Exposure Measurements on Biomimetic Lobules Using Virtual Experiments to Help Improve IVIVE

The in vitro-in vivo extrapolation (IVIVE) methods used currently to predict the hepatic clearance of new chemical entities are plagued by poorly understood inaccuracies. To begin identifying plausible sources, we challenge two of core hypotheses. Hypothesis-1: the intralobular micro-anatomical organization of hepatocytes (HPCs) can be abstracted away. By accepting that hypothesis, one can assume that intrinsic clearance per HPC is essentially the same in vitro and in vivo, and thus an IVIVE method can employ a simplified liver model, typically the “well-stirred” liver model. Hypothesis-2: when the simplified liver model is the “parallel tube model,” drug concentration decreases exponentially from portal to central vein. When either simplified liver model is used, a core assumption is that intrinsic clearance is directly proportional to the unbound fraction of drug. A barrier to progress has been the fact that it is currently infeasible to challenge the two hypotheses using wet-lab experiments. In this work, we challenge virtual counterparts of the two hypotheses by experimenting on virtual mice in which hepatic disposition and clearance are consequences of concretized model mechanisms that have met several demanding requirements, including the following. The virtual liver’s structure and organization are strongly analogous to those of an actual liver, and the hepatic disposition and clearance of several virtual compounds have achieved quantitative validation targets. We study two virtual compounds. Compound-1 simulates the extreme of low-clearance, highly permeable compounds. Compound-2 simulates a highly permeable compound exhibiting maximum intrinsic clearance. We simulate changes in unbound fraction by changing the probability (pEnter) that a Compound-1 or -2 will enter an adjacent HPC during a simulation cycle. Compound-1 and -2 HPC exposure rates do not decrease from portal to central vein: they increase, and that contradicts both hypotheses. Further, the relationship between exposure rates and pEnter is nonlinear. The insights achieved help explain the frequently reported underprediction of in vivo hepatic clearance values. We suggest that IVIVE methods can be improved by utilizing a liver model that couples a biomimetic representation of intralobular HPC organization with biomimetic representations of intrahepatic disposition dynamics.

Identifying the active components of Baihe–Zhimu decoction that ameliorate depressive disease by an effective integrated strategy: a systemic pharmacokinetics study combined with classical depression model tests

Background Modern pharmacological studies have demonstrated that Baihe–Zhimu decoction (BZD) has antidepressant effects. However, the complex composition and lack of clear evaluation standards for BZD make it less likely to be understood and accepted than evidence-based active natural compounds. Methods In this study, an effective method for the identification of antidepressant components was demonstrated and applied to BZD. The first step was to evaluate the efficacy of BZD by the forced swimming test (FST) and the tail suspension test (TST), followed by successive quantitative analyses of the absorbed constituents at different stages, such as before hepatic disposition, liver distribution, after hepatic disposition and brain distribution after the oral administration of BZD. Finally, the compounds detected in the brain were confirmed by activity testing. Results Our investigation observed that timosaponin BII and timosaponin BIII were accurately determined in the brain after oral administration of BZD, and they were further confirmed to reduce the immobility time in the FST and TST. As described above, timosaponin BII and timosaponin BIII were used to scientifically and reasonably explain the effective chemical basis of the effect of BZD on depression. Conclusions This research affords an effective method to discover lead molecules for antidepressants from traditional Chinese medicine.