Check initial fixed effects
When clicking on the “Check the initial fixed effects”, the simulations obtained with the initial population fixed effects values are displayed for each individual together with the data points, in case of continuous observations. This feature is very useful to find some “good” initial values. Although Monolix is quite robust with respect to initial parameter values, good initial estimates speed up the estimation. You can change the values of the parameters on the bottom of the screen and see how the agreement with the data change. In addition, you can change the axis to log-scale and choose the same limit on all axis to have a better comparison of the individuals. When you are confident with the initial values, you can click on the green “SET AS INITIAL VALUES” button on the top of the frame.
In addition, if you think that there are not enough points for the prediction (if there are a lot of doses for example), you can change the discretization and increase the number of points as displayed in the blue box of the figure.
Starting from the 2019 version, it is possible to add a reference and thus change a parameter to see the impact of the variation of this parameter. In this example, we click on reference to use the current fit as reference and change V2 from 1 to 5 as can be seen on the following figure.
The solid red curve corresponds to the current curve and the dashed one corresponds to the reference. At any time, you can change the reference to use the current fit, restore and delete the reference by clicking on the grey button “REFERENCE” on the top of the frame.
Automatic initialization of the parameters of the PK library
Starting from the 2019 version, in case of a model from the PK library, an auto-init button appears on the top right of the frame as shown below
By clicking on this button, Monolix will compute initial population parameters that best fit the data points. The computation is the combination of both empirical rules from practical experience and optimization. The purpose is not to find a perfect match but rather to have all the parameters in the good range for starting the population modeling approach.
After clicking on the button, the population parameters are updated and the corresponding fit is displayed. To use these parameters as initial estimates, you need to click on on the top right of the frame on the button “SET AS INITIAL VALUES”.
Note that the auto-init procedure takes into account the current initial values. Therefore, in the few cases where the auto-init might give poor results, it is possible to improve the results by changing manually the parameter values before running the auto-init again.