SBIR Phase I: Drug discovery using stem cell derived organoids

这一小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是使儿童罕见疾病的新疗法得以开发。据估计，全世界有3.5亿人--其中一半是儿童--每年约有7000多种已知的罕见疾病，但95%的罕见疾病仍然缺乏治疗。尽管80%的罕见疾病源于基因，但实际的药物发现相对较少。这是一个巨大的问题，因为30%患有罕见疾病的儿童将无法活到他们的5岁生日。为了解决这个问题，可以通过筛选针对与患者相似的年轻器官和具有相同基因突变的微型器官(“有机类”)的研究药物来加速药物开发。在一个简单的培养皿中，有机化合物能够直接研究患者的基因和他/她的疾病之间的关系。这类有机化合物为快速确定新的疾病机制和靶向治疗提供了机会。该团队正在将有机化合物技术扩展到一个自动化药物开发平台，该平台高通量、健壮，适用于儿童的多种遗传病。该项目通过完成两个主要目标来推动儿科罕见疾病的药物开发：(1)从人类干细胞自动获得心脏、肝脏和脑有机物质，以及(2)自动机器学习(ML)检测来自遗传病患者的有机物质中的疾病，这些疾病影响这三个器官中的任何一个。要做到这一点，机器人技术和特定方案的结合将在标准化条件下区分组织和疾病特异性有机物。当有机物质在组织状态之间转换时，用显微镜进行监测。ML模型了解健康的有机化合物看起来是什么样子，并使用这些信息来识别有机化合物何时表现出疾病表型。这些目标对于减少一批又一批有机物的可变性和可能扰乱药物发现努力的人为错误非常重要。在这些相同的有机模型中，将进行药物筛选和开发，以试图逆转或延缓每种疾病特有的疾病表型。这项研究的结果将是生产高准确度和精确度的有机化合物，以及检测心脏、肝脏和神经有机化合物变化的自动化手段，这将是寻找新疗法的关键。这一奖项反映了NSF的法定使命，并通过使用基金会的智力价值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 I project is to enable the development of new therapies for rare diseases in children. An estimated 350 million people worldwide - half of which are children - suffer from an estimated 7,000+ known rare diseases annually, yet 95% of rare diseases still lack treatment. Even though 80% of rare diseases are genetic in origin, there have been relatively few actual drug discoveries. This is an enormous problem as 30% of children with rare diseases will not live to see their 5th birthdays. To address this, drug development can be accelerated by screening investigational drugs against micro-organs (“organoids”) that resemble young organs and have the same gene mutations as the patients. In a simple petri dish, organoids enable the direct study of the relationship between a patient’s genes and his/her disease. Such organoids present an opportunity to rapidly identify new disease mechanisms and targeted therapies. The team is scaling organoid technology into an automated drug development platform that is high throughput, robust, and applicable to multiple genetic diseases in children. This project advances drug development for pediatric rare diseases by accomplishing two primary objectives: (1) automated heart, liver, and brain organoid derivation from human stem cells, and (2) automated machine learning (ML) detection of disease in organoids derived from patients with genetic diseases affecting any of these three organs. To do this, a combination of robotics and specific protocols will differentiate tissue- and disease-specific organoids under standardized conditions. The organoids are monitored with microscopy as they transition between tissue state. The ML model learns what healthy organoids look like and uses that information to identify when an organoid exhibits a disease phenotype. These objectives are important for reducing batch-to-batch organoid variability and human error that can confound drug discovery efforts. In these same organoid models, drug screening and development will be performed to try to reverse or retard the disease phenotype unique to each disease. The result of this research will be the production of organoids with high accuracy and precision, as well as an automated means for detecting changes in heart, liver, and neural organoids that will be essential for finding new therapies.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.