Behavioral economic demand metrics for abuse deterrent and abuse potential quantification. (1st May 2019) - Schwartz, Lindsay P.; Roma, Peter G.; Henningfield, Jack E.; Hursh, Steven R.; Cone, Edward J.; Buchhalter, August R.; Fant, Reginald V.; Schnoll, Sidney H.
Highlights: Behavioral economics can provide the FDA information to determine drug labeling. Behavioral economics may help measure abuse potential of novel drug formulations. OUD patients with opioid pill experience have less demand for tamper-proof pills. Abstract: Introduction: Behavioral economics provides a framework for quantifying drug abuse potential that can inform public health risk, clinical treatment, and research. Hypothetical purchase task (HPT) questionnaires may provide a low-cost and sensitive method by which to measure and predict the appeal of pharmaceutical drugs that differ by formulation. However, the validity of this type of analysis must be empirically established by comparing the "essential value" (EV) of different drugs across subgroups. Procedures: This pilot study used HPT assessments and the Exponential Model of Demand to quantify the EV of opioid medications—specifically, easily tampered formulations versus (vs.) abuse-deterrent formulations—in patients with a history of opioid abuse. Main findings: Participants had more inelastic demand for opioid pills than for cigarettes and alcohol. Participants with experience manipulating pills (M group) had more inelastic demand for standard pills vs. participants with no manipulation experience (NM group), and the M group had a more elastic demand for the abuse-deterrent opioid pill than for the standard pill. There was no effect of formulation in the NM group and there was no difference in demand elasticity for abuse-deterrent pills between the two groups. There was a positive correlation between the EVs of different drugs, and between some behavioral economic indices and treatment variables. Conclusions: Our results suggest that HPTs may provide a sensitive measure of abuse potential that can distinguish between different formulations in at-risk populations.