Considerations for Updates to ICH Q1 and Q5C Stability Guidelines: Embracing Current Technology and Risk Assessment Strategies.

In consideration of the recent ICH Quality Discussion Group (QDG) recommended revision to the ICH series of stability guidelines, the IQ Consortium (International Consortium for Innovation and Quality in Pharmaceutical Development) Science- and Risk-based Stability Working Group conducted a comprehensive review of ICH Q1A, Q1B, Q1C, Q1D, Q1E, and Q5C to identify areas where the guidelines could be clarified, updated, and amended to reflect the potential knowledge gained from current risk-based predictive stability tools and to consider other science- and risk-based stability strategies in accordance with ICH Q8-12. The recommendations propose a holistic approach to stability understanding, utilizing historical data, prior knowledge, modeling, and a risk assessment process to expand the concept of what could be included (or would be acceptable) in the core stability data package, including type and amount of stability evidence, assignment of retest period and shelf-life for a new product, and assessment of the impact of post-approval changes.

Topical drug classification.

Current definitions of lotions, gels, creams and ointments vary depending on literature source, market history or traditional use. This often leads to confusion when deciding which dosage form to prescribe and/or purchase. The existing classification of topical dosage forms needs to be re-examined to ensure that definitions for different dosage forms are based on consistent scientific principles and that dosage forms can be distinguished from one another.

Shelf life determination based on equivalence assessment.

In a regular analysis of covariance (ANCOVA) approach to stability analysis, the decision for pooling data from different batches plays a key role in the determination of the shelf life of the drug product. Conventionally, the decision to pool data for the estimate of slope and intercept of common or individual regression lines is made by "no evidence to reject the null hypothesis of no difference." With typically limited observations, a significance level of much higher than 0.

ANCOVA approach for shelf life analysis of stability study of multiple factor designs.

For a traditional multiple batch stability design with no other factor, the conventional analysis is analysis of covariance (ANCOVA) modeling using F-tests based on type I sum of squares to determine whether the batches may be pooled for a common estimate of the linear regression line(s). In the last decade, many multiple factor designs were proposed in stability studies. With the objective of model selection, the generalization of the conventional ANCOVA model using type I sum of squares to designs with multiple factors requires a prespecified hierarchical pooling test ordering to determine whether any of the factors may be eliminated.

Overview of stability study designs.

Stability requirements for the worldwide registration of pharmaceutical products have changed dramatically in the past few years. A series of guidelines on the design, conduct, and data analysis of stability studies of pharmaceuticals have been published by the International Conference on Harmonization (ICH); however, the statistical discussion on study design is limited. In this paper, stability designs including full, bracketing, and matrixing designs will be exemplified.