title: Innovative approaches to optimizing the delivery of vancomycin in individual patients.
abstract: The delivery of personalized antimicrobial therapy is a critical component in the treatment of patients with invasive infections. Vancomycin, the drug of choice for infections due to methicillin-resistant Staphylococcus aureus, requires the use of therapeutic drug monitoring (TDM) for delivery of optimal therapy. Current guidance on vancomycin TDM includes the measurement of a trough concentration as a surrogate for achieving an AUC to minimum inhibitory concentration (MIC) by broth microdilution (AUC/MICBMD) ratio≥400. Although trough-only monitoring has been widely integrated into clinical practice, there is a high degree of inter-individual variability between a measured trough concentration and the actual AUC value. The therapeutic discordance between AUC and trough may lead to suboptimal outcomes among patients with infections due to less susceptible pathogens or unnecessarily increase the probability of acute kidney injury (AKI) in others. Given the potentially narrow vancomycin AUC range for optimal effect and minimal AKI, clinicians need a "real-time" system to predict accurately the AUC with limited pharmacokinetic (PK) sampling. This article reviews two innovative approaches for calculating the vancomycin AUC in clinical practice based on one or two drug concentrations. One such approach involves the use of Bayesian computer software programs to estimate the "true" vancomycin AUC value with minimal PK sampling and provide AUC-guided dosing recommendations at the bedside. An alternative involves use of two concentrations (peak and trough) and simple analytic equations to estimate AUC values. Both approaches provide considerable improvements over the current trough-only concentration monitoring method.
authors.affiliation: Albany College of Pharmacy and Health Sciences, Albany, NY, USA.
authors.forename: Manjunath P
authors.initials: MP
authors.lastname: Pai
authors.affiliation: University of Southern California, Keck School of Medicine, Los Angeles, CA, USA; Laboratory of Applied Pharmacokinetics and Bioinformatics (LAPKB), Children's Hospital of Los Angeles, Los Angeles, CA, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Neely
authors.affiliation: Colleges of Pharmacy and Medicine, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Keith A
authors.initials: KA
authors.lastname: Rodvold
authors.affiliation: Albany College of Pharmacy and Health Sciences, Albany, NY, USA. Electronic address: thomas.lodise@acphs.edu.
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Lodise
mesh_terms: D000818:Animals; D000900:Anti-Bacterial Agents / Q000008:administration & dosage* / Q000493:pharmacokinetics; D019540:Area Under Curve; D016503:Drug Delivery Systems; D016903:Drug Monitoring / Q000379:methods; D006801:Humans; D055624:Methicillin-Resistant Staphylococcus aureus / Q000187:drug effects; D008826:Microbial Sensitivity Tests; D013203:Staphylococcal Infections / Q000188:drug therapy / Q000382:microbiology; D014640:Vancomycin / Q000008:administration & dosage* / Q000493:pharmacokinetics
chemical_list: D000900:Anti-Bacterial Agents; D014640:Vancomycin
keywords: AUC; Bayesian; Pharmacodynamics; Pharmacokinetics; Trough; Vancomycin