## 3 Results
In Figure 4, a consistent trend is evident across all scenarios examined. Again, it should be emphasized that the BE acceptance rate of the generated dataset is consistently higher than that of both the subsampled and original datasets in all cases. Additionally, as expected, the BE acceptance rate decreases for all groups with the increase (or decrease) in the T/R values. Importantly, even in this scenario, the percentage of BE acceptance for the generated data is the least affected. Figure 5 shows the impact of within-subject variability of CVw on BE acceptance \"gain\" between the generated and original datasets (i.e., % BE acceptance generated--original). The scenarios explored referred to different performances between the two drug products under comparison, namely, T/R values of 1.0 (Figure 5A), 1.1 (Figure 5B), and 1.2 (Figure 5C). Figure 5 illustrates that, in all cases, the acceptance rate of bioequivalence between the T and R groups is significantly higher in the case of the generated dataset. When the T and R groups have equal means (Figure 5A), this increase is more pronounced for larger within-subject variability and larger subsample proportions. Similar findings are observed when the T/R ratio is 1.1, with the increase being even higher (Figure 5B). For more extreme differences between the T and R groups (T/R = 1.2), an even more substantial increase in the acceptance rate is observed, although the increase is very similar for both 15% and 30% CVw and for all subsample proportions (Figure 5C). Figure 4: Bioequivalence acceptance rate (%) for the “original”, “subsampled”, and VAE–”generated” datasets for high variability values (CVw = 30%). The T/R of the Test (T) and Reference (R) products was set at 1.0 (**A**), 1.1 (**B**), and 1.2 (**C**), while the subsample proportions were 25%, 50%, 75%, and 100%. Four different original sample sizes (N) were utilized (12, 24, 48, and 72). Finally, Figure 6 investigates the relationship between the generated sample size and the original dataset. In other words, the aim of this figure is to show how many times larger the generated dataset can be compared to the original one. Two typical N values were chosen: N = 12, which refers to the lowest accepted sample size for a BE study by regulatory authorities [4; 5], and N = 24, which is a typical sample size commonly used in BE studies. Two levels of the generated sample size were tested: 1\(\times\) and 2\(\times\). This means that the generated dataset can be either as large as the original or twice the original sample size. Thus, by using only part of the original dataset (i.e., 25%, 50%, or 75%), the aim was to evaluate the performance of the reconstructed dataset. In all cases, two CVw values were utilized (15% for Figure 6A and 30% for Figure 6B) and three levels of the relationship between the T and R groups (i.e., T/R equal to 1.0, 1.1, and 1.2). Figure 6 demonstrates that the acceptance rate increases when the sample size of the generated dataset is twice the original size, compared to cases where the original sample size is equal to the generated sample size. In Figure 6A, when CVw is 15% and the original sample size is 24, a slight increase in the acceptance rate is observed for a subsample proportion of 50% across all T/R ratios. When the original sample size is 12, there is a modest increase when the generated sample size is twice the original for a subsample proportion of 100% and a more significant increase when the subsample proportion is 50%. Figure 5: Bioequivalence acceptance “gain” of the VAE-“generated” dataset minus the “original” datasets. Three Test/Reference (T/R) ratios of the average endpoint were considered: 1.0 (**A**), 1.1 (**B**), and 1.2 (**C**). In all cases, a range of subsample proportions (25%, 50%, 75%, and 100%) was investigated, while the within-subject variability (CVw) was set at either 15% (typical case) or 30% (highly variable situation). This pattern is evident for all three T/R ratio values. In Figure 6B, where CVw is 30%, the results mirror those of Figure 6A.