Innovative precision medicine methods in subgroup identification for Alzheimer's disease
阿尔茨海默病亚组鉴定的创新精准医学方法
基本信息
- 批准号:10740649
- 负责人:
- 金额:$ 23.33万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-01 至 2025-06-30
- 项目状态:未结题
- 来源:
- 关键词:AccelerationAddressAducanumabAffectAgingAlzheimer&aposs DiseaseAmericanAreaBehavioralBiologicalCause of DeathCharacteristicsClinical DataClinical TrialsCognitiveCollaborationsCommunitiesComputer softwareCountryDataDementiaDevelopmentDiseaseDisease ProgressionFutureGoalsGroupingHealthHealthcareIndividualInvestigational DrugsInvestigational TherapiesKnowledgeMachine LearningMeasuresMethodologyMethodsModelingOutcomePatient SelectionPatientsPersonsPharmaceutical PreparationsPharmacotherapyPopulationPopulation HeterogeneityPublic HealthReportingResearchResearch PersonnelSelection for TreatmentsSubgroupTherapeutic AgentsTreatment outcomeTreesanalytical methodanalytical tooldata miningdesigndonepezilevidence baseflexibilityimprovedindividual variationindividualized medicineinnovationinterestnovelnovel therapeuticspaymentprecision medicinepreventprimary outcomeprospectiveresponsetooltreatment effecttreatment researchtreatment responsetreatment trialuser-friendly
项目摘要
is a major and rapidly increasing public health concern: over 30 million individuals
worldwide suffer from AD, which is projected to quadruple by 2050. AD has been reported to be the third leading
cause of death in the US. With this impending global public health crisis, treatments that prevent onset or slow
progression of AD are urgently needed but rarely available until the recent accelerated approval for aducenumab.
Therefore, it is of great interest to identify subpopulations which benefit most from a medication when the overall
treatment effect is minimum or not clinically meaningful. If such subpopulations can be identified, some of the
treatments from the negative trials can be proven to at least help a portion of the AD population. In this proposal
we will employ non-parametric interaction tree (IT)-based methods on mixed models for repeated measures
(MMRM) and regression-based methods to identify such subpopulations. IT for MMRM builds on the assessment
of the treatment-by-covariates interactions and can automatically seek subgroups of individuals in whom the
treatment shows heterogeneous effects. We also explore a new and more attractive fusion penalty approach for
final tree determination without any prior knowledge of grouping information. The regression-based methods aim
to identify subpopulations who will benefit from AD treatment based on their characteristics, which is very flexible
to make individualized treatment selection. Finally, we will develop and disseminate a user-friendly statistical
software package that will enable researchers to implement these methods with ease. Our extensions will better
capture individual heterogeneity in disease progression and facilitate evidence-based precision medicine in
future AD studies and other research areas.
