Bridging an old QC lot to a new one is fundamentally a three-part exercise: parallel testing across enough data points to characterize the new material, a defined statistical comparison against pre-set acceptance criteria, and documentation that captures the decisions made along the way. CLSI C24-Ed4 provides the underlying framework, but the practical execution depends on how each laboratory designs and documents the transition.
Most clinical and forensic laboratories change QC lots several times per year, yet written transition procedures remain inconsistent across the industry. The gap matters. Done well, a lot transition preserves the continuity of long-running QC charts and reinforces confidence in patient and casework results. Done poorly, it can introduce subtle shifts that erode trust in your method or, in the worst case, mask a genuine performance problem. Inspectors from CAP, ISO 15189 assessors, and CLIA surveyors are increasingly asking to see the procedure, the parallel data, and the rationale behind the decisions. The more than 50 years that our team at UTAK has spent alongside clinical and forensic laboratories has given us a close view of how lot transitions play out, from routine swaps to high-stakes changes on sensitive assays. In our experience, the labs that handle lot changes most smoothly share a common trait: they treat the transition as a planned event with defined acceptance criteria, not as an administrative afterthought. They also recognize that vendor-assigned values are a useful starting reference, not a substitute for in-lab characterization. The sections below walk through what that planned process looks like in practice.
The Foundational Reference: CLSI C24
For QC material lot transitions in clinical and forensic laboratories, CLSI C24-Ed4 (Statistical Quality Control for Quantitative Measurement Procedures: Principles and Definitions) is the most directly applicable reference. C24 addresses target value establishment, QC rule selection, and the broader statistical framework that governs how new QC lots integrate into an existing quality control program.
CLSI EP26 (User Evaluation of Acceptability of a Reagent Lot Change), which replaced the 2013 EP26-A guideline in 2022, is sometimes cited in this context, but it focuses specifically on reagent lot variation. While some of its statistical concepts can be conceptually adapted to QC material transitions, C24 remains the appropriate primary anchor when the question is, “How do I validate a new QC lot?”
Vendor-Assigned Values vs. In-Lab Establishment
The certificate of analysis (COA) for a new QC lot typically provides assigned values and acceptable ranges based on the manufacturer’s testing across multiple methods or platforms. These are useful, but they have limits:
- Assigned values reflect the manufacturer’s testing population, not your specific instrument, calibrators, or technique.
- Method-specific ranges, where provided, are pooled from multiple laboratories and may be wider than your own historical performance window.
- Your laboratory’s mean and SD are the result of your specific configuration, and that is exactly the value of in-lab characterization.
Use vendor-assigned values as a sanity check during parallel testing, but rely on your own data, collected under your own conditions, to establish the operational mean and SD that you will use going forward. C24 reinforces this approach: the laboratory’s QC rules and limits should be derived from the laboratory’s actual performance, not from generalized manufacturer ranges.
Designing Parallel Testing
Parallel testing means running both the old and new QC lots side by side over a defined period before transitioning. The objective is to collect enough new-lot data to characterize its performance and compare it directly to the old lot under identical conditions.
In our experience, the laboratories that get the most useful information from parallel testing share these practices:
- Run frequency: Include both lots in every routine QC run during the parallel period. This captures real-world variability across operators, calibrator lots, and instrument states.
- Duration: A minimum of 20 data points per QC level on the new lot is a widely cited starting figure, drawn from the same statistical foundation that C24 uses for establishing means and SDs. Some laboratories prefer 10 days at minimum to capture day-to-day variability; others extend to 20 or 30 days for high-stakes assays or low-frequency runs.
- Conditions: Do not artificially clean up the data. Operator turnover, calibrator changes, and routine instrument maintenance during parallel testing reflect the conditions your QC will actually encounter once the new lot goes live.
Statistical Comparison: What to Look For
Once you have collected parallel data, the comparison is conceptually straightforward, even when the math gets detailed. You are asking three questions:
1. Is the new lot’s mean acceptably close to the old lot’s? A meaningful shift suggests either a true difference between materials (real and expected) or an analytical issue worth investigating before transitioning.
2. Is the new lot’s variability comparable? A noticeably wider SD on the new lot may indicate a less homogeneous material, a method change you were not tracking, or a need to extend the parallel testing window.
3. Does the new lot’s mean fall within the vendor’s assigned range? If yes, this confirms basic alignment. If no, you have a flag worth resolving before going live.
C24 emphasizes that the laboratory must define what counts as an acceptable shift before the comparison happens. Setting acceptance criteria after seeing the data is a common documentation gap and an audit vulnerability.
When to Update Target Values, When to Carry Them Forward
This is one of the most common questions we hear: if the new lot is the same product, can I just keep using my established target values?
