Discovering Plausible Mechanistic Details of Hepatic Drug Interactions

Abstract

ABSTRACT:We sought a single set of mechanisms that could provide a quantitative explanation of three pairs of published time series data: perfusate concentration of digoxin and its metabolite in perfusates of isolated perfused rat livers 1) in the absence of any predose and with a predose of either 2) the uptake inhibitor rifampicin or 3) the efflux inhibitor quinidine. We used the synthetic modeling and simulation method because it provides a means of developing a scientific, experimental approach to unraveling and understanding some of the complexities of drug-drug interactions. We plugged together validated, quasi-autonomous software components to form abstract but mechanistically realistic analogs of livers undergoing perfusion [recirculating in silico livers (RISLs)], into which we could add objects representing each of the above three drugs, alone or in combination. Each RISL was a hypothesis about plausible mechanisms responsible for the referent time series data. Simulations tested each hypothesis. We used similarity measures (SMs) to compare results to the six sets of referent data. From many candidates, we identified an RISL having time-invariant mechanisms that achieved a weak SM (SM-1) but failed to achieve a stronger SM. Replacing four time-invariant with time-variant mechanisms along with addition of new enzyme and transporter components achieved the most stringent SM: simulated digoxin and metabolite perfusate levels were experimentally indistinguishable from the referent data for all three treatments. The mechanisms simulated unanticipated loss of hepatic viability during the original wet-lab experiments: erosion of hepatic accessibility and of enzyme and transporter activities.Given the variety of transporters and enzymes that can be involved, how can we enhance substantially our ability to confidently anticipate the consequences of hepatic drug-drug interactions in advance of costly wet-lab experiments? To do so, we need improved knowledge of multilevel spatiotemporal mechanistic details. We need new classes of models with capabilities beyond those of the current pharmacokinetic (PK) and pharmacodynamic variety, plus methods to more realistically represent critical spatiotemporal details, all within singlemodel systems. Finally, we must be able to explore realistic, concurrent, interaction consequences of two or more drugs when given key physicochemical properties, which is infeasible using current PK models. An essential first step in realizing those needs is to show a fine-grained, computational analog in which measures of simulated interactions of two drugs are experimentally indistinguishable from those of referent wet-lab experiments. When the analog's assembled components map realistically to hepatic components and the measured consequences of in silico and wet-lab mechanisms are indistinguishable, we can posit that the responsible mechanisms of both systems are similar, as diagrammed in Fig. 1. Achieving these important goals has been an objective of this project.The referent wet-lab exp...

In silico drug absorption tract: An agent-based biomimetic model for human oral drug absorption

“…Drug objects are autonomous [13] and independent/heterogeneous [20,22] agents. Four types of drug objects were used: midazolam; clonazepam; and one metabolite for each.…”

“…This passive permeation process is probabilistic, and this probability parameter is chosen in respect of the partition equilibrium, which is in turn determined by the drug’s innate permeability and ionization status. A more detailed description of the implementation was presented in our previous reports [7,9,20]. …”

“…In this project, we aimed to develop an in silico agent-based analogue of the human GI tract to model oral drug absorption. Assembling with abstract semi-validated prototypical components from previous studies [7,9,20], the model consists of agents that represent the key aspects of the physicochemical and PK properties of the simulated drugs, and the GI physiological features. They are validated against available human absorption data from bioequivalence studies for two drugs, namely, midazolam and clonazepam.…”

Computational experiments reveal plausible mechanisms for changing patterns of hepatic zonation of xenobiotic clearance and hepatotoxicity

“…To achieve targeted attributes, we followed an iterative construction and refinement protocol similar to that detailed most recently in (Hunt et al, 2009) and (Lam and Hunt, 2009). The objective was to discover CELL level mechanisms that would make patterns of clearance effort (defined below) following compound dosing, increasingly biomimetic, with the long-term goal of achieving ZoRLAs that exhibit all Box 1 attributes, and do so while adhering to a strong parsimony guideline.…”

“…In related work, we built in silico liver analogues to challenge mechanistic hypotheses and gain improved insight into plausible micromechanistic details of xenobiotic clearance (Hunt et al, 2006; Yan et al, 2008a,b), hepatic drug interactions (Lam and Hunt, 2009), diseased-caused differences in spatiotemporal micro-mechanisms influencing hepatic drug disposition (Park et al, 2009), and heterogeneities in intra lobular enzyme induction (Ropella et al, 2008). At the start of this project, we drew on these methods and their validated components to instantiate and experiment on lobular analogues targeting subsets of attributes 1–10 in Box 1.…”