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Evaluating the performance of the ICH guidelines for shelf life estimation
Michelle Quinlan1, Walter Stroup, James Schwenke
1Novartis Oncology, Florham Park, NJ 07932, USA. mquinlan22@yahoo.com
Shelf life estimation needs improvement. Current guidelines have issues, suggesting random batch effects and quantile focus for more accurate product shelf life determination applicable to all future batches.
Area of Science:
- Pharmaceutical Sciences
- Biostatistics
- Quality Control
Background:
- Shelf life estimation aims to define product storage duration ensuring specifications are met with high probability.
- Current International Conference on Harmonization (ICH) guidelines (Q1E) for shelf life estimation face challenges.
- Identified issues include fixed batch effects, poolability tests, and confidence intervals for the mean.
Purpose of the Study:
- To address limitations in existing International Conference on Harmonization (ICH) shelf life estimation procedures.
- To propose an improved methodology for shelf life estimation.
- To develop a procedure that accounts for random batch effects and focuses on quantile estimation.
Main Methods:
- Evaluation of the existing International Conference on Harmonization (ICH) procedure for shelf life estimation.
- Analysis of issues related to fixed batch effects, poolability tests, and confidence intervals.
- Development of a new procedure incorporating random batch effects and quantile-based estimation.
Main Results:
- Evidence suggests that batch effects in shelf life estimation should be treated as random.
- Focusing on a quantile, rather than the mean, is more appropriate for shelf life estimation.
- A novel procedure is proposed that integrates random batch effects with the objective of minimum batch shelf life.
Conclusions:
- The International Conference on Harmonization (ICH) guidelines for shelf life estimation require revision.
- Treating batch effects as random and focusing on quantiles enhances the accuracy of shelf life predictions.
- The proposed procedure offers a more robust approach to estimating shelf life applicable to future product batches.
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