Demonstrating Bioequivalence for a Lumacaftor Monosubstance Formulation Versus Orkambi® (Lumacaftor/Ivacaftor) in Healthy Subjects
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: , which is used for treating cystic fibrosis. Experimental evidence suggests that lumacaftor can be used as a monotherapy to improve brain perfusion and memory in heart failure. To clinically assess this therapeutic intervention, a formulation with demonstrated bioequivalence to the currently approved combination product is required. METHODS: (lumacaftor 400 mg/ivacaftor 250 mg; Reference Product) in the fed state and (ii) oral administration of lumacaftor (400 mg; Test Product) in the fasted to fed state. Plasma lumacaftor concentrations were measured with a standard liquid chromatography with tandem mass spectrometry approach. RESULTS: The "Test-to-Reference ratio" of the geometric least-square means for maximum plasma concentration and area under the curve met the Food and Drug Administration-defined criteria for bioequivalence; median times to maximum plasma concentration values were not statistically different. The "Fed to Fasted ratio" of the geometric least-square means for maximum plasma concentration and area under the curve indicated a clear food effect on bioavailability. Lumacaftor exposure was approximately two times higher when administered with fatty foods than when taken in a fasting state. The monosubstance formulation was well tolerated. CONCLUSIONS: We conclude that the lumacaftor monosubstance formulation delivers lumacaftor exposure that is not meaningfully different than the currently approved combination product. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT05968612.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".