Incurred Sample Reanalysis (ISR) Failure: Investigating the Root Cause

The ISR failure (only 55% within ±20%, mean bias −15%) indicates a systematic difference between original and repeat results, not random variability. Since repeat QCs and calibrators were acceptable, the issue is likely specific to the incurred samples. Possible root causes: (1) Instability of drug Y in the incurred samples during storage or after thawing-though 6-month stability at −80°C is claimed, the stability test may not have used incurred samples or may not reflect the actual storage conditions (e.g., freeze-thaw cycles, time at room temperature during original analysis). (2) Differences in sample handling: original samples may have been thawed multiple times or stored differently. (3) Matrix effects or recovery differences due to sample aging (e.g., protein precipitation efficiency changes). (4) Internal standard variability: if the internal standard response changed, but QCs are prepared in surrogate matrix, it may not reflect incurred samples. (5) Calibration curve differences: though acceptable, a small bias in the repeat curve could contribute. (6) Degradation of the analyte in the original samples over time (e.g., enzymatic degradation not observed in spiked stability samples). Investigation: (1) Review original and repeat run acceptance, including internal standard responses and retention times. (2) Re-assay a subset of samples with a fresh calibration curve and new QCs, and also re-assay using a different analytical column or mobile phase to check for interference. (3) Perform stability experiments using incurred samples stored under the same conditions. (4) Check for freeze-thaw stability using incurred samples. (5) Evaluate the effect of hematocrit or sample homogeneity. (6) Consider re-analysis of all samples with a validated method and compare with original data to determine which set is biased. If the repeat data are more accurate (e.g., due to instrument issues in original), original data may need to be invalidated.

Regulatory guidelines (e.g., ICH M10, FDA guidance) require ISR to be performed and for the failure to be investigated. The original data cannot be simply reported without justification. Actions: (1) Conduct a thorough investigation to identify the root cause. (2) If the investigation shows that the repeat analysis is biased (e.g., due to a preparation error or instrument issue in the repeat batch), then the original data may be acceptable, but the ISR should be repeated with a corrected repeat analysis. (3) If the original data are biased (e.g., due to sample degradation over time), then the original data may need to be invalidated and samples re-analyzed, if possible. (4) If the cause cannot be determined, the data may be considered unreliable, and the study report should include a discussion of the ISR failure and its impact. (5) The laboratory should implement corrective actions, such as improved stability testing with incurred samples, better sample storage and handling procedures, and possibly a more robust analytical method. (6) Communicate with the sponsor and regulatory authorities as required. In summary, the original data should not be reported without a scientifically sound justification; the investigation must be documented, and the decision should be based on evidence of which dataset is more accurate. Repeating ISR after corrective actions is recommended.