| Literature DB >> 35735989 |
Michael P Eaton1, Sergiy M Nadtochiy1, Tatsiana Stefanos1, Dana LeMoine1, Brian J Anderson2.
Abstract
INTRODUCTION: Dabigatran is an anticoagulant with potential use during cardiopulmonary bypass in children and adults. The pharmacokinetic-pharmacodynamic relationship for dabigatran anticoagulation effect was investigated in an intact animal model using rabbits.Entities:
Keywords: cardiopulmonary bypass; coagulation; dabigatran; pharmacokinetics
Mesh:
Substances:
Year: 2022 PMID: 35735989 PMCID: PMC9541555 DOI: 10.1111/pan.14511
Source DB: PubMed Journal: Paediatr Anaesth ISSN: 1155-5645 Impact factor: 2.129
FIGURE 1A diagram representing the two models. The upper panel demonstrates the effect compartment model. Drug is delivered into a central compartment (V1) that distributes to a peripheral compartment (V2) linked by an intercompartment clearance (Q). A rate constant (k1e) links the central compartment to an effect compartment. The rate constant k1e is the same as keo when the system is at equilibrium. The lower panel demonstrates an indirect response (turnover) model. This model assumes that pharmacodynamic effect (i.e., PD, inhibition or stimulation) are due to factors (Cofact) that control the production or dissipation of drug response The measured response (PD) to dabigatran is due to factors controlling the synthesis turnover rate, kin (TNOVER = Ln (2)/kin).
Standardized dabigatran population pharmacokinetic parameter estimates
| Parameter | Estimate | BSV% | SE% | 95% CI |
|---|---|---|---|---|
| CLstd (L.min−1.70 kg−1) | 0.135 | 24.7 | 8.0 | 0.109–0.157 |
| V1std (L.70 kg−1) | 12.3 | 12.3 | 8.5 | 11.4–12.4 |
| Qstd (L.min−1.70 kg−1) | 0.33 | 7.8 | 20.5 | 0.291–0.349 |
| V2std (L.70 kg−1) | 30.1 | 10 | 40.2 | 25.9–38.7 |
| RUVADD (mg/L) | 1.31 | ‐ | 11.2 | 0.05–1.48 |
| RUVPROP (%) | 0.9 | ‐ | 81.9 | 0.02–9 |
Note: BSV is the between subject parameter variability, SE is the standard error of the structural parameter, and CI is the confidence interval.
Pharmacodynamic population parameter estimates for activated clotting times (ACT)
| Parameter | Estimate | BSV% | 95% CI | Estimate | BSV% |
|---|---|---|---|---|---|
| Effect compartment model | Turnover model | ||||
| E0 (sec) | 100 FIX | ‐ | ‐ | 100 FIX | ‐ |
| Emax (sec) | 899 FIX | ‐ | ‐ | 899 FIX | ‐ |
| Ce50 / Cp50 mg.L−1 | 20.1 | 0.7 | 19.7,22.6 | 25.9 | 26.2 |
|
| 0.66 | ‐ | 0.58, 0.77 | 0.671 | ‐ |
| T1/2keo / TRNOVR (min) | 1.4 | 16.2 | 0.74, 1.79 | 0.952 | 12.2 |
| RUVADD (sec) | 22.5 | ‐ | 16.0 | 0.025 | ‐ |
| RUVPROP (%) | 135 | ‐ | 95, 169 | 8.5 | ‐ |
Pharmacodynamic population parameter estimates for reaction times (R)
| Parameter | Estimate | BSV% | 95% CI | Estimate | BSV% |
|---|---|---|---|---|---|
| Effect compartment model | Turnover model | ||||
| E0 (min) | 0.4 FIX | ‐ | ‐ | 0.4 FIX | ‐ |
| Emax (min) | 34 FIX | ‐ | ‐ | 34 FIX | ‐ |
| Ce50 (mg/L) | 65.3 | 0.7 | 51.7,83.9 | 47.6 | 26.2 |
|
| 0.80 | ‐ | 0.72, 0.86 | 0.917 | ‐ |
| T1/2keo/TRNOVR (min) | 2.04 | 16.2 | 1.28, 2.47 | 1.38 | 12.2 |
| RUVADD (min) | 0.116 | ‐ | 0.06, 0.15 | 0.09 | ‐ |
| RUVPROP (%) | 10.3 | ‐ | 8.7, 11.5 | 19.3 | ‐ |
FIGURE 2Population prediction corrected visual predictive checks (PC‐VPC) for the pharmacodynamic activated clotting time response. All plots show median and 90% confidence intervals (solid and dashed lines). Left‐hand plot shows all observed concentrations. Right‐hand plot shows percentiles (10, 50, 90) for observations (lines with symbols) and predictions (lines) with 95% confidence intervals for prediction percentiles (gray‐shaded areas). The upper panel shows that for an effect compartment model while the lower is for a turnover model.
FIGURE 3Population prediction corrected visual predictive checks (PC‐VPC) for the pharmacodynamic reaction time (R) response. The upper panel shows that for an effect compartment model while the lower is for a turnover model. The effect compartment model shows adequacy of model predictions with little apparent deviations between model and data. Reaction time at approximately 1 h shows some deviation between model and data in the turnover model.