Pharmacodynamic Variability beyond That Explained by MICs

Abstract

bMonte Carlo simulations (MCS) present a powerful tool to evaluate candidate regimens by determining the probability of target attainment. Although these assessments have traditionally incorporated variability in pharmacokinetic (PK) parameters and MICs, consideration of interstrain pharmacodynamic (PD) variability has been neglected. A population PK/PD model was developed for doripenem using murine thigh infection data based on 20 bacterial strains. PK data were fit to a linear two-compartment model with first-order input and elimination processes and an absorption lag time from a separate site (r 2 > 0.96). PK parameters were utilized to simulate free-drug profiles for various regimens in PD studies, from which the percentage of the dosing interval for which free-drug concentrations exceed the MIC of the targeted strain (%fT>MIC) was calculated. Doripenem PD was excellently described with Hill-type models (r 2 > 0.98); significant differences between mean PD estimates determined using a two-stage approach versus population analyses were not observed (P > 0.05); however, the variance in 50% effective concentration (EC 50 ) and maximum effect (E max ) among strains was much greater using the two-stage approach. Even using the population approach, interstrain variability in EC 50 (coefficient of variation expressed as a percentage [CV%] ‫؍‬ 29.2%) and H (CV% ‫؍‬ 46.1%) parameters was substantive, while the variability in E max (CV% ‫؍‬ 19.7%) was modest. This resulted in extensive variability in the range of %fT>MIC targets associated with stasis to those associated with a 2-log 10 reduction in bacterial burden (CV% ϳ 50%). It appears that MCS, based on the assumption that PD variability is due to MIC alone, underestimates variability and may consequently underestimate treatment failures.T he emerging threat posed by multidrug-resistant (MDR) bacterial strains has heightened, necessitating an urgent review of antimicrobial treatment strategies. Carbapenems are synthetic parenteral broad-spectrum ␤-lactam antibiotics, commonly employed as empirical therapy for the treatment of serious nosocomial infections. Doripenem (Doribax; Ortho-McNeil Pharmaceuticals, NJ) (1) is the most recent addition to the carbapenem class and boasts a broad spectrum of activity, providing excellent coverage across a wide range of Gram-positive and -negative bacteria (including MDR and ␤-lactamase-producing strains) as well as anaerobes (2). In comparison to the other carbapenems, doripenem has been credited with several advantages, including enhanced potency, superior stability when reconstituted in standard diluents for infusion (3, 4), and a lower potential to cause seizurerelated toxicities in animal studies (5). The percentage of the dosing interval for which free-drug concentrations exceed the MIC of the targeted strain (i.e., %fTϾMIC) is believed to be the pharmacokinetic (PK)/pharmacodynamic (PD) index most predictive of carbapenem efficacy. The extended stability of doripenem thus makes it a suitable candidate for administration ...

Pharmacokinetics of doripenem during high volume hemodiafiltration in patients with septic shock

“…For bactericidal effect, 35%–40% of time above MIC has commonly been reported as sufficient for carbapenems, although 50% was found necessary in critically ill patients and 75% in patients with febrile neutropenia . Importantly, in vitro and in vivo experiments have demonstrated large interstrain pharmacodynamic variability both between and within bacterial species in terms of cell kill and suppression of resistance . Our data show that doripenem doses of 500 mg every 8 hours are necessary for the treatment of susceptible bacteria and targeting 50%T > MIC during extended HVHDF.…”

Tissue Penetration of Antifungal Agents

“…This persistence of tissue concentrations may explain why, in specific situations, linking the tissue pharmacokinetic data with pharmacodynamic data produces a significantly more robust PK/PD model than using plasma PK data alone (31,63). The technique of comodeling both PK and PD data may also produce a more insightful reflection of the impact of tissue concentration than the simplistic comparison of peak tissue concentration with the breakpoint MIC (64).…”

“…First, comodeling both PK and PD data (if possible) provides key insights into the importance of tissue concentrations (64).…”

Mechanism‐Based Disease Progression Model Describing Host‐Pathogen Interactions During the Pathogenesis of Acinetobacter baumannii Pneumonia

“…In vitro models of infection include static time-kill, dynamic onecompartment, and hollow-fiber systems; in vivo infection models typically utilize neutropenic mice. 3,4 However, current preclinical translational designs and models fail to take the host immune response, which is key to initiating bacterial clearance and clinical outcome, into account. The interaction between the invading bacterial pathogen and host innate immune system is the principal pathway for elimination of virulent extracellular grampositive and gram-negative pathogens from the lung, tipping the immune balance toward inflammation.…”

“…Current translational research primarily optimizes existing antibiotics against these hard‐to‐treat pathogens using in vitro and in vivo infection pharmacokinetic (PK) and pharmacodynamic (PD) models of drugs and bacteria. In vitro models of infection include static time‐kill, dynamic one‐compartment, and hollow‐fiber systems; in vivo infection models typically utilize neutropenic mice …”