Mechanistic study of the cellular interplay of transport and metabolism using the synthetic modeling method

In Silico Resources of Drug-Likeness as a Mirror: What Are We Lacking in Pesticide-Likeness?

Unfavorable bioavailability is an important aspect underlying the failure of drug candidates. Computational approaches for evaluating drug-likeness can minimize these risks. Over the past decades, computational approaches for evaluating drug-likeness have sped up the process of drug development and were also quickly derived to pesticide-likeness. As a result of many critical differences between drugs and pesticides, many kinds of methods for drug-likeness cannot be used for pesticide-likeness. Therefore, it is crucial to comprehensively compare and analyze the differences between drug-likeness and pesticide-likeness, which may provide a basis for solving the problems encountered during the evaluation of pesticide-likeness. Here, we systematically collected the recent advances of drug-likeness and pesticide-likeness and compared their characteristics. We also evaluated the current lack of studies on pesticide-likeness, the molecular descriptors and parameters adopted, the pesticide-likeness model on pesticide target organisms, and comprehensive analysis tools. This work may guide researchers to use appropriate methods for developing pesticide-likeness models. It may also aid non-specialists to understand some important concepts in drug-likeness and pesticide-likeness.

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

Background

An agent-based modeling approach has been suggested as an alternative to traditional, equation-based modeling methods for describing oral drug absorption. It enables researchers to gain a better understanding of the pharmacokinetic (PK) mechanisms of a drug. This project demonstrates that a biomimetic agent-based model can adequately describe the absorption and disposition kinetics both of midazolam and clonazepam.

Methods

An agent-based biomimetic model, in silico drug absorption tract (ISDAT), was built to mimic oral drug absorption in humans. The model consisted of distinct spaces, membranes, and metabolic enzymes, and it was altogether representative of human physiology relating to oral drug absorption. Simulated experiments were run with the model, and the results were compared to the referent data from clinical equivalence trials. Acceptable similarity was verified by pre-specified criteria, which included 1) qualitative visual matching between the clinical and simulated concentration-time profiles, 2) quantitative similarity indices, namely, weighted root mean squared error (RMSE), and weighted mean absolute percentage error (MAPE) and 3) descriptive similarity which requires less than 25% difference between key PK parameters calculated by the clinical and the simulated concentration-time profiles. The model and its parameters were iteratively refined until all similarity criteria were met. Furthermore, simulated PK experiments were conducted to predict bioavailability (F). For better visualization, a graphical user interface for the model was developed and a video is available in Supporting Information.

Results

Simulation results satisfied all three levels of similarity criteria for both drugs. The weighted RMSE was 0.51 and 0.92, and the weighted MAPE was 5.99% and 8.43% for midazolam and clonazepam, respectively. Calculated PK parameter values, including area under the curve (AUC), peak plasma drug concentration (C_max), time to reach C_max (T_max), terminal elimination rate constant (Kel), terminal elimination half life (T_1/2), apparent oral clearance (CL/F), and apparent volume of distribution (V/F), were reasonable compared to the referent values. The predicted absolute oral bioavailability (F) was 44% for midazolam (literature reported value, 31–72%) and 93% (literature reported value, ≥ 90%) for clonazepam.

Conclusion

The ISDAT met all the pre-specified similarity criteria for both midazolam and clonazepam, and demonstrated its ability to describe absorption kinetics of both drugs. Therefore, the validated ISDAT can be a promising platform for further research into the use of similar in silico models for drug absorption kinetics.

An Agent-Based Approach to Dynamically Represent the Pharmacokinetic Properties of Baicalein

Baicalein, a typical flavonoid presented in Scutellariae radix, exhibits a unique metabolic profile during first-pass metabolism: parallel glucuronidation and sulfation pathways, with possible substrate inhibition in both pathways. In this project, we aimed to construct an agent-based model to dynamically represent baicalein pharmacokinetics and to verify the substrate inhibition hypothesis. The model consisted of three 3D spaces and two membranes: apical space (S1), intracellular space (S2), basolateral space (S3), apical membrane (M1), and basolateral membrane (M2). In silico enzymes (UDP-glucuronosyltransferases (UGTs) and sulfotransferases (SULTs)) and binder components were placed in S2. The model was then executed to simulate one-pass metabolism experiments of baicalein. With the implementation of a two-site enzyme design, the simulated results captured the preset qualitative and quantitative features of the wet-lab observations. The feasible parameter set showed that substrate inhibition happened in both conjugation pathways of baicalein. The simulation results suggested that the sulfation pathway was dominant at low concentrations and that SULT was more inclined to substrate inhibition than UGT. Cross-model validation was satisfactory. Our findings were consistent with a previously reported catenary model. We conclude that the mechanisms represented by our model are plausible. Our novel modeling approach could dynamically represent the metabolic pathways of baicalein in a Caco-2 system.

