Despite the fact that many drug abusers engage in poly-drug use, there has been no rigorous quantification of the drug-drug interactions (known mathematically as 'joint action analysis') in withdrawal after poly-drug exposure. The rigor of such analysis increases with the ability to measure drug concentration as close to the site of action as possible. Rodent and monkey models have inherent limitations related to inability to know drug concentration - rather than dose - due to pharmacokinetic factors (i.e., the two drugs can affect each other's absorption, distribution, metabolism, or excretion). Indeed, studies using these models have yielded conflicting results. The PI has recently developed a convenient and sensitive metric in a model that is less susceptible to the above limitations. The metric, carefully selected to be physiologically-relevant, capitalizes on the advantages of Planaria, which have a long and rich history of productive use for modeling mammalian behaviors and psychopharmacologic effects. Planaria are particularly relevant for these studies because of their mammalian-like CNS (a primitive brain and spinal cord that is capable of learning and memory) and mammalian neurotransmitter systems (e.g., dopaminergic, 5-HT, and opioid). Significant advantages over other models include: a sensitive measure of withdrawal; an ability to measure drug concentration; ability to obtain precise ED50 values, and relative absence of PK interference between drugs. Antagonist-sensitive, receptor-mediated withdrawal from drugs of abuse (cocaine and opioid) have already been reproducibly elicited in Planaria and quantified by the PI in a form that is amenable to joint-action analysis.
The aims of the proposal are: (1) to apply the metric to representative abused drugs and exposure schedules, then (2) subject these data to joint-action analyses previously developed and published by the PI and Co-Investigator (e.g., comparison of Zmix vs Zadd values). Such analyses are applicable if the withdrawal from two drugs produces either similar or different behaviors, or even if one drug does not produce measurable effects (the Co-Investigator has established the methodology to analyze such 'one-arm' interaction). The results of these studies will focus and establish the basis for future, more mechanistic, studies using, e.g., electrophysiologic or molecular biology techniques. An improved understanding of how withdrawal is influenced by poly-drug abuse could lead to development of enhanced clinical treatment.
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|Rawls, Scott M; Gerber, Kristin; Ding, Zhe et al. (2008) Agmatine: identification and inhibition of methamphetamine, kappa opioid, and cannabinoid withdrawal in planarians. Synapse 62:927-34|
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