A Model- and Systems-Based Approach to Efficacy and Safety Questions Related to Generic Substitution

基于模型和系统的方法来解决与仿制药替代相关的功效和安全性问题

• 批准号: 9355367
• 负责人: LAWRENCE LESKO
• 金额: $ 25万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-10 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9355367
• 关键词: Model; Systems; Based; Approach; Efficacy

Subtopic 2 (Pharmacometric M&S for Generic Drug Substitutability Evaluation and Post- Marketing Assessment of small molecule) A Model- and Systems-Based Approach to Efficacy and Safety Questions Related to Generic Substitution The Office of Generic Drugs (OGD) occasionally receives reports from patients, physicians and/or professional organizations about the therapeutic INequivalence of marketed generic drugs. Frequently, there is little scientific evidence to conclusively support a rationale for problems following generic substitution. Given that a 2009 study by OGD demonstrated that the average difference in Cmax and AUC between generic and innovator products was 4.35% and 3.56%, respectively for 2,070 bioequivalence products conducted between 1996 and 2007, this raises the question of whether these bioINequivalence (BIN) signals are real or perceived. However, generic drugs can be complex because of things like input-rate sensitivity in pharmacodynamics (e.g., hypotension related to nifedipine) following oral administration or different mechanisms of extended release for once-a-day oral formulations (e.g., with methylphenidate). Therefore, it is critical to have a process in place to assess purported therapeutic INequivalence. The broad goal of this research strategy is to define a process whereby the OGD can specifically evaluate the potential BIN of approved generic products in patients under clinical use conditions during the post-marketing period, and investigate purported adverse drug reactions arising from generic substitution. It is essential that a scientifically rigorous workflow be established to challenge the notion that generic drugs don't work as well as reference drugs. The results of this research will help to instill confidence in the American public about the quality of generic drugs and the willingness of FDA to use an evidence-based approach to investigate claims of BIN. We are proposing a mechanistic and quantitative research strategy using modeling and simulation techniques that moves from assessing pharmaceutical equivalence (i.e. quality), through bioequivalence (i.e., biopharmaceutical performance) and on to therapeutic equivalence (i.e., clinical efficacy and safety profile), that is a risk-based, comprehensive and pragmatic approach to addressing issues of post-market risk of generic drugs, and interpretation of post- market adverse event reports or product substitution complaints using systems biology principles. It is intended that the research strategy represent a workflow and analysis for the Office of Generic Drugs (OGD) to systematically investigate purported BIN arising from generic drug substitution. Our approach would be conducted as a pilot study in close collaboration with scientists and clinicians in OGD who would help identify high-risk generic substitution situations for evaluating the quality and consistency of the research strategy.

子专题2（仿制药替代性评价和后评价的药理计量学M&S） 小分子的上市评估） 一种基于模型和系统的方法来解决与以下相关的疗效和安全性问题： 通用替代 仿制药办公室（OGD）偶尔会收到来自患者、医生、 和/或专业组织关于已上市仿制药的治疗不等效性 毒品通常，很少有科学证据可以最终支持 通用替代品的问题。鉴于OGD 2009年的一项研究表明， 仿制药和原研药之间Cmax和AUC的平均差异为4.35%， 1996年至2007年期间进行的2，070种生物等效性产品分别为3.56%， 提出了这些生物不等效（BIN）信号是真实的还是感知的问题。 然而，仿制药可能是复杂的，因为像输入速率敏感性， 药效学（例如，与硝苯地平相关的低血压），或 每日一次口服制剂的不同缓释机制（例如，与 哌甲酯）。因此，至关重要的是要有一个过程，以评估据称 治疗不等效。 这项研究战略的广泛目标是确定一个过程，使OGD能够具体地 在临床使用条件下，评价获批仿制药在患者中的潜在BIN 在上市后期间，并调查由以下原因引起的据称药物不良反应： 类属替换必须建立科学严谨的工作流程， 挑战仿制药不如参考药的观念。的结果 这项研究将有助于美国公众对仿制药的质量建立信心。 药物和FDA愿意使用循证方法来调查声称 斌 我们提出了一个机械和定量的研究策略，使用建模和 模拟技术从评估药物等效性（即质量）， 通过生物等效性（即，生物制药性能）和治疗等效性 (i.e.,临床疗效和安全性），这是一个基于风险的，全面的和务实的 处理仿制药上市后风险问题的方法，以及对 使用系统生物学的市场不良事件报告或产品替代投诉 原则研究战略旨在代表一个工作流程和分析， 仿制药办公室（OGD）系统地调查仿制药引起的所谓BIN 药物替代我们的做法将作为一项试验研究，与 OGD的科学家和临床医生，他们将帮助确定高风险的通用替代情况 用于评估研究策略的质量和一致性。