Approval Regulation

审批规定

• 批准号: 0519082
• 负责人: Michael Ting
• 金额: --
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0519082&HistoricalAwards=false
• 关键词: Approval; Regulation

In the United States and other advanced industrial societies, many economic activities share two features. First, private parties (such as individuals or firms) perform research and development (R&D) of projects, often at considerable expense. Second, political agencies have the ability to veto the entry or use of these projects. This combination of R&D and regulatory deliberation, termed approval regulation, is a significant component of large segments of modern economies. For example, it characterizes the pre-market activity of the pharmaceutical industry, which saw U.S. sales of over $160 billion in 2003, or approximately 1.5% of GDP.This project has two scientific objectives. First, it develops a set of theoretical models. This is essential because there are presently no theories that describe the approval regulation process. Over the past few decades, political scientists and economists have developed models that describe each of the above components-R&D and regulatory decision-making-piecemeal. However, models of R&D do not consider the influence of a strategic regulator, and models of regulatory approval do not consider the strategic development of products for submission. To generate predictions about firm and regulator strategies, it is therefore essential that a theory of approval regulation integratethe two approaches. The second objective is to test the predictions of the theoretical models. These studies focus on the U.S. pharmaceutical market. One of the main challenges will be that of building the appropriate data sets. As the integration of R&D and regulatory decision-making would suggest, this requires collecting data on Food and Drug Administration's (FDA) regulatory decisions, as well as firms' pharmaceutical R&D projects (including those that were never submitted for review). Moreover, some of the critical variables are difficult to measure. Specific issues to be addressed include the incidence of regulatory error and delay, the effects of firm characteristics (such as size)on R&D and regulatory strategy, and the effects of recent FDA reforms.The project builds on preliminary work conducted at Columbia and Harvard universities over the past two years. This work has resulted in a number of promising preliminary results, both theoretical and empirical. A basic theoretical model has been developed that treats the interaction between a firm and a regulator as a game of incomplete information. The model predicts some counter-intuitive relationships between firm size and regulatory error. These predictions are largely confirmed by the available data. However, more work is needed to address Type II errors (which are inherently more difficult to measure), as well as to incorporate multi-firm competition and amore realistic regulatory review process.Broader Value: The results of this project will be of interest to both academics and policy specialists. In addition to filling an important gap in the scholarly literature on regulation and bureaucratic politics, the project promises to provide timely and policy-relevant knowledge about a highly controversial issue area. For example, recent controversies over the FDA's handling of COX-2 inhibitors and other products have highlighted the tensions between Type I errors (i.e., approving "bad" products), and Type II errors (i.e., rejecting "good" products). An understanding of the incentives faced by submitting firms and the FDA is crucial for striking a balance between both types of error. The results will also be useful for evaluating the effects of possible policy changes, such as the imposition of submission fees, or the implementation of an independent post-approval monitoring agency. Finally, the data set used in these studies will be a resource for other analysts interested in the topic.

在美国和其他先进的工业社会，许多经济活动都有两个特点。第一，私人当事方（如个人或公司）进行项目的研究和开发（研发），往往花费相当大的费用。其次，政治机构有能力否决这些项目的进入或使用。研发和监管审议的这种结合，被称为审批监管，是现代经济大部分的重要组成部分。例如，它描述了制药行业的上市前活动，2003年美国的销售额超过1600亿美元，约占GDP的1.5%。首先，建立了一套理论模型。这是必要的，因为目前还没有理论来描述批准监管过程。在过去的几十年里，政治学家和经济学家已经开发出了描述上述每个组成部分的模型-研发和监管决策-零碎的。然而，研发模型不考虑战略监管机构的影响，监管批准模型不考虑提交产品的战略开发。因此，为了预测企业和监管者的策略，有必要将这两种方法整合为一个审批监管理论。第二个目标是测试理论模型的预测。这些研究主要针对美国医药市场。主要挑战之一将是建立适当的数据集。正如研发和监管决策的整合所表明的那样，这需要收集食品药品监督管理局（FDA）监管决策的数据，以及企业的制药研发项目（包括从未提交审查的项目）。 此外，一些关键变量难以衡量。要解决的具体问题包括发生率的监管错误和延误，公司的特点（如规模）对研发和监管战略的影响，以及最近的FDA改革的影响。该项目建立在哥伦比亚和哈佛大学在过去两年进行的初步工作。这项工作已经产生了一些有希望的初步结果，无论是理论还是经验。一个基本的理论模型已经开发，把一个公司和监管机构之间的互动作为一个不完全信息的游戏。该模型预测了公司规模和监管误差之间的一些反直觉的关系。这些预测在很大程度上得到了现有数据的证实。然而，还需要做更多的工作来解决第二类错误（这本身就更难衡量），以及纳入多公司竞争和更现实的监管审查过程。更广泛的价值：这个项目的结果将是学者和政策专家感兴趣。除了填补监管和官僚政治的学术文献中的一个重要空白外，该项目还有望就一个极具争议的问题领域提供及时的政策相关知识。例如，最近关于FDA处理考克斯-2抑制剂和其他产品的争议突出了I型错误（即，批准“坏”产品），和II型错误（即，拒绝“好”产品）。了解提交公司和FDA所面临的激励对于在两种类型的错误之间取得平衡至关重要。这些结果也将有助于评估可能的政策变化的影响，例如征收提交费，或实施独立的批准后监测机构。最后，这些研究中使用的数据集将成为对该主题感兴趣的其他分析师的资源。