openpkflow 0.1.2

Python-first toolkit for dissolution, NCA, PK/PD simulation, and pharmacometric reporting.

OpenPKFlow

A transparent, reproducible, open-source Python workflow for dissolution, NCA, PK/PD simulation, and pharmacometric reporting.

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What it does

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

• Dissolution similarity — f1, f2, bootstrap f2, model fitting
• NCA — AUC, Cmax, Tmax, half-life, CL/F, Vz/F (planned v0.4.0)
• PK simulation — 1- and 2-compartment models, oral/IV/infusion (planned v0.5.0)
• Report generation — Markdown, HTML, PDF, Word (planned v0.3.0)

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

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Install

pip install openpkflow

For report generation:

pip install openpkflow[reports]

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Quick start

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}")
print(f"f2 = {f2(reference, test):.2f}")

From a CSV file

from openpkflow.dissolution import DissolutionStudy

study = DissolutionStudy.from_csv("dissolution.csv")

result = study.compare(reference="reference", test="test")
result.summary()
result.report("dissolution_report.html")

CSV format

formulation,batch,time,percent_released
reference,R1,5,18.2
reference,R1,10,31.4
reference,R1,15,47.9
test,T1,5,17.5
test,T1,10,30.1
test,T1,15,46.2

CLI

openpkflow version
openpkflow similarity --reference "20,40,60,80" --test "21,39,61,79"

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Current status (v0.1.0)

Module	Status
dissolution.f1 / dissolution.f2	Stable
Dissolution CSV loader	Stable
Markdown + HTML report stub	Stable
CLI	Stable
Bootstrap f2	Planned v0.1.1
Dissolution model fitting	Planned v0.2.0
Full report generation	Planned v0.3.0
NCA	Planned v0.4.0
PK simulation	Planned v0.5.0
Population PK	Planned v0.6.0
Bayesian PK	Planned v0.8.0
ML / neural ODE	Planned v0.9.0

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Validation

All formula implementations are validated against:

• Published FDA/EMA guidance examples
• R package reference outputs (PKNCA, bootf2)
• Manual Excel calculations

Validation test cases cite their sources. See tests/ for details.

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Disclaimer

This software is for research and decision-support workflows. Final regulatory interpretation should be reviewed by qualified formulation, pharmacokinetic, and regulatory experts.

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Contributing

Issues and PRs welcome at https://github.com/priyamthakar/openpkflow/issues

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Citation

If you use OpenPKFlow in research, please cite:

Thakar, P. (2026). OpenPKFlow: Python-first pharmacometrics and dissolution toolkit.
https://github.com/priyamthakar/openpkflow

License

MIT — see LICENSE