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Predictive Design of Polymer-Based Amorphous Solid Dispersion

Predictive Design of Polymer-Based Amorphous Solid Dispersion
聚合物基非晶固体分散体的预测设计
批准号:
2030991
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:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
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英文摘要
Amorphous solid dispersions comprising drug dissolved in polymers are known to enhance the dissolution performance and bioavailability of poorly water soluble drug. The exploitation of these approaches in marketed products has however been limited because of the inherent instability of the amorphous form, leading to physical instability and recrystallisation of the active ingredient rendering the product inactive. Thus, designing stable dispersed systems is a major challenge in the development of polymer based amorphous molecular dispersions. The aim of this project is to develop and test approaches for applying pair distribution function (PDF) analysis to reveal local short-range structure, and assess the ability to predict stable, metastable or unstable formulations. Specifically the project will develop tools that provide insight into structure-process-property interactions towards more predictive design of amorphous materials and formulated systems through control of short range packing within known solubility ranges. In addition, the project will provide experimental data to contribute to the development of advanced group contribution methods for drug-polymer solubility prediction. The aim of this project is to develop and test approaches for applying pair distribution function (PDF) analysis to reveal local short-range structure, and assess the ability to predict stable, metastable or unstable formulations. Specifically the project will develop tools that provide insight into structure-process-property interactions towards more predictive design of amorphous materials and formulated systems through control of short range packing within known solubility ranges. In addition, the project will provide experimental data to contribute to the development of advanced group contribution methods for drug-polymer solubility prediction. - The project will involve preparation of amorphous materials utilising melt-quench, lyophilisation and spray drying and exploit a suite of physical analysis methods in addition to x-ray scattering for PDF generation. - PDF analysis will be with combined with other techniques available in the CMAC National Facility including DSC, dissolution, nano-CT, imaging spectroscopies, AFM and ToF-SIMS to provide an unprecedented insight into the homogeneity, structure, physical composition and performance of molecular dispersions. Multivariate data analysis will be utilised to identify early changes in phase composition marking the onset of instability.- Solubility and phase composition data determined from these well characterised systems will then contribute directly to the development and testing of solubility predictions utilising the novel gSAFT framework being developed by collaborators at Imperial College (C. Adjiman).
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DOI: 10.1021/acs.molpharmaceut.9b00703
发表时间: 2019-10-01
期刊: MOLECULAR PHARMACEUTICS
影响因子: 4.9
作者: [Bordos, Ecaterina, Islam, Muhammad T., Robertson, John]
通讯作者: Robertson, John
国内基金
海外基金
Applications of AI in Market Design
  • 批准号:
    --
  • 项目类别:
    外国青年学者研 究基金项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    Manshu Khanna
  • 依托单位:
基于“Design-Build-Test”循环策略的新型紫色杆菌素组合生物合成研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2021
  • 负责人:
  • 依托单位:
在噪声和约束条件下的unitary design的理论研究
  • 批准号:
    12147123
  • 项目类别:
    专项基金项目
  • 资助金额:
    18万元
  • 批准年份:
    2021
  • 负责人:
    顾炎武
  • 依托单位: