A comprehensive Quarto book documenting the PKNCA R package (≥ 0.12.2) with runnable examples throughout. Every function, option, and parameter is verified against live PKNCA output.
Live book: https://teunp.github.io/PKNCA.doc/
Intended home (pending org setup): https://humanpred.github.io/pknca-book/
# Install PKNCA 0.12.2
remotes::install_github("humanpred/pknca")git clone https://github.com/TeunP/PKNCA.doc
cd PKNCA.doc
quarto render
open _book/index.html| Chapter | Topics |
|---|---|
| Workflow | PKNCAconc → PKNCAdose → PKNCAdata → pk.nca; all 21 options with defaults |
| Interval selection & parameter catalogue | Interval data frame structure; group matching; all 143 calculable parameters |
| AUC types & integration methods | auclast/aucall/aucinf; partial AUC; lin up/log down vs linear vs lin-log; aucabove; time_above; AUMC; cav.int |
| Half-life & terminal phase | Curve stripping; adj.r.squared.factor; quality filters; Tobit regression; lambda.z.corrxy |
| Extravascular (oral/SC) | BLQ handling; imputation strategies; tmin; lag time; multiple peaks |
| Intravascular (IV) | IV bolus NCA; C0 back-extrapolation; IV infusion with ceoi; MRT correction |
| Multiple-dose / steady-state | deg.fluc; swing; PTR; Cav; tau detection |
| Urine excretion | ae; fe; clr.; volpk; ermax/ertmax/ertlst; clr..dn |
| Sparse PK sampling | sparse_auclast + SE + df; sparse AUMC; mrt/cl/kel.sparse.last |
| Superposition | Predicting multiple-dose profiles from single-dose data |
| Time to steady state | pk.tss.monoexponential; pk.tss.stepwise.linear; pk.tss |
| Post-processing | exclude(); normalize(); 17 .dn parameters; PKNCA.set.summary; get_halflife_points |
| Units | pknca_units_table() S3 generic; PKNCAdata method; preferred units; conversions |
| Imputation | start_conc0; start_predose; start_cmin; custom imputation methods |
| Dose-aware interpolation | interp.extrap.conc.dose; .dose AUCint variants |
| Custom parameters | add.interval.col; registering new NCA parameters |
| Utility functions | geomean; geocv; clean.conc.*; assert_conc_time |
| Regulatory & CDISC | PP domain column mapping; exclude → PPEXCLFL; summary() for CSR tables |
| Validation & testing | testthat suite; version pinning; manual AUClast spot-check |
| Chapter | Topics |
|---|---|
| Function dependencies | Parameter dependency graph |
| Architecture | Internal structure of PKNCA |
- Tobit regression for half-life — handles BLQ terminal-phase observations via censored likelihood
normalize()/normalize_by_col()— normalize results by any column (body weight, BSA, etc.)tmin— time of minimum concentration;first.tminoption- Sparse AUMC (
sparse_aumclast, SE, df) and derived parameters (mrt.sparse.last,cl.sparse.last,kel.sparse.last) - New urine parameters:
volpk,ermax,ertmax,ertlst,clr.last.dn,clr.obs.dn,clr.pred.dn lambda.z.corrxy— correlation between time and log-concentration for the λz regression windowpknca_units_table()now an S3 generic with aPKNCAdatamethodallow_partial_missing_unitsoption
- PKNCA source: https://github.com/humanpred/pknca
- pkgdown reference: https://humanpred.github.io/pknca/reference/index.html
- CRAN: https://cran.r-project.org/package=PKNCA
- Discussion: humanpred/pknca#541
- Setup guide for org repo + hub site: BUILDING_SETUP.md