Chemical Cartography via High-Throughput Experimentation: Predictive Models, Catalyst Development, and New Synthetic Methodology

通过高通量实验进行化学制图:预测模型、催化剂开发和新的合成方法

基本信息

  • 批准号:
    RGPIN-2019-04985
  • 负责人:
  • 金额:
    $ 2.99万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2022
  • 资助国家:
    加拿大
  • 起止时间:
    2022-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

Organic synthesis is among the most impactful scientific developments in history, dramatically improving quality of life via breakthroughs in medicine, agriculture, and materials. Despite these advances and more than a century of research, in most labs the practice of organic synthesis is remarkably unchanged from how it was done in the early 1900s. Individual chemical reactions are optimized through an iterative and often trial-and-error approach using single experiments carried out in flasks. While this has worked well in the past, we are now at a point where continued progress in the field requires new, more efficient techniques and tools to enable a deeper understanding of chemical reactivity. The theme of the Leitch group program is "the exploration of uncharted chemical space." This means finding new points on the map (novel chemical structures), and studying the paths between these points (chemical reactivity). Specifically, we will address a centrally important but still unsolved problem in organic chemistry: how can one predict chemical reactivity in a quantitative manner, and use these predictions to develop new and more efficient chemical syntheses? My group will tackle this problem by combining fundamental physical chemistry principles with modern high-throughput experimental methods and data analytics. We will use this approach to generate quantitative mechanistic models - i.e. maps of chemical reactivity - for key chemical reactions currently used for pharmaceutical synthesis, and to develop scalable syntheses of novel three-dimensional carbon frameworks that are at the forefront of modern drug discovery research. Critical to this endeavour is the simultaneous measurement of hundreds-to-thousands of chemical reaction rates and activation energies using high-throughput experimentation. Combining these values with computed molecular parameters for each chemical species will generate large, reliable, and consistent data sets. The size and mechanistic foundation of these data sets will be a distinct advantage in building meaningful quantitative models via algorithm-driven statistical analysis. These models will allow us to predict the outcome of a chemical reaction under a variety of hypothetical conditions, leading to a deeper and more holistic understanding of the factors that control chemical reactivity. The potential impact of this research in both academic and industrial contexts is substantial. The ability to predict the outcome of a given reaction will save countless person-hours in the pursuit of new therapeutics, agrochemicals, and advanced materials. Being able to quantitatively map how chemical structure affects reactivity will enable the discovery of new and more efficient syntheses in a rational manner. Finally, our reactivity maps will be powerful data sets on which to build predictive artificial intelligence systems for chemical synthesis design; this facet is one of the ultimate goals of this program.
有机合成是历史上最具影响力的科学发展之一,通过在医学、农业和材料方面的突破,极大地提高了生活质量。尽管有了这些进步和一个多世纪的研究,在大多数实验室里,有机合成的实践与20世纪初的做法相比,没有明显的变化。单个化学反应是通过在烧瓶中进行的单个实验的迭代和经常试错的方法来优化的。虽然这在过去很有效,但我们现在所处的阶段是,该领域的持续进步需要新的、更有效的技术和工具,以便更深入地了解化学反应性。利奇小组项目的主题是“探索未知的化学空间”。这意味着在地图上寻找新的点(新的化学结构),并研究这些点之间的路径(化学反应性)。具体来说,我们将解决有机化学中一个重要但仍未解决的问题:如何以定量的方式预测化学反应性,并利用这些预测来开发新的、更有效的化学合成?我的小组将通过将基本的物理化学原理与现代高通量实验方法和数据分析相结合来解决这个问题。我们将使用这种方法为目前用于药物合成的关键化学反应生成定量机制模型,即化学反应性图,并开发新型三维碳框架的可扩展合成,这是现代药物发现研究的前沿。这项工作的关键是使用高通量实验同时测量成百上千的化学反应速率和活化能。将这些值与计算出的每种化学物质的分子参数相结合,将生成大型、可靠和一致的数据集。这些数据集的规模和机制基础将是通过算法驱动的统计分析建立有意义的定量模型的明显优势。这些模型将使我们能够在各种假设条件下预测化学反应的结果,从而对控制化学反应的因素有更深入、更全面的了解。这项研究在学术和工业背景下的潜在影响是巨大的。预测某一特定反应结果的能力,将在研发新疗法、农用化学品和先进材料的过程中节省无数工时。能够定量绘制化学结构如何影响反应性,将有助于以合理的方式发现新的、更有效的合成。最后,我们的反应性图将成为强大的数据集,为化学合成设计构建预测性人工智能系统;这方面是这个项目的最终目标之一。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Leitch, David其他文献

Leitch, David的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Leitch, David', 18)}}的其他基金

