Bioequivalence and Bioavailability Forum

Dear Mathews!

❝ I know only the Cmax value of the drug from the literature. It is around 42.34 ± 13.27.

❝ How i can calculate the intra subject CV from this Cmax value? (is it required for Sample Size calculation?)

Unfortunatelly there's no way to calculate CV_intra from CV_total (CV_total = CV_intra + CV_inter). Actually you don't even have CV_total (in log scale), because CV = SD/mean (what you have) comes from untransformed data.
Also see this post.

❝ which value of "delta" we commonly used for calculating Sample Size?

With exception of Canada, where delta should be set to zero (ratio=1) and a correction for actual content should be made in the assessment of BE, delta should be set to the expected difference (e.g., from a reasonably sized pilot study).
The commonly applied approach is to set the expected ratio to 0.95 (or -5%). Rationale behind is that release specifications of a batch generally are ±5%; since this applies to both test and reference - and we assume an average deviation from declared content of ±2.5% we end up with ±5% for the study.

❝ there are different sample size formulas for additive model and multiplicative model?

Sure. Different model --> different error distribution / power function / sample sizes.

❝ which model we commonly used? why?

It's a generally accepted assumption that many biological variables (including PK metrics like AUC, C_max) follow a lognormal distribution. Furthermore serial dilutions in analytics also lead to multiplicative errors. Since additivity of effects and homoscedasticity (homogeneity of variance) is a prerequisite for ANOVA, we apply a multiplicative model (i.e., work with log-transformed data instead with raw data). By this the distribution skewed to the right becomes symetrical and values below zero are avoided.

For t_max an additive model is most suitable; although a nonparametric analysis is also a must (ANOVA is incorrect for discrete data).