CONCLUSION
In conclusion, our study highlights the importance of incorporatingin vitro fm data into PBPK models to improve the
accuracy of predicting DDIs. While in silico fmmay have some potential, its influence on predictions appears to be
limited. Our findings suggest that drugs with high
Clliver levels (>15
L·h-1) and high fm(>75%) are particularly susceptible to the impact of
CYP3A4 inhibitor ketoconazole, highlighting the need for further
research to better understand the relationship between clearance,fm , and the risk of CYP3A4 drug-drug
interactions. By improving our ability to predict DDIs, our research has
the potential to enhance drug safety and efficacy, ultimately benefiting
patient health.