Population Pharmacokinetic Analysis of Ixazomib, an Oral Proteasome Inhibitor, Including Data from the Phase III TOURMALINE-MM1 Study to Inform Labelling
Bibliographic record
Abstract
Ixazomib is an oral proteasome inhibitor, approved in USA, Canada, Australia and Europe in combination with lenalidomide and dexamethasone, for the treatment of patients with multiple myeloma who have received at least one prior therapy. We report a population pharmacokinetic model-based analysis for ixazomib that was pivotal in describing the clinical pharmacokinetics of ixazomib, to inform product labelling. Plasma concentration–time data were collected from 755 patients who received oral or intravenous ixazomib in once- or twice-weekly schedules in ten trials, including the global phase III TOURMALINE-MM1 study. Data were analysed using nonlinear mixed-effects modelling (NONMEM software version 7.2, ICON Development Solutions, Hanover, MD, USA). Ixazomib plasma concentrations from intravenous and oral studies were described by a three-compartment model with linear distribution and elimination kinetics, including first-order linear absorption with a lag time describing the oral dose data. Body surface area on the volume of the second peripheral compartment was the only covariate included in the final model. None of the additional covariates tested including body surface area (1.2–2.7 m 2 ), sex, age (23–91 years), race, mild/moderate renal impairment and mild hepatic impairment were found to impact systemic clearance, suggesting that no dose adjustment is required based on these covariates. The geometric mean terminal disposition phase half-life was 9.5 days, steady-state volume of distribution was 543 L and systemic clearance was 1.86 L/h. The absolute bioavailability of an oral dose was estimated to be 58%.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".