feat: add BestDose optimization by Siel · Pull Request #293 · LAPKB/Pmetrics

Siel · 2026-02-12T09:10:21Z

Port BestDose from Pmetrics_rust#bestdose. Adds PM_bestdose/PM_bestdose_problem R6 classes, Rust backend, example data, and docs. Bumps pmcore to 0.22.1.

Add BestDose dose optimization feature ported from Pmetrics_rust bestdose branch: - R/PM_bestdose.R: PM_bestdose and PM_bestdose_problem R6 classes for Bayesian dose optimization with support for concentration and AUC targets - src/rust/src/bestdose_executor.rs: Rust backend for BestDose optimization using pmcore's BestDoseProblem with ODE model support - Updated lib.rs with bestdose, bestdose_prepare, bestdose_optimize exports - Updated extendr-wrappers.R with R-side wrapper functions - Updated NAMESPACE with PM_bestdose, PM_bestdose_problem, bestdose exports - Bumped pmcore dependency from 0.21.1 to 0.22.1 (required for bestdose) - Added libloading dependency for dynamic model loading - Added bestdose example data (past, prior, target CSVs) and test script - Fixed executor.rs mutability issue for pmcore 0.22.1 compatibility

Copilot

Pull request overview

Adds BestDose dose-optimization support to the Pmetrics R package by introducing new R6 interfaces and wiring them to a Rust backend (ported from Pmetrics_rust#bestdose), along with docs and example inputs. This also bumps the Rust pmcore dependency to enable the new capability.

Changes:

Add Rust BestDose executor + extendr exports (bestdose, plus a prepare/optimize handle workflow).
Add R6 classes PM_bestdose / PM_bestdose_problem and R wrappers to drive the Rust backend.
Add roxygen-generated man pages and example CSV/script assets; bump pmcore to 0.22.1 and add libloading.

Reviewed changes

Copilot reviewed 14 out of 16 changed files in this pull request and generated 7 comments.

Show a summary per file

File	Description
src/rust/src/lib.rs	Adds BestDose-related extendr exports and module wiring.
src/rust/src/executor.rs	Minor adjustment to fit result mutability.
src/rust/src/bestdose_executor.rs	New Rust implementation for BestDose prepare/optimize and R conversions.
src/rust/Cargo.toml	Bumps `pmcore` to `0.22.1` and adds `libloading`.
Cargo.lock	Lockfile updates from dependency bump/additions.
R/extendr-wrappers.R	Adds R-level `.Call()` wrappers for BestDose functions.
R/PM_bestdose.R	New R6 classes and helpers for BestDose workflows.
NAMESPACE	Exports new R6 classes and `bestdose`.
man/bestdose.Rd	New generated documentation for `bestdose()`.
man/PM_bestdose.Rd	New generated documentation for `PM_bestdose`.
man/PM_bestdose_problem.Rd	New generated documentation for `PM_bestdose_problem`.
inst/Examples/src/bestdose_*.csv	Example prior/past/target datasets.
inst/Examples/Rscript/bestdose_simple_test.R	Example script demonstrating reusable problem workflow.
.gitignore	Ensures example assets and example test scripts are not ignored.

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Copilot · 2026-02-12T09:17:48Z

src/rust/src/bestdose_executor.rs

+        Self {
+            id: id.to_string(),
+            time: pred.time(),
+            observed: pred.obs().unwrap_or(0.0),
+            pop_mean: pred.pop_mean(),
+            pop_median: pred.pop_median(),


observed is set to 0.0 when the prediction has no observation (pred.obs() is None). This will silently turn missing observations into real zeros in the returned data.frame. Prefer representing missing as NA by changing the field type (e.g., Option<f64>/Rfloat) and passing through pred.obs() without coercion.

Copilot · 2026-02-12T09:17:49Z

src/rust/src/bestdose_executor.rs

+    let pred_rows: Vec<BestDosePredictionRow> = result
+        .predictions()
+        .predictions()
+        .iter()
+        .map(|p| BestDosePredictionRow::from_np_prediction(p, "subject_1"))
+        .collect();


The predictions data.frame hardcodes id to "subject_1" for all rows. This will mislabel results when the subject id is not exactly that string, and makes multi-subject extensions harder. Thread the actual subject id through from the problem/result (or at least use the target_data subject id used to build the problem) when constructing BestDosePredictionRows.

Copilot · 2026-02-12T09:17:49Z

R/extendr-wrappers.R


+#' Run BestDose optimization to find optimal doses
+#'@export
+bestdose <- function(model_path, prior_path, past_data_path, target_data_path, time_offset, dose_min, dose_max, bias_weight, target_type, params, kind) .Call(wrap__bestdose, model_path, prior_path, past_data_path, target_data_path, time_offset, dose_min, dose_max, bias_weight, target_type, params, kind)


bestdose() is exported to users, but the Rust backend returns errors as a character string (not an R error). The wrapper also does no is.character()/cli_abort() check, so failures may look like successful returns. Either make the Rust function return Result<...> so extendr raises an R error, or add an error check in the R wrapper and cli::cli_abort() when a character error is returned.

