Enhancement/Expansion of TLG Catalog

[h5hoang]

Issue

Closes #1343

Description

Expands the TLG catalog with new table, graph, and listing functions for PK reports, following the insightsengineering TLG catalog specifications.

New TLG functions (26 new entries in tlg.yaml):

• Tables (9): t_pkct01 (summary concentration table with 4 variants: by TRT, by dose, TAD, dose+TAD), t_pkpt03_col (summary PK parameters), t_pkpt03_MP_col (metabolite/parent ratios), t_pkpt07_norm (dose-normalized parameters), t_pkpt08_uri (urine amount/percent recovered), t_pkpt11_gmr (geometric mean ratio with CIs)
• Graphs (12): g_pkcg01/02/03_sbs (side-by-side concentration plots), p_pkcg03_lin/log/sbs_dose (mean concentration by dose), p_pkpg01_cum/per (urine recovery profiles), p_pkpg02_doseprop (dose-proportionality scatter with power-model regression), p_pkpg03_boxp / p_pkpg04_boxp (PK parameter boxplots), p_pkpg06_mp (metabolite/parent ratio boxplots)
• Listings (5): l_pkcl01_tad (concentration listing by TAD), l_pkcl02_uri (urine concentration listing), l_pkpl01 (individual PK parameters), l_pkpl01_mp (metabolite ratios), l_pkpl04_mp (treatment comparison)

Shared helpers (R/utils-tlg.R):

• split_and_apply — splits data by grouping variables and applies a function to each subset (used by all new TLG functions)
• filter_metabolite_rows — three-tier metabolite detection fallback (METABFL → PPCAT → PARAM)
• .summarise_adpp — descriptive statistics for PK parameter values (n, Mean, SD, CV%, GeoMean, GeoCV%, Median, Min, Max)
• .build_pkpp_table — deduplicates ADPP rows and applies summary statistics per stratum/parameter
• .get_var_label — label attribute lookup with column-name fallback

Shiny wiring improvements:

• Added type = "table" support to tlg_module_server / tlg_module_ui (tables render via reactable)
• ADPP data now flows from tab_nca_server → tab_tlg_server → modules via a dedicated adpp reactive, avoiding recomputation
• filter_tlg_excluded applied once at the tab_tlg boundary (not per-module), and extended to handle ADPP's PPSUMFL flag alongside ADNCA's PKSUM1F
• Fixed NA handling in filter_tlg_excluded — rows with NA in exclusion flag columns were silently dropped; now correctly preserved
• Replaced random module ID suffixes with deterministic IDs + a registration environment to prevent duplicate Shiny observer accumulation on re-submit
• Extracted .build_tlg_panels helper to eliminate copy-paste across table/graph/listing renderUI blocks

Other changes:

• export_cdisc: carries DOSEA/DOSEU columns through to ADPP for dose-proportionality TLGs
• Fixed g_pkcg02_sbs YAML entry pointing to g_pkcg02_log instead of g_pkcg02_sbs
• Removed stray print(tlg_order()) debug statement in tab_tlg.R

Definition of Done

• List of proposed new TLGs discussed and agreed
• New graph functions implemented and registered in tlg.yaml
• New table functions implemented and registered in tlg.yaml
• Each new function has unit tests
• All new TLGs render correctly in the app

How to test

1. Run NCA on a dataset that includes multiple treatment arms and at least one analyte
2. Navigate to the TLG tab, the new Tables sub-tab should be functional (previously a placeholder)
3. Submit the default TLG selection and verify tables render as reactable widgets with pagination
4. Enable non-default entries (dose-proportionality, urine, GMR, boxplots) and verify they render without error
5. For ADPP-based TLGs: confirm that data reflects the NCA results (not stale or recomputed)
6. Re-submit the TLG order multiple times, verify no duplicate observer accumulation (pagination buttons should fire exactly once per click)
7. For urine TLGs (t_pkpt08_uri, p_pkpg01_cum/per, l_pkcl02_uri): test with a dataset containing urine specimens; verify the condition: "URINE" auto-selects these entries when urine data is present (don't forget to click urine in NCA set-up tab like me :'))

