Project 3: Using abuse liability data to test hypotheses about advanced-generation ECIGs and generate population-level predictions regarding potential regulatory action

项目摘要。烟草产品研究中心(CSTP)开发了一个模型，用于 使用加热液体的电子烟(ECIG)作为样本来评估新型烟草产品 通常含有尼古丁，形成一种气雾剂，使用者可以吸入。现在，CSTP利用ECIG的专业知识来 从产品评估转向影响分析的综合主题。具体而言，CSTP提出了 FDA可以用来对潜在法规的影响进行预测的方法，然后 无论是否发生在总体中发生的预测影响，都可以得到检验。CSTP的模型评估了 监管可能会影响产品毒性(项目1)、用户行为(项目2)和产品成瘾/滥用 责任(项目3)。在这方面，项目3将产生关于先进的-- 新一代ECIG将与项目1和项目2一起，为人口一级的预测作出贡献。项目4将 测试这些人口水平的预测。 FDA的规定旨在促进健康，但也可能产生意想不到的后果。例如, 将ECIG液体的尼古丁含量限制在20毫克/毫升，就像在欧盟(EU)一样，可以推动更高功率的使用 雾化更多液体/烟尘的设备，导致使用者吸入更多尼古丁。意外后果可能 也可由其他行动引起，如限制ECIG尼古丁流量(尼古丁排放速率)，或减少 加味ECIG液体供应。这些法规和其他潜在法规对ECIG的使用和 可以通过评估滥用责任或持续使用/依赖药物的可能性来预测依赖性。 行为经济任务是滥用责任的有效指标，并揭示了人们愿意 支付一种药物，他们会付出多大的努力来赚取一种药物，以及他们对药品价格的变化有多敏感。 项目3的具体目标使用标准的滥用责任评估，在独立的实验室研究中 涉及60名独家ECIG使用者和60名双重ECIG和烟草使用者，在多大程度上 对一系列行为经济任务的反应受到三种潜在监管行动的影响：(1) 尼古丁的限制，(2)尼古丁流量的限制，以及(3)风味可获得性的减少。项目3已通知 通过上下文知识核心，确保独立变量反映真实世界的条件。 总体而言，项目3的结果将提供有关两个人群滥用ECIG责任的新数据，这将 可能会受到监管行动的不同影响，它还将提供有关 三个潜在监管行动的后果。项目4检查了人口中的这些预测 水平。因此，该项目是一个具有综合影响分析主题的中心的一部分，该主题来自 团队的滥用责任专业知识，提供FDA可用于指导法规制定的工具， 到法规生效时，已经使用经过验证的方法对其进行测试、改进和生成 数据表明，其促进健康的效果是最大的，意外后果是最小的。

Project Summary. The Center for the Study of Tobacco Products (CSTP) has developed a model for evaluating novel tobacco products using, as exemplars, electronic cigarettes (ECIGs) that heat a liquid that often contains nicotine, forming an aerosol that users inhale. Now, CSTP leverages this ECIG expertise to pivot from product evaluation to an integrative theme of impact analysis. Specifically, the CSTP proposes methods with which FDA can generate predictions regarding a potential regulation’s effects and then whether or not the predicted effects occur in the population can be tested. The CSTP’s model assesses how potential regulation might influence product toxicity (Project 1), user behavior (Project 2), and product addiction/abuse liability (Project 3). In this context, Project 3 will generate new data regarding the abuse liability of advanced- generation ECIGs and will contribute, along with Projects 1 and 2, to population-level predictions. Project 4 will test those population-level predictions. FDA regulations are intended to promote health, but also may have unintended consequences. For example, limiting ECIG liquids to <20 mg/ml nicotine, as in the European Union (EU), can drive use of higher power devices that aerosolize more liquid/puff, leading users to inhale more nicotine. Unintended consequences may also occur from other actions, such as constraining ECIG nicotine flux (rate of nicotine emission), or reducing flavored ECIG liquid availability. The consequences of these and other potential regulations on ECIG use and dependence can be predicted by assessing abuse liability, or likelihood of persistent drug use/dependence. Behavioral economic tasks are validated indicators of abuse liability and reveal how much people are willing to pay for a drug, how hard they will work to earn a drug, and how sensitive they are to changes in drug prices. Project 3 specific aims use standard abuse liability assessments to examine, in independent lab studies each involving 60 exclusive ECIG users and 60 dual ECIG and tobacco cigarette users, the extent to which responding to a battery of behavioral economic tasks is influenced by three potential regulatory actions: (1) limits on nicotine, (2) constraints on nicotine flux, and (3) reduction in flavor availability. Project 3 is informed by the Contextual Knowledge Core that ensures that independent variables reflect real-world conditions. Overall, results from Project 3 will provide new data regarding ECIG abuse liability in two populations that will likely be impacted by regulatory action differently, and it also will inform testable predictions regarding the consequences of three potential regulatory actions. Project 4 examines these predictions at the population level. Thus, this project is part of a center with an integrative theme of impact analysis that draws from the team’s abuse liability expertise to provide FDA tools that can be used to guide regulation development so that, by the time a regulation goes into effect, validated methods have been used to test it, refine it, and generate data that show that its health-promoting effects are maximized and unintended consequences are minimized.