2003
   Verona, Italy

A Modeling Approach to Assessing Bioequivalence (BE) with Presence of Sparsely Sampled Subjects

C. Hu, J.Y. Kim, K.H.P. Moore, M.E. Sale

Clinical Pharmacology and Discovery Medicine, GlaxoSmithKline,

Objectives: Traditional BE assessment requires the evaluation of a 90% confidence interval (CI) for the ratio of AUC and Cmax for the test and reference formulation. AUC and Cmax must be obtained from every individual. However in many circumstances (e.g., pediatrics and adult patients), subjects may be sparsely sampled, making the individual evaluation infeasible. In such cases, population PK modeling seems appealing. The difficulty lies in the incompatibility between the exploratory nature of usual modeling process and the confirmatory nature of traditional BE assessment. Using conventional population PK modeling for BE would violate the principle of traditional BE assessment. E.g., if the formulation, as a covariate, was found "insignificant" in the model, BE would have to be declared by default. This is clearly unacceptable from the view point of traditional BE assessment. A paradigm presented here bridges the two approaches.

Methods: The paradigm first develops a population PK model, with the aim of being consistent with the traditional BE assessment principle. From the final model parameters, the average AUC and Cmax can be predicted, and the ratio of average AUC and Cmax can be calculated. The BE assessment can then be made based on 90% CI for these ratios using bootstrapping. A detailed analysis plan following this paradigm was developed a priori for a BE-type assessment to examine GW433908 with and without ritonavir in healthy and HIV-infected subjects.

Results: 1013 concentrations from 104 subjects in four studies were available. The fourth study was sparsely sampled, with 123 samples from 43 subjects. A population PK model was developed using NONMEM and the parameters were consistent with previously reported data. Then, 3000 bootstrap runs were conducted. The 90% CI for the AUC ratio was (0.908, 1.174). For Cmax, the CI for GW433908 alone was (0.951, 1.297). The CI for GW433908+ritonavir was (0.956, 1.244). The analysis between healthy and HIV-infected subjects demonstrated equivalence among AUC. For Cmax, equivalence was demonstrated for GW433908+RTV, and similarity was demonstrated for GW433908 given alone.

Conclusion: When sparse sampling is employed in patient studies, this paradigm provides a modeling approach resolving some of the controversies in BE-type assessments.