Manufacture of Active Pharmaceutical Ingredients using Transition Metal Catalysts for Selective Functionalization of C-H Bonds
使用过渡金属催化剂选择性官能化 C-H 键来制造活性药物成分
  • 批准号:
    557162-2020
  • 财政年份:
    2021
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Alliance Grants
A universal palladium precatalyst for efficient chemical synthesis of molecules and materials
用于高效化学合成分子和材料的通用钯预催化剂
  • 批准号:
    561560-2021
  • 财政年份:
    2021
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Idea to Innovation
Chemical Cartography via High-Throughput Experimentation: Predictive Models, Catalyst Development, and New Synthetic Methodology
通过高通量实验进行化学制图:预测模型、催化剂开发和新的合成方法
  • 批准号:
    RGPIN-2019-04985
  • 财政年份:
    2021
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Discovery Grants Program - Individual
A Modular Continuous Flow System for the Synthesis of Molecules and Materials
用于分子和材料合成的模块化连续流系统
  • 批准号:
    RTI-2022-00385
  • 财政年份:
    2021
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Research Tools and Instruments
Chemical Cartography via High-Throughput Experimentation: Predictive Models, Catalyst Development, and New Synthetic Methodology
通过高通量实验进行化学制图:预测模型、催化剂开发和新的合成方法
  • 批准号:
    RGPIN-2019-04985
  • 财政年份:
    2020
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Discovery Grants Program - Individual
Manufacture of Active Pharmaceutical Ingredients using Transition Metal Catalysts for Selective Functionalization of C-H Bonds
使用过渡金属催化剂选择性官能化 C-H 键来制造活性药物成分
  • 批准号:
    557162-2020
  • 财政年份:
    2020
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Alliance Grants
Chemical Cartography via High-Throughput Experimentation: Predictive Models, Catalyst Development, and New Synthetic Methodology
通过高通量实验进行化学制图:预测模型、催化剂开发和新的合成方法
  • 批准号:
    DGECR-2019-00241
  • 财政年份:
    2019
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Discovery Launch Supplement
Chemical Cartography via High-Throughput Experimentation: Predictive Models, Catalyst Development, and New Synthetic Methodology
通过高通量实验进行化学制图:预测模型、催化剂开发和新的合成方法
  • 批准号:
    RGPIN-2019-04985
  • 财政年份:
    2019
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Discovery Grants Program - Individual
Ultra-High Performance Liquid Chromatography as a High-Throughput Analytics Platform for Organic Chemistry
超高效液相色谱作为有机化学的高通量分析平台
  • 批准号:
    RTI-2019-00343
  • 财政年份:
    2018
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Research Tools and Instruments
Palladium-Catalyzed Multicomponent Synthesis of Structurally Diverse Conjugated Polymers for Organic Electronic Devices
用于有机电子器件的结构多样共轭聚合物的钯催化多组分合成
  • 批准号:
    403833-2011
  • 财政年份:
    2013
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Postdoctoral Fellowships

相似海外基金

Gravity Cartography Catalyst
重力制图催化剂
  • 批准号:
    10107128
  • 财政年份:
    2024
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Small Business Research Initiative
OSIB: Metabolic cartography of influenza A virus infection and host-pathogen interaction in the natural and accidental host
OSIB:自然和意外宿主中甲型流感病毒感染和宿主-病原体相互作用的代谢制图
  • 批准号:
    2318557
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Standard Grant
What was, is, and might be: Cartography on Arctic Shores
过去、现在和可能是什么:北极海岸的制图
  • 批准号:
    2885198
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Studentship
The genetic and epigenetic cartography of multiple myeloma
多发性骨髓瘤的遗传和表观遗传制图
  • 批准号:
    10648380
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
The Cartography of the Political Novel in Europe
欧洲政治小说的制图
  • 批准号:
    10051867
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    EU-Funded
The Cartography of the Political Novel in Europe
欧洲政治小说的制图
  • 批准号:
    10073486
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    EU-Funded
OSIB: Metabolic cartography of influenza A virus infection and host-pathogen interaction in the natural and accidental host
OSIB:自然和意外宿主中甲型流感病毒感染和宿主-病原体相互作用的代谢制图
  • 批准号:
    2344946
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Standard Grant
The Cartography of the Political Novel in Europe
欧洲政治小说的制图
  • 批准号:
    10061848
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    EU-Funded
GCC - Gravity Cartography Catalyst
GCC - 重力制图催化剂
  • 批准号:
    10084679
  • 财政年份:
    2023
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Small Business Research Initiative
CIF: Small: Latent Neural Factor Models for Radio Cartography From Bits
CIF:小:来自 Bits 的无线电制图的潜在神经因子模型
  • 批准号:
    2210004
  • 财政年份:
    2022
  • 资助金额:
    $ 2.99万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了