Pharmacokinetic-Pharmacodynamic Modelling in Hemophilia A: Relating Thrombin and Plasmin Generation to Factor VIII Activity After Administration of a VWF/FVIII Concentrate

BACKGROUND

Hemophilia A patients are treated with factor (F) VIII prophylactically to prevent bleeding. In general, dosage and frequency are based on pharmacokinetic measurements. Ideally, an alternative dose adjustment can be based on the hemostatic potential, measured with a thrombin generation assay (TGA), like the Nijmegen hemostasis assay.

OBJECTIVE

The objective of this study was to investigate the predicted performance of a previously developed pharmacokinetic-pharmacodynamic model for FVIII replacement therapy, relating FVIII dose and FVIII activity levels with thrombin and plasmin generation parameters.

METHODS

Pharmacokinetic and pharmacodynamic measurements were obtained from 29 severe hemophilia A patients treated with pdVWF/FVIII concentrate (Haemate P®). The predictive performance of the previously developed pharmacokinetic-pharmacodynamic model was evaluated using nonlinear mixed-effects modeling (NONMEM). When predictions of FVIII activity or TGA parameters were inadequate [median prediction error (MPE) > 20%], a new model was developed.

RESULTS

The original pharmacokinetic model underestimated clearance and was refined based on a two-compartment model. The pharmacodynamic model displays no bias in the observed normalized thrombin peak height and normalized thrombin potential (MPE of 6.83% and 7.46%). After re-estimating pharmacodynamic parameters, EC50 and Emax values were relatively comparable between the original model and this group. Prediction of normalized plasmin peak height was inaccurate (MPE 58.9%).

CONCLUSION

Our predictive performance displayed adequate thrombin pharmacodynamic predictions of the original model, but a new pharmacokinetic model was required. The pharmacodynamic model is not factor specific and applicable to multiple factor concentrates. A prospective study is needed to validate the impact of the FVIII dosing pharmacodynamic model on bleeding reduction in patients.

ChatGPT in pharmacometrics? Potential opportunities and limitations

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. 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 reproducibility regarding codes generated by ChatGPT. Overall, our study demonstrates the potential of using ChatGPT in pharmacometrics, but researchers must carefully evaluate its use for their specific needs.