是一个主要的和迅速增长的公共卫生问题:超过3000万人
全球范围内都遭受着AD,预计到2050年将翻两番。据报道,AD是第三大
美国的死因。随着这场即将到来的全球公共卫生危机,
AD进展是迫切需要的,但在最近加速批准aducenumab之前很少可用。
因此,当总体药物治疗效果不佳时,确定从药物治疗中获益最多的亚群是非常有意义的。
治疗效果最小或无临床意义。如果能够确定这些亚群,
来自阴性试验的治疗可以被证明至少帮助一部分AD人群。本提案中
我们将在重复测量的混合模型上使用基于非参数交互树(IT)的方法
(MMRM)和基于回归的方法来识别这些亚群。IT for MMRM基于评估
治疗与协变量的相互作用,并可以自动寻找其中
治疗显示出异质效应。我们还探索了一种新的,更有吸引力的融合惩罚方法,
最终的树确定而无需分组信息的任何先验知识。基于回归的方法旨在
根据其特征确定将从AD治疗中获益的亚群,这是非常灵活的
进行个体化治疗选择。最后,我们会编制和发放一套方便使用的统计数字,
软件包,使研究人员能够轻松实现这些方法。我们的扩展会更好
捕获疾病进展中的个体异质性,并促进基于证据的精准医学,
未来的研究方向和研究领域。
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 }}
Lei Liu其他文献
Development of indirect competitive immunoassay for highly sensitive determination of ractopamine in pork liver samples based on surface plasmon resonance sensor
基于表面等离子共振传感器的间接竞争免疫分析法高灵敏测定猪肝样品中的莱克多巴胺
- DOI:
10.1016/j.snb.2011.09.078 - 发表时间:
2012-01 - 期刊:
- 影响因子:0
- 作者:
Ming Liu;Baoan Ning;Lijie Qu;Yuan Peng;Jianwei Dong;Na Gao;Lei Liu;Zhixian Gao - 通讯作者:
Zhixian Gao
Lei Liu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('Lei Liu', 18)}}的其他基金
Innovative Analytical Methods for DNA Methylation Age
DNA 甲基化时代的创新分析方法
- 批准号:
10226664 - 财政年份:2021
- 资助金额:
$ 23.33万 - 项目类别:
Innovative Analytical Methods for DNA Methylation Age
DNA 甲基化时代的创新分析方法
- 批准号:
10414080 - 财政年份:2021
- 资助金额:
$ 23.33万 - 项目类别:
A previously unrecognized β/γ-secretases complex as a therapeutic target for AD
以前未被认识的 β/γ 分泌复合物作为 AD 的治疗靶点
- 批准号:
9902298 - 财政年份:2019
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8337204 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8529465 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8723753 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8088732 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Statistical Analysis of Longitudinal Medical Cost Data
纵向医疗费用数据统计分析
- 批准号:
7323323 - 财政年份:2007
- 资助金额:
$ 23.33万 - 项目类别:
相似海外基金
Rational design of rapidly translatable, highly antigenic and novel recombinant immunogens to address deficiencies of current snakebite treatments
合理设计可快速翻译、高抗原性和新型重组免疫原,以解决当前蛇咬伤治疗的缺陷
- 批准号:
MR/S03398X/2 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Fellowship
Re-thinking drug nanocrystals as highly loaded vectors to address key unmet therapeutic challenges
重新思考药物纳米晶体作为高负载载体以解决关键的未满足的治疗挑战
- 批准号:
EP/Y001486/1 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Research Grant
CAREER: FEAST (Food Ecosystems And circularity for Sustainable Transformation) framework to address Hidden Hunger
职业:FEAST(食品生态系统和可持续转型循环)框架解决隐性饥饿
- 批准号:
2338423 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Continuing Grant
Metrology to address ion suppression in multimodal mass spectrometry imaging with application in oncology
计量学解决多模态质谱成像中的离子抑制问题及其在肿瘤学中的应用
- 批准号:
MR/X03657X/1 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Fellowship
CRII: SHF: A Novel Address Translation Architecture for Virtualized Clouds
CRII:SHF:一种用于虚拟化云的新型地址转换架构
- 批准号:
2348066 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Standard Grant
BIORETS: Convergence Research Experiences for Teachers in Synthetic and Systems Biology to Address Challenges in Food, Health, Energy, and Environment
BIORETS:合成和系统生物学教师的融合研究经验,以应对食品、健康、能源和环境方面的挑战
- 批准号:
2341402 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Standard Grant
The Abundance Project: Enhancing Cultural & Green Inclusion in Social Prescribing in Southwest London to Address Ethnic Inequalities in Mental Health
丰富项目:增强文化
- 批准号:
AH/Z505481/1 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Research Grant
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
EU-Funded
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
EU-Funded
Recite: Building Research by Communities to Address Inequities through Expression
背诵:社区开展研究,通过表达解决不平等问题
- 批准号:
AH/Z505341/1 - 财政年份:2024
- 资助金额:
$ 23.33万 - 项目类别:
Research Grant