Automatized reporting in the applications of MonolixSuite
Frano Mihaljevic (1), Jonathan Chauvin (1), Géraldine Cellière (1), Claude Magnard (1), Pauline Traynard (1), Monika Twarogowska (1)
(1) Simulations Plus, Lixoft division, Antony, France
Objectives: Monolix, a tool for parameter estimation in non-linear mixed effects models and model diagnosis, provides an efficient way to perform population PKPD modeling. PKanalix, a graphical and interactive software for non-compartmental and compartmental analysis, can be used to efficiently perform non-compartmental and compartmental analyses, as well as bioequivalence calculations. New and innovative features in terms of data formatting and reporting are available through the Monolix and PKanalix graphical user interface in the MonolixSuite 2023R1 release version. These features include a possibility to automate the process of creating project reports by using default or custom-made report templates. We have demonstrated the ability of the 2023R1 MonolixSuite features to generate diverse reports containing all relevant project settings, result tables and diagnostic plots.
Methods: Created project reports are based on population PKPD models developed in Monolix on multiple data sets, as well as several non-compartmental analyses performed using PKanalix on data sets obtained from diverse clinical study designs [1, 2, 3]. Templates of custom project reports were constructed using Microsoft Word. The templates contain placeholders, which consist of texts that specify the types and visual characteristics of tables and plots to be produced when the report is generated.. The placeholders in the templates were then converted to project settings, tables and plots, using options available in Monolix and PKanalix interfaces, in order to generate full and project-specific reports.
Results: Project reports were successfully generated for multiple projects based on different data sets and models, containing multiple plots and tables that present the results of model development calculated by Monolix and non-compartmental and bioequivalence analyses calculated by PKanalix. The softwares could generate both default reports, composed of predefined tables and project settings, and plots as they are displayed in the interface, and custom reports based on predefined templates. Generated plots include plots containing observed data, diagnostic plots, predictive checks and graphical representation of results. Each plot can be generated multiple times in the same report using different display settings. Generated tables include the results of the different analysis tasks run in Monolix and PKanalix. While plots in reports can use the same settings present in the interface, tables can incorporate display settings that are not accessible through the graphical user interface of the applications for more flexibility. It is also possible to display certain parts of report templates conditionally, if certain tasks have or have not been run. Results presented in the reports were consistent with the results available in the Monolix and PKanalix graphical user interface. In addition, reports were generated using the applications’ graphical interface and using command line and R connectors, with computational efficiency.
Conclusion: The new version of MonolixSuite provides features that facilitate Monolix and PKanalix workflows by shortening the time needed to generate reports that can be customized to meet the users’ needs.
References:
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