Bayesian forecasting for intravenous tobramycin dosing in adults with Cystic Fibrosis using one versus two serum concentrations in a dosing interval

BackgroundIntravenous tobramycin requires therapeutic drug monitoring (TDM) to ensure safety and efficacy when used for prolonged treatment, as in infective exacerbations of Cystic Fibrosis (CF). The 24 hour area under the concentration time curve (AUC24) is widely used to guide dosing, however there remains variability in practice around methods for its estimation. ObjectivesTo determine the potential for a sparse sampling strategy using a single post-infusion tobramycin concentration and Bayesian forecasting, to assess the AUC24 in routine practice. MethodsAdults with CF receiving once daily tobramycin had paired concentrations measured 2 hours (c1) and 6 hours (c2) following end of infusion as routine monitoring. We estimated AUC24 exposures using Tucuxi, a Bayesian forecasting application incorporating a validated population pharmacokinetic model. We performed simulations to estimate AUC24 using the full dataset using c1 and c2, compared to estimates using depleted datasets (c1 or c2 only), with and without concentration data from earlier in the course. We assessed agreement between each simulation condition and the reference graphically, and numerically using median difference ({Delta}) AUC24, and (relative) root mean square error (rRMSE) as measures of bias and accuracy respectively. Results55 patients contributed 512 concentrations from 95 tobramycin courses and 256 TDM episodes. Single concentration methods performed well, with median {Delta}AUC24 <2 mg.h.l-1 and rRMSE of <15% for sequential c1 and c2 conditions. ConclusionsBayesian forecasting, using single post-infusion concentrations taken 2-6 hours following tobramycin administration can adequately estimate true exposure in this patient group and are suitable for routine TDM practice. Key Points- In stable adult patients with Cystic fibrosis without significant renal impairment, Bayesian forecasting allows accurate estimation of tobramycin AUC24 using a single blood sample taken 2-6 hours post-infusion with acceptable accuracy, especially when including prior measured concentrations. - A single sample approach with Bayesian forecasting is logistically less complicated than a two-sample approach, and could facilitate best-practice TDM in the outpatient setting. - A more intensive sampling strategy with Bayesian forecasting using two tobramycin concentrations in a dosing interval should be considered in unstable patients, or where observed concentrations deviate significantly from model predictions.