Publications by authors named "Sjoerd F Koopman"
Article Synopsis
- Patients with hemophilia B receive factor IX concentrates to prevent bleeding, and new extended half-life (EHL) options allow for less frequent dosing compared to standard treatments.
- The recombinant FIX-Fc fusion protein (rFIXFc) is highlighted for its rapid distribution, potentially due to its binding to type IV collagen in the body, which may help prevent bleeding even when FIX activity is not measurable in plasma.
- A physiologically based pharmacokinetic (PBPK) model accurately predicts how rFIXFc behaves in the body, showing significantly higher concentrations of the drug in the extravascular space compared to plasma, indicating its crucial role in achieving effective bleeding control after treatment.
The potential of using ChatGPT in pharmacometrics was explored in this study, with a focus on developing a population 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 to identify as well fix errors in the code.
View Article and Find Full Text PDFAims: Recombinant factor IX Fc fusion protein (rFIX-Fc) is an extended half-life factor concentrate administered to haemophilia B patients. So far, a population pharmacokinetic (PK) model has only been published for patients aged ≥12 years. The aim was to externally evaluate the predictive performance of the published rFIX-Fc population PK model for patients of all ages and develop a model that describes rFIX-Fc PK using real-world data.
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