Adaptive Statistical Methods for Category Specific Release Testing of Drug Products

药品类别特定释放测试的自适应统计方法

• 批准号: 9168711
• 负责人: Kenneth Morris
• 金额: $ 100万
• 依托单位: LONG ISLAND UNIVERSITY BROOKLYN CAMPUS
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9168711
• 关键词: Adaptive; Statistical; Methods; Category; Specific

Project Summary/Abstract The main goal of this proposal is to generate data and develop a statistical sampling/analysis strategy to aid FDA/COER policy in drafting data-based guidance in support of the use of appropriate statistical tools and standards. The goal will be addressed by organizing the work under the following specific aims: 1) Selection of recently distributed pharmaceutical products: Develop a selection rationale to identify major dosage form categories based on the complexity of the dosage form and key characteristics including dose, release mechanism, BCS, therapeutic index, and manufacturing method. 2) Sampling organization and data generation: Organize the sampling to insure that sufficient data are collected for the range of statistical treatments to be developed and tested. Generate the data for selected critical quality, chemical and physical attributes (e.g., tablet weight, hardness, friability, assay, content uniformity, and dissolution) and determine the mean and variance of the entire sample. 3)Comparative estimation accuracy of current/proposed models: Using current standards and alternate models' ability to predict the means and variance against those actually observed from experimentation. 4) Generate standards and alternates for dosage form category specific statistical methods: Develop and identify approaches for inter and intra-category variability suitable for lot release for the categories of dosage forms studied. Variability in the way drug products perform is a major reason for product recalls and potentially negative outcomes in the patient population. This variability may be manifested in the physical-chemical characteristics of the final dosage form as produced, the way it delivers the drug substance, or the way it retains the desired behavior with time, i.e., the self-life. The goal of process control and product testing is to assess the quality of the dosage forms upon release to detect issues and to anticipate problems that may occur during its shelf-life. Because different dosage forms may be designed to perform differently and be variable over a range of characteristics, the proposed project will provide both an exhaustive benchmarking of the variability over the range of dosage forms currently marketed and advanced statistical analysis tools that are “tailored” to identity meaningful variability within each categories of dosage form identified. This will be driven by an adaptive statistical approach for directing the experimentation as well as developing to desired dosage form category specific tools. The significance of the project is that; 1) it will provide targeted statistical methods to be applied to product release and trouble shooting for the major dosage form categories, and 2) these methods will facilitate the review and approval of new drug products and generic drug products. Together this means higher quality, reduced time to market, and reduced cost.

项目总结/摘要 本提案的主要目标是生成数据和制定统计抽样/分析战略 协助FDA/COER政策起草基于数据的指南，以支持使用适当的统计数据， 工具和标准。为实现这一目标，将按照以下具体目标安排工作： 1)最近分销的药品的选择：制定选择依据，以确定主要 基于剂型的复杂性和包括剂量的关键特征的剂型类别， 释放机制、BCS、治疗指数和制造方法。2)取样组织和数据 生成：组织抽样，以确保为统计范围收集足够的数据。 待开发和测试的治疗方法。生成选定的关键质量、化学和物理数据 属性（例如，片剂重量、硬度、脆碎度、含量测定、含量均匀度和溶出度），并测定 整个样本的均值和方差。3)当前/拟议模型的比较估计准确度： 使用当前标准和替代模型的能力来预测均值和方差， 从实验观察。4)生成特定剂型类别的标准品和替代品 统计方法：制定和确定适用于批次内部和类别内差异的方法 研究剂型类别的放行。 药品性能的变化是产品召回的主要原因， 患者人群的结果。这种变化可能表现在物理化学特性上， 生产的最终剂型，其递送药物的方式，或其保留所需药物的方式， 随时间变化的行为，即，自我生活。过程控制和产品测试的目标是评估产品的质量， 剂型在释放时检测问题并预测在其保质期内可能发生的问题。 因为不同的剂型可以被设计成不同地执行并且在一定范围内是可变的， 特性，拟议的项目将提供一个详尽的基准变化超过 目前市售的一系列剂型和先进的统计分析工具， 确定了各剂型类别内有意义的变异性。这将由一个适应性的 用于指导实验以及开发所需剂型类别的统计方法 具体工具。该项目的意义在于：1）它将提供有针对性的统计方法， 适用于主要剂型类别的产品放行和故障排除，以及2）这些 方法将促进新药和仿制药的审评和批准。 这意味着更高的质量、更短的上市时间和更低的成本。