Sampling from covariate distribution may not always be necessary in PK/PD simulations: illustrative examples with antibiotics.

Pharmacokinetics (PK)/pharmacodynamics (PD) modeling and simulation is crucial for optimizing antimicrobial dosing. This study assessed covariate impact on PK variability and identified scenarios where fixing the covariate with median value proves effective PK/PD simulations for antibiotics with population PK (popPK) model including only one covariate effect. Three published popPK models were employed, with creatinine clearance (CRCL) identified as a covariate on clearance (CL) for meropenem and tobramycin, and total body weight (WT) associated with the volume of distributions for daptomycin. Given a fixed dose for Meropenem (1000 mg), and a WT based dose for tobramycin (7 mg/kg) and daptomycin (6 mg/kg), PK/PD simulation outcomes (e.g., percentage of PK/PD target attainment (PTA) and toxicity risk) were compared between fixed covariate-based and covariate distribution-based approaches. Covariate impact on PK was assessed through deterministic simulation using outer bounds of covariate versus simulation using median covariate value, with an overlap ratio calculated the percentage of overlapped area under concentration-time curve (AUC) between these two simulation approaches. Meropenem and tobramycin simulations showed a broader PK profiles and distinct PTA distribution with sampled covariate distribution, while daptomycin simulations exhibited consistency in PK/PD characteristics. CRCL had a relative strong impact on meropenem and tobramycin PK, while a weak impact of WT on daptomycin PK was observed from extensive overlap in simulated PK curves, with an overlap ratio of 99.5%. Regarding a weak covariate impact on PK with high overlap ratio, sampling from covariate distribution may not significantly enhance simulation performance, fixing covariate with median value could be efficient for antibiotic PK/PD simulations.