Population Pharmacokinetic/Pharmacodynamic Analysis of the DPP-4 Inhibitor Linagliptin in Japanese Patients with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
OBJECTIVES: Linagliptin is a novel, highly selective and long acting DPP-4 inhibitor for the treatment of type 2 diabetes mellitus (T2DM). Linagliptin exhibits non-linear pharmacokinetics (PK) due to saturable binding to plasma and tissue DPP-4. The aim of this study was to characterize the PK and PK/DPP-4 inhibition relationship of linagliptin in Japanese patients with T2DM using a population PK/DPP-4 model and to support the rationale for the therapeutic dose in Japanese patients by simulation. METHODS: Linagliptin plasma concentration and DPP-4 inhibition measurements from a placebo-controlled, parallel group multiple (28 days) dose trial that included 36 T2DM patients (18 patients each in 2.5 mg and 10 mg dose group) were used for analysis. Modeling was performed using FOCE INTERACTION estimation method implemented in NONMEM V. The linagliptin plasma concentration- and DPP-4 inhibition- time profiles were simulated for Japanese patients receiving 5 mg linagliptin once daily by the model established. RESULTS: Nonlinear PK of linagliptin in T2DM patients were well described by a 2-compartment model assuming concentration-dependent binding to DPP-4 in the central and peripheral compartment. Plasma DPP-4 inhibition was integrated in the model by relating the model-predicted DPP-4 occupancy with linagliptin linearly to DPP-4 inhibition. The simulation predicted that for the 5 mg dose group the trough DPP-4 inhibition at steady-state was 84.2%, which is higher than the target inhibition (≥80%) for an effective dose of DPP-4 inhibitor. In 2.5 mg dose group, steady-state DPP-4 inhibition of >80% was not maintained over 24 hours (observed and simulated). CONCLUSIONS: The nonlinear PK of linagliptin and its plasma DPP-4 inhibition in patients were well characterized by a target-mediated drug disposition model relating DPP-4 occupancy with linagliptin to DPP-4 inhibition. Simulations of plasma DPP-4 inhibition suggest that 5 mg linagliptin once daily is an appropriate therapeutic dose for Japanese patients with T2DM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".