Enabling clearance predictions to emerge from in silico actions of quasi-autonomous hepatocyte components

We demonstrate the feasibility of using in silico hepatocyte cultures (ISHCs) to provide predictions of the intrinsic clearance (CL) of compounds in hepatocyte cultures. We compare results with predictions obtained using a multiple linear regression method. Our expectation is that the method can be extended to predict in vivo clearance of new compounds in humans. Within ISHCs, mobile "compounds" carry information describing referent compound properties. We used an iterative refinement protocol for ISHC refinement and development of parameterization methods. Quasi-autonomous "hepatocytes" and their components (including "transporters" and "enzymes") use a small, event-specific subset of compound properties to decide how to interact with encountered compounds each simulation cycle. The probability of occurrence for each event is specified by a rule that uses a subset of compound properties known to influence that event in vitro. ISHC experiments mimic in vitro counterparts. In silico clearance is measured the same as in vitro clearance and is used to predict a corresponding CL value. For 39 of 73 compounds having calculated CL S.D.s, 79% of ISHC predictions and 23% of regression predictions were within CL ± 2 S.D. For all 73 compounds, 38% of ISHC predictions and 32% of regression predictions were within a factor of 2 of the referent CL values. ISHC details during simulations stand as a mechanistic hypothesis of how clearance phenomena emerge during in vitro experiments.

Mechanistic insight from in silico pharmacokinetic experiments: roles of P-glycoprotein, Cyp3A4 enzymes, and microenvironments

Saquinavir exhibits paradoxical transport across modified Caco-2 cell monolayers (doi: 10.1124/jpet.103.056390) expressing P-glycoprotein and Cyp3A4. The data implicate complicated intracellular transport mechanisms. Drawing on recent discrete event modeling and simulation advances, we built an in silico analog of the confluent, asymmetric cell monolayer used in the cited work. We call it in silico experimental Caco-2 (cell monolayer) culture (ISECC). Concrete, working, hypothesized spatial mechanisms were implemented. Validation was achieved when in silico experimental results met similarity measure (SM) expectations that targeted 16 wet-lab experimental conditions. Initial mechanistic hypotheses turned out to be necessary parts of a more complicated explanation. We progressed through four stages of an iterative refinement and validation protocol that enabled and facilitated discovery of plausible, new mechanistic details. The process exercised abductive reasoning, a primary means of scientific knowledge creation and creative cognition. The ISECC that survived the most stringent SM challenge produced transport data that was statistically indistinguishable from referent wet-lab observations. It required a 7:1 ratio of apical transporters to metabolizing enzymes, a 97% reduction of efflux activity by an inhibitor, a biased distribution of metabolizing enzymes, heterogeneous intracellular spaces, and restrictions on intracellular drug movement. Experimenting on synthetic analogs such as ISECC provides a former unavailable means of discovering new mechanistic details and testing their plausibility. The approach thus provides a powerful new expansion of the scientific method: an independent, scientific means to challenge, explore, better understand, and improve any inductive mechanism and, importantly, the assumptions on which it rests.

At the biological modeling and simulation frontier

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine.

Elongation, proliferation & migration differentiate endothelial cell phenotypes and determine capillary sprouting

BACKGROUND

Angiogenesis, the growth of capillaries from preexisting blood vessels, has been extensively studied experimentally over the past thirty years. Molecular insights from these studies have lead to therapies for cancer, macular degeneration and ischemia. In parallel, mathematical models of angiogenesis have helped characterize a broader view of capillary network formation and have suggested new directions for experimental pursuit. We developed a computational model that bridges the gap between these two perspectives, and addresses a remaining question in angiogenic sprouting: how do the processes of endothelial cell elongation, migration and proliferation contribute to vessel formation?

RESULTS

We present a multiscale systems model that closely simulates the mechanisms underlying sprouting at the onset of angiogenesis. Designed by agent-based programming, the model uses logical rules to guide the behavior of individual endothelial cells and segments of cells. The activation, proliferation, and movement of these cells lead to capillary growth in three dimensions. By this means, a novel capillary network emerges out of combinatorially complex interactions of single cells. Rules and parameter ranges are based on literature data on endothelial cell behavior in vitro. The model is designed generally, and will subsequently be applied to represent species-specific, tissue-specific in vitro and in vivo conditions. Initial results predict tip cell activation, stalk cell development and sprout formation as a function of local vascular endothelial growth factor concentrations and the Delta-like 4 Notch ligand, as it might occur in a three-dimensional in vitro setting. Results demonstrate the differential effects of ligand concentrations, cell movement and proliferation on sprouting and directional persistence.