Contributor checklist

• Code passes lintr checks
• Code passes all unit tests
• New logic covered by unit tests
• New logic is documented
• App or package changes are reflected in NEWS
• Package version is incremented
• R script works with the new implementation (if applicable)
• Settings upload works with the new implementation (if applicable)
• If any .scss change was done, run data-raw/compile_css.R
• If a package dependency was added/changed, run data-raw/test_suggests_hidden.R

Notes to reviewer

• All new graph functions use direct ggplot2 (no tern dependency), per Enhancement: Remove tern dependency from TLG plots #1319.
• The t_pkct01 summary function has its own .summarise_group rather than reusing .summarise_adpp. This is intentional because concentration tables have BLQ-specific semantics (BLQ counting, different n definition that includes BLQ subjects) that don't map cleanly to the ADPP helper.
• The condition auto-selection for ADPP-based TLGs (e.g. t_pkpt08_uri with condition: "URINE") evaluates against ADNCA's PCSPEC column, not ADPP's PPSPEC. This works in practice (if ADNCA has urine specimens, ADPP should too) but could be tightened in a follow-up if needed.
• The DOSEA column is now carried through export_cdisc for dose-proportionality graphs (p_pkpg02_doseprop, p_pkcg03_*_dose). If DOSEA is absent from the source data, these TLGs will show an error message at render time (caught by tryCatch in tlg_module_server). They are all is_default: false so they won't be pre-selected.

[KOBANAK]

Hi, thanks for all the work on this.

I wanted to share a few observations regarding the summary tables so far.
These are mostly around ordering and presentation.
I confirm the tables render as reactable widgets and pagination works.

• When a table is split by parameter and specimen (PARAM × PCSPEC), the resulting tables are stacked without a title, so it's not immediately clear which analyte/specimen each one corresponds to. It would be really helpful to display the group as a header above each table.

• Looking at the PK Summary Conc by TRT for example, the tables should be organized by TRT01A, then by ordered ATPTREF and NFRLT, so that all rows for a given treatment arm are grouped together. At the moment the same TRT01A values reappear further down the table. Grouping each arm with its timepoints ordered would make the table much easier to read.

• It would be great to have readable labels for the statistic columns instead of the programming names ( GeoMean → "Geometric Mean", GeoCV_pct → "Geometric CV%", CV_pct → "CV%" etc..).

I'll continue going through the rest and follow up with anything else I find.
Thanks again :)

[Gero1999]

hey @h5hoang if possible give a look to @KOBANAK feedback. Feel free to also keep the discussion thread if you feel that something is not worthy or better for later. I will try to give a look to this later today as well

[Gero1999]

suggestion: The expected value is URINE based on CDISC, but you can be more protective than this:

Suggested change

	urine_specs = c("URINE", "Urine"),
	listgroup_vars = c("PARAM", "PCSPEC"),
	displaying_vars = NULL,
	...
	) {
	if ("PCSPEC" %in% names(data)) {
	data <- data[data$PCSPEC %in% urine_specs, , drop = FALSE]
	urine_specs = c("URINE"),
	listgroup_vars = c("PARAM", "PCSPEC"),
	displaying_vars = NULL,
	...
	) {
	if ("PCSPEC" %in% names(data)) {
	data <- data[toupper(data$PCSPEC) %in% urine_specs, , drop = FALSE]

[h5hoang]

Thank you both for the feedback! I really appreciate it a lot 😄

I've addressed everything raised from the urine specimen filters now matching case-insensitively to making the summary tables more readable (split tables show a group header, rows are grouped by treatment arm and ordered by timepoint, and the statistic columns now use readable labels instead of the raw names). I've also added in new unit tests to cover these changes as well

please let me know if there are any other changes/feedback you guys might have! thanks!!