PKanalix is a user-friendly and fast application
for compartmental analysis (CA) and

non-compartmental analysis (NCA)

Choose a Module:

Can we make NCA & CA intuitive, efficient, and integrated into the modeling & simulation workflow? PKanalix does the trick with:

  • A clear user-interface with a simple workflow to efficiently run the NCA and CA analysis.
  • Easily accessible PK models library and auto-initialization method to improve the convergence of the optimization of CA parameters.
  • Automatically generated results and plots to give an immediate feedback.
  • Interconnection with MonolixSuite application to export projects to Monolix for the population analysis.

Very intuitive interface & automatization via scripting

PKanalix can be used via a graphical interface to easily define settings and rules, check the calculations and display the results. It can also be used via R for powerful scripting.

Straightforward NCA

PKanalix calculates NCA parameters with industry-standard methods, and automatically generates a full set of plots to visualize the data, the distributions of calculated parameters and correlations with covariates.

Reliable and clear results

All results are available as tables and summaries, and as interactive plots for a fast and intuitive interpretation. All settings are saved in the project for reproducible results, and the integrated validation suite ensures correct installation and calculation.

Compartmental analysis & integration towards population modeling

Calculation of the parameters in the Compartmental Analysis framework is also proposed with a large library of PK models. In addition, it includes a direct link toward population modeling using Monolix.

What are we providing with PKanalix?

Data exploration

Perform a first quality-check of your data and get an overview of the full trial in a glimpse with automatically generated, interactive, fully customizable plots covering PK dynamics and relations between covariates.

Non Compartmental analysis of PK datasets

The first main feature of PKanalix is the calculation of the parameters in the Non Compartmental Analysis framework.

This task requires defining rules for the calculation of the λz(slope of the terminal elimination phase) to be able to compute the NCA parameters. This definition can be done either globally via rules (e.g adjusted R2 or time window) or on each individual where the user can choose or remove any point for the calculation.

Compartmental Analysis of PK datasets

The second main feature of PKanalix is the calculation of the parameters in the Compartmental Analysis framework. It consists in finding parameters of a PK model representing the kinetics in compartments for each individual. Automatic initialization is performed for a better convergence of each parameter for each individual.

This task defines a structural model (based on a user-friendly PK models library) and estimates the parameters for all the individuals. Automatic initialization method improves the convergence of parameters for each individual.

Outputs and plots

All NCA and/or CA outputs are displayed in sortable formatted tables easy to copy to any document, and exported in the result folder in an R-compatible format. Interactive plots are also generated for straightforward interpretation of the results.

R API to automate your process

All steps performed in PKanalix can be run from R with the LixoftConnectors package. What you have done once intuitively in the interface on a specific dataset can be generalized to a script automating the process for any other dataset.

Integration of your NCA/CA projects to the Modeling & Simulation & Trial Design workflow

Use the same data file for all your analyses – Data exploration, NCA, CA, Population Modeling. PKanalix alone does not include population analysis. However, exporting your PKanalix projects to Monolix will speed up your population modeling since it automatically sets everything you need in Monolix to run parameter estimation in a population modeling framework in a click: interpreted dataset, structural model, initial values do not need to be redefined. Importing formatted datasets from clinical trials simulated in Simulx is also possible to post-process your outputs and analyse trials with your favorite NCA parameters.

How is PKanalix being applied?

PKanalix has been widely used by pharmaceutical companies and academics to:

  • Fulfill regulatory submissions with reliable NCA parameters calculation, following all standards of regulatory agencies.
  • Analyse multiple candidate drugs in phase I to find the most promising ones.
  • Prepare future population modeling steps by checking the impact of covariates and dose on NCA parameters, and finding a first PK model to start with in the compartmental analysis.
  • Design the next clinical trial by post-processing their simulations in Simulx with their preferred NCA parameters.

Check our Video Tutorials to learn more!

What’s New in PKanalix 2020?

  • Filters of a dataset to easily perform the analysis on several data subsets without modifying the original file.
  • Module to select and scale output units for better analysis and reporting.
  • Flexibility: selection of NCA parameters for computation and display, stratification of results by categorical covariates and acceptance criteria for comparison, multiple partial AUC
  • More statistics of observed data in the plots.
  • More interface features: dark theme, font size, choice of significant digits

How do I move forward from here?

Request for a demo with PKanalix to support internal research projects and regulatory interactions.

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