Subtopic 1 : Population pharmacokinetic and pharmacodynamic, dose-toxicity modleing and simulation for narrow therapeutic index (NTI) drugs

项目摘要 联邦法规法典将狭义治疗指数(NTI)药物定义为那些 半数致死剂量和半数有效剂量相差超过2倍或不到2倍 血液中最低毒性浓度和最低有效浓度的差异。 然而，目前还缺乏一套明确客观的启发式方法来定义非专利技术。有一个明确的客观定义是 从监管和行业角度来看，这是至关重要的。 CFR暗示在生物等效性(BE)评价中将NTI作为一个因素。有几个 强调如果在品牌和品牌之间发生转换会对疗效和安全性产生负面影响的出版物 非专利药品的仿制药。此外，药学咨询委员会(ACPS) 在2010年4月的一次会议上建议FDA制定一份具有明确专门知识的NTI药物清单 对于NTI药物来说，标准和现行的BE标准是不够的。这突显了 为评估NTI药物的BE制定准确、客观的标准。 本研究的目的是利用药代动力学(PK)、药效学(PD)的原理 和PK/PD关系的陡度，以提出识别NTI药物的定量指标和建议的BE 标准，以更好地理解品牌药物和仿制药之间的区别。模拟以及 将利用出版的NTI药物的文献信息进行分析。质量方面，包括 疾病的严重性和不良事件的可逆性将被纳入决策树。这个 将通过应用于批准的NTI和非NTI来评估决策树的敏感性和特异性 毒品。然后根据治疗目标的统计比较对BE标准进行评估 (超过治疗窗口的患者比例和治疗窗口以下的患者比例) 还有仿制药。此外，将评估PK生物等效性的不同标准以确定 应选择哪种PK生物等效性标准来满足给定的治疗生物等效性标准 在品牌和非专利之间。此步骤将涉及对经批准的品牌和仿制药的PK和PD进行模拟 被认为是NTI的药物。 这项研究的可交付成果将是)决策树，它将结合定性和 判定一种药物是否属于非专利药品的定量特征b)非专利药品生物等效性标准 纳入PK信息的药品以及批准的品牌和仿制药的治疗窗口。

Project Summary The Code of Federal Regulations has defined narrow therapeutic index (NTI) drugs as those having less than 2 - fold difference in median lethal dose and median effective dose or have less than a 2 - fold difference in the minimum toxic concentrations and minimum effective concentrations in the blood. However, there is lack of clear objective set of heuristics to define NTI. Having a clear objective definition is critical from regulatory and industry points of view. The CFR alludes to consider NTI as a factor during bioequivalence (BE) evaluation. There are several publications highlighting the negative impact on efficacy and safety if switching occurs between brand and generic forms of NTI drugs. Furthermore, the Advisory Committee for Pharmaceutical Sciences (ACPS) recommended in April 2010 meeting that the FDA should develop a list of NTI drugs with clear specialized criteria and the current BE standards are not sufficient for NTI drugs. This highlights the importance of development of precise, objective criteria for assessing the BE for NTI drugs. The objective of this research is to utilize principles of pharmacokinetics (PK), pharmacodynamics (PD) and steepness of PK/PD relationship to propose quantitative metrics to identify NTI drugs and propose BE criteria to better understand the difference between brand and generic drugs. Simulations as well as published literature information for NTI drugs will be utilized for analysis. Qualitative aspects including the severity of disease and reversibility of adverse events will be incorporated in the decision tree. The decision tree will be evaluated for sensitivity and specificity by applying to approved NTI and non NTI drugs. Followed by evaluation of BE criteria based on statistical comparison of therapeutic goalposts (proportion of patients exceeding and proportion of patients below the therapeutic window) for the brand and the generic drug. In addition, different criteria for PK bioequivalence will be evaluated to determine which PK bioequivalence criteria should be chosen to satisfy a given criteria for therapeutic bioequivalence between brand and generic. This step will involve simulations of PK and PD of approved brand and generic drugs considered as NTI. The deliverables from this research will be a) decision tree that will incorporate both qualitative and quantitative features for deciding whether a drug belongs to NTI or not b) bioequivalence criteria for NTI drugs incorporating information from PK and therapeutic window of approved brand and generic drugs.