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OpenPKFlow

A transparent, reproducible, open-source Python workflow for dissolution, NCA, PK/PD simulation, and pharmacometric reporting, backed by executable reference and analytical tests with report-first documentation.

CI PyPI version Python License: MIT

What it does

OpenPKFlow gives formulation scientists, PK/PD researchers, and CRO/CDMO teams a clean Python workflow for:

Module What it covers
dissolution f1, f2, bootstrap f2, MSD, max deviation, model-dependent comparison, multi-media, SUPAC screening, alcohol dose-dumping f2, model fitting
nca AUClast, AUCinf, Cmax, Tmax, lambda_z, t1/2, CL/F, Vz/F — three AUC methods, explicit BLQ, %AUCextrap flag, C0 back-extrapolation, DN params, CDISC PP, plus model-informed sparse oral screening
be Paired 2x2 TOST, formal complete balanced TR/RT 2x2 ANOVA, power / sample size, research-grade replicate screening
bayes MAP individual PK (scipy), full Bayesian posterior (PyMC), Bayesian 2x2 crossover BE
pop FOCE-I and SAEM estimation (1/2-cmt; frozen for extension), GOF plots, VPC, NONMEM-style dataset helpers
sim 1- and 2-compartment IV bolus/infusion/oral, transit absorption, steady-state metrics, repeated dosing, superposition
ivivc Level A (Wagner-Nelson, Loo-Riegelman, convolution, Levy, %PE) plus Level B/C MDT/MRT helpers
pipeline Multi-stage study orchestration (dissolution + NCA + BE) with unified reports and reproducibility audit bundles
report Markdown, HTML, PDF (ReportLab), Word (python-docx)
ml Experimental torch MLP surrogate for 1-cmt oral profiles
validation Utility functions for cross-checking against reference values

It does not replace expert regulatory judgement or validated commercial platforms. It makes routine analysis faster, cleaner, and more reproducible.

What it is and is not

OpenPKFlow is a transparent Python toolkit for exploratory and reproducible pharmacometric workflows: dissolution comparison, NCA, simulation, bioequivalence screening, IVIVC, population PK diagnostics, and report generation.

OpenPKFlow is not a substitute for qualified regulatory judgement, validated commercial platforms, or jurisdiction-specific submission workflows. Research features, including replicate bioequivalence screening and validation-gated FDA RSABE, should be treated as decision-support until independently validated against the required SAS/R or agency-specific reference process.

Full scope language, pipeline focus, PopPK / RSABE validation boundaries, and validation links: Positioning.

Install

pip install openpkflow

For PDF and Word reports:

pip install openpkflow[reports]

For ML surrogate (torch):

pip install openpkflow[ml]

Quick example

from openpkflow.dissolution import f1, f2

reference = [20.0, 40.0, 60.0, 80.0, 90.0]
test      = [21.0, 39.0, 61.0, 79.0, 88.0]

print(f"f1 = {f1(reference, test):.2f}")   # 1.33
print(f"f2 = {f2(reference, test):.2f}")   # 72.80

See the Tutorials section for complete worked examples.

Documentation

  • Theory Guide — Full LaTeX formula derivations for every module
  • Migration Guide — WinNonlin / NONMEM / R quick-reference mapping
  • Tutorials — Step-by-step worked examples for supported analysis workflows
  • Validation Matrix — External comparators and executable reference tests
  • Validation API — Bias, RMSE, and percent-tolerance helper reference
  • API Reference — Function and class reference across public analysis modules

Philosophy

OpenPKFlow is report-first: every analysis ends in a clean, shareable output — HTML, PDF, or Word — suitable for supervisors, clients, CROs, and regulatory teams. Calculation correctness is necessary but not sufficient.

This package is open-source. Final regulatory interpretation should be reviewed by qualified formulation, pharmacokinetic, and regulatory experts.