40: Personalized Dynamic Dose-Finding for Longitudinal Observational Data

Music City Center 

The prescribed doses for many drugs are based on population norms or physician discretion. For example, very low birth weight (VLBW) infants (BW < 1500 grams) often experience slower postnatal growth and require glucose treatment to support weight gain and prevent hyperglycemia. A uniform dosage is unsuitable due to individual differences in glucose metabolism influenced by weight, gestational age, and other factors. Personalized dynamic dosing adjusts to an infant's observed responses, but quantifying uncertainty is essential in patient-critical environments. This study employs a longitudinal mixed model to estimate personalized optimal doses, using patient-specific random effects as biomarkers to capture individual sensitivities. We quantify the uncertainty of these doses through the implicit value delta method, aiding in safe clinical decision-making. Simulation studies validate our model's robustness, and analysis of NICU data on glucose treatments for VLBW infants over their first seven days demonstrates key differences between optimal and prescribed dosing strategies.

Personalized medicine

Optimal dose

Longitudinal Data Analysis

Implicit Delta Method 

ENAR