Introduction: Ex vivo experiments in extracorporeal membrane oxygenation (ECMO) circuits have identified octanol-water partition coefficient (logP, a marker of lipophilicity) and protein binding (PB) as key drug factors affecting pharmacokinetics (PK) during ECMO. Using ovine models, in this study we investigated whether these drug properties can be used to predict PK alterations of antimicrobial drugs during ECMO.
Methods: Single-dose PK sampling was performed in healthy sheep (HS, n = 7), healthy sheep on ECMO (E24H, n = 7) and sheep with smoke inhalation acute lung injury on ECMO (SE24H, n = 6). The sheep received eight study antimicrobials (ceftriaxone, gentamicin, meropenem, vancomycin, doripenem, ciprofloxacin, fluconazole, caspofungin) that exhibit varying degrees of logP and PB. Plasma drug concentrations were determined using validated chromatographic techniques. PK data obtained from a non-compartmental analysis were used in a linear regression model to predict PK parameters based on logP and PB.
Results: We found statistically significant differences in pH, haemodynamics, fluid balance and plasma proteins between the E24H and SE24H groups (p < 0.001). logP had a strong positive linear relationship with steady-state volume of distribution (Vss) in both the E24H and SE24H groups (p < 0.001) but not in the HS group (p = 0.9) and no relationship with clearance (CL) in all study groups. Although we observed an increase in CL for highly PB drugs in ECMO sheep, PB exhibited a weaker negative linear relationship with both CL (HS, p = 0.01; E24H, p < 0.001; SE24H, p < 0.001) and Vss (HS, p = 0.01; E24H, p = 0.004; SE24H, p = 0.05) in the final model.
Conclusions: Lipophilic antimicrobials are likely to have an increased Vss and decreased CL during ECMO. Protein-bound antimicrobial agents are likely to have reductions both in CL and Vss during ECMO. The strong relationship between lipophilicity and Vss seen in both the E24H and SE24H groups indicates circuit sequestration of lipophilic drugs. These findings highlight the importance of drug factors in predicting antimicrobial drug PK during ECMO and should be a consideration when performing and interpreting population PK studies.