The short answer is usually no, and here is why. Even within a single product line, QC materials are biological mixtures that vary slightly between manufacturing lots. Carrying forward old target values onto a new lot can mask a small but real shift, and when that shift compounds over multiple lot changes, it can drift your QC chart away from the underlying truth of your method.
The defensible practice is:
- Establish a new mean and SD for each new lot based on your parallel testing data.
- Document the comparison between old and new lots, including means, SDs, and any observed shifts.
- Update QC rules and limits accordingly, consistent with how you originally established ranges for the assay.
- Retain the old lot’s data for trending purposes, but do not blend it with new-lot data in your active charts.
C24 supports this approach. The standard treats each lot as having its own statistical fingerprint, even when the underlying product specification is identical.
Documentation That Holds Up Under Inspection
A defensible lot-to-lot transition includes:
- The new lot’s COA, retained in the quality record
- Parallel testing protocol and acceptance criteria, defined before testing began
- Raw data from parallel testing, traceable to specific runs and operators
- Statistical comparison summary (means, SDs, and shift evaluation against pre-defined criteria)
- Decision record: target values used going forward and the rationale
- Any deviations from the parallel testing protocol and how they were handled
Inspectors from CAP, ISO 15189 assessors, and CLIA surveyors increasingly look for evidence of a planned, repeatable process, not just the final QC chart.
Connecting Back to Your Quality Program
Lot transitions do not exist in isolation. They sit alongside the broader work of establishing QC ranges for your assays, recognizing common QC failure patterns, and matching your QC materials to your testing population. When these elements are aligned, lot transitions become routine. When they are not, every lot change becomes a small crisis.
Key Takeaway: Lot-to-Lot Transition Readiness Checklist
☐ Written transition procedure exists and references CLSI C24 principles
☐ Parallel testing protocol defines minimum data points (typically 20+ per level) and duration
☐ Acceptance criteria for mean and SD comparison are defined before testing begins
☐ Vendor-assigned values used as a reference point, not adopted automatically
☐ New target values and limits established from in-lab parallel data
☐ Documentation package ready for inspection: COA, raw data, comparison summary, decision record
☐ Old-lot data retained but separated from new-lot active QC charts
☐ Process for escalating unexpected shifts to method validation review
Frequently Asked Questions
How long should parallel testing run?
A minimum of 20 data points per QC level is a common starting figure, supported by the statistical principles in CLSI C24. Most laboratories collect this over 10 to 20 days to capture day-to-day and operator-to-operator variability. High-stakes assays, low-volume tests, or methods with known matrix sensitivity may warrant longer parallel periods.
Can I use the manufacturer’s target values without parallel testing?
Manufacturer-assigned values are useful as a reference but are not a substitute for in-lab characterization. Your laboratory’s mean and SD reflect your specific instrument, calibrators, technique, and operator pool. C24 expects QC limits to be derived from the laboratory’s actual performance.
What if the new lot’s mean is meaningfully different from the old lot’s?
First, confirm the difference is real by extending parallel testing or running additional replicates. If the shift is reproducible and the new lot’s mean falls within the vendor’s assigned range, the difference likely reflects normal lot-to-lot variability and the new mean should be adopted. If the shift is large or falls outside the assigned range, treat it as an investigation, not an automatic transition.
Is CLSI EP26 the right reference for QC lot transitions?
EP26 (formerly EP26-A, replaced in 2022) specifically addresses reagent lot variation. While its statistical framework can be conceptually adapted, CLSI C24-Ed4 is the more directly applicable reference for QC material lot transitions and is the standard most clinical and forensic laboratories use.
What documentation do inspectors typically request?
The most common requests we hear: parallel testing data, defined acceptance criteria from before the testing began, the statistical comparison summary, and a clear decision record showing what target values were adopted and why.
Work with an Experienced Partner for your Next Lot Transition
Our technical team has worked through lot-to-lot transitions with hundreds of laboratories over the past five decades, across clinical, forensic, and public health settings. If you are building or refining a transition procedure, working through an unexpected shift between lots, or trying to align your documentation with what inspectors increasingly expect, we are here to talk it through. Reach out at welovecontrol@utak.com or call 888.882.5522. Explore our QC Tech Support and Purpose-Built Resources for additional context on how we work alongside laboratory teams.
References
1. Clinical and Laboratory Standards Institute. Statistical Quality Control for Quantitative Measurement Procedures: Principles and Definitions. 4th ed. CLSI guideline C24. Wayne, PA: CLSI; 2016. Available at: https://clsi.org/shop/standards/c24/
2. Clinical and Laboratory Standards Institute. User Evaluation of Acceptability of a Reagent Lot Change. 2nd ed. CLSI guideline EP26. Wayne, PA: CLSI; 2022. Available at: https://clsi.org/shop/standards/ep26/
