课题基金 / 基金详情

ACTION on cancer

ACTION on cancer
对癌症采取行动
批准号:
EP/R022925/1
负责人:
Ross King
金额:
$114.9万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --
关键词:

项目摘要

项目成果

Ross King的其他基金

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中文摘要
翻译
癌症死亡通常既缓慢又痛苦,很少有家庭能幸免于癌症的祸害。癌症也是世界上最大的杀手之一(到2025年,每年有1300万人死亡,2200万新病例),据估计,地球上每两个人就会在一生中的某个阶段患上癌症。在过去的30年里,我们对癌症的了解大大增加,现在,我们第一次了解了这种疾病的根本性质(S):癌细胞处理信息的方式发生了故障。我们身体中的所有细胞都会处理有关其内部状态的信息,并与邻居进行交流,当这种情况出现问题时,就会发生癌症。由于每个细胞都不同,这种信息处理可能会出错并导致癌症的方式非常不同,因此不可能设计出针对癌症的单一治疗方法,甚至是针对乳腺癌等亚类型癌症的治疗方法。相反,需要的是针对每个患者的癌症量身定做的个性化治疗。然而,这种个性化的治疗方法设计成本非常高,而且这样做的专业知识有限。此外,经常有必要进行定制设计的实验,以更好地了解什么是最好的治疗方法。因此,让每个人都能获得个性化癌症治疗的唯一方法是通过实验室自动化和人工智能(AI)的使用。在这个项目中,我们将开发ACTION,这将是一个用于设计个性化癌症治疗的原型AI系统。行动将专注于化疗-药物鸡尾酒的设计。给定关于癌症的初始信息,行动将从科学家开发的细胞信息处理的数据库和计算模型中提取它所能找到的关于癌症的所有相关知识。行动将合理地整合这些知识,并推断需要哪些额外的知识来做出如何治疗癌症的最佳决定。然后,ACTION将使用实验室机器人自动执行定制设计的实验,以确定丢失的信息。最后,利用它收集的所有知识,ACTION将决定最好的化疗方法。我们将使用实验室中培养的不同类型的癌细胞来评估ACTION。这避免了与病人合作的伦理复杂性,而且成本更低,速度更快。如果ACTION的开发成功,它将转移到对患者起源的癌症的测试。
英文摘要
Death from cancer is typically both slow and painful, and few families have been spared its scourge. Cancer is also one of the world's greatest killers (13 million deaths and 22 million new cases per year by 2025), and it is estimated that every second person on the planet will develop cancer at some stage of their life. Over the last 30 years our knowledge about cancer has increased enormously, and now, for the first time, we understand the fundamental nature of the disease(s): malfunctioning in the way that cancer cells process information. All the cells in our bodies process information about their internal state, and communicate with their neighbours, and when this goes wrong cancer can occur.As everyone's cells are different, and there are very many different ways that this information processing can go wrong and cause cancer, it is not possible to design a single treatment for cancer, or even for a sub-type of cancer such as breast cancer. Instead what is needed are personalised treatments tailored to each patient's cancer. However, such personalised treatments are very expensive to design, and the expertise to do so is limited. In addition, it is often necessary to execute custom designed experiments to better understand what is the best treatment. Therefore the only way to make personalised cancer treatment available to everyone is through laboratoryautomation, and the use of artificial intelligence (AI).In this project we will develop ACTION, which will be a prototype AI system for the design of personalised cancer treatments. ACTION will focus on chemotherapies - design of drug cocktails. Given initial information about a cancer ACTION will extract all the relevant knowledge it can find about the cancer, both from databases and computational models of cellular information processing that scientists have developed. ACTION will rationally integrate this knowledge, and infer what extra knowledge is required to make the best decision on how to treat the cancer. ACTION will then automatically execute custom designed experiments using laboratory robotics to determine the missing information. Finally, using all the knowledge it has gathered, ACTION will decide on the best chemotherapy.We will evaluate ACTION using different types of cancer cells grown in the laboratory. This avoids the ethical complexities of working with patients, and is much cheaper and faster. If the development of ACTION is successful it will then move to testing with patient derived cancers.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1007/s10994-020-05881-9
发表时间: 2020-08
期刊: Machine Learning
影响因子: 7.5
作者: [Oghenejokpeme I. Orhobor;N. Alexandrov;R. King]
通讯作者: Oghenejokpeme I. Orhobor;N. Alexandrov;R. King
DOI: 10.1073/pnas.2108013118
发表时间: 2021-12-07
期刊: Proceedings of the National Academy of Sciences of the United States of America
影响因子: 11.1
作者: [Olier I, Orhobor OI, Dash T, Davis AM, Soldatova LN, Vanschoren J, King RD]
通讯作者: King RD
Imbalanced regression using regressor-classifier ensembles
使用回归器-分类器集成的不平衡回归
DOI: 10.1007/s10994-022-06199-4
发表时间: 2022
期刊: Machine Learning
影响因子: 7.5
作者: [Orhobor O]
通讯作者: Orhobor O
A simple spatial extension to the extended connectivity interaction features for binding affinity prediction.
用于结合亲和力预测的扩展连接交互特征的简单空间扩展。
DOI: 10.17863/cam.92354
发表时间: 2022
期刊:
影响因子: --
作者: [Orhobor O]
通讯作者: Orhobor O
The Robot Experimentalist
  • 批准号:
    EP/X032418/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $112.29万
  • 财政年份:
    2023
  • 负责人:
    Ross King
  • 依托单位:
AMBITION: AI-driven biomedical robotic automation for research continuity
  • 批准号:
    EP/W004801/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $38.58万
  • 财政年份:
    2021
  • 负责人:
    Ross King
  • 依托单位:
ACTION on cancer
  • 批准号:
    EP/R022925/2
  • 项目类别:
    Research Grant
  • 资助金额:
    $78.55万
  • 财政年份:
    2020
  • 负责人:
    Ross King
  • 依托单位:
A Robot Chemist
  • 批准号:
    EP/S014128/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $31.0万
  • 财政年份:
    2019
  • 负责人:
    Ross King
  • 依托单位:
国内基金
海外基金
脊髓电刺激活化Na(V)1.1阳性GABA神经元持续缓解癌痛
  • 批准号:
    82371223
  • 项目类别:
    面上项目
  • 资助金额:
    49.00万元
  • 批准年份:
    2023
  • 负责人:
    闻大翔
  • 依托单位:
5'-tRF-GlyGCC通过SRSF1调控RNA可变剪切促三阴性乳腺癌作用机制及干预策略
  • 批准号:
    82372743
  • 项目类别:
    面上项目
  • 资助金额:
    49.00万元
  • 批准年份:
    2023
  • 负责人:
    陈卓佳
  • 依托单位:
丁酸梭菌代谢物(如丁酸、苯乳酸)通过MYC-TYMS信号轴影响结直肠癌化疗敏感性的效应及其机制研究
  • 批准号:
    82373139
  • 项目类别:
    面上项目
  • 资助金额:
    48.00万元
  • 批准年份:
    2023
  • 负责人:
    李孟鸿
  • 依托单位:
均相液相生物芯片检测系统的构建及其在癌症早期诊断上的应用
  • 批准号:
    82372089
  • 项目类别:
    面上项目
  • 资助金额:
    48.00万元
  • 批准年份:
    2023
  • 负责人:
    李万万
  • 依托单位: