Software Relating Genes to Disease and Clinical Outcomes

描述(申请人摘要)：软件系统的开发是 提出了将统计理论、计算机科学算法和 遗传学专业知识，以利用大量涌入的数据 人类基因组的研究和廉价基因分型的创造 技巧。该软件将阐明药物与药物之间的复杂关系 疗效和副作用，以及多个相互作用的基因和环境 各种因素。利用模拟数据获得的初步结果表明， 将表型与候选列表中的基因联系起来可能是可行的 统计方法有望取得成功，即使 疾病机制因人而异。通过分析和 通过解释临床试验数据，该软件将把药物与靶点进行匹配 根据其特定的基因型别对种群进行分类。这将使 制药公司将创造出最大限度发挥作用的新药 有效且副作用最小，即对症下药 人。 建议的商业应用： 这项研究的目标市场包括制药公司、CRO 大学和政府机构。它具有很好的商业化潜力 因为它有望帮助创造新药，提高药物治疗的安全性， 节省大量资源，并理解复杂的基因/表型关系 在临床试验方面。

DESCRIPTION (Applicant's abstract): 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 both the study of the human genome and the creation of inexpensive genotyping techniques. This software will elucidate the complex relationship between drug efficacy and side effects, and multiple interacting genes and environmental factors. Preliminary results, obtained by using simulated data, indicate that it might be feasible to link phenotype to genotype for a list of "candidate genes." The 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. PROPOSED COMMERCIAL APPLICATION: The target markets for the research include pharmaceutical companies, CRO'S universities, and government agencies. It has good potential for commercialization because it is expected to help create novel drugs, boost the safety of drug treatments, save substantial resources, and make sense of complex genotype/phenotype relationships in clinical trials context.