Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin

Heitzmann, Julia; Thoma, Yann; Bricca, Romain; Gagnieu, Marie‐Claude; Leclerc, Vincent; Roux, Sandrine; Conrad, Anne; Ferry, Tristan; Goutelle, Sylvain

doi:10.3390/pharmaceutics14010114

Cited by 9 publications

(6 citation statements)

References 35 publications

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“…Software tools for modelling or research. References [14,[17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] are cited in the supplementary materials.…”

Section: Supplementary Materialsmentioning

confidence: 99%

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review

Del Valle-Moreno,

Suarez-Casillas,

Mejías-Trueba

et al. 2023

Pharmaceutics

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Background: Pharmacokinetic nomograms, equations, and software are considered the main tools available for Therapeutic Drug Monitoring (TDM). Model-informed precision dosing (MIPD) is an advanced discipline of TDM that allows dose individualization, and requires a software for knowledge integration and statistical calculations. Due to its precision and extensive applicability, the use of these software is widespread in clinical practice. However, the currently available evidence on these tools remains scarce. Objectives: To review and summarize the available evidence on MIPD software tools to facilitate its identification, evaluation, and selection by users. Methods: An electronic literature search was conducted in MEDLINE, EMBASE, OpenAIRE, and BASE before July 2022. The PRISMA-ScR was applied. The main inclusion criteria were studies focused on developing software for use in clinical practice, research, or modelling. Results: Twenty-eight software were classified as MIPD software. Ten are currently unavailable. The remaining 18 software were described in depth. It is noteworthy that all MIPD software used Bayesian statistical methods to estimate drug exposure and all provided a population model by default, except NONMEN. Conclusions: Pharmacokinetic software have become relevant tools for TDM. MIPD software have been compared, facilitating its selection for use in clinical practice. However, it would be interesting to standardize the quality and validate the software tools.

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“…Software tools for modelling or research. References [14,[17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] are cited in the supplementary materials.…”

Section: Supplementary Materialsmentioning

confidence: 99%

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review

Del Valle-Moreno,

Suarez-Casillas,

Mejías-Trueba

et al. 2023

Pharmaceutics

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“…While the goodness of fit is a classic criterion in the validation of population PK models, we think that dose recommendations should be the primary diagnostic criterion when evaluating the dosing tools in a “fit-for-purpose” validation approach [ 27 ]. The previous studies evaluating dosing software considered this criterion as well [ 28 , 29 ].…”

Section: Discussionmentioning

confidence: 99%

Implementation and Cross-Validation of a Pharmacokinetic Model for Precision Dosing of Busulfan in Hematopoietic Stem Cell Transplanted Children

et al. 2022

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Busulfan, a drug used in conditioning prior to hematopoietic stem cell transplantation (HSCT) in children, has a narrow therapeutic margin. The model-informed precision dosing (MIPD) of busulfan is desirable, but there is a lack of validated tools. The objective of this study was to implement and cross-validate a population pharmacokinetic (PK) model in the Tucuxi software for busulfan MIPD in HSCT children. A search of the literature was performed to identify candidate population PK models. The goodness of fit of three selected models was assessed in a dataset of 178 children by computing the mean error (ME) and root-mean-squared error of prediction (RMSE). The best model was implemented in Tucuxi. The individual predicted concentrations, the area under the concentration-time curve (AUC), and dosage requirements were compared between the Tucuxi model and a reference model available in the BestDose software in a subset of 61 children. The model from Paci et al. best fitted the data in the full dataset. In a subset of 61 patients, the predictive performance of Tucuxi and BestDose models was comparable with ME values of 6.4% and −2.5% and RMSE values of 11.4% and 13.6%, respectively. The agreement between the estimated AUC and the predicted dose was good, with 6.6% and 4.9% of the values being out of the 95% limits of agreement, respectively. To conclude, a PK model for busulfan MIPD was cross-validated and is now available in the Tucuxi software.

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“…7 The authors used a two-compartment model with first-order elimination described previously. 6 In this model, creatinine clearance estimated by the Cockcroft and Gault formula and body weight influenced the elimination rate constant and central volume of distribution, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…This was a new analysis of a previously described data set. 6 However, in this analysis, the authors discarded data from patients with 1 or 2 samples, and only patients with 3 concentration measurements obtained on a single TDM occasion were included. All patients were administered daptomycin for BJI.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration–Time Curve: A Short Communication

Tuloup

Millet

Taricco

et al. 2023

Therapeutic Drug Monitoring

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Increasing evidence supports daptomycin therapeutic drug monitoring. The author's reference center used to perform therapeutic drug monitoring in patients who receive high-dose daptomycin for bone and joint infections, with a three-sample strategy to estimate the daptomycin daily area under the concentration-time curve (AUC). The objective of this study was to evaluate simpler strategies based on only 2 or 1 sample(s). Methods:The authors used the BestDose software to estimate the daptomycin AUC after Bayesian posterior estimation of individual pharmacokinetic (PK) parameters at steady state. The reference AUC (AUC full ) was based on 3 samples obtained predose (T0) and approximately 1 hour (T1) and 6 hours (T6) after the start of a 30-minute infusion of IV daptomycin. It was compared with the AUC based on all possible 2-sample and 1-sample strategies. Bias, imprecision, regression, and Bland-Altman plots were used to assess the performance of the alternative strategies.

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Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin

Cited by 9 publications

References 35 publications

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review

Implementation and Cross-Validation of a Pharmacokinetic Model for Precision Dosing of Busulfan in Hematopoietic Stem Cell Transplanted Children

Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration–Time Curve: A Short Communication

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