Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models. (1st February 2018) - Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally
Abstract: 1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUCinf ) of dalbavancin is a key parameter and AUCinf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. Cmax ) Cmax versus AUCinf relationship for dalbavancin was established by regression analyses (i.e. linear, log–log, log–linear and power models) using 21 pairs of subject data. 3. The predictions of the AUCinf were performed using published Cmax data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient ( r ) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The Cmax versus AUCinf exhibited excellent correlation ( r  > 0.9488). The internal data evaluation showed narrow confinement (0.84–1.14-fold difference) with a RMSE < 10.3%. The external data evaluation showed that the models predicted AUCinf with a RMSE of 3.02–27.46% with fold difference largely contained within 0.64–1.48. 5. Regardless of the regression models, a single time point strategy of using Cmax (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUCinf of dalbavancin in patients.