Bioequivalence and food effect of a fixed‐dose combination of macitentan and tadalafil: Adaptive design in the COVID‐19 pandemic
Bibliographic record
Abstract
Abstract The COVID‐19 pandemic has forced clinical studies to accommodate imposed limitations. In this study, the bioequivalence part could not be conducted as planned. Thus, the aim was to demonstrate bioequivalence, using an adaptive study design, of tadalafil in fixed‐dose combination (FDC) tablets of macitentan/tadalafil with single macitentan and tadalafil (Canadian‐sourced) tablets and assess the effect of food on FDC tablets in healthy subjects. This Phase 1, single‐center, open‐label, single‐dose, two‐part, two‐period, randomized, crossover study enrolled 62 subjects. Tadalafil bioequivalence as part of FDC of macitentan/tadalafil (10/40 mg) with single‐component tablets of macitentan (10 mg) and tadalafil (40 mg) was determined by pharmacokinetic (PK) assessment under fasted conditions. The effect of food on FDC was evaluated under fed and fasted conditions. Fasted 90% confidence intervals (CIs) for geometric mean ratios (GMRs) were within bioequivalence limits for tadalafil and macitentan. Fed and fasted 90% CIs for area under the curve (AUC) GMR were within bioequivalence limits. However, 90% CIs for maximum plasma concentration ( C max ) GMR for macitentan and tadalafil were outside bioequivalence limits. One FDC‐treated subject experienced a serious adverse event of transient ischemic attack (bioequivalence part). To address pandemic‐imposed limitations, an adaptive study design was implemented to demonstrate that the FDC tablet was bioequivalent to the free combination of macitentan and tadalafil (Canadian‐sourced). No clinically significant differences in PK were determined between fed and fasted conditions; the FDC formulation could be taken irrespective of meals. The FDC formulation under fasted and fed conditions was well tolerated with no clinically relevant differences in safety profiles between the treatment groups. NCT Number: NCT04235270.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".