STTR Phase II: Optimized manufacturing and machine learning based automation of Endothelium-on-a-chip microfluidic devices for drug screening applications.

这个小企业技术转让（STTR）第二阶段项目的更广泛的影响/商业潜力是解决镰状细胞病（SCD）伴随诊断指导治疗市场中未满足的需求。SCD是一种影响全球数百万人的终身疾病。新兴疗法估计每年每位患者15万至20万美元。SCD抗粘连治疗的伴随诊断成本估计为每位患者至少3，000美元。随着生活在低收入和中等收入国家的患者可及性的改善以及可扩展的治疗性疗法，预计到2029年，全球SCD治疗市场规模将增加到87.5亿美元。此外，伴随诊断指导药物在III期临床试验中的监管批准概率增加了50%。具有人类供体细胞的专有Endothelium-on-a-chip平台提供了研究血液-内皮相互作用的生理相关手段。该平台可以整合到临床前研究中，以筛选新候选药物的效果以及评估药物毒性。在STTR项目的第一阶段，建立了内皮细胞芯片实验条件的标准和质量控制标准。与制药公司的持续项目强调了扩大生产工艺的必要性。这个小企业技术转让（STTR）第二阶段项目将专注于优化生产工艺，以实现检测的规模化，并开发用于自动数据分析的机器学习系统。目前，该检测试剂盒涉及内部制造，仅限于公司所在地的中心实验室。将通过适当选择材料、制造方法、可扩展技术和系统整合试验的不同元素来优化生产。这将有可能使该技术的商业化和更大规模的实施成为可能。目前的分析方法包括手动计数粘连事件。这种方法将被基于机器学习的系统所取代，以识别和分类粘附事件，并将其与背景中的内皮细胞分离。自动化数据分析将实现更快的结果并消除用户偏见。由于这一方法依赖于增强现有平台的能力，以扩大规模和简化分析，预计它将提高其对更广泛的研究社区的可访问性。该奖项反映了NSF的法定使命，并被认为值得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来支持。

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to address the unmet need in the companion diagnostic guided therapy market for Sickle Cell Disease (SCD). SCD is a lifelong disease affecting millions of people worldwide. Emerging therapies are estimated to be $150k-$200k per patient each year. A companion diagnostic cost in SCD anti-adhesive therapies is estimated at least $3,000 per patient. With improved accessibility to patients living in low- and middle-income countries and scalable curative therapies, the global SCD treatment market size is projected to increase to $8.75B by 2029. Additionally, companion diagnostic-guided drugs have an increased regulatory approval probability of 50% in Phase III clinical trials. The proprietary Endothelium-on-a-chip platform with human donor cells provides a physiologically relevant means to study blood-endothelium interaction. This platform can be integrated into preclinical studies to screen the effect of novel drug candidates as well as for assessment of drug toxicity. In Phase I of the STTR project, standards and quality control criteria for experimental conditions on the Endothelium-on-a-chip were established. The continuing projects with pharmaceutical companies have highlighted the need to scale the manufacturing process.This Small Business Technology Transfer (STTR) Phase II project will focus on optimizing the manufacturing process to enable the scale-up of the assay and develop the machine learning system for automated data analysis. Currently, this assay involves in-house fabrication and is limited to the central laboratory at the company’s location. Manufacturing will be optimized with proper selection of material, fabrication methods, scalable techniques, and systematic integration of different elements of the assay. This will potentially enable the commercialization and implementation of the technology at a larger scale. Current methods of analysis include counting adhesion events manually. This method will be replaced by a machine learning-based system to identify and classify adhesion events and separate those from the endothelial cells in the background. Automated data analysis will enable faster outcomes and remove user bias. Since this approach relies on enhancing the capabilities of the existing platform for scale-up and streamlined analysis, it is anticipated that it will improve its accessibility to the broader research community.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.