Suggested change

bestdose <- function(model_path, prior_path, past_data_path, target_data_path, time_offset, dose_min, dose_max, bias_weight, target_type, params, kind) .Call(wrap__bestdose, model_path, prior_path, past_data_path, target_data_path, time_offset, dose_min, dose_max, bias_weight, target_type, params, kind)

bestdose <- function(model_path, prior_path, past_data_path, target_data_path, time_offset, dose_min, dose_max, bias_weight, target_type, params, kind) {

res <- .Call(

wrap__bestdose,

model_path,

prior_path,

past_data_path,

target_data_path,

time_offset,

dose_min,

dose_max,

bias_weight,

target_type,

params,

kind

)

if (is.character(res)) {

cli::cli_abort(res)

}

res

}

Copilot · 2026-02-12T09:17:49Z

R/PM_bestdose.R

+                model_for_settings <- if (!is.null(model_info$model)) model_info$model else model
+                settings <- bestdose_default_settings(prior, model_for_settings)


When model is provided as a compiled model path (character), bestdose_parse_model() sets model_info$model <- NULL, but if settings is also NULL this code will pass a character string into bestdose_default_settings(), which expects a PM_model and will error. Either require settings when model is a path, or implement a way to derive default ranges/settings from the compiled model metadata.

Suggested change

model_for_settings <- if (!is.null(model_info$model)) model_info$model else model

settings <- bestdose_default_settings(prior, model_for_settings)

if (is.null(model_info$model)) {

cli::cli_abort(

"When 'model' is provided as a compiled model path, 'settings' must be supplied explicitly."

)

}

settings <- bestdose_default_settings(prior, model_info$model)

Copilot · 2026-02-12T09:17:50Z

R/PM_bestdose.R

+            self$model_info <- model_info
+            self$settings <- settings
+
+            cli::cli_alert_success("BestDose problem prepared with %d support points", dim[1])


cli::cli_alert_success() uses glue-style interpolation, not printf-style formatting. As written, "%d" will be printed literally. Use glue syntax (e.g., "... {dim[1]} ...") or pass a named argument for interpolation.

Suggested change

cli::cli_alert_success("BestDose problem prepared with %d support points", dim[1])

cli::cli_alert_success(

"BestDose problem prepared with {n_support} support points",

n_support = dim[1]

)

Copilot · 2026-02-12T09:17:50Z

R/PM_bestdose.R

+#' @export
+PM_bestdose_problem <- R6::R6Class(


New exported user-facing functionality (PM_bestdose, PM_bestdose_problem, and bestdose) is introduced without any testthat coverage. Since this repo already uses testthat, add at least basic tests for argument validation/error paths and (if feasible) a small end-to-end smoke test using the included example data (or a skipped test when compilation/runtime prerequisites aren’t available).

Copilot · 2026-02-12T09:17:50Z

src/rust/src/bestdose_executor.rs

+        let (library, (eq, meta)) =
+            unsafe { pmcore::prelude::pharmsol::exa::load::load::<ODE>(model_path) };
+
+        let settings = settings(params, meta.get_params(), "/tmp/bestdose")
+            .map_err(|e| format!("Failed to parse settings: {}", e))?;
+


settings(params, meta.get_params(), "/tmp/bestdose") hardcodes a Unix-specific path and reuses the same directory across runs. This can break on Windows and can cause collisions when multiple BestDose problems are prepared concurrently. Use a per-run temp directory (e.g., std::env::temp_dir() + unique subdir) or accept an output/log directory from R and pass it through here.

Siel added 2 commits February 12, 2026 09:03

fix: use devtools::load_all() in bestdose example script

04f741b

Copilot AI review requested due to automatic review settings February 12, 2026 09:10

Copilot started reviewing on behalf of Siel February 12, 2026 09:10 View session

Copilot AI reviewed Feb 12, 2026

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feat: add BestDose optimization#293

feat: add BestDose optimization#293
Siel wants to merge 2 commits intomainfrom
bestdose

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		model_for_settings <- if (!is.null(model_info$model)) model_info$model else model
		settings <- bestdose_default_settings(prior, model_for_settings)

-                model_for_settings <- if (!is.null(model_info$model)) model_info$model else model
-                settings <- bestdose_default_settings(prior, model_for_settings)
+                if (is.null(model_info$model)) {
+                    cli::cli_abort(
+                        "When 'model' is provided as a compiled model path, 'settings' must be supplied explicitly."
+                    )
+                }
+                settings <- bestdose_default_settings(prior, model_info$model)

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Pull request overview

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