Model Informed Precision Dosing
Conditions
Brief summary
Achieving optimal antibiotic exposure in critically ill pediatric patients is difficult due to (their) dynamic physiology and variability. Conventional weight-based regimens often fail to reach pharmacokinetic/pharmacodynamic (PK/PD) targets for narrow therapeutic index agents such as vancomycin and amikacin. Model-Informed Precision Dosing (MIPD), which integrates Bayesian forecasting with population pharmacokinetics (popPK), offers a potentially valuable yet underexplored approach in pediatric intensive care to better attain and sustain target exposure. This pilot randomized clinical trial evaluated MIPD-guided dosing of vancomycin and amikacin using InsightRX Nova® versus standard of care (SoC) in a tertiary PICU. Patients whose model-recommended doses matched standard regimens were analyzed under SoC. Primary outcomes included prediction accuracy (a priori vs a posteriori) and model fit; secondary outcomes assessed dose optimization, inflammatory response, renal safety, treatment duration, and mortality.
Interventions
DEVICEMIPD Tool
It is a precision dosing platform that combines population pharmacokinetic/pharmacodynamic (popPK/PD) modeling with artificial intelligence and machine learning to optimize individualized drug therapy. It uses patient-specific demographic, clinical, and laboratory data to generate real-time personalized dosing recommendations based on validated popPK models.
Sponsors
Hacettepe University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
38 Months to 81 Months
Healthy volunteers
No
Inclusion criteria
* Hospitalized patients (NICU) receiving vancomycin or amikacin * Treatment with vancomycin or amikacin initiated during hospitalization * At least one therapeutic drug monitoring (TDM) measurement obtained
Exclusion criteria
* Failure to obtain written informed consent * Death within the first 24 hours after treatment initiation * Discontinuation of therapy before the first TDM measurement * Determined unsuitable for study participation by the treating physician
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Predictive Accuracy of Model-Informed Precision Dosing (MIPD) Based on Median Absolute Error (MdAE) | From first therapeutic drug monitoring (TDM) sample to second TDM sample (typically within 3-5 days of therapy) | Predictive accuracy of the pharmacokinetic model will be evaluated by calculating the Median Absolute Error (MdAE) between model-predicted and observed antibiotic serum concentrations. MdAE was prespecified as the primary accuracy metric due to its robustness to outliers in small pediatric samples. |
| Predictive Accuracy of Model-Informed Precision Dosing (MIPD) Based on Mean Absolute Error (MAE) | From first therapeutic drug monitoring (TDM) sample to second TDM sample (typically within 3-5 days of therapy) | Mean Absolute Error (MAE) between model-predicted and observed serum antibiotic concentrations will be calculated to assess overall prediction error. |
| Predictive Accuracy of Model-Informed Precision Dosing (MIPD) Based on Median Error (MdE) | From first therapeutic drug monitoring (TDM) sample to second TDM sample (typically within 3-5 days of therapy) | Median Error (MdE) will be calculated to evaluate directional bias between predicted and observed serum antibiotic concentrations. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in C-Reactive Protein (CRP) Level | Baseline to approximately day 3-5 of therapy | The absolute change in serum C-reactive protein (CRP) level from baseline (within 24 hours of antibiotic initiation) to the time of the second TDM sample will be evaluated as an inflammatory response marker. |
| Change in Pharmacokinetic Model-Fit Category | From first to second TDM sample (typically within 3-5 days) | Within-patient change in pharmacokinetic model-fit category (poor, intermediate, good) between the first and second TDM measurements will be assessed to evaluate improvement in model performance after Bayesian updating. |
| Change in Procalcitonin Level | Baseline to approximately day 3-5 of therapy | The absolute change in serum procalcitonin level from baseline to the time of the second TDM sample will be assessed. |
| Change in Serum Creatinine Level | Baseline to approximately day 3-5 of therapy | The absolute change in serum creatinine level from baseline to the time of the second TDM sample will be evaluated as a marker of renal safety. |
Countries
Turkey (Türkiye)
Outcome results
None listed