Biology subjects

Ropella, G. E. P.

Publications and source records attributed to Ropella, G. E. P..

3 recordsLinked to original sources

bioRxiv2020

Virtual experiments provide plausible explanations for IVIVE underpredictions of hepatic clearance

We explore a virtual experiment strategy to discover plausible mechanism-based explanations for frequently inaccurate predictions of hepatic drug clearance made using established in vitro-in vivo extrapolation methods. We describe a three-protocol plan that uses validated software analogs of real in vitro and in vivo systems constructed using a common set of objects, components, spaces, and methods. Both systems utilize identical quasi-autonomous hepatocyte analogs containing enzyme-like objects. We parameterize concrete mobile objects (virtual compounds) to simulate the referent drugs disposition and removal characteristics in vitro and in vivo. The goal of Protocol one (Protocol two) is that measures of virtual compound removal using the in vitro analog (in vivo analog) map directly to the measurements used to compute intrinsic clearance (in vivo hepatic clearance). Protocol three, the focus of this work, requires achieving an essential cross-system validation target. For a subset of virtual compounds, measurements of unbound compounds entering hepatocytes (and their subsequent removal) during virtual in vitro experiments will directly predict corresponding measures made during virtual in vivo experiments. We study four highly permeable virtual compounds when their unbound fraction is fixed at one of seven values (0.05-1.0). Results span the range of hepatic extraction ratios. We achieve the cross-system validation target in 15 cases. In the other 13 cases, explanations of the in vitro-in vivo differences in disposition and removal trace to differences in compound-hepatocyte access within the two analogs during execution. The hepato-mimetic structural organization of hepatocytes within the in vivo analog, which is absent within the in vitro analog, is the determining factor. The results taken together support the feasibility of using the three-protocol plan to help explain observed in vitro-in vivo extrapolation discrepancies. We conjecture that, for some cases, the model mechanism-based explanations of discrepancies described herein will have wet-lab counterparts.

bioengineering↗

bioRxiv2019

Contrasting model mechanisms of alanine aminotransferase (ALT) release from damaged and necrotic hepatocytes as an example of general biomarker mechanisms

Interpretations of elevated blood levels of alanine aminotransferase (ALT) for drug-induced liver injury often assume that the biomarker is released passively from dying cells. However, the mechanisms driving that release have not been explored experimentally. The usefulness of ALT and related biomarkers will improve by developing mechanism-based explanations of elevated levels that can be expanded and elaborated incrementally. We provide the means to challenge the ability of closely related concretized model mechanisms to generate patterns of simulated hepatic injury and ALT release that scale (or not) to be quantitatively similar to the wet-lab validation targets. The validation targets for this work are elevated measures of plasma ALT following acetaminophen (APAP) exposure in mice. We build on a published model mechanism that helps explain the generation of characteristic spatiotemporal features of APAP hepatotoxicity within hepatic lobules. Discrete event and agent-oriented software methods are most prominent. We instantiate and leverage a small constellation of concrete model mechanisms. Their details during execution help bring into focus ways in which particular sources of uncertainty become entangled within and across several levels with cause-effect details. Monte Carlo sampling and simulations comprise a virtual experiment. Falsification of one (or more) of the model mechanisms provides new knowledge and shrinks the model mechanism constellation incrementally. We challenge the sufficiency of four potentially explanatory theories for ALT release. The first model mechanism tested failed to achieve the initial validation target, but each of the three others succeeded. We scale ALT amounts in virtual mice directly to target plasma ALT measures in individual mice. Results for one of the three model mechanisms matched all target ALT measures quantitatively. We assert that the actual mechanisms responsible for ALT measures in individual mice and the virtual causal processes occurring during model execution are strongly analogous within and among real hepatic lobular levels. Author summaryInterpretations of elevated biomarkers for drug-induced liver injury assume passive release during hepatocyte death, yet indirect evidence indicates that plasma levels can increase absent injury. Limitations on measurements make it infeasible to resolve causal linkages between drug disposition and plasma levels of biomarkers. To improve explanatory knowledge, we instantiate within virtual mice, plausible mechanism-based causal linkages between acetaminophen disposition and alanine aminotransferase (ALT) behavior that enables simulation results to meet stringent quantitative validation prerequisites. We challenge the sufficiency of four model mechanisms by scaling ALT measurements in virtual mice to corresponding plasma values. Virtual experiment results in which ALT release is a combined consequence of lobular-location-dependent hepatocyte death and drug-induced cellular damage, matches all validation targets. We assert that the actual mechanisms responsible for plasma ALT measures in individual mice and the virtual causal processes occurring during model execution are strongly analogous within and among real hepatic lobular levels.

pharmacology and toxicology↗

bioRxiv2017

A Model Mechanism Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

An improved understanding of in vivo-to-in vitro hepatocyte changes is crucial to interpreting in vitro data correctly and further improving hepatocyte-based in vitro-to-in vivo extrapolations to human targets. We demonstrate using virtual experiments as a means to help untangle plausible causes of inaccurate extrapolations. We start with virtual mice that have biomimetic software livers. Earlier, using those mice, we discovered model mechanisms that enabled achieving quantitative validation targets while also providing plausible causal explanations for temporal characteristics of acetaminophen hepatotoxicity. We isolated virtual hepatocytes, created a virtual culture, and then conducted dose-response experiments in both culture and mice. We expected the two dose-response curves to be displaced. We were surprised that they crossed because it evidenced that simulated acetaminophen metabolism and toxicity are different for virtual culture and mouse contexts even though individual hepatocyte mechanisms were unchanged. Crossing dose-response curves is a virtual example of an in vivo-to-in vitro disconnect. We use detailed results of experiments to explain the disconnect. Individual hepatocytes contribute differently to system level phenomena. In liver, hepatocytes are exposed to acetaminophen sequentially. Relative production of the reactive acetaminophen metabolite is largest (smallest) in pericentral (periportal) hepatocytes. Because that sequential exposure is absent in culture, hepatocytes from different lobular locations do not respond the same. A virtual Culture-to-Mouse translation can stand as a scientifically challengeable theory explaining an in vitro-in vivo disconnect. It provides a framework to develop more reliable interpretations of in vitro observations, which then may be used to improve extrapolations.\n\nAbbreviations

pharmacology and toxicology↗