Individual Control Optimization of Drug Dosage Using Individual Bayesian Pharmacokinetics Model Approach

Abstract Giving the right dose of medicine is very important in the healing process from a disease. Improper dosing may worsen the disease or even can cause death. Drug dosing should not only be done based on the population because each individual has different body characteristics. Therefore, the drug dosage was carried out individually using the individual Bayesian pharmacokinetics modeling approach. This case evokes problems regarding how to obtain the estimated population and individual parameters and then determine the optimal dose. The purpose of this analysis is to get the parameters estimation of both population and individual and determine their optimal dose. The data used in this study is patient data who received gentamicin injection. Variables used is gentamicin levels in serum as response variables and sampling times and initial doses as predictor variables. The results obtained are individual pharmacokinetic models with 100% prediction accuracy and dose ranges that can still be tolerated for each individual.