Premium
Monte Carlo Simulation Methodologies for β‐Lactam/β‐Lactamase Inhibitor Combinations: Effect on Probability of Target Attainment Assessments
Author(s) -
Kidd James M.,
Stein Gary E.,
Nicolau David P.,
Kuti Joseph L.
Publication year - 2020
Publication title -
the journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 116
eISSN - 1552-4604
pISSN - 0091-2700
DOI - 10.1002/jcph.1510
Subject(s) - pharmacokinetics , ceftazidime , avibactam , pharmacodynamics , medicine , pharmacology , covariate , population , mathematics , statistics , biology , environmental health , bacteria , pseudomonas aeruginosa , genetics
Monte Carlo simulations (MCSs) are used in antibiotic development to predict the probability of pharmacodynamic target attainment (PTA) for a dosing regimen. However, for β‐lactam/β‐lactamase inhibitor combinations (BL‐BLICs), methods for linking simulated concentration profiles of the β‐lactam (BL) and β‐lactamase inhibitor (BLI) components are rarely described. Using a previously defined pharmacokinetic model of ceftazidime/avibactam from critically ill patients, we performed four 5000‐patient MCSs using different methods of increasing complexity to couple the BL and BLI components and compared PTA for ceftazidime and avibactam targets of >70% f T>MIC and >70% f T>1 mg/L, respectively, at MICs from 1 to 128 mg/L. Method A ignored all covariates and correlations, whereas methods B, C, and D enhanced associations by adding (B) pharmacokinetic parameter correlation within each drug only; (C) pharmacokinetic parameter correlation within each drug and creatinine clearance (CRCL); and (D) pharmacokinetic parameter correlation within each drug, CRCL, and pharmacokinetic parameter correlation between drugs. Method D produced a simulated patient population that best recapitulated the observed relationships between pharmacokinetic parameters in actual patients. Ceftazidime/avibactam PTA at MIC 8 mg/L (the susceptibility break point) and 16 mg/L ranged from 92.4% to 98.3% and 80.2% to 88.4%, respectively. PTA was lowest with method A, whereas PTA estimates were similar for all other methods. Compared with ignoring all pharmacokinetic parameter associations, the inclusion of covariate relationships and parameter correlation between both components of ceftazidime/avibactam leads to fewer patients with discordant pharmacokinetic parameters and results in higher PTA. Consideration of these methodologies should guide future MCS analyses for BL‐BLIC.