Prerequisite | Define the concentration | Define an error model | Simulate the observed concentration | A couple of useful functions in action

Prerequisite | Retrieve your parameters | Access parameter values | Replace parameters | Delete parameters

Prerequisite | Load your base PK model | Load an effect-compartment model | Append PD model to PK model | Simulate our PK/PD model

Prerequisite | Create a minimalist model in the Notepad++ editor | Create the same model programmatically

Load example from model library | Write Campsis model | Read Campsis model | Export Campsis model to rxode2 | Export Campsis model to mrgsolve

Prerequisite | Equation | Ordinary differential equation (ODE) | Line break | Comment | If-statement | Additional remarks

Prerequisite | Create new compartment properties | Simulate our model | A couple of useful functions in action

Bioavailability implemented in model | Bioavailability implemented in dataset

Filgrastim PK/PD model

Add a body weight covariate into the model | Constant body weight | Fix body weight values (1/subject) | Uniform distribution | Normal distribution | Log-normal distribution | Bootstrap

Instantiate a dataset | Add a bolus | Add an infusion | Add observations | Export dataset | Add several arms

Library import | Load model | Create dataset | Simulate | Plot results | Simulate 2 arms | Going further

Infusion duration or rate implemented in model | Infusion duration or rate implemented in dataset

Init central compartment

Treatment IOV on KA

Dose adaptation based on Ctrough value

Lag time implemented in model | Lag time implemented in dataset

Direct-effect model | Effect-compartment model | Transit-compartment model | Indirect-response model

Track the simulation progress in an R script | Track the simulation progress in a targets project

Simulate uncertainty on percentiles

Base model and dataset | Run replicates in parallel | Run scenarios in parallel | Run slices in parallel | Setup plan with package future | Run Campsis in parallel within the pipeline tool targets

Simulate several protocols at once | Make a model parameter vary | Compare different distributions

Adapt the dose based on a covariate

Body weight as a time varying covariate

Simulate with all variabilities | Simulate without RUV | Simulate without RUV and IIV