Glen E. P. Ropella

Essential operating principles for tumor spheroid growth

BackgroundOur objective was to discover in silico axioms that are plausible representations of the operating principles realized during characteristic growth of EMT6/Ro mouse mammary tumor spheroids in culture. To reach that objective we engineered and iteratively falsified an agent-based analogue of EMT6 spheroid growth. EMT6 spheroids display consistent and predictable growth characteristics, implying that individual cell behaviors are tightly controlled and regulated. An approach to understanding how individual cell behaviors contribute to system behaviors is to discover a set of principles that enable abstract agents to exhibit closely analogous behaviors using only information available in an agents immediate environment. We listed key attributes of EMT6 spheroid growth, which became our behavioral targets. Included were the development of a necrotic core surrounded by quiescent and proliferating cells, and growth data at two distinct levels of nutrient.ResultsWe then created an analogue made up of quasi-autonomous software agents and an abstract environment in which they could operate. The system was designed so that upon execution it could mimic EMT6 cells forming spheroids in culture. Each agent used an identical set of axiomatic operating principles. In sequence, we used the list of targeted attributes to falsify and revise these axioms, until the analogue exhibited behaviors and attributes that were within prespecified ranges of those targeted, thereby achieving a level of validation.ConclusionThe finalized analogue required nine axioms. We posit that the validated analogues operating principles are reasonable representations of those utilized by EMT6/Ro cells during tumor spheroid development.

Modeling and Simulation of Hepatic Drug Disposition Using a Physiologically Based, Multi-agent In Silico Liver

PurposeValidate a physiologically based, mechanistic, in silico liver (ISL) for studying the hepatic disposition and metabolism of antipyrine, atenolol, labetalol, diltiazem, and sucrose administered alone or in combination.Materials and MethodsAutonomous software objects representing hepatic components such as metabolic enzymes, cells, and microarchitectural details were plugged together to form a functioning liver analogue. Microarchitecture features were represented separately from drug metabolizing functions. Each ISL component interacts uniquely with mobile objects. Outflow profiles were recorded and compared to wet-lab data. A single ISL structure was selected, parameterized, and held constant for all compounds. Parameters sensitive to drug-specific physicochemical properties were tuned so that ISL outflow profiles matched in situ outflow profiles.ResultsISL simulations were validated separately and together against in situ data and prior physiologically based pharmacokinetic (PBPK) predictions. The consequences of ISL parameter changes on outflow profiles were explored. Selected changes altered outflow profiles in ways consistent with knowledge of hepatic anatomy and physiology and drug physicochemical properties.ConclusionsA synthetic, agent-oriented in silico liver has been developed and successfully validated, enabling us to posit that static and dynamic ISL mechanistic details, although abstract, map realistically to hepatic mechanistic details in PBPK simulations.

Moving Beyond in Silico Tools to in Silico Science in Support of Drug Development Research

Exploitation of concretized mechanistic models and simulation methods enables the acquisition of a competitive advantage through deeper, easily shared, mechanistic insight into the disease and/or health phenomena that are the focus of the research and development (R&D) organization. The models are analogues of the biological wet‐lab models used to support that R&D. An analogue is an explanatory and evolving hypothesis about the mechanistic consequences of xenobiotic or biologic interventions. As such, it is fundamentally different from the familiar inductive, equation‐based, pharmacokinetic, pharmacodynamic, and related models. Analogues are designed for experimentation and to be useful in the face of incomplete data and multiple uncertainties. These models use interchangeable components and require iterative refinement. They enable linking coarse‐grained systemic phenomena to fine‐grained molecular details, including molecular targets. To simplify and focus this discussion, we describe one example of the new class of models, in silico livers (ISLs). We present a vision of how the biological wet‐lab side of the R&D process might function when these models and methods are fully implemented within a common computational framework. Accumulated mechanistic knowledge is easily measured and visualized in action; thus, it can be easily challenged. Components within analogues that have been validated for many compounds can use programmed “intelligence” to automatically parameterize for, and respond to, a new, not previously seen compound based on its physicochemical properties. Each analogue can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete, while moving closer to personalized medicine. Drug Dev Res 72: 153–161, 2011.

Biomimetic in silico devices

We introduce biomimetic in silico devices, and means for validation along with methods for testing and refining them. The devices are constructed from adaptable software components designed to map logically to biological components at multiple levels of resolution. In this report we focus on the liver; the goal is to validate components that mimic features of the lobule (the hepatic primary functional unit) and dynamic aspects of liver behavior, structure, and function. An assembly of lobule-mimetic devices represents an in silico liver. We validate against outflow profiles for sucrose administered as a bolus to isolated, perfused rat livers. Acceptable in silico profiles are experimentally indistinguishable from those of the in situ referent. This new technology is intended to provide powerful new tools for challenging our understanding of how biological functional units function in vivo.

Agent-based simulation of drug disposition in cirrhotic liver

Cirrhosis, a chronic liver disease, alters hepatic drug disposition. Little is known about mechanisms underpinning the disease progression and how they contribute to changes in liver disposition properties. Here we present multilevel, agent-based and agent-directed In Silico Livers (ISLs) to probe plausible answers for a cationic drug, diltiazem, in two different types of cirrhotic rat livers. Starting with ISLs that validated against diltiazem disposition data from normal livers, we systematically transformed ISL characteristics to achieve validation against perfusion outflow profiles from the two types of diseased livers. For detailed analysis, we developed and implemented methods to trace each object representing diltiazem during simulated perfusion experiments. So doing enabled gaining heretofore-unavailable insight into plausible disposition details from diltiazem perspective in normal and diseased livers. From the results, we posit that changes in ISL micromechanistic details may have disease caused counterparts during disposition.