Implementation and validation of a Bayesian method for accurately forecasting duration of optimal pharmacodynamic target attainment with dalbavancin during long-term use for treating subacute and/or chronic staphylococcal infections.

Dalbavancin is being increasingly used for long-term treatment of subacute and/or chronic staphylococcal infections. Here we implemented and validated a new Bayesian model by means of the MwPharm software for accurately forecasting duration of pharmacodynamic target attainment above the efficacy thresholds of 4.02 or 8.04 mg/L against staphylococci. Forecasting accuracy improved substantially with the a posteriori approach compared to the a priori approach, especially when two measured concentrations were used. This strategy may help clinicians in estimating proper duration of optimal exposure with dalbavancin during long-term treatment.