was set. Neil draws the five means on its first night and raises it.

F-02 feed track, lot by lot
F-02's feed track
Five lotsIt counts what was said, too.
The records counted no interventions. Neil read what was said on Line 2 and found four jams; QA decides what each was.

Line 2, Aug to Nov
Line 2's stops
Aug to NovEvery count on the certificate adds up.
41,860 filled, 61 lost at the stop, 318 at inspection, 142 sampled, 41,339 released: every count is the record's own. The QP certifies.

Lot 26-0917
Lot 26-0917's certificate
Filled Fri 6 NovQuestions about APQR.
What is APQR software?
It manages the scope, population, evidence, analyses, conclusions, approvals and actions for an annual product quality review. It replaces manual compilation from separate sources, while scientific and quality review remains with your team.
Are APQR, APR and PQR the same?
They all describe a periodic evaluation of product and process quality, but the terms and detailed expectations vary by jurisdiction. Seal can be configured for the applicable scope, sections, review cycle and approvals. One template does not necessarily satisfy every market.
Can Seal collect APQR data from other systems?
Yes. Integrations can bring in manufacturing, LIMS, QMS, stability, supplier, complaint and partner records. Population completeness, late data, duplicates and source versions remain visible before approval.
How does Seal check that each batch is included?
The review definition sets an expected population and reconciles records across source systems by identity and state. Missing, excluded, rejected, reworked or pending batches need explicit handling rather than dropping out of a released-batch list.
Can APQR software calculate Cp and Cpk?
Seal can run configured statistical methods against a defined dataset, cohort, limits and exclusions. Your team decides whether a capability statistic is appropriate for the data and approves its interpretation.
How are OOS and invalidated results represented?
The full analytical history stays linked to its samples and investigations. Configured reportable-result rules decide which values enter a product statistic, while invalidated and retested results remain visible for review.
Does Seal support multi-site product reviews?
Yes. Site, process version, scale and contract party remain explicit dimensions. Reviewers can evaluate the product overall and in comparable cohorts without averaging away site or process differences.
How are prior APQR actions tracked?
Each action carries its owner, due date, source conclusion and completion evidence. Open or ineffective actions remain visible to the next review.
Can the approved report change when source data changes?
No. Approval fixes the scope, source snapshots, analyses, conclusions and signatures. Significant later information is handled through an amendment or assessment, and the next period continues separately.
How does APQR connect to continued process verification?
CPV supplies ongoing process and quality evidence. The annual review evaluates it alongside quality events, stability, complaints, suppliers and changes, and can raise new CPV actions or monitoring changes.
Can external manufacturer data be included?
Yes. Partner data keeps its source, period, batch population, receipt and review status. Missing or late partner evidence remains an explicit exception in the review.
Does it replace Spotfire, Tableau, JMP or SIMCA?
No. Process scientists explore and model in JMP, SIMCA or Spotfire, and a BI tool shows management its dashboards; each can read the record through Seal’s API. Seal counts the numbers that are themselves part of the GMP record, such as the product review, a trend against its limit and a lot’s reconciliation, where each figure has to open to the rows behind it and be signed.
Who writes the product review?
Neil drafts it from the record: the lots in the period with their yields, deviations, changes and results, each figure linked to the rows it counts. Section owners review and correct the draft, and QA approves and signs it.
Does Neil decide anything in the review?
No. Neil counts, drafts and points to what it found. Whether a trend is a shift, what an event was and what the review concludes are decided and signed by your team.
What should the first APQR implementation prove?
Take one product and reconcile its full batch population, including rejected and pending batches. Reproduce the statistics, handle missing and changed data, approve the conclusions and create the follow-up work, then check that each chart leads back to its sources.
In depth
The APQR guide7 sections
All 10 capabilities
- Controlled review scope
- Define the products, presentations, sites, period, population rules, sections, owners and approval before analysis begins.
- Batch population reconciliation
- Reconcile manufactured, released, rejected, reworked, returned and pending batches across source systems, so each batch in scope appears with its state at the data cut.
- Laboratory and stability evidence
- Results keep their sample, method, specification, OOS or OOT history, stability condition and timepoint.
- Deviation and CAPA patterns
- Group quality events by process, cause, material or equipment, and review recurrence and CAPA effectiveness in the same product context.
- Supplier and material quality
- Link the materials and sources actually used to incoming failures, supplier changes and complaints.
- Complaints and field evidence
- Connect complaints, returns, adverse events and recalls to the manufactured populations they concern.
- Governed statistics
- Each analysis keeps its dataset, cohort, denominator, exclusions and method version, so a chart or capability figure can be reproduced.
- Change effectiveness
- Compare an implemented change’s expected outcome with the batches and evidence produced after it took effect.
- Evidence-backed conclusions
- Each review conclusion links to the datasets and source records behind it, with its limitations and approval.
- Persistent follow-up
- Conclusions become CAPA, change, validation or supplier actions with owners, and their completion evidence is available to the next review.


See your process in Seal.
Working 48 hours after we agree its scope: tested, with evidence your QA approves.