Disintegration And Dissolution Of Solid Oral Dose Forms In The Fed Stomach : Novel Insights Using MRI Imaging In Humans

固体口服剂型在胃中的崩解和溶解：利用人体 MRI 成像的新见解

• 批准号: 2753934
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2753934
• 关键词: Disintegration; Dissolution; Solid; Oral; Dose

Significant gaps remain in our basic knowledge of solid oral dosage form behaviour in the fed state. MRI imaging has the potential to provide new information on spatial and temporal processes occurring in the stomach. This iCASE collaboration between GSK and gastrointestinal imaging and specialists at the University of Nottingham addresses some of these key basic issues, with the potential to lead to better in-vitro and in-silico (modelling) tools for oral product development, and ultimately enhance our ability to tailor drug release in the fed state.The student will optimise and exploit the ability of MRI imaging to detect and characterise the behaviour of dosage forms in the fed stomach by:1) Identification and design of suitable test disintegrating formulations. 2) Optimisation of MRI techniques and image analysis for the evaluation of dosage form disintegration. In-vitro assessment will perform a key part of this work. 3) Evaluation of MRI techniques in human volunteers with carefully selected test formulations and test mealsThe student will benefit from a world-leading research environment, a unique multi-disciplinary approach with clear translational applications, and tailored training opportunities including training in image data processing, biomedical imaging, machine learning and artificial intelligence

我们对固体口服剂型在进食状态下的行为的基本知识仍存在重大差距。MRI成像有可能提供有关胃中发生的空间和时间过程的新信息。GSK与诺丁汉大学的胃肠成像和专家之间的iCASE合作解决了其中一些关键的基本问题，并有可能导致更好的体外和计算机模拟口腔产品开发（建模）工具，并最终增强我们在进食状态下定制药物释放的能力。学生将优化和利用MRI成像的能力来检测和识别通过以下方式在进食胃中对剂型进行评价：1）鉴定和设计合适的试验崩解制剂。2)用于评价剂型崩解的MRI技术和图像分析的优化。体外评估将是这项工作的关键部分。3)通过精心挑选的测试配方和测试餐在人类志愿者中评估MRI技术学生将受益于世界领先的研究环境，具有明确转化应用的独特多学科方法以及量身定制的培训机会，包括图像数据处理，生物医学成像，机器学习和人工智能方面的培训。