About this blog – Marian Klose

Motivation

In pharmacometrics, I’ve found that some concepts are either poorly documented or explained in such technical language that they become hard to grasp (at least for me). This can be quite frustrating when you’re trying to learn or understand something new for which you don’t have a suitable mathematical and statistical background.

Luckily, there are many publicly available resources, such as blogs, podcast and websites, that explain these topics in a more accessible way or generally share knowledge about pharmacometrics. Some of my favorites include:

For instance, Danielle Navarro’s post on population pharmacokinetic models in stan was incredibly helpful in my understanding of implementing pop-PK models in Stan. She just explained the concepts in a very easy-to-understand way and it is at the same time quite entertaining to read. Please check out her blog, if you haven’t already!

I often explain new concepts to myself using Quarto or RMarkdown documents and I thought I might as well share them as little blog posts. While I don’t expect to match the quality of the blogs I’ve mentioned, I still hope that some posts can be helpful to others who are tackling similar challenges.

Disclaimers

Before diving in, a few things to note:

I’m really not an expert in everything I write about; I’m simply learning as I go while documenting my process. So please expect some mistakes along the way!
English is not my first language, so I rely on tools like ChatGPT and DeepL to help with writing. I also use tools like ChatGPT to generate ideas or to find good ways to visualize concepts.
I do my best to give credit and cite sources when appropriate. Much of what I share builds on others’ work, and I’m not reinventing the wheel. However, a blog post shouldn’t become a scientific paper, so I might not always provide a full reference list. If you feel that I haven’t given proper credit, please let me know.

--- title: "About this blog" description: "Some motivations and disclaimers" author: - name: Marian Klose url: https://github.com/marianklose orcid: 0009-0005-1706-6289 date: 12-05-2024 categories: [Motivation, Disclaimer] image: preview.jpg draft: false echo: true execute: freeze: true # never re-render during project render (dependencies might change over time) echo: true message: false warning: false format: html: number-sections: false toc: true code-fold: true code-tools: true --- ## Motivation In pharmacometrics, I’ve found that some concepts are either poorly documented or explained in such technical language that they become hard to grasp (at least for me). This can be quite frustrating when you’re trying to learn or understand something new for which you don't have a suitable mathematical and statistical background. Luckily, there are many publicly available resources, such as blogs, podcast and websites, that explain these topics in a more accessible way or generally share knowledge about pharmacometrics. Some of my favorites include: - [Danielle Navarro's Blog](https://blog.djnavarro.net/) - [Clinical Pharmacology Podcast](https://teuschersolutions.com/) - [mrgsolve blog](https://mrgsolve.org/blog/) - [PMX Solutions Tutorials](https://www.pmxsolutions.com/blog/) - [Tingjie Guo’s NMHelp](https://nmhelp.tingjieguo.com/) For instance, Danielle Navarro’s post on [population pharmacokinetic models in stan](https://blog.djnavarro.net/posts/2023-06-10_pop-pk-models/) was incredibly helpful in my understanding of implementing pop-PK models in Stan. She just explained the concepts in a very easy-to-understand way and it is at the same time quite entertaining to read. Please check out her blog, if you haven't already! I often explain new concepts to myself using Quarto or RMarkdown documents and I thought I might as well share them as little blog posts. While I don’t expect to match the quality of the blogs I've mentioned, I still hope that some posts can be helpful to others who are tackling similar challenges. ## Disclaimers Before diving in, a few things to note: - I’m really not an expert in everything I write about; I’m simply learning as I go while documenting my process. So please expect some mistakes along the way! - English is not my first language, so I rely on tools like ChatGPT and DeepL to help with writing. I also use tools like ChatGPT to generate ideas or to find good ways to visualize concepts. - I do my best to give credit and cite sources when appropriate. Much of what I share builds on others’ work, and I’m not reinventing the wheel. However, a blog post shouldn't become a scientific paper, so I might not always provide a full reference list. If you feel that I haven’t given proper credit, please let me know.