2 Introduction

Thank you for your interest in Pmetrics! This online book provides instructions and examples to assist users of the Pmetrics R package, by the Laboratory of Applied Pharmacokinetics and Bioinformatics at the Saban Research Institute, Children’s Hospital Los Angeles, and the Department of Pediatrics, Keck School of Medicine, University of Southern California. Please see our website at http://www.lapk.org for more information.

2.1 What is Pmetrics?

Pmetrics is a population modeling and simulation package for R. It can model data using nonparametric and parametric approaches. Some excellent articles discussing the differences, strengths, and limitations of both approaches are: Goutelle, Woillard, Neely, et al. (2022), Goutelle, Woillard, Buclin, et al. (2022), Guidi, Csajka, and Buclin (2022).

2.2 Disclaimer

You, the user, assume all responsibility for acting on the results obtained from Pmetrics. The Laboratory of Applied Pharmacokinetics and Bioinformatics (LAPKB), members and consultants to LAPKB, and Children’s Hospital Los Angeles and the University of Southern California and their employees assume no liability whatsoever. Your use of the package

2.3 What This Guide Is Not

We assume that the user has familiarity with population modeling and R, and thus this manual is not a tutorial for basic concepts and techniques in either domain. We have tried to make the R code simple, regular and well documented. A very good free online resource for learning the basics of R can be found at Stat Methods. However, there are a number of other free or low-cost online resources which you can find with a simple or AI-assisted web search.

We recognize that initial use of a new software package can be complex, so please feel free to contact us at any time, preferably through the Pmetrics Disussions. You can report issues online as well.

This manual is also not intended to be a theoretical treatise on the algorithms Pmetrics uses. For that, the user is directed to our website.

2.4 How do I get Pmetrics?

It’s easy and all free!

Pmetrics and all required components will run under MacOS (Unix), Windows, and Linux. Instructions on obtaining and installing the package are in the README section of our source code repository in GitHub.

2.5 How do I start using Pmetrics?

Note

After installing Pmetrics, run the following code in your R console. This will set up the necessary files and directories to work through examples in this book.

library(Pmetrics)
PM_tutorial()

PM_tutorial() will install a Learn folder at your chosen location. Together with this book, it will get you started building and simulating from population models. All functions are extensively documented, most with examples, which can be seen in the Reference section of the website. There is also more information and references on our Laboratory of Applied Pharmacokinetics and Bioinformatics website.

2.6 Getting Help and Updates

Within R, you can use help("command") or more simply just ?command in the R console to see detailed help files for any Pmetrics command. Many commands have examples included in this documentation and you can execute the examples with example(command).

You can also type PM_manual() to launch this website from within Pmetrics.

Pmetrics will check for updates automatically every time you load it with library(Pmetrics) and you are connected to the internet. If an update is available, it will provide a brief message to inform you. You can then reinstall the package.

2.7 Code Examples

Included in this book are numerous code examples that will help you learn how to use Pmetrics for R. They are designed to be read in sequence.

Items that are hyperlinked can be selected to cross reference within this manual or link to external sites.
Items correspond to inline examples of R code, which are not evaluated in this document, but serve as templates for what may be typed into your R console or script. They may not necessarily be executable if typed verbatim.

You can copy and paste many of the code chunks into your own script or Quarto document to see how they work. Hover over the code chunks to see a copy icon. Click that to copy the code to your clipboard so you can paste it into your own script or document. Alternatively, you can click the Copy all code button at the top right of chapters to copy all the code chunks on that page to your clipboard.

There are two kinds of code blocks in this book.

# These darker blocks are for illustration and not meant to be copied.
# Hovering over them will not show a copy icon.

# These lighter blocks are meant to be copied, pasted, and executed in Rstudio or Positron.
# Hovering over them will show a copy icon.

Note: In many cases, we do not evaluate the code chunks here because the ouput is too long, so you will need to run them in your own script or document.

Head on over to our Discussion board at Github.

2.8 Citations

Goutelle, Sylvain, Jean-Baptiste Woillard, Thierry Buclin, Laurent Bourguignon, Walter Yamada, Chantal Csajka, Michael Neely, and Monia Guidi. 2022. “Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts’ Discussion on Use, Strengths, and Limitations.” The Journal of Clinical Pharmacology 62 (2): 158–70. https://doi.org/10.1002/jcph.1993.

Goutelle, Sylvain, Jean-Baptiste Woillard, Michael Neely, Walter Yamada, and Laurent Bourguignon. 2022. “Nonparametric Methods in Population Pharmacokinetics.” The Journal of Clinical Pharmacology 62 (2): 142–57. https://doi.org/10.1002/jcph.1650.

Guidi, Monia, Chantal Csajka, and Thierry Buclin. 2022. “Parametric Approaches in Population Pharmacokinetics.” Journal of Clinical Pharmacology 62 (2): 125–41. https://doi.org/10.1002/jcph.1633.