Abstract
The potential of using chatGPT in pharmacometrics was explored in this
study, with a focus on developing a pharmacokinetic (PK) model for
standard half-life factor VIII. Our results demonstrated that chatGPT
can be utilized to accurately obtain typical PK parameters from
literature, generate a population PK model in R, and develop an
interactive Shiny application to visualize the results. ChatGPT’s
language generation capabilities enabled the development of R codes with
minimal programming knowledge and helped identify and fix errors in the
code. While chatGPT presents several advantages, such as its ability to
streamline the development process, its use in pharmacometrics also has
limitations and challenges, including the accuracy and reliability of
AI-generated data, the lack of transparency and interpretability of AI.
Overall, our study demonstrates the potential of using chatGPT in
pharmacometrics, but researchers must carefully evaluate its use for
their specific needs.