# pkpdutils

> Pharmacokinetic and pharmacodynamic analysis of timecourses and parameters: non-compartmental analysis, curve fitting, uncertainty, significance tests, bioequivalence, drug-drug interactions and meta-analysis

The links below point to the markdown source of the documentation. [llms-full.txt](https://matthiaskoenig.github.io/pkpdutils/llms-full.txt) contains all of it in a single file.

## Documentation

- [Home](https://matthiaskoenig.github.io/pkpdutils/index.md): `pkpdutils` is a python library for the pharmacokinetic (PK) and pharmacodynamic (PD) analysis of timecourses and parameters.
- [Installation](https://matthiaskoenig.github.io/pkpdutils/installation.md): `pkpdutils` requires python >= 3.13 and is available from pypi.
- [Workflows](https://matthiaskoenig.github.io/pkpdutils/workflows.md): Five walk-throughs from the data of a study to the table and the figure a report prints.
- [References](https://matthiaskoenig.github.io/pkpdutils/references.md): `pkpdutils` implements the standard methods of pharmacokinetic data analysis.
- [Contributing](https://matthiaskoenig.github.io/pkpdutils/development.md): Contributions are welcome.

## User guide

- [Timecourses](https://matthiaskoenig.github.io/pkpdutils/timecourses.md): A pharmacokinetic timecourse is the concentration of a substance in a tissue over time after a dose; a pharmacodynamic timecourse is an effect over time.
- [Data formats](https://matthiaskoenig.github.io/pkpdutils/formats.md): Pharmacokinetic data is exchanged as tables, not as `Timecourse` objects, and the field uses a handful of table layouts: the event record of NONMEM and Monolix, the two tables of PKNCA, and the CDISC ADaM ADNCA dataset.
- [Non-compartmental analysis](https://matthiaskoenig.github.io/pkpdutils/nca.md): Non-compartmental analysis (NCA) describes a concentration timecourse by parameters computed directly from the measured points, without a model of the body: the exposure as the area under the curve, the peak, the terminal half-life, and, with the dose, the clearance and the volume of distribution.
- [Uncertainty](https://matthiaskoenig.github.io/pkpdutils/uncertainty.md): Published pharmacokinetic data are mostly group data[^bailer][^nedelman]: the mean concentration of a group at every sampling time with its standard deviation or standard error and the number of subjects.
- [Urinary excretion](https://matthiaskoenig.github.io/pkpdutils/urine.md): A urine study does not sample a concentration over time.
- [Sparse sampling](https://matthiaskoenig.github.io/pkpdutils/sparse.md): A preclinical study rarely samples one animal repeatedly: the animal is sacrificed for its sample (a destructive design, one sample per animal) or contributes a few samples out of the schedule (a batch design).
- [Curve fitting](https://matthiaskoenig.github.io/pkpdutils/fitting.md): Non-compartmental analysis reads parameters from the observed points; some questions need a curve through them: the rate constants of the phases of a decline, the absorption rate of an oral curve, the concentration of half-maximal effect, whether the exposure grows in proportion to the dose, how a clearance scales with body weight.
- [Pharmacodynamics](https://matthiaskoenig.github.io/pkpdutils/pd.md): A pharmacodynamic timecourse measures an effect over time, a concentration-effect relationship measures the effect against the concentration.
- [Statistics](https://matthiaskoenig.github.io/pkpdutils/statistics.md): Statistics on pharmacokinetic parameters: comparisons of two groups, geometric mean ratios, average bioequivalence, the classification of drug-drug interactions and the meta-analysis of published studies.
- [Bioequivalence](https://matthiaskoenig.github.io/pkpdutils/bioequivalence.md): Two formulations of the same drug are bioequivalent when they deliver the same exposure to the systemic circulation.
- [Drug-drug interactions](https://matthiaskoenig.github.io/pkpdutils/ddi.md): A drug-drug interaction study gives a substrate alone and together with a perpetrator and reads the change of the exposure.
- [Reporting](https://matthiaskoenig.github.io/pkpdutils/reporting.md): An analysis of `pkpdutils` ends in data frames and figures.
- [Plotting](https://matthiaskoenig.github.io/pkpdutils/plotting.md): The figures of `pkpdutils.plot` are matplotlib figures.
- [Units](https://matthiaskoenig.github.io/pkpdutils/units.md): Every timecourse and every result of `pkpdutils` carries its units.
- [Gallery](https://matthiaskoenig.github.io/pkpdutils/gallery.md): Every figure of this page is written by one of the examples of the repository.
- [Glossary](https://matthiaskoenig.github.io/pkpdutils/glossary.md): The names used for the variables of the result datasets, with their symbols and the page that defines them.
- [Validation](https://matthiaskoenig.github.io/pkpdutils/validation.md): `pkpdutils` computes the same non-compartmental parameters that Phoenix WinNonlin, PKNCA, NonCompart and PKanalix compute, and an analysis is only worth as much as the evidence that it agrees with them.

