Drug effects can vary considerably between patients and occasions. Pharmacometrics is the field where models based on biology, pharmacology, disease and physiology are used to describe and quantitate the interaction between drug and patient. Simulation based on these models help in understanding disease processes, deciding on dosing strategies, improving therapy with existing drugs, and designing studies of new drugs.

PsN ('Perl-speaks-NONMEM') is an open source pharmacometrics software, developed at Uppsala university. It is used by all major pharmaceutical companies, in combination with the commercial software (NONMEM). The proposed project concerns adding new functionality, handling of time-to-event data, to the Visual Predictive Check (VPC) module of PsN. VPC is a popular method used to check the validity of models.

A common type of pharmacometrics model is a system of ordinary differential equations, where the parameters vary between individuals and occasions. Parameter variation is described by mean values and variances, which are obtained by fitting to the available data. The principle of a VPC is to simulate a large number of datasets based on an existing model, and then to compare the distribution of the simulated datasets to the real data. The VPC module of PsN cannot at present handle time-to-event data, for example time to normal heart-rate after drug administration at atrial fibrillation. The tasks of the proposed project include simulation of time-to-event data using NONMEM, translating the simulated data into Kaplan-Meier curves, computing the parameters necessary for a visual presentation of the simulated distribution, and automating all these steps in PsN.