Curve-free phase I/II clinical trial designs for molecularly targeted agents and immunotherapy
Curve-free phase I/II clinical trial designs for molecularly targeted agents and immunotherapy
批准号:
10490477
负责人:
Yong Zang
金额:
$13.7万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-17 至 2024-08-31
关键词:
AddressAlgorithmsAreaBinomial ModelClinicalClinical Trials DesignCommunitiesComplexCytotoxic agentDataDecision MakingDevelopmentDimensionsDoseDrug CombinationsGoalsImmunotherapeutic agentImmunotherapyJointsLeadLearningLikelihood FunctionsLiteratureMaximum Tolerated DoseMethodsModelingMolecular TargetMonitorOutcomePatientsPatternPerformancePhasePhase I Clinical TrialsPhase I/II Clinical TrialPhase I/II TrialPhysiciansProbabilityResearchSeriesTestingTherapeutic EffectTimeToxic effectTranslationsWeightbasecancer therapyclinical practicecostdesignefficacy outcomesflexibilityfollow-upinterestmathematical modelnovelresponsesimulationtargeted agenttrial designtwo-dimensionalunpublished worksuser-friendlyweb app
中文摘要
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英文摘要
Project Summary/Abstract
The primary goal of this proposal is to develop transparent, flexible and efficient phase I/II clinical trial designs
identifying optimal doses for molecularly targeted agents (MTA) and immunotherapy (IT). Conventional phase I/II
clinical trial designs often use sophisticated parametric models to characterize the joint toxicity-efficacy distribu-
tions and to conduct the trials. However, the parametric models are hard to justify in practice, and misspecification
of parametric models can lead to substantially undesirable performances of phase I/II trials. Moreover, it is difficult
for the physicians conducting the trials to clinically interpret the parameters of these sophisticated models, and
such great learning costs impede the translation of novel statistical designs into real-world trial implementation.
To solve these issues, in this proposal we will propose transparent curve-free phase I/II clinical trial designs.
The proposed designs make no parametric assumptions on either dose-response relationship or toxicity-efficacy
correlation and therefore performs robustly under any clinically meaningful dose-response curves. The concise
clinically interpretable model expression and dose-finding algorithm make the proposed designs highly transla-
tional from the statistical community to the clinical community. The proposed designs are also highly flexible
because they are applicable for both single-agent trial and drug-combination trial with either quickly observable
outcomes or delayed outcomes. The preliminary simulation studies show that the proposed designs are highly
efficient in optimal dose selection and patient allocation. In addition, we will develop user-friendly web apps to
facilitate the widespread application of the proposed designs in clinical practice.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.3390/genes12111723
发表时间:
2021-10-28
期刊:
Genes
影响因子:
3.5
作者:
[Chen Z, Zang Y]
通讯作者:
Zang Y
Use Bayesian methods to facilitate the data integration for complex clinical trials
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批准号:10714225
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项目类别:
-
资助金额:$32.02万
-
财政年份:2023
-
负责人:Yong Zang
-
依托单位:
Curve-free phase I/II clinical trial designs for molecularly targeted agents and immunotherapy
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批准号:10304652
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项目类别:
-
资助金额:$14.0万
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财政年份:2021
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负责人:Yong Zang
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依托单位:
海外基金