title: Monte Carlo simulation analysis of ceftobiprole, dalbavancin, daptomycin, tigecycline, linezolid and vancomycin pharmacodynamics against intensive care unit-isolated methicillin-resistant Staphylococcus aureus.
abstract: The aim of the present study was to compare the potential of ceftobiprole, dalbavancin, daptomycin, tigecycline, linezolid and vancomycin to achieve their requisite pharmacokinetic/pharmacodynamic (PK/PD) targets against methicillin-resistant Staphylococcus aureus isolates collected from intensive care unit (ICU) settings. Monte Carlo simulations were carried out to simulate the PK/PD indices of the investigated antimicrobials. The probability of target attainment (PTA) was estimated at minimum inhibitory concentration values ranging from 0.03 to 32 μg/mL to define the PK/PD susceptibility breakpoints. The cumulative fraction of response (CFR) was computed using minimum inhibitory concentration data from the Canadian National Intensive Care Unit study. Analysis of the simulation results suggested the breakpoints of 4 μg/mL for ceftobiprole (500 mg/2 h t.i.d.), 0.25 μg/mL for dalbavancin (1000 mg), 0.12 μg/mL for daptomycin (4 mg/kg q.d. and 6 mg/kg q.d.) and tigecycline (50 mg b.i.d.), and 2 μg/mL for linezolid (600 mg b.i.d.) and vancomycin (1 g b.i.d. and 1.5 g b.i.d.). The estimated CFR were 100, 100, 70.6, 88.8, 96.5, 82.4, 89.4, and 98.3% for ceftobiprole, dalbavancin, daptomycin (4 mg/kg/day), daptomycin (6 mg/kg/day), linezolid, tigecycline, vancomycin (1 g b.i.d.) and vancomycin (1.5 g b.i.d.), respectively. In conclusion, ceftobiprole and dalbavancin have the highest probability of achieving their requisite PK/PD targets against methicillin-resistant Staphylococcus aureus isolated from ICU settings. The susceptibility predictions suggested a reduction of the vancomycin breakpoint to 1 μg/mL.
authors.affiliation: Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA; Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt.
authors.forename: Ahmed Hamed
authors.initials: AH
authors.lastname: Salem
authors.forename: George G
authors.initials: GG
authors.lastname: Zhanel
authors.forename: Safaa A
authors.initials: SA
authors.lastname: Ibrahim
authors.forename: Ayman M
authors.initials: AM
authors.lastname: Noreddin
mesh_terms: D000081:Acetamides / Q000494:pharmacology; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D002511:Cephalosporins / Q000494:pharmacology; D003198:Computer Simulation; D003428:Cross Infection / Q000382:microbiology*; D017576:Daptomycin / Q000494:pharmacology; D004305:Dose-Response Relationship, Drug; D006801:Humans; D007362:Intensive Care Units; D000069349:Linezolid; D016106:Methicillin Resistance; D055624:Methicillin-Resistant Staphylococcus aureus / Q000187:drug effects*; D008911:Minocycline / Q000031:analogs & derivatives / Q000494:pharmacology; D008954:Models, Biological; D009010:Monte Carlo Method; D023303:Oxazolidinones / Q000494:pharmacology; D013203:Staphylococcal Infections / Q000382:microbiology*; D017334:Teicoplanin / Q000031:analogs & derivatives / Q000494:pharmacology; D000078304:Tigecycline; D014640:Vancomycin / Q000494:pharmacology
chemical_list: D000081:Acetamides; D000900:Anti-Bacterial Agents; D002511:Cephalosporins; D023303:Oxazolidinones; C443755:ceftobiprole; D017334:Teicoplanin; D014640:Vancomycin; D000078304:Tigecycline; C469289:dalbavancin; D008911:Minocycline; D000069349:Linezolid; D017576:Daptomycin
keywords: Monte Carlo simulation; ceftobiprole; intensive care unit; methicillin-resistant Staphylococcus aureus; vancomycin