Pharmacokinetics and safety of olodaterol administered with the Respimat Soft Mist inhaler in subjects with impaired hepatic or renal function
Bibliographic record
Abstract
PURPOSE: In two trials, the influences of hepatic and renal impairment on the pharmacokinetics of olodaterol, a novel long-acting inhaled β2-agonist for treatment of COPD, were investigated. SUBJECTS AND METHODS: The first trial included eight subjects with mild hepatic function impairment (Child-Pugh A), eight subjects with moderate impairment (Child-Pugh B), and 16 matched healthy subjects with normal hepatic function. The second trial included eight subjects with severe renal impairment (creatinine clearance <30 mL·min(-1)) and 14 matched healthy subjects with normal renal function. Subjects received single doses of 20 or 30 μg olodaterol administered with the Respimat Soft Mist inhaler. RESULTS: Olodaterol was well tolerated in all subjects. The geometric mean ratios and 90% confidence intervals of dose-normalized area under the plasma concentration-time curve from time zero to 4 hours (AUC0-4) for subjects with mild and moderate hepatic impairment compared to healthy subjects were 97% (75%-125%) and 105% (79%-140%), respectively. Corresponding values for dose-normalized maximum concentration (C max) were 112% (84%-151%) (mild impairment) and 99% (73%-135%) (moderate impairment). The geometric mean ratio (90% confidence interval) of AUC0-4 for subjects with severe renal impairment compared to healthy subjects was 135% (94%-195%), and for C max was 137% (84%-222%). There was no significant relationship between creatinine clearance and AUC0-4 or C max. Renal clearance of olodaterol was reduced to 20% of normal in severe renal impairment. CONCLUSION: Mild to moderate hepatic function impairment or severe renal function impairment did not result in a clinically relevant increase of olodaterol systemic exposure after a single inhaled dose.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".