Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America.
Tempus Dictum, Inc., Olympia, WA, United States of America.
PLoS One. 2022 Jul 22;17(7):e0269775. doi: 10.1371/journal.pone.0269775. eCollection 2022.
Predictions of xenobiotic hepatic clearance in humans using in vitro-to-in vivo extrapolation methods are frequently inaccurate and problematic. Multiple strategies are being pursued to disentangle responsible mechanisms. The objective of this work is to evaluate the feasibility of using insights gained from independent virtual experiments on two model systems to begin unraveling responsible mechanisms. The virtual culture is a software analog of hepatocytes in vitro, and the virtual human maps to hepatocytes within a liver within an idealized model human. Mobile objects (virtual compounds) map to amounts of xenobiotics. Earlier versions of the two systems achieved quantitative validation targets for intrinsic clearance (virtual culture) and hepatic clearance (virtual human). The major difference between the two systems is the spatial organization of the virtual hepatocytes. For each pair of experiments (virtual culture, virtual human), hepatocytes are configured the same. Probabilistic rules govern virtual compound movements and interactions with other objects. We focus on highly permeable virtual compounds and fix their extracellular unbound fraction at one of seven values (0.05-1.0). Hepatocytes contain objects that can bind and remove compounds, analogous to metabolism. We require that, for a subset of compound properties, per-hepatocyte compound exposure and removal rates during culture experiments directly predict corresponding measures made during virtual human experiments. That requirement serves as a cross-system validation target; we identify compound properties that enable achieving it. We then change compound properties, ceteris paribus, and provide model mechanism-based explanations for when and why measures made during culture experiments under- (or over-) predict corresponding measures made during virtual human experiments. The results show that, from the perspective of compound removal, the organization of hepatocytes within virtual livers is more efficient than within cultures, and the greater the efficiency difference, the larger the underprediction. That relationship is noteworthy because most in vitro-to-in vivo extrapolation methods abstract away the structural organization of hepatocytes within a liver. More work is needed on multiple fronts, including the study of an expanded variety of virtual compound properties. Nevertheless, the results support the feasibility of the approach and plan.
使用体外-体内外推方法预测异生物质在人体中的肝清除率通常不准确且存在问题。目前正在采用多种策略来阐明相关机制。本工作的目的是评估使用两个模型系统的独立虚拟实验获得的见解来开始阐明相关机制的可行性。虚拟培养物是体外肝细胞的软件模拟，虚拟人映射到理想化模型人体内的肝内肝细胞。移动对象（虚拟化合物）映射到异生物质的量。两个系统的早期版本都实现了内在清除率（虚拟培养物）和肝清除率（虚拟人）的定量验证目标。两个系统之间的主要区别在于虚拟肝细胞的空间组织。对于每对实验（虚拟培养物，虚拟人），肝细胞的配置相同。概率规则控制虚拟化合物的运动和与其他对象的相互作用。我们专注于高渗透性的虚拟化合物，并将其细胞外未结合分数固定在七个值（0.05-1.0）之一。肝细胞包含可以结合和去除化合物的对象，类似于新陈代谢。我们要求，对于化合物性质的一部分子集，在培养实验期间，每个肝细胞的化合物暴露和去除率直接预测虚拟人实验期间的相应测量值。该要求作为跨系统验证目标；我们确定了可以实现该目标的化合物性质。然后，我们在不改变其他条件的情况下改变化合物的性质，并提供基于模型机制的解释，说明为什么在培养实验中测量值低于（或高于）虚拟人实验中测量值的原因。结果表明，从化合物去除的角度来看，虚拟肝脏内的肝细胞组织比培养物内的肝细胞组织更有效，效率差异越大，预测值越低。这种关系值得注意，因为大多数体外-体内外推方法都忽略了肝脏内肝细胞的结构组织。需要在多个方面开展更多工作，包括对更多种类的虚拟化合物性质的研究。然而，结果支持该方法和计划的可行性。
