Simulo – a platform for advanced model based simulations using R
Quentin Leirens (1), Ruben Faelens (1), Per Olsson Gisleskog (1), Andreas Lindauer (1), Daniel Rӧshammar (1)
(1) SGS Exprimo NV, Mechelen, Belgium
Objectives: Clinical trial simulation is a powerful tool in the optimization of study designs and for making model-based inference. However, including all various aspects of the model, the target population and the experimental design may be complex and time-consuming. Adequate post-processing, integration and visualisation of the simulated data, needed to convince decision-makers, is not always a trivial task. Simulo was developed to offer a clear framework and user-friendly interface with the ability to simulate and visualise the likely outcome of clinical studies or dosing scenarios, using public or custom-developed nonlinear mixed-effects models.
Methods: Simulo is a Java-based application running on an R backend with a graphical user interface. Simulations are performed after automatic translation of a user defined model and study protocol to R code, followed by efficient execution of the code. The model can be described through algebraic, ordinary and/or delayed differential equations. Model parameters can include different levels of uncertainty and variability. Inclusion criteria, treatments (route of administration, dosing schedule), observations (type and sampling schedule) and study designs are easily defined. If and whenever desired, the user may directly modify the R code and include various R-packages as fit for purpose. Moreover, the resulting simulation code may always be executed outside of Simulo in any standard R environment.
Results: Simulo comes in two versions. Simulo Light, a limited version, is offered for free to scientists who wants to illustrate the model based results from a single or few simulation replicates, to familiarize with the strengths of simulation and for training purposes. Simulo Expert is the full version, recommended for intensive simulation projects where models are used to more thoroughly address key questions in project work. Any empirical or advanced PK/PD and disease model may be applied in simulation scenarios of all complexities. Recent applications of Simulo showed how simulations can help in predicting the effect of dose adaptation on clinical endpoints as well in comparing different study designs and data analysis approaches.
Conclusions: Simulo offers a platform for all sorts of model-based simulation activities, both for experienced and non-technical users. Simulo can facilitate both internal and regulatory decision making in a clear and visually attractive way.