Determination of minimal sampling time points for reliable pharmacokinetic evaluation of recombinant factor VIII – an exploratory population pharmacokinetic analysis in paediatric patients suffering from severe haemophilia
Bibliographic record
Abstract
Summary. Data obtained from 19 paediatric patients (mean age, range: 12.8, 4.3–12 years) with haemophilia A from one clinical trial (see Barnes et al in these proceedings) were used to develop a population model of the pharmacokinetics (PK) of intravenous recombinant Factor VIII (rFVIII) given as a single bolus infusion of 50 IU kg−1 body weight. Eleven plasma samples per patient were drawn and assayed using the one stage coagulation assay. These data and the patient covariables were modelled by iterative two step analysis, thus generating PK parameter values for both individuals and the overall study population. The partial derivatives method of analysis (from WinNonlin®) was used to identify the optimal sampling times (OST). Minimization of the sampling schedule was validated by comparison of parameter estimates obtained by OST with data calculated from the full (11 samples/patient) data set using compartmental and non‐compartmental PK approaches and sensitivity analysis with respect to patients’ covariables. The PK parameters were best described by a two compartment model with an IV input‐function to the central compartment. Base line FVIII levels were built into the model as a continuous constant rate delivery function. Lean body mass (LBM) had a moderate influence on clearance and central volume of distribution (∼2.5% per kg LBM). Inter‐subject variability on both parameters was moderate (Cl: 27.2%, V: 15.5%) residual error was low (5.7%). Base line estimates were generally below 1% for all subjects in accordance with their severe state of disease. Five OST (end of infusion, 2.5–3.5, 8–10, 22–26 and 46–50 h) provided maximum information and allowed PK parameter values to be estimated by both compartmental and non‐compartmental methods with comparable accuracy as that obtained using the full sampling schedule. Additionally, a predose sample may be added to get an improved base line estimate. Our results indicate that even after substantial reduction of the number of samples (from 11 to 5) adequate rFVIII PK data can be obtained using OST schedules in severe haemophiliacs. PK studies conducting using the much fewer sampling time points are less burdensome to patients, particularly very young patients, and thus may be easier to implement into routine haemophilia care.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".