SBIR Phase II: A multi-omics data integration approach for precision medicine and improved clinical trial success

这一小型企业创新研究(SBIR)第二阶段项目的更广泛影响/商业潜力将是开发一种分析方法和软件包，以使用组学数据识别人类疾病亚型。这项技术将能够为患者提供个性化治疗，并更成功和更具成本效益的临床试验，更快地将药物推向市场。目标是识别疾病亚型和患者亚组，这是区分哪些患者处于危险之中、需要最积极的治疗，以及哪些患者不太适合治疗的先决条件，因为他们永远不会进展或复发，或者会产生耐药性。目前，进入三期临床试验的药物有70%失败，导致每年损失超过1万亿美元。这可以通过完善试验纳入标准并只对最有可能有反应的患者使用该药物来避免。这项技术旨在识别最有可能对给定治疗有效或无效的患者亚群。这项技术还可以通过减少受试者的数量和/或达到足够功率所需的持续时间来降低预防性临床试验的成本。该技术将显著降低药物开发成本，同时通过为每个患者选择正确的治疗方法来改善患者护理。这个SBIR第二阶段项目的智力优势是开发了一种新的分析方法和软件包，能够基于多种类型的组学数据的集成来识别疾病的亚型。许多候选药物失败，许多患者接受不适当的治疗，因为目前无法区分患者亚组(受访者与非受访者)和/或亚类型疾病(侵袭性与非侵袭性)。目前尚未解决的挑战是发现疾病的分子亚型和患者的亚群。仅基于基因表达签名来实现这一点的尝试已经进行，但只取得了一定的成功(到目前为止，很少有基因表达测试是FDA批准的)。这里提出的技术可以用于通过整合多种类型的高通量数据来发现临床相关的疾病亚型。此外，在真实患者数据上获得的I期结果表明，该技术能够仅根据分子特征来区分侵袭性更强和侵袭性更弱的癌症类型。这个第二阶段的项目建议将这项技术扩展到整合基因组和临床数据。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be the development of an analysis method and software package to identify human disease subtypes using omics data. This technology will enable the ability to provide personalized treatment for patients, and more successful and cost-effective clinical trials, bring drugs to market more rapidly. The goal is identification of disease subtypes and patient subgroups, a prerequisite to the ability to distinguish between patients who are in danger and need the most aggressive treatments, and those who are less suited to treatment because they will never progress or recur or they will develop resistance. Currently, 70% of drugs entering Phase III clinical trials fail, leading to a loss of more than $1 trillion per year. This may be avoided by refining trial inclusion criteria and administering the drug only to the patients most likely to respond. The technology is designed to identify patient subgroups most likely to respond or not respond to a given treatment. This technology also may reduce the cost of prophylactic clinical trials by reducing the number of subjects and/or duration necessary to achieve sufficient power. The technology will significantly reduce drug development costs while simultaneously improving patient care by selecting the correct treatment for each patient. The intellectual merit of this SBIR Phase II project is to develop a novel analysis method and software package that is able to identify subtypes of disease based on the integration of multiple types of omics data. Many drug candidates fail and many patients receive inappropriate treatment because of the current inability to distinguish between subgroups of patients (respondents vs. non-respondents) and/or subtypes of disease (aggressive vs. non-aggressive). The current unmet challenge is to discover the molecular subtypes of disease and subgroups of patients. Attempts to achieve this based solely on gene expression signatures have been undertaken but yielded only modest success (very few gene expression tests are FDA-approved to date). The technology proposed here may be used to discover clinically relevant disease subtypes by integrating multiple types of high-throughput data. In addition, the Phase I results obtained on real patient data demonstrated that the technology is able to distinguish between more and less aggressive types of cancer based on their molecular profiles alone. This Phase II project proposes to extend this technology to integrate genomic and clinical data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.