Evaluation of dosing designs of carbapenems for severe respiratory infection using Monte Carlo simulation.

Using the Monte Carlo simulation method, the influence of various doses and dosing frequencies of carbapenems on the antimicrobial activities against Streptococcus pneumoniae, Haemophilus influenzae, and Pseudomonas aeruginosa, which are the main causative organisms of respiratory infections, was studied with the aim of identifying optimized effectiveness. Based on pharmacokinetic (PK) parameters of individual carbapenems in healthy adults, data on changes in the respective blood concentrations in 2000 cases were simulated by applying a lognormal distribution to probability distributions of their volume of distributions and half-life periods. Based on minimum inhibitory concentration (MIC) distribution data of the individual carbapenems against these strains, MICs in the 2000 cases were also simulated. Using these data in blood concentrations and MICs, the probabilities of attaining various percentages of the dosing interval during which drug concentrations remain above MIC (T > MIC) were calculated at several dosing regimens. Considering the probabilities of attaining the bactericidal effect (50% T>MIC) and daily drug costs, imipenem (IPM) at 500 mg i.v. BID, panipenem (PAPM) at 500 mg i.v. BID, and biapenem (BIPM) at 300 mg i.v. BID against Streptococcus pneumoniae; meropenem (MEPM) at 500 mg i.v. BID or TID against Haemophilus influenzae infections; and MEPM at 500 or 1000 mg i.v. TID against Pseudomonas aeruginosa, each over 30 min, were determined as appropriate empirical treatments. Selecting carbapenems with superior antimicrobial activities and optimizing their dose regimens are important to improve the efficacy. Application of Monte Carlo simulation to MIC distributions allows determination of appropriate empiric therapy even if drug susceptibility of a causative organism in individual patients is unknown.