Evaluation of Oral Modified-Release Tablets to Support the Approval of Additional Strengths

评估口服缓释片以支持其他规格的批准

• 批准号: 10937015
• 负责人: Jie Shen
• 金额: $ 20万
• 依托单位: NORTHEASTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10937015
• 关键词: Evaluation; Oral; Modified; Release; Tablets

ABSTRACT Oral modified-release (MR) drug products with modulated drug release characteristics (e.g., rate, duration, and the site of drug release) have been widely used to achieve desired therapeutic effects, reduced adverse effects and/or improved patient compliance than conventional oral solid dosage forms. More than half of the FDA approved oral MR drug products are extended-release (ER) tablet products with multiple strengths. Until now, appropriate factors to scale the formulation for additional strengths for oral MR tablets have yet to be determined. Moreover, the key variables affecting drug release mechanism and formulation design spaces for different MR technologies have not been fully understood and identified. The main objectives of this project are to: 1) determine the impact of formulation variables (e.g., drug properties and excipients) on the drug release mechanism of in-house made ER tablets based on quality-by-design (QbD) principles; 2) develop mechanistic models parameterized with dissolution data obtained using comprehensive dissolution testing technologies to compare the ER tablets and the corresponding reference drug products across multiple strengths to establish dissolution safe spaces and to identify critical quality attributes (CQA’s); and 3) construct a “proof-of-concept” machine learning model leveraging the database of complex oral MR drug products to identify key variables that affect drug release mechanisms for different formulation design strategies. The proposed research builds upon our extensive research on the formulation development, comparative product characterization, in vitro dissolution testing as well as bioequivalence assessment and mechanistic modeling of complex oral MR solid dosage forms. Biopharmaceutics classification system (BCS) Class I and Class II compounds ropinirole hydrochloride and nifedipine will be studied as model drugs, respectively. ER tablets across multiple strengths with formulation and process variables will be produced and comparatively characterized using the corresponding reference drug products as controls. The drug release mechanism and in vitro dissolution profiles of the ER tablets across multiple strengths will be characterized under different testing conditions including fasted and fed conditions with simulated gastrointestinal motility. Moreover, mechanistic models (e.g., physiologically based pharmacokinetic (PBPK), physiologically based biopharmaceutics models (PBBM)-PBPK) parameterized with the in vitro data obtained will be developed to identify appropriate factors to scale the formulation for additional strengths for oral MR tablets. Lastly, a comprehensive database of the approved oral MR drug products will be established, and ML techniques will be employed to identify the key variables that impact drug release mechanism. The proposed research will help advance the regulatory review and approval processes of oral MR tablet products, and support the approval of additional strengths for such drug products. Facilitating the development of complex generic oral MR drug products will ultimately help increase the public access to high quality and affordable oral medications.

抽象的 具有调节药物释放特性（例如速率、持续时间和 药物释放部位）已被广泛使用以达到预期的治疗效果，减少不良反应 和/或比 FDA 传统口服固体剂型提高了一半以上的患者依从性。 迄今为止，已批准的口服 MR 药物产品是具有多种优势的缓释 (ER) 片剂产品。 调整口服缓释片剂配方以获得额外强度的适当因素尚未确定。 此外，影响不同MR药物释放机制和制剂设计空间的关键变量 技术尚未得到充分理解和确定。该项目的主要目标是：1) 确定配方变量（例如药物特性和赋形剂）对药物释放的影响 基于质量源于设计 (QbD) 原则的自制缓释片机制 2) 开发机制； 使用综合溶出测试技术获得的溶出数据参数化的模型 比较缓释片剂和相应的参考药品的多种优势，以确定 溶出安全空间并确定关键质量属性 (CQA)；3) 构建“概念验证”； 机器学习模型利用复杂的口服 MR 药品数据库来识别关键变量 影响不同制剂设计策略的药物释放机制。 我们对配方开发、产品比较表征、体外溶出度进行了广泛的研究 复杂口服 MR 固体剂型的测试以及生物等效性评估和机制建模。 生物制药分类系统 (BCS) I 类和 II 类化合物盐酸罗匹尼罗和 硝苯地平将分别作为多种规格的缓释片剂的模型药物进行研究。 将产生过程变量并使用相应的参考药物进行比较表征 缓释片剂的药物释放机制和体外溶出曲线。 将在不同的测试条件下表征多种强度，包括禁食和进食条件 此外，模拟胃肠运动。 （PBPK），基于生理的生物药剂学模型（PBBM）-PBPK）用体外数据参数化 所获得的结果将被开发以确定适当的因素来调整配方以获得额外的口服强度 最后，将建立已批准的口服 MR 药物产品的综合数据库，并且 将采用机器学习技术来识别影响药物释放机制的关键变量。 研究将有助于推进口服 MR 片剂产品的监管审查和批准流程，并支持 批准此类药品的额外优势，促进复杂仿制药口服药物的开发。 MR 药品最终将有助于增加公众获得高质量且负担得起的口服药物的机会。