Software Relating Genes to Disease and Clinical Outcomes

将基因与疾病和临床结果相关的软件

• 批准号: 6693828
• 负责人: Christophe G. Lambert
• 金额: $ 41.65万
• 依托单位: GOLDEN HELIX, INC.
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-04-01 至 2005-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6693828
• 关键词: artificial intelligence; computer data analysis; computer program /software; computer system design /evaluation; drug adverse effect; drug screening /evaluation; gene environment interaction; health care facility information system; molecular biology information system; statistics /biometry

DESCRIPTION (provided by applicant): The development of a software system is proposed that will combine statistical theory, computer science algorithms, and genetics expertise to take advantage of the great influx of data generated by the study of the human genome, clinical trials data and the creation of inexpensive genotyping techniques. This software will elucidate the complex relationship between drug efficacy and side effects, multiple interacting genes and environmental factors. Our Phase I results show it is feasible to link phenotype to genotype for a list of "candidate" genes. A novel haplotype trend test has been developed to aid in finding associations across large SNP maps. Commercialization of this technique is essential for companies that intend to use large public or private SNP maps to locate genes that are associated with disease and drug safety and efficacy. Our statistical methods are expected to be successful even if the disease mechanism can differ from one person to another. By analyzing and interpreting clinical trial data, the software will match drugs to target populations according to their specific genotype. This will enable pharmaceutical companies to create novel drugs that render maximum effectiveness and have minimum side effects, i.e. the right drug for the right person.

描述（由申请人提供）：提出了将统计理论，计算机科学算法和遗传学专业知识相结合的软件系统的开发，以利用人类基因组研究，临床试验数据和创建不经典基因分型技术产生的数据大量涌入。该软件将阐明药物疗效与副作用，多个相互作用基因和环境因素之间的复杂关系。 我们的I阶段结果表明，将表型与“候选”基因列表的基因型联系起来是可行的。已经开发了一种新型的单倍型趋势测试，以帮助查找大型SNP图的关联。该技术的商业化对于打算使用大型公共或私人SNP地图来定位与疾病以及药物安全和功效相关的基因的公司至关重要。即使疾病机制因一个人而异，我们的统计方法也将成功。 通过分析和解释临床试验数据，该软件将根据其特定基因型将药物与靶向人群相匹配。这将使制药公司能够创建新的药物，从而产生最大的有效性并具有最小的副作用，即适合合适人士的合适药物。