Computational Drug Repurposing for All Epidermolysis Bullosa Simplex (EBS) Cases
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- Joyce Teng
- 入组人数
- 60
- 试验地点
- 1
- 主要终点
- Characterize gene expression changes in EB using RNA sequencing (RNA-seq) and Computational Profiling Potential Drug Targets
研究概览
简要总结
The study will compare gene expression differences between blistered and non-blistered skin from individuals with all subtypes of EB, as well as normal skin from non-EB subjects. State of the art computational analysis will be performed to help identify new drugs that might help all EB wound healing and reduce pain. Researchers will focus on drugs that have already been approved for treatment of other dermatologic or non-dermatologic diseases, and therefore be repurposed for treatment of EB. Drug development is a very expensive process taking decades for execution. Drug repurposing on the other hand, significantly reduces the cost and shortens the amount of time that is needed to bring effective treatments to clinical use. To date, there is no specific treatment targeting the physiology and immunologic response in EB patients during wound healing. Market availability of repurposed medications will provide all EB patients rapid access to treatments, thus improving their quality of life.
详细描述
Although gene, cell, and protein-based therapies are in development for patients suffering from all subtypes of epidermolysis bullosa (EB), new pharmacological treatments are in dire need. Characterizing molecular changes in EB, including gene expression, can identify new therapeutic targets and drugs that modulate those targets. However, sifting through gene expression information to identify the most promising drug targets is a complex data challenge. The goal of the study will identify a computational approach to evaluate and identify existing drugs approved for other diseases that can be repurposed for EB patients. The study will perform an unprecedented characterization of gene expression changes in EB patients compared to healthy, non-EB individuals across multiple tissues. Using a validated computational drug discovery platform, researchers will analyze gene expression and drug data using unique algorithms. In the first year, a list of ten, safety drugs more probable to treat the EB disease state will be identified. The most promising drugs discovered will then be tested in the clinic setting.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 0 Years 至 —（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Subjects of all ages
- •Diagnosis of all subtypes of EB subjects
- •Healthy, non-EB subjects
- •Ability to complete study visit to collect tissue and blood specimen
排除标准
- •Pregnancy, breast feeding
- •Prior history of liver disease
- •Serious known concurrent medical illness or infection, which could potentially present a safety risk and/or prevent tissue collection from subjects
结局指标
主要结局
Characterize gene expression changes in EB using RNA sequencing (RNA-seq) and Computational Profiling Potential Drug Targets
时间窗: Through the completion of study in 1 year.
Using bioinformatic algorithms to identify changes in gene expression and review of over 2000 FDA-approved drugs based on predicted modulation of gene expression changes using a computational evolutionary algorithm system.
次要结局
未报告次要终点
研究者
Joyce Teng
Director of Pediatric Dermatology
Stanford University