IUCRC Phase I University of Michigan Ann Arbor: Center for Data-Driven Drug Development and Treatment Assessment (DATA)

药物开发和评估面临着主要挑战，特别是：1)在药物发现的早期阶段，筛选数千种可能的药物既昂贵又耗时。2)当医疗保健提供者使用药物进行治疗时，评估其疗效和潜在的不良反应是非常重要的。新的计算方法，如机器学习（ML）和人工智能（AI），不仅为药物设计提供了解决方案，也为个性化治疗提供了解决方案。数据驱动药物开发和治疗评估中心（DATA）通过与其行业合作伙伴的合作，打算在竞争前研究中推广这种计算解决方案。近年来，人工智能和机器学习方法影响了社会的许多方面；DATA将开发和应用新的AI/ML方法，用于药物设计和评估的几个方面，如筛选/检测药物和靶点之间的相互作用，以及考虑先前存在的疾病的治疗定制。DATA的数学算法和方法可以产生工具和解决方案，以解决药物设计和治疗监测整个生命周期中的主要障碍。该中心还通过整合和管理新的/现有的公共和专有医疗保健/制药数据集开发大型数据库，为新药的建模、开发和评估提供新的资源。DATA将开发培训下一代数据科学家的项目，尤其是那些来自弱势群体的数据科学家。DATA将在学术界之外开展新的合作，将数据科学应用转化为有影响力的产品/服务，从而降低药物开发成本，同时优化治疗方法，改善患者的整体健康状况。这反过来又减轻了患者和提供者的经济/社会负担。DATA将使学员与制药/医疗保健行业领导者之间进行直接互动，为学员提供对现实需求的宝贵见解。DATA将通过直接培训这些未来的劳动力，解决对数据科学、药物设计和治疗评估方面综合专业知识的毕业生的迫切需求。数据整合、管理和存储过程打算在第一阶段（和第二阶段，如果适用）的范围和持续时间之后继续进行。DATA计划继续收集、管理、整合和预处理由DATA当前和未来成员共享的数据库以及公开可用的数据库。这些集成数据库的一个子集，其中一些将通过我们的完全同态加密方法加密，可以在中心章程制定的指导方针下与外部实体共享。数据库和软件工具将由合作伙伴通过一个带有文件的专用安全网站共享。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Drug development and assessment present major challenges, in particular: 1) In the early stages of drug discovery, it is costly and time-consuming to screen thousands of possible drugs. 2) When healthcare providers use the drug for treatment, it is highly important to assess their efficacy as well as potential adverse effects. Novel computational approaches, such as machine learning (ML) and artificial intelligence (AI), present solutions not only for drug design but also for personalized treatments. The Center for Data-Driven Drug Development and Treatment Assessment (DATA), through collaboration with its industry partners, intends to promote such computational solutions within precompetitive research.In recent years AI and ML methods have impacted many aspects of society; DATA will develop and apply novel AI/ML methods for several aspects of drug design and assessment such as screening/detecting interactions between drugs and targets, and treatment customization considering preexisting conditions. DATA’s mathematical algorithms and methodologies can result in tools and solutions to address major obstacles throughout the lifecycle of drug design and treatment monitoring. The Center also develops large databases by integrating and curating new/existing public and proprietary healthcare/pharmaceutical datasets, allowing new resources for modeling, development, and assessment of new drugs.DATA will develop programs to educate the next generation of data scientists, especially those from underrepresented groups. DATA will form new collaborations beyond academia to translate data science applications into impactful products/services, thereby reducing drug development costs while optimizing treatments and improving overall patient health. This in turn reduces the financial/societal burden on patients and providers alike. DATA will enable direct interactions between trainees and pharmaceutical/healthcare industry leaders, providing trainees with invaluable insight into real-world needs. DATA will address the urgent need for additional graduates with combined expertise in data science, drug design, and treatment assessment by directly training this future workforce.The data integration, curation and storage processes are intended to continue beyond the scope and duration of the Phase I (and Phase II, if applicable). DATA intends to continue collecting, curating, integrating, and pre-processing databases shared by the current and future members of DATA as well as publicly available databases. A subset of these integrated databases, some of which will be encrypted through our Fully Homomorphic Encryption approach, can be shared with external entities under the guidelines set by the Center’s bylaws. Databases and software tools will be shared by the partners through a dedicated and secure website with documentation.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.