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Prediction of micafungin area under the curve data by using peak concentration: applicability and utility in
1Suramus Bio, Drug Development, J.P. Nagar I Phase, Bangalore 560078, Karnataka, India.
Aim:
To describe a predictive model to obtain the area under the plasma concentration versus time curve (AUC) for micafungin to aid in dosing strategies in pediatric patients.
Methods:
Using published pharmacokinetic data a linear regression model to describe the Cmax versus AUCtau was developed. The mean absolute error prediction, root mean square error prediction along with correlation coefficient (r) and fold prediction criteria were used to evaluate the developed linear regression model for micafungin.
Results:
The predicted AUC for micafungin were contained within 0.5-1.5 fold difference. The mean absolute error and root mean square error for the developed model was 15 and 27%, respectively.
Conclusion:
The model may be used in a prospective manner for dosing decisions of micafungin in pediatric patients.
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