Development and validation of a best practices framework for PBPK analysis for biopharmaceutic applications in support of model-informed biowaivers of fed state BE studies for BCS class II drugs

开发和验证生物制药应用 PBPK 分析的最佳实践框架，以支持 BCS II 类药物的联邦州 BE 研究的模型知情生物豁免

• 批准号: 10454243
• 负责人: Rodrigo Cristofoletti
• 金额: $ 30万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10454243
• 关键词: Development; validation; best; practices; framework

PROJECT SUMMARY Lower-cost generic drugs generated $313 billion in savings to the US healthcare system in 2019 and approximately $2.2 trillion in the past decade. Therefore, generic drugs play a pivotal role in the sustainability of the US health system. A generic drug is approved on the basis of sufficient demonstration of sameness to the corresponding brand-name drug. Critical evidence for approval is bioequivalence (BE). Even though well established, pharmacokinetic-based BE studies are both costly and lengthy. In the case of orally administered drug products, co-administration with food may influence oral absorption, thus BE should be demonstrated under both fasting and fed conditions if the reference listed drug labeling states the product can be taken with or without meals. This requirement poses an additional financial burden on generic manufacturers, which will ultimately be passed along to patients. Furthermore, the regulatory requirement of two in vivo BE studies slows down the generic drug product development process and may increase review cycles and attrition rates due to variability that is related to the drug itself rather than the formulation. Quantitative methods and modeling have been widely used in the realm of new drug discovery and development to inform more efficient and cost-effective development programs. Physiologically-based pharmacokinetic (PBPK) modeling is one of the key tools under the overarching umbrella of quantitative models. PBPK models are an effective tool to integrate information about the product characteristics, the physiology of the individual subject, and the variability among subjects within a population to simulate the absorption and subsequent systemic disposition of the drug without conducting in vivo PK studies. PBPK models have shown promise in supporting generic drug development and regulatory decision-making, since, under a model-integrated evidence perspective, it enables the leveraging of all prior knowledge generated to support the regulatory approval of the respective brand-name drug product. We will develop a best practices framework for integrating drug and drug product data together with gastrointestinal physiology in PBPK models tailored to oral drug administration to predict food-formulation interactions and promote biowaivers of fed state BE studies for poorly soluble and highly permeable drugs. This will be done at both the individual and population levels. We have excellent in vitro testing and PBPK modeling capabilities, along with unique PK and luminal drug concentration data sets. Once established, this framework can also be applied to address emerging issues in generic drug development and assessment, such as BE study protocol changes necessitated, for example, by pandemic situations and hypochlorhydria-formulation interactions.

项目概要 2019 年，低成本仿制药为美国医疗保健系统节省了 3130 亿美元 过去十年约2.2万亿美元。因此，仿制药在可持续发展方面发挥着关键作用。 美国的卫生系统。仿制药的批准是在充分证明与原药相同的基础上的 相应的品牌药。批准的关键证据是生物等效性（BE）。尽管很好 已建立的基于药代动力学的 BE 研究既昂贵又耗时。在口服给药的情况下 药品，与食物共同给药可能会影响口服吸收，因此应在以下条件下证明BE 空腹和进食条件下，如果参考列出的药物标签说明该产品可以服用或不服用 膳食。这一要求给仿制药制造商带来了额外的财务负担，最终将 传递给患者。此外，两项体内 BE 研究的监管要求减慢了 仿制药产品开发过程，并可能由于变异性而增加审查周期和损耗率 这与药物本身有关，而不是与配方有关。 定量方法和建模已广泛应用于新药发现和开发领域 为更高效、更具成本效益的发展计划提供信息。基于生理学的药代动力学 （PBPK）建模是定量模型总体框架下的关键工具之一。 PBPK模型 是整合有关产品特性、个人生理信息的有效工具 受试者，以及群体内受试者之间的变异性，以模拟吸收和随后的情况 药物的全身处置，无需进行体内 PK 研究。 PBPK 模型在以下领域显示出前景： 支持仿制药开发和监管决策，因为在模型综合证据下 从角度来看，它能够利用生成的所有先验知识来支持监管部门的批准 各自的品牌药品。 我们将开发一个最佳实践框架，将药品和药品数据与 PBPK 模型中的胃肠道生理学适合口服药物给药以预测食物配方 相互作用并促进联邦州对难溶性和高渗透性药物的 BE 研究的生物豁免。这 将在个人和人口层面进行。我们拥有出色的体外测试和PBPK建模 功能，以及独特的 PK 和管腔药物浓度数据集。这个框架一旦建立 也可应用于解决仿制药开发和评估中出现的新问题，例如BE研究 例如，由于流行病和胃酸过少而需要改变方案 互动。