Prediction of area under the concentration–time curve for lopinavir from peak or trough lopinavir concentrations in patients receiving lopinavir–ritonavir therapy

Srinivas, Nuggehally R.

doi:10.2146/ajhp150417

American Journal of Health-System Pharmacy

2016

DOI: 10.2146/ajhp150417

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Prediction of area under the concentration–time curve for lopinavir from peak or trough lopinavir concentrations in patients receiving lopinavir–ritonavir therapy

Nuggehally R. Srinivas¹

Abstract: Equations incorporating lopinavir peak and trough concentrations were found to satisfactorily predict lopinavir AUC values in data sets describing patients receiving lopinavir with ritonavir boosting. Variability in predictions was higher with use of the trough-AUC model.

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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

et al. 2017

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1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC) of dalbavancin is a key parameter and AUC/MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C) C versus AUC 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 AUC were performed using published C 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 C versus AUC 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 AUC 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 C (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC of dalbavancin in patients.

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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

et al. 2017

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The saudi critical care society clinical practice guidelines on the management of COVID-19 patients in the intensive care unit

et al. 2020

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Prediction of area under the concentration–time curve for lopinavir from peak or trough lopinavir concentrations in patients receiving lopinavir–ritonavir therapy

Abstract: Equations incorporating lopinavir peak and trough concentrations were found to satisfactorily predict lopinavir AUC values in data sets describing patients receiving lopinavir with ritonavir boosting. Variability in predictions was higher with use of the trough-AUC model.

Cited by 2 publications

References 55 publications

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

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

The saudi critical care society clinical practice guidelines on the management of COVID-19 patients in the intensive care unit

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