Models of relative reinforcing efficacy of drugs and their predictive utility

Behav Pharmacol. 1990;1(4):283-301. doi: 10.1097/00008877-199000140-00003.

Abstract

Studies of drugs as reinforcers in animals have indicated a close agreement between the drugs that function as reinforcers in animals and those that are abused by humans. This agreement has prompted the use of results of studies in animals as a model to predict the abuse of newly synthesized drugs. While this model has widely accepted nominal predictive utility, there have been attempts to extend its predictive capability to assess the relative reinforcing efficacy of drugs. This concept implies that the reinforcing effects of drugs can be compared on ordinal, interval or ratio scales. Relative reinforcing efficacy has been assessed in studies of performances under progressive-ratio schedules and choice procedures, and it has been suggested that results of these studies might be used to predict the extent to which a drug will be abused. In order to use these data for prediction, scaling issues need to be addressed. With progressive-ratio schedules, it is unclear whether the results represent interval or ordinal data. Development and analysis of choice procedures must to occur before each study will yield more than a pair of ordered data points. In order to assess the predictive utility of models of relative reinforcing efficacy, laboratory data from assessments of known drugs of abuse need to be validated with data on the actual abuse of the compounds. There are significant issues in determining what data on "actual abuse" (e.g. epidemiologic results) should be used in attempts to validate the experimental results. Results of epidemiological surveys are influenced by non-pharmacological variables, such as social, marketing and legal factors, that can affect the degree to which results of laboratory studies agree with those from the surveys. Differential influences of these factors on particular drugs may render results of epidemiologic surveys unsuitable for validation of laboratory results. Other types of data, such as laboratory reports of subjective effects or reinforcing effects of drugs in humans subjects, may be influenced less by those factors but are not themselves reflective of "actual abuse." Currently nominal scaling may represent the best information that can be provided for predicting abuse of drugs. However, there are clear paths to take to overcome these shortcomings. More directed laboratory studies that concentrate on scaling issues as well as more pharmacological specificity of epidemiologic studies will undoubtedly increase our predictive ability.