CONCLUSION

This systems biology model offers a paradigm closely related to biological phenomena and highlights previously unexplored interactions of cell elongation, migration and proliferation as a function of ligand concentration, giving insight into key cellular mechanisms driving angiogenesis.

Mechanistic simulations explain paradoxical saquinavir metabolism during in vitro vectorial transport study

We were confronted by an unexpected observation: in a Transwell study of confluent, Cyp3A4 and P-gp-expressing Caco-2 cells, higher intracellular saquinavir levels, yet less first metabolite (M7) formation were observed following apical dosing, compared to basal dosing. To test two seemingly plausible hypothesized explanations, we constructed an in silico working analogue using the synthetic method. Neither mechanism alone was sufficient, but when combined and tuned within the analogue, the results generated were a semi-quantitative match to the experimental data. After 60 cycles, more of the simulated dose was present within analogue cells as parent drug after apical dosing. Furthermore, less M7 was present after apical dose. The paradox disappeared by having simulated drugs equilibrate among separate intracellular zones. Building, studying, and exploring mechanistic explanations for complex wet-lab phenomena using the new methods improved insight into the referent system, while providing a straightforward, scientific means of testing the plausibility of mechanistic hypotheses.

An In Silico Transwell Device for the Study of Drug Transport and Drug–Drug Interactions

PURPOSE

Validate and exemplify a discrete, componentized, in silico, transwell device (ISTD) capable of mimicking the in vitro passive transport properties of compounds through cell monolayers. Verify its use for studying drug-drug interactions.

METHODS

We used the synthetic modeling method. Specialized software components represented spatial and functional features including cell components, semi-porous tight junctions, and metabolizing enzymes. Mobile components represented drugs. Experiments were conducted and analyzed as done in vitro.

RESULTS

Verification experiments provided data analogous to those in the literature. ISTD parameters were tuned to simulate and match in vitro urea transport data; the objects representing tight junction (effective radius of 6.66 A) occupied 0.066% of the surface area. That ISTD was then tuned to simulate pH-dependent, in vitro alfentanil transport properties. The resulting ISTD predicted the passive transport properties of 14 additional compounds, individually and all together in one in silico experiment. The function of a two-site enzymatic component was cross-validated with a kinetic model and then experimentally validated against in vitro benzyloxyresorufin metabolism data. Those components were used to exemplify drug-drug interaction studies.

CONCLUSIONS

The ISTD is an example of a new class of simulation models capable of realistically representing complex drug transport and drug-drug interaction phenomena.

Dynamics of in silico leukocyte rolling, activation, and adhesion

Background

We present a multilevel, agent based, in silico model that represents the dynamics of rolling, activation, and adhesion of individual leukocytes in vitro. Object-oriented software components were designed, verified, plugged together, and then operated in ways that represent the molecular and cellular mechanisms believed responsible for leukocyte rolling and adhesion. The result is an in silico analogue of an experimental in vitro system. The experimentally measured, phenotypic attributes of the analogue were compared and contrasted to those of leukocytes in vitro from three different experimental conditions.

Results

The individual in silico dynamics of "rolling" on simulated P-selectin, and separately on simulated VCAM-1, were an acceptable match to individual in vitro distance-time and velocity-time measurements. The analogues are also able to represent the transition from rolling to adhesion on P-selectin and VCAM-1 in the presence of GRO-α chemokine. The individual in silico and in vitro behavioral similarities translated successfully to population level measures. These behavioral similarities were enabled in part by subdividing the functionality of the analogue's surface into 600 independent, "cell"-controlled, equally capable modules of comparable functionality.

Conclusion

The overlap in phenotypic attributes of our analogue with those of leukocytes in vitro confirm the considerable potential of our model for studying the key events that determine the behavioral outcome of individual leukocytes during rolling, activation, and adhesion. Our results provide an important foundation and framework for future in silico research into plausible causal links between well-documented, subcellular molecular level events and the variety of systemic phenotypic attributes that distinguish normal leukocyte adhesion from abnormal disease-associated adhesion.

Physiologically based synthetic models of hepatic disposition

Current physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming. A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together. PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.