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DR. EPS: Drug Repurposing for Extended Patient Survival

博士。

基本信息

批准号：
10465034
负责人：
Lana X Garmire
金额：
$ 34.18万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-21 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10465034
关键词：
Algorithms Animal Model Beds Bioinformatics Cancer Center Cancer Etiology Cancer Prognosis Cancer cell line Canes Cessation of life Clinic Communities Complex Computer Models Computing Methodologies Contracts DNA DNA Methylation Data Data Set Development Diagnosis Disease Disease Management Gene Expression Profile Genomics Goals Heterogeneity Human Hybrids In Vitro Incidence Internet Investigational Therapies Learning Libraries Longevity Malignant Neoplasms Malignant neoplasm of liver Methodology Methods Michigan MicroRNAs Modeling Multiomic Data Network-based Neurons Pathology Patient-Focused Outcomes Patients Pharmaceutical Preparations Pharmacogenetics Pharmacogenomics Pharmacotherapy Population Predictive Cancer Model Primary carcinoma of the liver cells Prognosis Prognostic Marker Research Research Personnel Resources Risk San Francisco Small RNA Survival Rate Technology The Cancer Genome Atlas Therapeutic Therapeutic Human Experimentation Time Universities Work autoencoder base bench to bedside cancer therapy cancer type chemotherapy clinically actionable clinically significant cohort computer framework curative treatments deep learning drug candidate drug repurposing drug sensitivity drug testing efficacious treatment ethnic disparity exome sequencing experimental study gender disparity genomic data genomic profiles genomic signature geographic disparity high dimensionality high risk improved innovation interest learning strategy liver cancer patient mRNA sequencing methylome molecular marker mortality multiple omics novel outcome prediction personalized management personalized medicine precision medicine prediction algorithm prognostic prognostic model response sound survival outcome survival prediction tool transcriptome sequencing user-friendly

项目摘要

Project Summary Human cancers are complex diseases that present vast heterogeneity, leading to widely different survival outcomes. Thus actionable and robust predictive models for cancer prognosis are much needed for more personalized treatment and disease management. However, There has been severely lacking of therapeutically actionable computational methods, which explicitly model patient survival difference as the objective while integrating multi-dimension high-throughput genomics data. To solve this issue, we propose a novel actionable framework for caner drug repurposing, called DR. EPS (Drug Repurposing for Extended Patient Survival). Towards this goal, we will develop the following strategies: (1) Constructing and validating a new class of hybrid-learning based, multi-omics prognosis modeling approach, using seven diverse liver cancer population cohorts. (2) Developing and experimentally validating an actionable computational drug- repurposing framework to improve the survival of high-risk liver cancer patients, using big sets of pharmacogenomics and pharmacogenetics data. (3) Building a user-friendly webtool that accelerates such bench-to-bed transition for liver cancer treatment. We expect that this project will be groundbreaking in many aspects, including building new prognostic models on multi-omics data sets, identifying new repurposed drugs to extend high-risk liver cancer patient life-spans, and providing a first-hand drug reposition resource for liver cancer therapeutics research community.

项目总结