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. 2012 Feb 3:3:4.
doi: 10.3389/fpsyt.2012.00004. eCollection 2012.

In silico Models of Alcohol Dependence and Treatment

Boris Kovatchev  1 , Marc Breton, Bankole Johnson
Affiliations

In silico Models of Alcohol Dependence and Treatment

Boris Kovatchev et al. Front Psychiatry. .

Abstract

In this paper we view alcohol dependence and the response to treatment as a recurrent bio-behavioral process developing in time and propose formal models of this process combining behavior and biology in silico. The behavioral components of alcohol dependence and treatment are formally described by a stochastic process of human behavior, which serves as an event generator challenging the metabolic system. The biological component is driven by the biochemistry of alcohol intoxication described by deterministic models of ethanol pharmacodynamics and pharmacokinetics to enable simulation of drinking addiction in humans. Derived from the known physiology of ethanol and the literature of both ethanol intoxication and ethanol absorption, the different models are distilled into a minimal model (as simple as the complexity of the data allows) that can represent any specific patient. We use these modeling and simulation techniques to explain responses to placebo and ondansetron treatment observed in clinical studies. Specifically, the response to placebo was explained by a reduction of the probability of environmental reinforcement, while the effect of ondansetron was explained by a gradual decline in the degree of ethanol-induced neuromodulation. Further, we use in silico experiments to study critical transitions in blood alcohol levels after specific average number of drinks per day, and propose the existence of two critical thresholds in the human - one at 5 and another at 11 drinks/day - at which the system shifts from stable to critical and to super critical state indicating a state of alcohol addiction. The advantages of such a model-based investigation are that (1) the process of instigation of alcohol dependence and its treatment can be deconstructed into meaningful steps, which allow for individualized treatment tailoring, and (2) physiology and behavior can be quantified in different (animal or human) studies and then the results can be integrated in silico.

Keywords: alcohol dependence; computer simulation; metabolic modeling; stochastic process.

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Figures

Figure 1
Figure 1
Recurrent bio-behavioral process of alcohol dependence and treatment.
Figure 2
Figure 2
Stochastic model of behavioral and social conditioning.
Figure 3
Figure 3
Widmark’s zero-order model of ethanol kinetics.
Figure 4
Figure 4
Norberg’s alcohol clearance model featuring Michaelis–Menten dynamics. Suitable for description of intravenous (IV) ethanol injection.
Figure 5
Figure 5
Blood alcohol level following oral alcohol ingestion.
Figure 6
Figure 6
The minimal model of ethanol dynamics following oral alcohol intake.
Figure 7
Figure 7
Common features of a clinical testing protocol collecting data for an individual ethanol dynamics profile. The blood alcohol level (BAL) sampling can be done directly through blood samples, or using a breath analyzer.
Figure 8
Figure 8
Model-predicted and observed effect of placebo and ondansetron treatment.
Figure 9
Figure 9
Model-predicted and observed treatment effect in heavy and non-heavy drinkers.
Figure 10
Figure 10
Minimum blood alcohol level during daytime (7 AM–11 PM) as a function of average number of drinks per day.
Figure 11
Figure 11
System phase transition from stable to unstable dynamics indicated by Poincaré plots of the system attractor.
Figure 12
Figure 12
Minimum blood alcohol level during the night (11 PM–7 AM) as a function of average number of drinks during the day (7 AM–11 PM).
See this image and copyright information in PMC

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