使用概率机器学习预测与肝功能相关的体外测试.

Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion, mediated...

In pharmaceutical development, it's crucial to establish a predictive in vitro–in vivo correlation (IVIVC) for two or more formulations to gain a comprehensive understanding of release properties. IVIVC reduces the need for costly in vivo studies and facilitates the establishment of meaningful dissolution specifications with significant cost savings and decreased regulatory burden. Furthermore, a meaningful IVIVC should predict Cmax and AUC within 20%, aligning with FDA guidance while adhering...

In clinical practice, the direct measurement of hepatic blood flow to evaluate liver function presents significant challenges due to the intricate and specialized nature of the necessary techniques. Consequently, healthcare professionals often rely on empirical estimates derived from thorough patient examinations and liver function tests to gauge liver health. Among the tools at their disposal, the Child–Pugh and MELD scoring systems stand out for their ability to categorize and assess the...