Sean H. J. Kim

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.

Tracing Multiscale Mechanisms of Drug Disposition in Normal and Diseased Livers

Hepatic drug disposition is different in normal and diseased livers. Different disease types alter disposition differently. What are the responsible micromechanistic changes and how do they influence drug movement within the liver? We provide plausible, concrete answers for two compounds, diltiazem and sucrose, in normal livers and two different types of cirrhotic rat livers: chronic pretreatment of rats with carbon tetrachloride (CCl4) and alcohol caused different types of cirrhosis. We started with simulated disposition data from normal, multilevel, physiologically based, object-oriented, discrete event in silico livers (normal ISLs) that validated against diltiazem and sucrose disposition data from normal livers. We searched the parameter space of the mechanism and found three parameter vectors that enabled matching the three wet-lab data sets. They specified micromechanistic transformations that enabled converting the normal ISL into two different types of diseased ISLs. Disease caused lobular changes at three of six levels. The latter provided in silico disposition data that achieved a prespecified degree of validation against wet-lab data. The in silico transformations from normal to diseased ISLs stand as concrete theories for disease progression from the disposition perspective. We also developed and implemented methods to trace objects representing diltiazem and sucrose during disposition experiments. This allowed valuable insight into plausible disposition details in normal and diseased livers. We posit that changes in ISL micromechanistic details may have disease-causing counterparts.

Computational Strategies Unravel and Trace How Liver Disease Changes Hepatic Drug Disposition

Liver disease changes the disposition properties of drugs, complicating drug therapy management. We present normal and “diseased” versions of an abstract, agent-oriented In Silico Livers (ISLs), and validate their mechanisms against disposition data from perfused normal and diseased rat livers. Dynamic tracing features enabled spatiotemporal tracing of differences in dispositional events for diltiazem and sucrose across five levels, including interactions with representations of lobular microarchitectural features, cells, and intracellular factors that sequester and metabolize. Differences in attributes map to measures of histopathology. We measured disease-causing differences in local, intralobular ISL effects, obtaining until now unavailable views of how and where hepatic drug disposition may differ in normal and diseased rat livers from diltiazems perspective. Exploration of disposition in less and more advanced stages of disease is feasible. The approach and technology represent an important step toward unraveling the complex changes from normal to disease states and their influences on drug disposition.

Agent‐based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity

A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent‐based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework—a dynamic knowledge repository—wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline. WIREs Syst Biol Med 2013, 5:461–480. doi: 10.1002/wsbm.1222

A computational approach to understand in vitro alveolar morphogenesis.

Primary human alveolar type II (AT II) epithelial cells maintained in Matrigel cultures form alveolar-like cysts (ALCs) using a cytogenesis mechanism that is different from that of other studied epithelial cell types: neither proliferation nor death is involved. During ALC formation, AT II cells engage simultaneously in fundamentally different, but not fully characterized activities. Mechanisms enabling these activities and the roles they play during different process stages are virtually unknown. Identifying, characterizing, and understanding the activities and mechanisms are essential to achieving deeper insight into this fundamental feature of morphogenesis. That deeper insight is needed to answer important questions. When and how does an AT cell choose to switch from one activity to another? Why does it choose one action rather than another? We report obtaining plausible answers using a rigorous, multi-attribute modeling and simulation approach that leveraged earlier efforts by using new, agent and object-oriented capabilities. We discovered a set of cell-level operating principles that enabled in silico cells to self-organize and generate systemic cystogenesis phenomena that are quantitatively indistinguishable from those observed in vitro. Success required that the cell components be quasi-autonomous. As simulation time advances, each in silico cell autonomously updates its environment information to reclassify its condition. It then uses the axiomatic operating principles to execute just one action for each possible condition. The quasi-autonomous actions of individual in silico cells were sufficient for developing stable cyst-like structures. The results strengthen in silico to in vitro mappings at three levels: mechanisms, behaviors, and operating principles, thereby achieving a degree of validation and enabling answering the questions posed. We suggest that the in silico operating principles presented may have a biological counterpart and that a semiquantitative mapping exists between in silico causal events and in vitro causal events.

