BackgroundVancomycin is commonly used for treatment of severe Gram+ neonatal infections. Currently, even with the use of optimized dosing regimens and therapeutic drug monitoring (TDM), target attainment rates are abominable, leaving patients at risk for therapeutic failure and toxicity. Model-informed precision dosing (MIPD) offers a large potential to improve therapy in the individual patient.The aim of this study was to identify a suitable model for bedside MIPD by assessing the predictive performance of published population pharmacokinetic (popPK) models.MethodsA literature search was conducted to identify parametric popPK models. PK vancomycin data were retrospectively collected from NICU patients at the Radboud University Hospital, Nijmegen, The Netherlands. The model predictive performance was assessed by comparison of predictions to observations, calculation of bias (Mean Percentage Errors, MPE) and imprecision (Normalized Root Mean Squared Errors, NRMSE). Evaluations included both a priori (model covariate input) and a posteriori (model covariate and TDM concentration input) scenarios.Results265 TDM measurements from 65 neonates (median postmenstrual age:32 weeks [range:25–45 weeks]; median weight:1281g [range:597–5360g]; median serum creatinine:0,48 mg/dL [range:0,15–1,28 mg/dL]) were used for model evaluation. Six popPK models were evaluated1–6. A posteriori predictions of all models were consistently more accurate and precise compared to the a priori (starting dose) predictions. PopPK models of Frymoyer et al. and Capparelli et al. consistently performed best through all evaluations in both the a priori and a posteriori scenario (MPE ranging from -18 to 6,4% in a priori scenario and -6,5 to -3,8% in a posteriori scenario; NRMSE ranging from 34 to 40% in a priori scenario and 23 to 24% in a posteriori scenario).ConclusionLarge differences in predictive performance of popPK models were observed. Repeated therapeutic drug monitoring remains necessary to increase target attainment rate. Best performing models for bedside MIPD were identified in our patient population.ReferencesZhao W, Lopez E, Biran V, et al. ( 2013). Vancomycin continuous infusion in neonates: Dosing optimisation and therapeutic drug monitoring. Arch Dis Child;98(6):449–453.Capparelli EV, Lane JR, Romanowski GL, et al. ( 2001). The influences of renal function and maturation on vancomycin elimination in newborns and infants. J Clin Pharmacol, 41:927–934.De Cock RFW, Allegaert K, Brussee JM, et al. ( 2014). Simultaneous pharmacokinetic modeling of gentamicin, tobramycin and vancomycin clearance from neonates to adults: towards a semi-physiological function for maturation in glomerular filtration. Pharm Res;31(10):2642–2654.Frymoyer A, Hersh AL, El-Komy MH, et al. ( 2014). Association between vancomycin trough concentration and area under the concentration-time curve in neonates. Antimicrob Agents Chemother, 58(11):6454–6461.Anderson BJ, Allegaert K, Van Den Anker JN, Cossey V, Holford NHG. ( 2006). Vancomycin pharmacokinetics in preterm neonates and the prediction of adult clearance. Br J Clin Pharmacol;63(1):75–84.Germovsek E, Osborne L, Gunaratnam F, Lounis SA, Busquets FB, Sinha AK. ( 2019). Development and external evaluation of a population pharmacokinetic model for continuous and intermittent administration of vancomycin in neonates and infants using prospectively collected data. J Antimicrob Chemother, 1–9.Disclosure(s)R. Keizer is an employee and stockholder of InsightRX.
Oncogenic activation of Nrf2 by specific knockout of Nrf1α that acts as a dominant tumor repressor