## API reference

- [Overview](https://matthiaskoenig.github.io/pkpdutils/api/index.md): The API reference is generated from the docstrings of the package.
- [units](https://matthiaskoenig.github.io/pkpdutils/api/units.md): Units of the package.
- [timecourse](https://matthiaskoenig.github.io/pkpdutils/api/timecourse.md): Timecourses, doses and dosing protocols.
- [result](https://matthiaskoenig.github.io/pkpdutils/api/result.md): Shared container of parameter results (`NCAResult`, `FitResult`): an `xarray.Dataset` over sample dimensions, units per variable, an integer `flags` variable, quantities, data frames and summaries.
- [report](https://matthiaskoenig.github.io/pkpdutils/api/report.md): The study report: the tables and the figures of an analysis in one document.
- [io](https://matthiaskoenig.github.io/pkpdutils/api/io.md): Exchange formats of pharmacokinetic data.
- [cdisc](https://matthiaskoenig.github.io/pkpdutils/api/cdisc.md): CDISC map of the parameters: `PKPARMCD` codes, `PKUNIT` spellings and the `PP` domain.
- [parallel](https://matthiaskoenig.github.io/pkpdutils/api/parallel.md): The shared worker pools of the analyses.
- [console](https://matthiaskoenig.github.io/pkpdutils/api/console.md): Shared rich console.
- [log](https://matthiaskoenig.github.io/pkpdutils/api/log.md): Logging of the package.
- [nca](https://matthiaskoenig.github.io/pkpdutils/api/nca.md): The non-compartmental analysis.
- [options](https://matthiaskoenig.github.io/pkpdutils/api/nca.options.md): Options and flags of the non-compartmental analysis.
- [result](https://matthiaskoenig.github.io/pkpdutils/api/nca.result.md): Units of the parameters and the result container of the NCA.
- [auc](https://matthiaskoenig.github.io/pkpdutils/api/nca.auc.md): Vectorized trapezoid areas of timecourses.
- [terminal](https://matthiaskoenig.github.io/pkpdutils/api/nca.terminal.md): Vectorized terminal phase regression.
- [intervals](https://matthiaskoenig.github.io/pkpdutils/api/nca.intervals.md): Parameters of the single dosing intervals of a multiple dose timecourse.
- [steady_state](https://matthiaskoenig.github.io/pkpdutils/api/nca.steady_state.md): Steady state parameters of the last dosing interval and superposition.
- [uncertainty](https://matthiaskoenig.github.io/pkpdutils/api/nca.uncertainty.md): Uncertainty of the NCA parameters of group timecourses.
- [report](https://matthiaskoenig.github.io/pkpdutils/api/nca.report.md): The tables and the methods sentence of a regulatory report.
- [urine](https://matthiaskoenig.github.io/pkpdutils/api/nca.urine.md): Non-compartmental analysis of urinary excretion data.
- [sparse](https://matthiaskoenig.github.io/pkpdutils/api/nca.sparse.md): Non-compartmental analysis of sparse and destructive sampling designs.
- [tss](https://matthiaskoenig.github.io/pkpdutils/api/nca.tss.md): Time to steady state from the trough concentrations of the dosing intervals.
- [bioavailability](https://matthiaskoenig.github.io/pkpdutils/api/nca.bioavailability.md): Absolute and relative bioavailability from two non-compartmental analyses.
- [analytes](https://matthiaskoenig.github.io/pkpdutils/api/nca.analytes.md): Several analytes in one analysis: the metabolite to parent ratio.
- [fit](https://matthiaskoenig.github.io/pkpdutils/api/fit.md): The fitting engine.
- [models](https://matthiaskoenig.github.io/pkpdutils/api/fit.models.md): Exponential models of concentration timecourses.
- [compare](https://matthiaskoenig.github.io/pkpdutils/api/fit.compare.md): Comparison of models by the corrected Akaike information criterion.
- [proportionality](https://matthiaskoenig.github.io/pkpdutils/api/fit.proportionality.md): Dose proportionality by the power model and the confidence interval criterion.
- [stats](https://matthiaskoenig.github.io/pkpdutils/api/stats.md): Parameter samples: individual values or summary statistics, on the linear or the log scale.
- [bioequivalence](https://matthiaskoenig.github.io/pkpdutils/api/stats.bioequivalence.md): Average bioequivalence: the two one-sided tests on the geometric mean ratio.
- [power](https://matthiaskoenig.github.io/pkpdutils/api/stats.power.md): Power and sample size of the two one-sided tests procedure.
- [ddi](https://matthiaskoenig.github.io/pkpdutils/api/stats.ddi.md): Classification of drug-drug interactions by the change of the exposure, and its publication table.
- [meta](https://matthiaskoenig.github.io/pkpdutils/api/stats.meta.md): Meta-analysis of a parameter over studies: effect sizes, fixed effect and random effects pooling.
- [plot](https://matthiaskoenig.github.io/pkpdutils/api/plot.md): Style of the figures.

## Optional

- [Repository](https://github.com/matthiaskoenig/pkpdutils): source code, issues and releases.
- [Sitemap](https://matthiaskoenig.github.io/pkpdutils/sitemap.xml): all pages of the rendered site.
- [objects.inv](https://matthiaskoenig.github.io/pkpdutils/objects.inv): the API objects of the reference as a sphinx inventory.