Pharmacokinetic Characteristics of Tofacitinib in Adult Patients With Moderate to Severe Chronic Plaque Psoriasis
Bibliographic record
Abstract
Tofacitinib is an oral Janus kinase (JAK) inhibitor. This study characterized the pharmacokinetics of tofacitinib in patients with psoriasis and evaluated the impact of patient factors on disposition. Pooled phase 2/3 data (2981 patients: 9735 concentrations, dose range: 2-15 mg twice daily) up to 56 weeks were used for modeling. A one-compartment model parameterized in terms of apparent oral clearance (CL/F), apparent volume of distribution, zero-order absorption (duration, D), with interindividual variability and inter-occasion variability terms, described tofacitinib pharmacokinetics. A full covariate model incorporated effects for age, sex, race, ethnicity, and baseline variables (body weight, Psoriasis Area Severity Index [PASI], C-reactive protein [CRP], creatinine clearance [CrCl]). The parameter estimates (95%CI) for CL/F, Vd/F, and D in a typical individual (white, male, 86 kg, 46 years, CrCl 121 mL/min, PASI 19.8, and CRP 0.267 mg/dL) were 26.7 (25.9, 27.5) L/h, 125 (120.8, 128.3) liters, and 0.69 (0.646, 0.735) hours, respectively. Only CrCl led to clinically relevant changes in exposure. The analysis suggested no dosing modifications for age, body weight, sex, race, ethnicity, baseline PASI, or CRP based on the magnitude of exposure change. Dosing adjustments for renal impairment were derived from a separate phase 1 study.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".