Dose Optimization of Vancomycin Using a Mechanism-based Exposure–Response Model in Pediatric Infectious Disease Patients

• Published in: Clinical therapeutics Vol. 43; no. 1; pp. 185 - 194.e16
• Main Authors: Jung, Woo Jin, Park, Jung-Hyuck, Goo, Sungwoo, Chae, Jung-woo, Kim, JaeWoo, Shin, Sooyoung, Yun, Hwi-yeol
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.2021; Elsevier Limited
• Subjects: Age; Anti-Bacterial Agents - administration & dosage; Anti-Bacterial Agents - pharmacokinetics; Antibiotics; Bacteria; Body Size; C-reactive protein; C-Reactive Protein - analysis; Child; Communicable Diseases - blood; Communicable Diseases - drug therapy; Communicable Diseases - metabolism; Creatinine; Dosage; dose optimization; Dose-Response Relationship, Drug; Electronic medical records; Female; Gram-positive bacteria; Humans; Infectious diseases; Internal Medicine; Kidneys; Male; mechanism-based PK/PD model; Microbial Sensitivity Tests; Minimum inhibitory concentration; Models, Biological; Optimization; Parameter estimation; Patients; Pediatrics; Pharmacodynamics; Pharmacokinetics; Premature birth; Proteins; Simulation; Software; Staphylococcus infections; Vancomycin; Vancomycin - administration & dosage; Vancomycin - pharmacokinetics; vancomycin; dose optimization; mechanism-based PK/PD model; pediatrics
• ISSN: 0149-2918; 1879-114X; 1879-114X
• DOI: 10.1016/j.clinthera.2020.10.016

This study aimed to determine the appropriate vancomycin dosage, considering patient size and organ maturation, by simulating the bacterial count and biomarker level for drug administration in pediatric patients with gram-positive bacterial (GPB) infections. Natural language processing for n-gram analysis was used to detect appropriate pharmacodynamic (PD) markers in infectious disease patients. In addition, a mechanism-based model was established to describe the systemic exposure and evaluate the PD marker simultaneously in pediatric patients. A simulation study was then conducted by using a mechanism-based model to evaluate the optimal dose of vancomycin in pediatric patients. : C-reactive protein (CRP) was selected as a PD marker from an analysis of ~270,000 abstracts in PubMed. In addition, clinical results, including the vancomycin plasma concentrations and CRP levels of pediatric patients (n = 93), were collected from electronic medical records. The vancomycin pharmacokinetic model with allometric scaling and a maturation function was built as a one-compartment model, with an additional compartment for bacteria. Both the effects of vancomycin plasma concentrations on the destruction of bacteria and those of bacteria on CRP production rates were represented by using a maximum achievable effect model (Emax model). Simulation for dose optimization was conducted not only by using the final model but also by exploring the possibility of therapeutic failure based on the MICs of vancomycin for GPB. Clinical cure was defined as when the CRP level fell below the upper limit of the normal range. Our dose optimization simulations suggested a vancomycin dosage of 10 mg/kg every 8 h as the optimal maintenance dose for pediatric patients with a postconceptual age <30 weeks and 10 mg/kg every 6 h for older children, aged up to 12 years. In addition, the MIC of 3 μg/mL was assessed as the upper concentration limit associated with successful vancomycin treatment of GPB infections. This study confirmed that the changes in bacterial counts and CRP levels were well described with mechanistic exposure–response modeling of vancomycin. This model can be used to determine optimal empiric doses of vancomycin and to improve therapeutic outcomes in pediatric patients with GPB. [Display omitted] •Determination of effective PD markers of vancomycin using big-data analysis method (Network analysis).•The first quantitative exposure-response modeling among bacterial counts, CRP levels and vancomycin concentration to cover whole range of age.•Dose optimization, especially pediatrics, depending on patients' scaling (weight) and maturation (age) factor.•Improvement of therapeutic outcomes in pediatric patients with GPB infections.