Simulation of lung alveolar epithelial wound healing in vitro

The mechanisms that enable and regulate alveolar type II (AT II) epithelial cell wound healing in vitro and in vivo remain largely unknown and need further elucidation. We used an in silico AT II cell-mimetic analogue to explore and better understand plausible wound healing mechanisms for two conditions: cyst repair in three-dimensional cultures and monolayer wound healing. Starting with the analogue that validated for key features of AT II cystogenesis in vitro, we devised an additional cell rearrangement action enabling cyst repair. Monolayer repair was enabled by providing ‘cells’ a control mechanism to switch automatically to a repair mode in the presence of a distress signal. In cyst wound simulations, the revised analogue closed wounds by adhering to essentially the same axioms available for alveolar-like cystogenesis. In silico cell proliferation was not needed. The analogue recovered within a few simulation cycles but required a longer recovery time for larger or multiple wounds. In simulated monolayer wound repair, diffusive factor-mediated ‘cell’ migration led to repair patterns comparable to those of in vitro cultures exposed to different growth factors. Simulations predicted directional cell locomotion to be critical for successful in vitro wound repair. We anticipate that with further use and refinement, the methods used will develop as a rigorous, extensible means of unravelling mechanisms of lung alveolar repair and regeneration.

Agent-Directed Tracing of Multi-Scale Drug Disposition Events within Normal and Diseased In Silico Livers

Cirrhosis, a chronic liver disease, alters hepatic drug disposition; however, little is known about micro-mechanisms underpinning disease progression and how they contribute to changes in liver disposition properties. In this article, the authors present multilevel, agent-based and agent-directed In Silico Livers ISLs to probe plausible micro-mechanistic details 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, the authors systematically transformed ISL characteristics to achieve validation against perfusion outflow profiles from the two types of diseased livers. In this regard, the authors developed and implemented multilevel methods to trace each object representing diltiazem during simulated perfusion experiments. This enabled gaining heretofore-unavailable insight into plausible micro-mechanistic details from diltiazems perspective in normal and diseased livers. The authors posit that the presented ISL micro-mechanistic details may have disease caused counterparts during disposition.

In silico, experimental, mechanistic model for extended-release felodipine disposition exhibiting complex absorption and a highly variable food interaction

The objective of this study was to develop and explore new, in silico experimental methods for deciphering complex, highly variable absorption and food interaction pharmacokinetics observed for a modified-release drug product. Toward that aim, we constructed an executable software analog of study participants to whom product was administered orally. The analog is an object- and agent-oriented, discrete event system, which consists of grid spaces and event mechanisms that map abstractly to different physiological features and processes. Analog mechanisms were made sufficiently complicated to achieve prespecified similarity criteria. An equation-based gastrointestinal transit model with nonlinear mixed effects analysis provided a standard for comparison. Subject-specific parameterizations enabled each executed analog’s plasma profile to mimic features of the corresponding six individual pairs of subject plasma profiles. All achieved prespecified, quantitative similarity criteria, and outperformed the gastrointestinal transit model estimations. We observed important subject-specific interactions within the simulation and mechanistic differences between the two models. We hypothesize that mechanisms, events, and their causes occurring during simulations had counterparts within the food interaction study: they are working, evolvable, concrete theories of dynamic interactions occurring within individual subjects. The approach presented provides new, experimental strategies for unraveling the mechanistic basis of complex pharmacological interactions and observed variability.

Individualized, discrete event, simulations provide insight into inter- and intra-subject variability of extended-release, drug products

ObjectiveDevelop and validate particular, concrete, and abstract yet plausible in silico mechanistic explanations for large intra- and interindividual variability observed for eleven bioequivalence study participants. Do so in the face of considerable uncertainty about mechanisms.MethodsWe constructed an object-oriented, discrete event model called subject (we use small caps to distinguish computational objects from their biological counterparts). It maps abstractly to a dissolution test system and study subject to whom product was administered orally. A subject comprises four interconnected grid spaces and event mechanisms that map to different physiological features and processes. Drugs move within and between spaces. We followed an established, Iterative Refinement Protocol. Individualized mechanisms were made sufficiently complicated to achieve prespecified Similarity Criteria, but no more so. Within subjects, the dissolution space is linked to both a product-subject Interaction Space and the GI tract. The GI tract and Interaction Space connect to plasma, from which drug is eliminated.ResultsWe discovered parameterizations that enabled the eleven subject simulation results to achieve the most stringent Similarity Criteria. Simulated profiles closely resembled those with normal, odd, and double peaks. We observed important subject-by-formulation interactions within subjects.ConclusionWe hypothesize that there were interactions within bioequivalence study participants corresponding to the subject-by-formulation interactions within subjects. Further progress requires methods to transition currently abstract subject mechanisms iteratively and parsimoniously to be more physiologically realistic. As that objective is achieved, the approach presented is expected to become beneficial to drug development (e.g., controlled release) and to a reduction in the number of subjects needed per study plus faster regulatory review.

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.