Software Relating Genes to Disease and Clinical Outcomes

描述(由申请人提供)：建议开发一个软件系统，该系统将结合统计学理论、计算机科学算法和遗传学专业知识，以利用人类基因组研究、临床试验数据和廉价基因分型技术产生的大量数据。该软件将阐明药物疗效与副作用、多个相互作用的基因和环境因素之间的复杂关系。 我们的第一阶段结果表明，将“候选”基因的表型与基因型联系起来是可行的。一种新的单倍型趋势测试已经被开发出来，以帮助寻找大型SNP图谱之间的关联。对于打算使用大型公共或私人SNP图谱来定位与疾病和药物安全性和有效性相关的基因的公司来说，这项技术的商业化至关重要。我们的统计方法有望取得成功，即使每个人的疾病机制可能不同。 通过分析和解释临床试验数据，该软件将根据特定的基因将药物与目标人群进行匹配。这将使制药公司能够创造出具有最大有效性和最小副作用的新药，即适合合适的人的合适的药物。

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.