Author Archives: Keith M. Bower

Statistical Assessments of Bioassay Validation Acceptance Criteria

Analytical linearity as well as assessments of precision and accuracy determine the range for a bioassay (1). USP <1033> recommends comparing confidence intervals (CIs) against target validation acceptance criteria in a bioassay validation exercise, but there are no clear guidelines for determining the criteria (2). Here I address several aspects of a bioassay validation, namely • Linearity (coefficient of determination (R2), slope, and intercept parameters) • Accuracy (%relative bias, %RB) • Precision (percent coefficient of variation, %CV) CIs for the…

The Relationship Between R2 and Precision in Bioassay Validation

Analytical linearity along with assessments of precision and accuracy determine the range for bioassays (1). Practitioners can include coefficient of determination (R2) criteria from a linearity study in the bioassay validation protocol. Herein I illustrate the relationship of R2 to study design and analytical method variation. Overview of the Simple Linear Regression Model Dilutional linearity assesses the “ability (within a given range) of a bioassay to obtain measured relative potencies that are directly proportional to the true relative potency of the…

A Statistical Approach to Assess and Justify Potential Product Specifications

As stated in ICH Q6B, specifications are critical quality standards that are both proposed and justified by drug product manufacturers. Xiaoyu et al. provide information on several statistically based strategies to establish specification acceptance criteria (SAC) (1). Here we address an alternative approach to relate proposed SAC for quantitative data to relevant lot history. In particular, proposed SAC can be derived in part by using calculated limits for which the lower bound of an approximate 95% confidence interval for the…