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Prediction of Structure and Stability of Amorphous Pharmaceuticals

Prediction of Structure and Stability of Amorphous Pharmaceuticals
无定形药物的结构和稳定性预测
批准号:
2746941
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
翻译
重点研究非晶态活性药物成分和微晶非晶态体系的结构和稳定性预测。它将筛选一系列原料药,将其配制为无定形材料,并确定其固态结构,以便为无定形药物建立新的数据库。随后,它将使用数据驱动的方法来确定非晶态稳定指数。原料药分子库将涵盖大小、结构复杂性和生物制药特性,以及来自选定MC-A系统的数据。材料将与测量和计算的分子数据相关,包括从文献中挖掘的数据。根据需要,将使用自动化、小规模的热法与其他方法一起制备非晶样样本库。将控制和记录工艺条件,并以标准化的样品制备和数据收集/还原方法对生成的样品进行测试,以优化测量数据质量。关键材料、工艺、设备和模型信息的元数据要求将为今后的比较研究提供背景。XRPD,DSC将提供所有样品的初步表征,使用X射线对分布函数、光谱分析、热分析、层析成像、显微镜和AFM分析局部、整体和表面结构,并利用关键物理性质补充以上分子数据。来自分子的计算输出也将被捕获。加速稳定性研究将评估每个样品在相关条件下开始结晶的时间,为训练ASI提供响应数据。AMDb将用于训练和基准ML模型,以开发ASI。这份非晶态稳定性的数字开发指南将允许用户预测给定分子的结晶阻力,从而迅速表明需要替代的稳定策略。PDF已被用于指纹分析纳米结晶度和储存过程中的非晶态变化。我们将使用高级散射和建模来研究选定原料药的分子结构、分子间堆积和稳定性之间的关系。新的结构改进方法允许将MD派生的模型拟合到实验性的PDF,从而实现模型改进。-描述非晶态API和MC-A的全面、公平的结构和物理化学数据;-独特的APDB结构--非晶态固体的属性数据库;-经过验证的基于ML的ASI,可根据分子结构预测非晶态行为;-预测可开发性模型,以选择基于ASI的配方体系的属性。在提供研究非晶态的基本理解和新工具方面,DDMAP将为新材料、产品和制造创造机会。制药是英国最大的制造业出口行业。然而,英国和欧洲的行业在保持其在全球经济中的竞争地位方面面临严峻挑战,而新冠肺炎只是让人们关注了我们面临的挑战。2020年的“欧洲药品战略”旨在“确保欧洲各地的患者在任何情况下都能迅速地在本国获得新药和疗法,并减少药品短缺”。应该确保这一点,同时提供允许个性化药物、打击假冒产品和减少相关制造的环境足迹的解决方案。通过我们的研究,我们实现了对HME和添加剂制造等工艺的更大开发,以及用于药品的预测性、数字化设计方法,从而解决了这一问题。我们还培养了一批训练有素的PDRA和博士生,他们精通尖端科学,具有高度发展的多学科和协作能力,准备成为这一令人兴奋的领域的未来领导者。
英文摘要
Focus on structure and stability prediction of amorphous active pharmaceutical ingredient and microcrystalline amorphous systems. It will screen a range of APIs, formulate as amorphous materials and determine their solid-state structure in order to populate a new data repository for amorphous pharmaceuticals. It will subsequently use data-driven approaches to determine an Amorphous Stability Index.The API molecule library will cover size, structural complexity and biopharmaceutical properties plus data from select mc-A systems. Materials will be related with measured and calculated molecular data including data mined from literature. Automated, small scale thermal methods will be used to prepare amorphous sample libraries with other methods as needed. Process conditions will be controlled and recorded and the resultant samples tested in Standardised sample preparation and data collection/reduction approaches will optimise measurement data quality. Metadata requirements for key material, process, equipment, and modelling information will give context for future comparative studies. XRPD, DSC will provide primary characterisation of all samples with analysis of local, bulk and surface structure using X-ray pair distribution function, spectroscopy, thermal, tomography, microscopy and AFM with key physical properties complement molecular data from above. Calculated outputs from molecular will also be captured. Accelerated stability studies will assess time to onset of crystallisation for each sample under relevant conditions giving response data to train the ASI.The AMDb will be used to train and benchmark ML models to develop the ASI. This digital development guide for amorphous stability will allow users to predict resistance to crystallisation for given molecules, rapidly indicating the need for alternative stabilisation strategies.PDF has been used to fingerprint nanocrystallinity4 and amorphous changes during storage. We will use advanced scattering and modelling to investigate the relationship between molecular structure, intermolecular packing and stability in selected APIs. New structure refinement methods allow fits of MD derived models to experimental PDF enabling model refinement. International facilities for ssNMR, synchrotron and neutron for time-resolved studies will be used when required.Deliverables:-Comprehensive, FAIR structural and physicochemical data describing amorphous API and mc-A;-Unique APDb structure-property database for amorphous solids;-Validated ML based ASI to predict amorphous behaviour based on molecular structure;-Predictive developability model to select properties of formulated systems based on ASI.In delivering the fundamental understanding and new tools for investigating amorphous state, DDMAP will create opportunities for novel materials, products and manufacturing. Pharma is the UK's largest manufacturing export sector. However, the UK and European industries face serious challenges to maintain their competitive position in the global economy and COVID-19 has only served to throw a spotlight on the challenge facing us. The "Pharmaceutical strategy for Europe" 2020 aims to "make sure that patients across Europe have new medicines and therapies in their countries quickly and under all circumstances and that there are fewer shortages of medicines". This should be ensured while at a same time delivering solutions allowing for personalised medicine, combating falsified products, and reducing the environmental footprint of related manufacturing. We address this by enabling the greater exploitation of processes such as HME and additive manufacturing coupled with predictive, digital design methodologies for pharmaceuticals through our research. We also deliver a talented cohort of trained PDRA and doctoral students skilled in state-of-the-art science and with highly developed multidisciplinary and collaborative abilities, primed to be the future leaders in this exciting area.
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