Setting up nonmem2rx for your model | Pointing nonmem2rx at the input data | General linear models (ADVAN5/ADVAN7) | Technical details about reading NONMEM to rxode2

General | Specific Drugs | DDMoRe

Introduction to nlmixr2targets | Initial conditions | Running one model with one dataset (tar_nlmixr()) | Running multiple models with one dataset (tar_nlmixr_multimodel()) | Model piping for multiple models estimated with one dataset | Continuing the pipeline when a model fails

What triggers a re-fit? | Examples of common edits | Inspecting and pruning the indirect cache | tar_outdated() is a quick way to preview what would rerun

Two forms accepted inside nlmixr2targets | What tar_nlmixr() does behind the scenes | Pipe forms | Known limitation: env functions never routed through tar_nlmixr() | Summary

Why a dedicated multimodel factory? | Minimal comparison plan | Extracting parameter estimates across models | Within-list piping for nested edits | Tips for large model libraries

Model library conventions within nlmixr2lib | Compartment naming | Estimated parameter naming | Parameter naming | Multi-component clearance | Parent drug + metabolite parameters | Parameter transforms | Random effects | Covariate effects | Drug effects | Model files

Introduction | Creating rxode2 models | Syntax | Note | Example model | Example | Interface and data handling between R and the generated C code

Overview | Population and units | Source trace | Typical-value simulations | Single-dose profiles (100 mg SC) | Target and complex trajectories (1-cmt models) | Repeated SC dosing — drug-concentration difference across structures | Regime-convergence check | Assumptions and deviations

Create your dataset | Create your model | Fit the model | Simulate your data | Summarize the simulations

Model and source | Population | Source trace | Virtual cohort | Simulation | Replicate published figures | Figure 1 / 3 — typical IV vs SC profiles | VPC-style percentile bands | PKNCA validation | Comparison against published NCA | Assumptions and deviations

Abstract | Provenance of the R optim::L-BFGS-B and related solvers | Functions in package lbfgsb3c | Candlestick function | Extended Rosenbrock function (from funconstrain) | Using compiled function code | References

Motivation | Creating lists of matrices with attached properties | Combining symmetric named matrices

Construct symbolic expressions | Create symbol x from a string. | Parse an expression from a string | Manipulating symbolic expressions | Expand an expression | Substitute variables | Compute derivatives | Solve a polynomial equation | Construct vector and matrix | Construct a vector with c | Construct a vector with Vector | Construct a symbolic matrix with Matrix | Construct a symbolic matrix with rbind | Numerically evaluate symbolic expressions | Print Latex in Rmarkdown document