NextDose: A web-based Bayesian dose forecasting tool

Last updated 30 July 2021

Voriconazole

Three NextDose models are based on published models (Pascual, Csajka et al. 2012, Dolton, Mikus et al. 2014, McDougall, Martin et al. 2016). A fourth model (Holford) was developed from pooling data from Pascual et al. (Pascual, Csajka et al. 2012) and Dolton et al. (Dolton, Mikus et al. 2014).

Visual predictive checks of the Pascual and Dolton models agree well with the pooled data set observations. The visual predictive check of the McDougall model does not agree which raises doubts about the suitability of the McDougall model (the implementation of the McDougall model was verified with the author) (Holford 2017).

Pascual propose first-order elimination (‘linear’) while Dolton used a mixed-order elimination model (‘non-linear’). The Holford model derived from the pooled data assumes first-order elimination without any clear evidence to support mixed-order elimination. However, the question of the elimination mechanism rests poorly answered.

Many covariates have been proposed as a predictor of voriconazole elimination. Weight is the most important. Drug interactions have a clear effect by induction or inhibition of metabolism. Pascual et al. proposed a categorical cholestasis grade 3 cholestasis criterion (alkaline phosphatase and/or gamma glutamyl transferase >20 times the upper limit of the reference value). An increased in total bilirubin has been correlated with lower clearance but the quantitative relationship was not defined (Tang, Yan et al. 2021).

Target Concentration

The target type for voriconazole, like many anti-infective agents, is not uniformly agreed. The default target type, proposed by NextDose, is commonly suggested (AUC24/MIC) with a target of 100 h (equivalent to an average steady state concentration of 4.17 mg/L). Trough concentration targets should be used with caution.

 

Dolton, M. J., G. Mikus, J. Weiss, J. E. Ray and A. J. McLachlan (2014). "Understanding variability with voriconazole using a population pharmacokinetic approach: implications for optimal dosing." J Antimicrob Chemother 69(6): 1633-1641.

Holford, N. H. G. (2017). "NextDose – A web based dosing tool – Development version 2017." PAGANZ 2017 https://www.paganz.org/abstracts/nextdose-a-web-based-dosing-tool-development-version-2017/ Accessed 20 Feb 2017.

McDougall, D. A., J. Martin, E. G. Playford and B. Green (2016). "Determination of a suitable voriconazole pharmacokinetic model for personalised dosing." J Pharmacokinet Pharmacodyn 43(2): 165-177.

Pascual, A., C. Csajka, T. Buclin, S. Bolay, J. Bille, T. Calandra and O. Marchetti (2012). "Challenging recommended oral and intravenous voriconazole doses for improved efficacy and safety: population pharmacokinetics-based analysis of adult patients with invasive fungal infections." Clin Infect Dis 55(3): 381-390.

Tang, D., M. Yan, B.-l. Song, Y.-c. Zhao, Y.-w. Xiao, F. Wang, W. Liang, B.-k. Zhang, X.-j. Chen, J.-j. Zou, Y. Tian, W.-l. Wang, Y.-f. Jiang, G.-z. Gong, M. Zhang and D.-x. Xiang (2021). "Population pharmacokinetics, safety and dosing optimization of voriconazole in patients with liver dysfunction: A prospective observational study." British Journal of Clinical Pharmacology 87(4): 1890-1902.

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